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Manne A, Bao Y, Sheel A, Sara A, Manne U, Thanikachalam K, Esnakula A, Pawlik TM, Cloyd JM, Tsai S, Kasi A, Paluri RK, Sherpally D, Jeepalyam S, Yu L, Yang W. Prognostic significance of serum MUC5AC in resected pancreatic ductal adenocarcinoma: initial insights. Front Oncol 2025; 15:1544928. [PMID: 40260290 PMCID: PMC12010103 DOI: 10.3389/fonc.2025.1544928] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2024] [Accepted: 03/17/2025] [Indexed: 04/23/2025] Open
Abstract
Background We investigated the association between serum MUC5AC (sMUC5AC) levels and patient outcomes in individuals who underwent resection for pancreatic ductal adenocarcinoma (PDA), including those treated with neoadjuvant therapy (NAT) and those who had upfront surgery (UpS) followed by adjuvant therapy. Methods Serum samples from the Ohio State University biorepository collected from January 2010 to June 2021 were utilized. The human MUC5AC kit (NBP2-76703) was used to perform enzyme-linked immunoassays to measure sMUC5AC levels. Logistic regression, Cox regression models (univariate and multivariate), recurrence prediction, analysis of variance (ANOVA), t-tests, and Wilcoxon tests were used for statistical analysis. Results In the NAT cohort (n = 23), elevated sMUC5AC levels were significantly (P < 0.05) associated with pathological treatment response, margin positivity, and residual disease. Among 21 patients who had an R0/R1 resection (R2 resection, n=2), higher sMUC5AC levels were associated with shorter progression-free survival (PFS) (HR: 1.64, P = 0.0006) and overall survival (OS) (HR: 1.6, P = 0.005) on univariate analysis. Multivariate models confirmed sMUC5AC as an independent predictor of PFS and OS alongside pathological differentiation and postoperative therapy. Patients with lower sMUC5AC levels had more favorable pathological characteristics, better treatment responses, and improved survival outcomes. These findings were consistent in the FOLFIRINOX subgroup (n = 17). In the UpS cohort (n = 17), post-resection sMUC5AC levels tend to be associated with PFS (P = 0.07) and OS (P = 0.05). Combining sMUC5AC with Carbohydrate antigen (CA) 19-9 enhanced sensitivity (79%) and specificity (67%) to predict recurrence. Higher sMUC5AC levels were associated with earlier recurrence and poor survival outcomes, highlighting its utility in post-surgery risk stratification. Among patients with pre-treatment data (n = 11), sMUC5AC levels were significantly higher among patients with poorly differentiated tumors. Conclusion This study provides compelling evidence for the clinical utility of sMUC5AC as a prognostic biomarker among patients with resected PDA. Future large-scale studies are needed to validate these findings and establish standard thresholds for sMUC5AC integration into clinical practice.
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Affiliation(s)
- Ashish Manne
- Department of Internal Medicine, Division of Medical Oncology, The Ohio State University Comprehensive Cancer Center (OSUCCC), Columbus, OH, United States
| | - Yonghua Bao
- Clinical & Translational Science Shared Resource, Comprehensive Cancer Center, The Ohio State University, Columbus, OH, United States
| | - Ankur Sheel
- Department of Internal Medicine, Division of Medical Oncology, The Ohio State University Comprehensive Cancer Center (OSUCCC), Columbus, OH, United States
| | - Amir Sara
- Department of Internal Medicine, Division of Medical Oncology, The Ohio State University Comprehensive Cancer Center (OSUCCC), Columbus, OH, United States
| | - Upender Manne
- Department of Pathology, University of Alabama at Birmingham, Birmingham, AL, United States
| | - Kannan Thanikachalam
- Department of Medicine, Roswell Park Comprehensive Cancer Center, Buffalo, NY, United States
| | - Ashwini Esnakula
- Department of Pathology, The Ohio State University Comprehensive Cancer Center (OSUCCC), Columbus, OH, United States
| | - Timothy M. Pawlik
- Department of Surgery, Division of Surgical Oncology, The Ohio State University Comprehensive Cancer Center (OSUCCC), Columbus, OH, United States
| | - Jordan M. Cloyd
- Department of Surgery, Division of Surgical Oncology, The Ohio State University Comprehensive Cancer Center (OSUCCC), Columbus, OH, United States
| | - Susan Tsai
- Department of Surgery, Division of Surgical Oncology, The Ohio State University Comprehensive Cancer Center (OSUCCC), Columbus, OH, United States
| | - Anup Kasi
- Division of Medical Oncology, University of Kansas Cancer Center, Westwood, KS, United States
| | - Ravi Kumar Paluri
- Division of Hematology-Oncology, Department of Internal Medicine, Atrium Health Wake Forest Baptist Comprehensive Cancer Center, Winston-Salem, NC, United States
| | - Deepak Sherpally
- Department of Internal Medicine, New York Medical College, Valhalla, NY, United States
| | - Sravan Jeepalyam
- Department of Internal Medicine, Stormont Vail Health, Topeka, KS, United States
| | - Lianbo Yu
- Center of Biostatistics and Bioinformatics, The Ohio State University, Columbus, OH, United States
| | - Wancai Yang
- Clinical & Translational Science Shared Resource, Comprehensive Cancer Center, The Ohio State University, Columbus, OH, United States
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2
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Cheng M, Consul N, Chung R, Del Castillo CF, Hernandez-Barco Y, Kambadakone A. Acinar cell carcinoma of the pancreas: can CT and MR features predict survival? Cancer Imaging 2025; 25:38. [PMID: 40119414 PMCID: PMC11929164 DOI: 10.1186/s40644-025-00859-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2024] [Accepted: 03/10/2025] [Indexed: 03/24/2025] Open
Abstract
OBJECTIVE To evaluate the CT and MRI features of pancreatic acinar cell carcinoma (pACC) and their association with patient outcome and survival. METHODS This retrospective single-center study included 49 patients with pathology-proven pancreatic acinar cell carcinoma who underwent diagnostic imaging between August 1998 - September 2019. Two radiologists reviewed CT and MRI features independently. Survival was estimated using the Kaplan-Meier method, and Cox proportional-hazards regression model was used to identify factors associated with survival. RESULTS pACC tended to present as a solid (31/49, 63.3%) pancreatic head mass (26/49, 53.1%) with ill-defined margins (32/49, 65.3%) and median maximal diameter of 4.1 cm (IQR, 2.9-6.2). Majority of lesions were hypo- or isodense (38/49, 77.6%) compared to normal pancreatic parenchyma, with heterogenous (39/49, 79.6%) enhancement pattern. Biliary ductal dilatation was uncommon, with pancreatic ductal dilatation in 22.4% (11/49) and common bile duct dilatation in 14.3% (7/49). Intralesional calcifications were seen in 6.1% (3/49). Metastasis was present in 71.4% (35/49) of patients at the time of diagnosis. On MRI, 88.9% (16/18) demonstrated diffusion restriction and 59.1% (13/22) with heterogenous enhancement. On multivariate analysis, the imaging presence of T1 hyperintensity (p = 0.02), hypoattenuating necrotic components (p = 0.02), and splenic vein invasion (p = 0.04) were associated with worse survival. CONCLUSION Pancreatic acinar cell carcinoma is a rare pancreatic neoplasm that often presents as a large ill-defined heterogeneously enhancing mass without biliary ductal dilation. T1 hyperintensity, presence of hypoattenuating necrotic components, and splenic vein invasion were independent predictors of survival.
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Affiliation(s)
- Monica Cheng
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, 55 Fruit Street, Boston, MA, 02114, USA.
| | - Nikita Consul
- Department of Radiology, University of Michigan, Ann Arbor, MI, USA
| | - Ryan Chung
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, 55 Fruit Street, Boston, MA, 02114, USA
| | | | - Yasmin Hernandez-Barco
- Department of Gastroenterology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Avinash Kambadakone
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, 55 Fruit Street, Boston, MA, 02114, USA
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3
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Chen J, Wu Q, Liu L, Yuan Y, Lai S, Wu Z, Yang R. Morphological characterization of atypical pancreatic ductal adenocarcinoma with cystic lesion on DCE-CT: a comprehensive retrospective study. BMC Med Imaging 2025; 25:87. [PMID: 40087584 PMCID: PMC11909956 DOI: 10.1186/s12880-025-01586-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2024] [Accepted: 02/10/2025] [Indexed: 03/17/2025] Open
Abstract
BACKGROUND Pancreatic ductal adenocarcinoma (PDAC) with cystic features presents significant challenges in achieving an accurate preoperative diagnosis and in implementing appropriate clinical management. The aim of this study was to analyze the dynamic contrast-enhanced computed tomography (DCE-CT) findings of PDACs with cystic lesions and correlate them with histopathological findings. METHODS We retrospectively reviewed 40 patients with pathology-proven PDACs exhibiting cystic lesions who underwent preoperative DCE-CT imaging. The CT manifestations were classified into three subtypes based on the morphological characteristics of the cystic lesions: Type 1, small proportion (< 50%) of intratumoral cystic lesions, with or without associated peritumoral cystic lesions; Type 2, large proportion (≥ 50%) of intratumoral cystic lesions, with or without associated peritumoral cystic lesions; Type 3, a solid pancreatic mass with accompanying peritumoral cystic lesions. The DCE-CT findings were analyzed based on location, size, contour, enhancement patterns, and secondary findings, and compared with the corresponding pathological diagnoses. RESULTS Among the 40 patients, 23 (57.5%) tumors were located in the pancreatic body or tail. Type 1 was identified in 21 cases, Type 2 in 6 cases, and Type 3 in 13 cases. All masses exhibited a bulging pancreatic contour, with 4 cases showing isoattenuating enhancement on DCE-CT. Secondary signs were present in 87.5% (35/40) of cases. Notably, 15 cases (37.5%) were misdiagnosed or missed. Surgical resection specimens demonstrated common pathological features, including large duct-like cysts and coagulative necrosis. CONCLUSION Atypical PDAC with cystic lesions is a relatively uncommon variant that exhibits a range of DCE-CT features, along with distinct pathological characteristics. Familiarity with these imaging features is essential for radiologists in order to minimize the risk of misdiagnosis and guide appropriate clinical management of these challenging cases.
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Affiliation(s)
- Jing Chen
- Department of Radiology, the First College of Clinical Medical Science, China Three Gorges University, Yichang Central People's Hospital, Yichang, China
| | - Qi Wu
- Department of Pathology, the First College of Clinical Medical Science, China Three Gorges University, Yichang Central People's Hospital, Yichang, China
| | - Ling Liu
- Department of Radiology, the First College of Clinical Medical Science, China Three Gorges University, Yichang Central People's Hospital, Yichang, China
| | - Yuan Yuan
- Department of Pathology, the First College of Clinical Medical Science, China Three Gorges University, Yichang Central People's Hospital, Yichang, China
| | - Shengsheng Lai
- School of Medical Equipment, Guangdong Food and Drug Vocational College, Guangzhou, Guangdong, China
| | - Zhe Wu
- Department of Radiology, the Second Affiliated Hospital, School of Medicine, South China University of Technology, Guangzhou, Guangdong, China
| | - Ruimeng Yang
- Department of Radiology, the Second Affiliated Hospital, School of Medicine, South China University of Technology, Guangzhou, Guangdong, China.
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Laga Boul-Atarass I, Cepeda Franco C, Sanmartín Sierra JD, Castell Monsalve J, Padillo Ruiz J. Virtual 3D models, augmented reality systems and virtual laparoscopic simulations in complicated pancreatic surgeries: state of art, future perspectives, and challenges. Int J Surg 2025; 111:2613-2623. [PMID: 39869381 DOI: 10.1097/js9.0000000000002231] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2024] [Accepted: 12/07/2024] [Indexed: 01/28/2025]
Abstract
Pancreatic surgery is considered one of the most challenging interventions by many surgeons, mainly due to retroperitoneal location and proximity to key and delicate vascular structures. These factors make pancreatic resection a demanding procedure, with successful rates far from optimal and frequent postoperative complications. Surgical planning is essential to improve patient outcomes, and in this regard, many technological advances made in the last few years have proven to be extremely useful in medical fields. This review aims to outline the potential and limitations of 3D digital and 3D printed models in pancreatic surgical planning, as well as the impact and challenges of novel technologies such as augmented/virtual reality systems or artificial intelligence to improve medical training and surgical outcomes.
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Affiliation(s)
- Imán Laga Boul-Atarass
- Department of Surgery, Virgen del Rocio University Hospital, Seville, Spain
- Oncology Surgery, Cell Therapy, and Organ Transplantation Group, Instituto de Biomedicina de Sevilla (IBiS), University of Sevilla, Seville, Spain
| | - Carmen Cepeda Franco
- Department of Surgery, Virgen del Rocio University Hospital, Seville, Spain
- Oncology Surgery, Cell Therapy, and Organ Transplantation Group, Instituto de Biomedicina de Sevilla (IBiS), University of Sevilla, Seville, Spain
| | | | | | - Javier Padillo Ruiz
- Department of Surgery, Virgen del Rocio University Hospital, Seville, Spain
- Oncology Surgery, Cell Therapy, and Organ Transplantation Group, Instituto de Biomedicina de Sevilla (IBiS), University of Sevilla, Seville, Spain
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Mohamed G, Munir M, Rai A, Gaddam S. Pancreatic Cancer: Screening and Early Detection. Gastroenterol Clin North Am 2025; 54:205-221. [PMID: 39880528 DOI: 10.1016/j.gtc.2024.09.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/31/2025]
Abstract
Pancreatic cancer, often diagnosed at advanced stages, has poor survival rates. Effective screening aims to detect the disease early, improving outcomes. Current guidelines recommend screening high-risk groups, including those with a family history or genetic predispositions, using methods like endoscopic ultrasound and MRI. The American Gastroenterological Association and other organizations advise annual surveillance for high-risk individuals, typically starting at the age of 50 or 10 years younger than the youngest affected relative. For certain genetic syndromes, such as Peutz-Jeghers syndrome or hereditary pancreatitis, screening may begin as early as the age of 35 to 40 years.
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Affiliation(s)
- Ghada Mohamed
- Department of Internal Medicine, Lahey Hospital & Medical Center, 41 Mall Road, Burlington, MA 01805, USA
| | - Malak Munir
- Karsh Division of Gastroenterology and Hepatology, Cedars-Sinai Medical Center, 8700 Beverly Boulevard, ST, Suite 7705, Los Angeles, CA 90048, USA
| | - Amar Rai
- Karsh Division of Gastroenterology and Hepatology, Cedars-Sinai Medical Center, 8700 Beverly Boulevard, ST, Suite 7705, Los Angeles, CA 90048, USA
| | - Srinivas Gaddam
- Karsh Division of Gastroenterology and Hepatology, Cedars-Sinai Medical Center, 8700 Beverly Boulevard, ST, Suite 7705, Los Angeles, CA 90048, USA.
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6
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Ruff A, Li X, Goldberg JD, Ehrhart M, Ginocchio L, Smereka P, O'Donnell T, Dane B. Optimal virtual monoenergy for the detection of pancreatic adenocarcinoma during the pancreatic parenchymal phase on photon counting CT. Abdom Radiol (NY) 2025:10.1007/s00261-024-04696-9. [PMID: 39775026 DOI: 10.1007/s00261-024-04696-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2024] [Revised: 11/07/2024] [Accepted: 11/11/2024] [Indexed: 01/11/2025]
Abstract
PURPOSE As the pancreas is a low contrast visibility organ, pancreatic ductal adenocarcinoma detection is challenging due to subtle attenuation differences between tumor and pancreatic parenchyma. Photon counting CT (PCCT) has superior iodine contrast-to-noise ratio than conventional CT and also affords the creation of low keV virtual monoenergetic images, both of which increase adenocarcinoma conspicuity. The purpose therefore was to identify the optimal virtual monoenergy for visualizing PDAC during the pancreatic parenchymal phase of enhancement at PCCT using both quantitative and qualitative analyses. METHODS Consecutive patients with pancreatic parenchymal phase PCCT source data were retrospectively identified by PACS search. For the quantitative analysis, region of interest (ROI) measurements were drawn in the pancreatic head, body, tail, pancreatic adenocarcinoma (if present), and psoas muscles on 40-120 keV virtual monoenergetic images in 10 keV increments. Based on the quantitative analysis results and vendor recommendations, four virtual monoenergies(40 keV, 55 keV, 70 keV, and 85 keV) were selected for additional qualitative analysis. Three radiologists blinded to four virtual monoenergies assessed overall image quality, image noise, pancreatic enhancement, and pancreatic mass conspicuity on 5-point Likert scales. RESULTS 54 patients (28/54 male, mean[SD] age: 62 [13] years) were included. Quantitatively, 40 keV had the highest pancreatic parenchymal CNR and attenuation difference between the adenocarcinoma and parenchyma, but also the highest noise (HUsd). Qualitatively, 70 keV had the best overall image quality (Mean [SE]: 3.7[0.1]) and lower noise than 40 and 55 keV (3.6[0.08] vs. 1.8[0.07] and 2.7[0.05], respectively, p < .001). 40 keV had the greatest pancreatic enhancement (mean[SE] 4.6[0.11]). Adenocarcinoma conspicuity ratings were greatest at 40 keV and 55 keV, and not significantly different from each other (mean[SE] 4.4[0.13] and 4.3[0.14], respectively, Tukey adj-p =.20). 55 keV had greater overall image quality and lower noise than 40 keV (mean[SE] 3.4[0.08] vs. 2.5[0.08], Tukey adj-p < .001 and 2.7[0.05] vs. 1.8[0.07], Tukey adj-p < .001 respectively). CONCLUSION 55 keV pancreatic parenchymal phase virtual monoenergetic images afford optimal pancreatic assessment at PCCT for the visualization of pancreatic adenocarcinoma. Routinely viewing 55 keV virtual monoenergetic images at PCCT may improve PDAC detection.
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7
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Sindhi K, Kanugo A. Recent Developments in Nanotechnology and Immunotherapy for the Diagnosis and Treatment of Pancreatic Cancer. Curr Pharm Biotechnol 2025; 26:143-168. [PMID: 38415488 DOI: 10.2174/0113892010284407240212110745] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2023] [Revised: 12/29/2023] [Accepted: 01/16/2024] [Indexed: 02/29/2024]
Abstract
Pancreatic cancer kills millions of people worldwide each year and is one of the most prevalent causes of mortality that requires prompt therapy. A large number of people suffering from pancreatic cancer are detected at an advanced stage, with incurable and drug-resistant tumor, hence the overall survival rate of pancreatic cancer is less. The advance phase of this cancer is generated because of expression of the cancer-causing gene, inactivation of the tumorsuppressing gene, and deregulation of molecules in different cellular signalling pathways. The prompt diagnosis through the biomarkers significantly evades the progress and accelerates the survival rates. The overexpression of Mesothelin, Urokinase plasminogen activator, IGFR, Epidermal growth factor receptor, Plectin-1, Mucin-1 and Zinc transporter 4 were recognized in the diagnosis of pancreatic cancer. Nanotechnology has led to the development of nanocarriersbased formulations (lipid, polymer, inorganic, carbon based and advanced nanocarriers) which overcome the hurdles of conventional therapy, chemotherapy and radiotherapy which causes toxicity to adjacent healthy tissues. The biocompatibility, toxicity and large-scale manufacturing are the hurdles associated with the nanocarriers-based approaches. Currently, Immunotherapybased techniques emerged as an efficient therapeutic alternative for the prevention of cancer. Immunological checkpoint targeting techniques have demonstrated significant efficacy in human cancers. Recent advancements in checkpoint inhibitors, adoptive T cell therapies, and cancer vaccines have shown potential in overcoming the immune evasion mechanisms of pancreatic cancer cells. Combining these immunotherapeutic approaches with nanocarriers holds great promise in enhancing the antitumor response and improving patient survival.
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Affiliation(s)
- Komal Sindhi
- Department of Pharmaceutics, SVKM NMIMS School of Pharmacy and Technology Management, Shirpur, 425405, India
| | - Abhishek Kanugo
- Department of Pharmaceutics, SVKM NMIMS School of Pharmacy and Technology Management, Shirpur, 425405, India
- Department of Pharmaceutical Quality Assurance, SVKM Institute of Pharmacy, Dhule, 424001, India
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8
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Javed S, Qureshi TA, Wang L, Azab L, Gaddam S, Pandol SJ, Li D. An insight to PDAC tumor heterogeneity across pancreatic subregions using computed tomography images. Front Oncol 2024; 14:1378691. [PMID: 39600638 PMCID: PMC11588633 DOI: 10.3389/fonc.2024.1378691] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2024] [Accepted: 10/21/2024] [Indexed: 11/29/2024] Open
Abstract
Pancreatic Ductal Adenocarcinoma (PDAC) is an exceptionally deadly form of pancreatic cancer with an extremely low survival rate. From diagnosis to treatment, PDAC is highly challenging to manage. Studies have demonstrated that PDAC tumors in distinct regions of the pancreas exhibit unique characteristics, influencing symptoms, treatment responses, and survival rates. Gaining insight into the heterogeneity of PDAC tumors based on their location in the pancreas can significantly enhance overall management of PDAC. Previous studies have explored PDAC tumor heterogeneity across pancreatic subregions based on their genetic and molecular profiles through biopsy-based histologic assessment. However, biopsy examinations are highly invasive and impractical for large populations. Abdominal imaging, such as Computed Tomography (CT) offers a completely non-invasive means to evaluate PDAC tumor heterogeneity across pancreatic subregions and an opportunity to correlate image feature of tumors with treatment outcome and monitoring. In this study, we explored the inter-tumor heterogeneity in PDAC tumors across three primary pancreatic subregions: the head, body, and tail. Utilizing contrast-enhanced abdominal CT scans and a thorough radiomic analysis of PDAC tumors, several morphological and textural tumor features were identified to be notably different between tumors in the head and those in the body and tail regions. To validate the significance of the identified features, a machine learning ML model was trained to automatically classify PDAC tumors into their respective regions i.e. head or body/tail subregion using their CT features. The study involved 200 CT abdominal scans, with 100 used for radiomic analysis and model training, and the remaining 100 for model testing. The ML model achieved an average classification accuracy, sensitivity, and specificity of 87%, 86%, and 88% on the testing scans respectively. Evaluating the heterogeneity of PDAC tumors across pancreatic subregions provides valuable insights into tumor composition and has the potential to enhance diagnosis and personalize treatment based on tumor characteristics and location.
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Affiliation(s)
- Sehrish Javed
- Cedars Sinai Medical Center, Los Angeles, CA, United States
| | | | | | | | | | | | - Debiao Li
- Cedars Sinai Medical Center, Los Angeles, CA, United States
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9
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Lencioni G, Gregori A, Toledo B, Rebelo R, Immordino B, Amrutkar M, Xavier CPR, Kocijančič A, Pandey DP, Perán M, Castaño JP, Walsh N, Giovannetti E. Unravelling the complexities of resistance mechanism in pancreatic cancer: Insights from in vitro and ex-vivo model systems. Semin Cancer Biol 2024; 106-107:217-233. [PMID: 39299411 DOI: 10.1016/j.semcancer.2024.09.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2024] [Revised: 09/07/2024] [Accepted: 09/09/2024] [Indexed: 09/22/2024]
Abstract
Pancreatic ductal adenocarcinoma (PDAC) is an aggressive cancer with poor prognosis and rising global deaths. Late diagnosis, due to absent early symptoms and biomarkers, limits treatment mainly to chemotherapy, which soon encounters resistance. PDAC treatment innovation is hampered by its complex and heterogeneous resistant nature, including mutations in key genes and a stromal-rich, immunosuppressive tumour microenvironment. Recent studies on PDAC resistance stress the need for suitable in vitro and ex vivo models to replicate its complex molecular and microenvironmental landscape. This review summarises advances in these models, which can aid in combating chemoresistance and serve as platforms for discovering new therapeutics. Immortalised cell lines offer homogeneity, unlimited proliferation, and reproducibility, but while many gemcitabine-resistant PDAC cell lines exist, fewer models are available for resistance to other drugs. Organoids from PDAC patients show promise in mimicking tumour heterogeneity and chemosensitivity. Bioreactors, co-culture systems and organotypic slices, incorporating stromal and immune cells, are being developed to understand tumour-stroma interactions and the tumour microenvironment's role in drug resistance. Lastly, another innovative approach is three-dimensional bioprinting, which creates tissue-like structures resembling PDAC architecture, allowing for drug screening. These advanced models can guide researchers in selecting optimal in vitro tests, potentially improving therapeutic strategies and patient outcomes.
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Affiliation(s)
- Giulia Lencioni
- Fondazione Pisana per La Scienza, San Giuliano Terme, Italy; Department of Biology, University of Pisa, Pisa, Italy
| | - Alessandro Gregori
- Cancer Biology and Immunology, Cancer Center Amsterdam, Amsterdam, the Netherlands; Department of Medical Oncology, Amsterdam UMC, Location Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Belén Toledo
- Cancer Biology and Immunology, Cancer Center Amsterdam, Amsterdam, the Netherlands; Department of Health Sciences, University of Jaén, Campus Lagunillas, Jaén E-23071, Spain
| | - Rita Rebelo
- Cancer Biology and Immunology, Cancer Center Amsterdam, Amsterdam, the Netherlands; Instituto de Investigação e Inovação em Saúde (i3S), University of Porto, Porto 4200-135, Portugal; Cancer Drug Resistance Group, Institute of Molecular Pathology and Immunology (IPATIMUP), University of Porto, Porto 4200-135, Portugal; Department of Biological Sciences, Faculty of Pharmacy of the University of Porto (FFUP), Porto, Portugal
| | - Benoît Immordino
- Fondazione Pisana per La Scienza, San Giuliano Terme, Italy; Institute of Life Sciences, Sant'Anna School of Advanced Studies, Pisa, Italy
| | - Manoj Amrutkar
- Department of Pathology, Oslo University Hospital Rikshospitalet, Oslo, Norway
| | - Cristina P R Xavier
- Instituto de Investigação e Inovação em Saúde (i3S), University of Porto, Porto 4200-135, Portugal; Cancer Drug Resistance Group, Institute of Molecular Pathology and Immunology (IPATIMUP), University of Porto, Porto 4200-135, Portugal; UCIBIO - Applied Molecular Biosciences Unit, Toxicologic Pathology Research Laboratory, University Institute of Health Sciences (1H-TOXRUN, IUCS-CESPU), Gandra, Portugal; Associate Laboratory i4HB - Institute for Health and Bioeconomy, University Institute of Health Sciences - CESPU, Gandra, Portugal
| | - Anja Kocijančič
- Centre for Embryology and Healthy Development, Department of Microbiology, Rikshospitalet, Oslo University Hospital, Oslo, Norway
| | - Deo Prakash Pandey
- Centre for Embryology and Healthy Development, Department of Microbiology, Rikshospitalet, Oslo University Hospital, Oslo, Norway
| | - Macarena Perán
- Department of Health Sciences, University of Jaén, Campus Lagunillas, Jaén E-23071, Spain; Biopathology and Regenerative Medicine Institute (IBIMER), Centre for Biomedical Research (CIBM), University of Granada, Granada, Spain; Excellence Research Unit "Modeling Nature" (MNat), University of Granada, Granada, Spain
| | - Justo P Castaño
- Maimonides Biomedical Research Institute of Cordoba (IMIBIC), Córdoba, Spain; Department of Cell Biology, Physiology, and Immunology, University of Córdoba, Córdoba, Spain; Reina Sofia University Hospital, Córdoba, Spain; CIBER Fisiopatología de la Obesidad y Nutrición (CIBERobn), Córdoba, Spain
| | - Naomi Walsh
- Life Sciences Institute, School of Biotechnology, Dublin City University, Dublin, Ireland
| | - Elisa Giovannetti
- Fondazione Pisana per La Scienza, San Giuliano Terme, Italy; Cancer Biology and Immunology, Cancer Center Amsterdam, Amsterdam, the Netherlands; Department of Medical Oncology, Amsterdam UMC, Location Vrije Universiteit Amsterdam, Amsterdam, the Netherlands.
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10
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Ahmed TM, Chu LC, Javed AA, Yasrab M, Blanco A, Hruban RH, Fishman EK, Kawamoto S. Hidden in plain sight: commonly missed early signs of pancreatic cancer on CT. Abdom Radiol (NY) 2024; 49:3599-3614. [PMID: 38782784 DOI: 10.1007/s00261-024-04334-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2024] [Revised: 04/03/2024] [Accepted: 04/05/2024] [Indexed: 05/25/2024]
Abstract
Pancreatic ductal adenocarcinoma (PDAC) has poor prognosis mostly due to the advanced stage at which disease is diagnosed. Early detection of disease at a resectable stage is, therefore, critical for improving outcomes of patients. Prior studies have demonstrated that pancreatic abnormalities may be detected on CT in up to 38% of CT studies 5 years before clinical diagnosis of PDAC. In this review, we highlight commonly missed signs of early PDAC on CT. Broadly, these commonly missed signs consist of small isoattenuating PDAC without contour deformity, isolated pancreatic duct dilatation and cutoff, focal pancreatic enhancement and focal parenchymal atrophy, pancreatitis with underlying PDAC, and vascular encasement. Through providing commentary on demonstrative examples of these signs, we demonstrate how to reduce the risk of missing or misinterpreting radiological features of early PDAC.
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Affiliation(s)
- Taha M Ahmed
- The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, JHOC 3140E, 601 N Caroline St, Baltimore, MD, 21287, USA
| | - Linda C Chu
- The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, JHOC 3140E, 601 N Caroline St, Baltimore, MD, 21287, USA
| | - Ammar A Javed
- Department of Surgery, New York University Grossman School of Medicine, New York, NY, USA
| | - Mohammad Yasrab
- The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, JHOC 3140E, 601 N Caroline St, Baltimore, MD, 21287, USA
| | - Alejandra Blanco
- The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, JHOC 3140E, 601 N Caroline St, Baltimore, MD, 21287, USA
| | - Ralph H Hruban
- Sol Goldman Pancreatic Cancer Research Center, Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Elliot K Fishman
- The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, JHOC 3140E, 601 N Caroline St, Baltimore, MD, 21287, USA
| | - Satomi Kawamoto
- The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, JHOC 3140E, 601 N Caroline St, Baltimore, MD, 21287, USA.
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11
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Kataria B, Woisetschläger M, Nilsson Althén J, Sandborg M, Smedby Ö. Image quality assessments in abdominal CT: Relative importance of dose, iterative reconstruction strength and slice thickness. Radiography (Lond) 2024; 30:1563-1571. [PMID: 39378665 DOI: 10.1016/j.radi.2024.09.060] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2024] [Revised: 08/20/2024] [Accepted: 09/23/2024] [Indexed: 10/10/2024]
Abstract
INTRODUCTION Low contrast resolution in abdominal computed tomography (CT) may be negatively affected by attempts to lower patient doses. Iterative reconstruction (IR) algorithms play a key role in mitigating this problem. The reconstructed slice thickness also influences image quality. The aim was to assess the interaction and influence of patient dose, slice thickness, and IR strength on image quality in abdominal CT. METHOD With a simultaneous acquisition, images at 42 and 98 mAs were obtained in 25 patients. Multiplanar images with slice thicknesses of 1, 2, and 3 mm and advanced modeled iterative reconstruction (ADMIRE) strengths of 3 (AD3) and 5 (AD5) were reconstructed. Four radiologists evaluated the images in a pairwise manner based on five image criteria. Ordinal logistic regression with mixed effects was used to evaluate the effect of tube load, ADMIRE strength, and slice thickness using the visual grading regression technique. RESULTS For all assessed image criteria, the regression analysis showed significantly (p < 0.001) higher image quality for AD5, but lower for tube load 42 mAs, and slice thicknesses of 1 mm and 2 mm, compared to the reference categories of AD3, 98 mAs, and 3 mm, respectively. AD5 at 2 mm was superior to AD3 at 3 mm for all image criteria studied. AD5 1 mm produced inferior image quality for liver parenchyma and overall image quality compared to AD3 3 mm. Interobserver agreement (ICC) ranged from 0.874 to 0.920. CONCLUSION ADMIRE 5 at 2 mm slice thickness may allow for further dose reductions due to its superiority when compared to ADMIRE 3 at 3 mm slice thickness. IMPLICATIONS FOR PRACTICE Combination of thinner slices and higher ADMIRE strength facilitates imaging at low dose.
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Affiliation(s)
- B Kataria
- Department of Radiology, Linköping University, Linköping, Sweden; Department of Health, Medicine & Caring Sciences, Linköping University, Linköping, Sweden; Center for Medical Image Science & Visualization (CMIV), Linköping University, Linköping, Sweden.
| | - M Woisetschläger
- Department of Radiology, Linköping University, Linköping, Sweden; Department of Health, Medicine & Caring Sciences, Linköping University, Linköping, Sweden; Center for Medical Image Science & Visualization (CMIV), Linköping University, Linköping, Sweden.
| | - J Nilsson Althén
- Department of Health, Medicine & Caring Sciences, Linköping University, Linköping, Sweden; Department of Medical Physics, Linköping University, Linköping, Sweden.
| | - M Sandborg
- Department of Health, Medicine & Caring Sciences, Linköping University, Linköping, Sweden; Center for Medical Image Science & Visualization (CMIV), Linköping University, Linköping, Sweden; Department of Medical Physics, Linköping University, Linköping, Sweden.
| | - Ö Smedby
- Department of Biomedical Engineering and Health Systems (MTH), KTH Royal Institute of Technology, Stockholm, Sweden.
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12
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Manne A, Esnakula A, Sheel A, Sara A, Manne U, Paluri RK, He K, Yang W, Sohal D, Kasi A, Noonan AM, Mittra A, Hays J, Roychowdhury S, Malalur P, Rahman S, Jin N, Cloyd JM, Tsai S, Ejaz A, Pitter K, Miller E, Thanikachalam K, Dillhoff M, Yu L. Mature MUC5AC Expression in Resected Pancreatic Ductal Adenocarcinoma Predicts Treatment Response and Outcomes. Int J Mol Sci 2024; 25:9041. [PMID: 39201728 PMCID: PMC11354508 DOI: 10.3390/ijms25169041] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2024] [Revised: 08/13/2024] [Accepted: 08/19/2024] [Indexed: 09/03/2024] Open
Abstract
Neoadjuvant therapy (NAT) for early-stage pancreatic ductal adenocarcinoma (PDA) has recently gained prominence. We investigated the clinical significance of mucin 5 AC (MUC5AC), which exists in two major glycoforms, a less-glycosylated immature isoform (IM) and a heavily glycosylated mature isoform (MM), as a biomarker in resected PDA. Immunohistochemistry was performed on 100 resected PDAs to evaluate the expression of the IM and MM of MUC5AC using their respective monoclonal antibodies, CLH2 (NBP2-44455) and 45M1 (ab3649). MUC5AC localization (cytoplasmic, apical, and extra-cellular (EC)) was determined, and the H-scores were calculated. Univariate and multivariate (MVA) Cox regression models were used to estimate progression-free survival (PFS) and overall survival (OS). Of 100 resected PDA patients, 43 received NAT, and 57 were treatment-naïve with upfront surgery (UpS). In the study population (n = 100), IM expression (H-scores for objective response vs. no response vs. UpS = 104 vs. 152 vs. 163, p = 0.01) and MM-MUC5AC detection rates (56% vs. 63% vs. 82%, p = 0.02) were significantly different. In the NAT group, MM-MUC5AC-negative patients had significantly better PFS according to the MVA (Hazard Ratio: 0.2, 95% CI: 0.059-0.766, p = 0.01). Similar results were noted in a FOLFIRINOX sub-group (n = 36). We established an association of MUC5AC expression with treatment response and outcomes.
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Affiliation(s)
- Ashish Manne
- Department of Internal Medicine, Division of Medical Oncology, The Ohio State University Comprehensive Cancer Center (OSU-CCC), Columbus, OH 43210, USA
| | - Ashwini Esnakula
- Department of Pathology, The Ohio State University Comprehensive Cancer Center (OSU-CCC), Columbus, OH 43210, USA;
| | - Ankur Sheel
- Department of Internal Medicine, Division of Medical Oncology, The Ohio State University Comprehensive Cancer Center (OSU-CCC), Columbus, OH 43210, USA
| | - Amir Sara
- Department of Internal Medicine, Division of Medical Oncology, The Ohio State University Comprehensive Cancer Center (OSU-CCC), Columbus, OH 43210, USA
| | - Upender Manne
- Department of Pathology, University of Alabama at Birmingham, Birmingham, AL 35233, USA
| | - Ravi Kumar Paluri
- Division of Hematology-Oncology, Department of Internal Medicine, Atrium Health Wake Forest Baptist Comprehensive Cancer Center, Winston-Salem, NC 27103, USA
| | - Kai He
- Department of Internal Medicine, Division of Medical Oncology, The Ohio State University Comprehensive Cancer Center (OSU-CCC), Columbus, OH 43210, USA
| | - Wancai Yang
- Comprehensive Cancer Center, The Ohio State University, Columbus, OH 43210, USA
| | - Davendra Sohal
- Department of Internal Medicine, Division of Hematology/Oncology, College of Medicine, University of Cincinnati, Cincinnati, OH 45267, USA
| | - Anup Kasi
- Division of Medical Oncology, University of Kansas Cancer Center, Westwood, KS 66205, USA
| | - Anne M. Noonan
- Department of Internal Medicine, Division of Medical Oncology, The Ohio State University Comprehensive Cancer Center (OSU-CCC), Columbus, OH 43210, USA
| | - Arjun Mittra
- Department of Internal Medicine, Division of Medical Oncology, The Ohio State University Comprehensive Cancer Center (OSU-CCC), Columbus, OH 43210, USA
| | - John Hays
- Department of Internal Medicine, Division of Medical Oncology, The Ohio State University Comprehensive Cancer Center (OSU-CCC), Columbus, OH 43210, USA
| | - Sameek Roychowdhury
- Department of Internal Medicine, Division of Medical Oncology, The Ohio State University Comprehensive Cancer Center (OSU-CCC), Columbus, OH 43210, USA
| | - Pannaga Malalur
- Department of Internal Medicine, Division of Medical Oncology, The Ohio State University Comprehensive Cancer Center (OSU-CCC), Columbus, OH 43210, USA
| | - Shafia Rahman
- Department of Internal Medicine, Division of Medical Oncology, The Ohio State University Comprehensive Cancer Center (OSU-CCC), Columbus, OH 43210, USA
| | - Ning Jin
- Department of Internal Medicine, Division of Medical Oncology, The Ohio State University Comprehensive Cancer Center (OSU-CCC), Columbus, OH 43210, USA
| | - Jordan M. Cloyd
- Department of Surgery, Division of Surgical Oncology, The Ohio State University Comprehensive Cancer Center (OSU-CCC), Columbus, OH 43221, USA
| | - Susan Tsai
- Department of Surgery, Division of Surgical Oncology, The Ohio State University Comprehensive Cancer Center (OSU-CCC), Columbus, OH 43221, USA
| | - Aslam Ejaz
- Department of Surgical Oncology, University of Illinois College of Medicine, Chicago, IL 60612, USA
| | - Kenneth Pitter
- Department of Radiation Oncology, The Ohio State University Comprehensive Cancer Center (OSU-CCC), Columbus, OH 43210, USA (E.M.)
| | - Eric Miller
- Department of Radiation Oncology, The Ohio State University Comprehensive Cancer Center (OSU-CCC), Columbus, OH 43210, USA (E.M.)
| | - Kannan Thanikachalam
- Center of Biostatistics and Bioinformatics, Roswell Park Comprehensive Cancer Center, 665 Elm St, Buffalo, NY 14203, USA
| | - Mary Dillhoff
- Department of Surgery, Division of Surgical Oncology, The Ohio State University Comprehensive Cancer Center (OSU-CCC), Columbus, OH 43221, USA
| | - Lianbo Yu
- Center of Biostatistics and Bioinformatics, The Ohio State University, Columbus, OH 43210, USA
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13
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Yang E, Kim JH, Min JH, Jeong WK, Hwang JA, Lee JH, Shin J, Kim H, Lee SE, Baek SY. nnU-Net-Based Pancreas Segmentation and Volume Measurement on CT Imaging in Patients with Pancreatic Cancer. Acad Radiol 2024; 31:2784-2794. [PMID: 38350812 DOI: 10.1016/j.acra.2024.01.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2023] [Revised: 12/29/2023] [Accepted: 01/03/2024] [Indexed: 02/15/2024]
Abstract
RATIONALE AND OBJECTIVES To develop and validate a deep learning (DL)-based method for pancreas segmentation on CT and automatic measurement of pancreatic volume in pancreatic cancer. MATERIALS AND METHODS This retrospective study used 3D nnU-net architecture for fully automated pancreatic segmentation in patients with pancreatic cancer. The study used 851 portal venous phase CT images (499 pancreatic cancer and 352 normal pancreas). This dataset was divided into training (n = 506), internal validation (n = 126), and external test set (n = 219). For the external test set, the pancreas was manually segmented by two abdominal radiologists (R1 and R2) to obtain the ground truth. In addition, the consensus segmentation was obtained using Simultaneous Truth and Performance Level Estimation (STAPLE) algorithm. Segmentation performance was assessed using the Dice similarity coefficient (DSC). Next, the pancreatic volumes determined by automatic segmentation were compared to those determined by manual segmentation by two radiologists. RESULTS The DL-based model for pancreatic segmentation showed a mean DSC of 0.764 in the internal validation dataset and DSC of 0.807, 0.805, and 0.803 using R1, R2, and STAPLE as references in the external test dataset. The pancreas parenchymal volume measured by automatic and manual segmentations were similar (DL-based model: 65.5 ± 19.3 cm3 and STAPLE: 65.1 ± 21.4 cm3; p = 0.486). The pancreatic parenchymal volume difference between the DL-based model predictions and the manual segmentation by STAPLE was 0.5 cm3, with correlation coefficients of 0.88. CONCLUSION The DL-based model efficiently generates automatic segmentation of the pancreas and measures the pancreatic volume in patients with pancreatic cancer.
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Affiliation(s)
- Ehwa Yang
- Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
| | - Jae-Hun Kim
- Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
| | - Ji Hye Min
- Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea.
| | - Woo Kyoung Jeong
- Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
| | - Jeong Ah Hwang
- Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
| | - Jeong Hyun Lee
- Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
| | - Jaeseung Shin
- Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
| | - Honsoul Kim
- Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
| | - Seol Eui Lee
- Research Institute for Future Medicine, Samsung Medical Center, Seoul, Republic of Korea
| | - Sun-Young Baek
- Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea; Research Institute for Future Medicine, Samsung Medical Center, Seoul, Republic of Korea
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14
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Ramaekers M, Viviers CGA, Hellström TAE, Ewals LJS, Tasios N, Jacobs I, Nederend J, van der Sommen F, Luyer MDP. Improved Pancreatic Cancer Detection and Localization on CT Scans: A Computer-Aided Detection Model Utilizing Secondary Features. Cancers (Basel) 2024; 16:2403. [PMID: 39001465 PMCID: PMC11240790 DOI: 10.3390/cancers16132403] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2024] [Revised: 06/27/2024] [Accepted: 06/28/2024] [Indexed: 07/16/2024] Open
Abstract
The early detection of pancreatic ductal adenocarcinoma (PDAC) is essential for optimal treatment of pancreatic cancer patients. We propose a tumor detection framework to improve the detection of pancreatic head tumors on CT scans. In this retrospective research study, CT images of 99 patients with pancreatic head cancer and 98 control cases from the Catharina Hospital Eindhoven were collected. A multi-stage 3D U-Net-based approach was used for PDAC detection including clinically significant secondary features such as pancreatic duct and common bile duct dilation. The developed algorithm was evaluated using a local test set comprising 59 CT scans. The model was externally validated in 28 pancreatic cancer cases of a publicly available medical decathlon dataset. The tumor detection framework achieved a sensitivity of 0.97 and a specificity of 1.00, with an area under the receiver operating curve (AUROC) of 0.99, in detecting pancreatic head cancer in the local test set. In the external test set, we obtained similar results, with a sensitivity of 1.00. The model provided the tumor location with acceptable accuracy obtaining a DICE Similarity Coefficient (DSC) of 0.37. This study shows that a tumor detection framework utilizing CT scans and secondary signs of pancreatic cancer can detect pancreatic tumors with high accuracy.
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Affiliation(s)
- Mark Ramaekers
- Department of Surgery, Catharina Cancer Institute, Catharina Hospital Eindhoven, EJ 5623 Eindhoven, The Netherlands;
| | - Christiaan G. A. Viviers
- Department of Electrical Engineering, Eindhoven University of Technology, AZ 5612 Eindhoven, The Netherlands; (C.G.A.V.); (T.A.E.H.); (F.v.d.S.)
| | - Terese A. E. Hellström
- Department of Electrical Engineering, Eindhoven University of Technology, AZ 5612 Eindhoven, The Netherlands; (C.G.A.V.); (T.A.E.H.); (F.v.d.S.)
| | - Lotte J. S. Ewals
- Department of Radiology, Catharina Cancer Institute, Catharina Hospital Eindhoven, EJ 5623 Eindhoven, The Netherlands; (L.J.S.E.); (J.N.)
| | - Nick Tasios
- Department of Hospital Services and Informatics, Philips Research, AE 5656 Eindhoven, The Netherlands (I.J.)
| | - Igor Jacobs
- Department of Hospital Services and Informatics, Philips Research, AE 5656 Eindhoven, The Netherlands (I.J.)
| | - Joost Nederend
- Department of Radiology, Catharina Cancer Institute, Catharina Hospital Eindhoven, EJ 5623 Eindhoven, The Netherlands; (L.J.S.E.); (J.N.)
| | - Fons van der Sommen
- Department of Electrical Engineering, Eindhoven University of Technology, AZ 5612 Eindhoven, The Netherlands; (C.G.A.V.); (T.A.E.H.); (F.v.d.S.)
| | - Misha D. P. Luyer
- Department of Surgery, Catharina Cancer Institute, Catharina Hospital Eindhoven, EJ 5623 Eindhoven, The Netherlands;
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15
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Sun X, Wang S, Wong CC. Mass spectrometry–based proteomics technology in pancreatic cancer research. JOURNAL OF PANCREATOLOGY 2024; 7:145-163. [DOI: 10.1097/jp9.0000000000000152] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/03/2025] Open
Abstract
Pancreatic ductal adenocarcinoma (PDAC) has become a significant health concern with increasing incidence and mortality rates over the past few decades. Researchers have turned their attention to cutting-edge mass spectrometry (MS) technology due to its high-throughput and accurate detection capacity, which plays a vital role in understanding the mechanisms and discovering biomarkers for pancreatic diseases. In this review, we comprehensively investigate various methodologies of quantitative and qualitative proteomics MS technologies, alongside bioinformatical platforms employed in pancreatic cancer research. The integration of these optimized approaches provides novel insights into the molecular mechanisms underlying tumorigenesis and disease progression, ultimately facilitating the discovery of potential diagnostic, prognostic biomarkers, and therapeutic targets. The robust MS-based strategy shows promise in paving the way for early diagnosis and personalized medicine for pancreatic cancer patients.
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Affiliation(s)
- Xue Sun
- First School of Clinical Medicine, Peking University Health Science Center, Peking University, Beijing 100871, China
- School of Pharmacy, University of Wisconsin-Madison, Madison, Wisconsin 53705, United States
| | - Siyuan Wang
- State Key Laboratory of Complex Severe and Rare Diseases, Clinical Research Institute, Peking Union Medical College Hospital, Chinese Academy of Medical Science & Peking Union Medical College, Beijing 100730, China
| | - Catherine C.L. Wong
- First School of Clinical Medicine, Peking University Health Science Center, Peking University, Beijing 100871, China
- State Key Laboratory of Complex Severe and Rare Diseases, Clinical Research Institute, Peking Union Medical College Hospital, Chinese Academy of Medical Science & Peking Union Medical College, Beijing 100730, China
- Tsinghua-Peking University Joint Center for Life Sciences, Tsinghua University, Beijing 100084, China
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16
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Mayer P, Hausen A, Steinle V, Bergmann F, Kauczor HU, Loos M, Roth W, Klauss M, Gaida MM. The radiomorphological appearance of the invasive margin in pancreatic cancer is associated with tumor budding. Langenbecks Arch Surg 2024; 409:167. [PMID: 38809279 PMCID: PMC11136832 DOI: 10.1007/s00423-024-03355-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2024] [Accepted: 05/16/2024] [Indexed: 05/30/2024]
Abstract
PURPOSE Pancreatic cancer (PDAC) is characterized by infiltrative, spiculated tumor growth into the surrounding non-neoplastic tissue. Clinically, its diagnosis is often established by magnetic resonance imaging (MRI). At the invasive margin, tumor buds can be detected by histology, an established marker associated with poor prognosis in different types of tumors. METHODS We analyzed PDAC by determining the degree of tumor spiculation on T2-weighted MRI using a 3-tier grading system. The grade of spiculation was correlated with the density of tumor buds quantified in histological sections of the respective surgical specimen according to the guidelines of the International Tumor Budding Consensus Conference (n = 28 patients). RESULTS 64% of tumors revealed intermediate to high spiculation on MRI. In over 90% of cases, tumor buds were detected. We observed a significant positive rank correlation between the grade of radiological tumor spiculation and the histopathological number of tumor buds (rs = 0.745, p < 0.001). The number of tumor buds was not significantly associated with tumor stage, presence of lymph node metastases, or histopathological grading (p ≥ 0.352). CONCLUSION Our study identifies a readily available radiological marker for non-invasive estimation of tumor budding, as a correlate for infiltrative tumor growth. This finding could help to identify PDAC patients who might benefit from more extensive peripancreatic soft tissue resection during surgery or stratify patients for personalized therapy concepts.
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Affiliation(s)
- Philipp Mayer
- Clinic for Diagnostic and Interventional Radiology, University Hospital Heidelberg, Heidelberg, 69120, Germany.
| | - Anne Hausen
- Institute of Pathology, University Medical Center Mainz, JGU-Mainz, Mainz, 55131, Germany.
| | - Verena Steinle
- Clinic for Diagnostic and Interventional Radiology, University Hospital Heidelberg, Heidelberg, 69120, Germany
| | - Frank Bergmann
- Institute of Pathology, University Hospital Heidelberg, Heidelberg, 69120, Germany
- Clinical Pathology, Klinikum Darmstadt GmbH, Darmstadt, 64283, Germany
| | - Hans-Ulrich Kauczor
- Clinic for Diagnostic and Interventional Radiology, University Hospital Heidelberg, Heidelberg, 69120, Germany
| | - Martin Loos
- Department of General, Visceral, and Transplantation Surgery, University Hospital Heidelberg, Heidelberg, 69120, Germany
| | - Wilfried Roth
- Institute of Pathology, University Medical Center Mainz, JGU-Mainz, Mainz, 55131, Germany
| | - Miriam Klauss
- Clinic for Diagnostic and Interventional Radiology, University Hospital Heidelberg, Heidelberg, 69120, Germany
| | - Matthias M Gaida
- Institute of Pathology, University Medical Center Mainz, JGU-Mainz, Mainz, 55131, Germany
- Translational Oncology, TRON, the University Medical Center, JGU-Mainz, Mainz, 55131, Germany
- Research Center for Immunotherapy, University Medical Center Mainz, JGU-Mainz, Mainz, 55131, Germany
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17
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Cai W, Zhu Y, Teng Z, Li D, Cong R, Chen Z, Ma X, Zhao X. Extracellular volume-based scoring system for tracking tumor progression in pancreatic cancer patients receiving intraoperative radiotherapy. Insights Imaging 2024; 15:116. [PMID: 38735009 PMCID: PMC11089023 DOI: 10.1186/s13244-024-01689-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2023] [Accepted: 04/03/2024] [Indexed: 05/13/2024] Open
Abstract
OBJECTIVES To investigate the value of extracellular volume (ECV) derived from portal-venous phase (PVP) in predicting prognosis in locally advanced pancreatic cancer (LAPC) patients receiving intraoperative radiotherapy (IORT) with initial stable disease (SD) and to construct a risk-scoring system based on ECV and clinical-radiological features. MATERIALS AND METHODS One hundred and three patients with LAPC who received IORT demonstrating SD were enrolled and underwent multiphasic contrast-enhanced CT (CECT) before and after IORT. ECV maps were generated from unenhanced and PVP CT images. Clinical and CT imaging features were analyzed. The independent predictors of progression-free survival (PFS) determined by multivariate Cox regression model were used to construct the risk-scoring system. Time-dependent receiver operating characteristic (ROC) curve analysis and the Kaplan-Meier method were used to evaluate the predictive performance of the scoring system. RESULTS Multivariable analysis revealed that ECV, rim-enhancement, peripancreatic fat infiltration, and carbohydrate antigen 19-9 (CA19-9) response were significant predictors of PFS (all p < 0.05). Time-dependent ROC of the risk-scoring system showed a satisfactory predictive performance for disease progression with area under the curve (AUC) all above 0.70. High-risk patients (risk score ≥ 2) progress significantly faster than low-risk patients (risk score < 2) (p < 0.001). CONCLUSION ECV derived from PVP of conventional CECT was an independent predictor for progression in LAPC patients assessed as SD after IORT. The scoring system integrating ECV, radiological features, and CA19-9 response can be used as a practical tool for stratifying prognosis in these patients, assisting clinicians in developing an appropriate treatment approach. CRITICAL RELEVANCE STATEMENT The scoring system integrating ECV fraction, radiological features, and CA19-9 response can track tumor progression in patients with LAPC receiving IORT, aiding clinicians in choosing individual treatment strategies and improving their prognosis. KEY POINTS Predicting the progression of LAPC in patients receiving IORT is important. Our ECV-based scoring system can risk stratifying patients with initial SD. Appropriate prognostication can assist clinicians in developing appropriate treatment approaches.
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Affiliation(s)
- Wei Cai
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Yongjian Zhu
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Ze Teng
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Dengfeng Li
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Rong Cong
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Zhaowei Chen
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Xiaohong Ma
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
| | - Xinming Zhao
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
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18
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Șolea SF, Brisc MC, Orășeanu A, Venter FC, Brisc CM, Șolea RM, Davidescu L, Venter A, Brisc C. Revolutionizing the Pancreatic Tumor Diagnosis: Emerging Trends in Imaging Technologies: A Systematic Review. MEDICINA (KAUNAS, LITHUANIA) 2024; 60:695. [PMID: 38792878 PMCID: PMC11122838 DOI: 10.3390/medicina60050695] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/27/2024] [Revised: 04/19/2024] [Accepted: 04/21/2024] [Indexed: 05/26/2024]
Abstract
Background and Objectives: The pancreas, ensconced within the abdominal cavity, requires a plethora of sophisticated imaging modalities for its comprehensive evaluation, with ultrasonography serving as a primary investigative technique. A myriad of pancreatic pathologies, encompassing pancreatic neoplasia and a spectrum of inflammatory diseases, are detectable through these imaging strategies. Nevertheless, the intricate anatomical confluence and the pancreas's deep-seated topography render the visualization and accurate diagnosis of its pathologies a formidable endeavor. The objective of our paper is to review the best diagnostic imagistic tools for the pancreas. Materials and Methods: we have gathered several articles using Prisma guidelines to determine the best imagistic methods. The imperative of pancreatic scanning transcends its diagnostic utility, proving to be a pivotal element in a multitude of clinical specialties, notably surgical oncology. Within this domain, multidetector computed tomography (MDCT) of the pancreas holds the distinction of being the paramount imaging modality, endorsed for its unrivaled capacity to delineate the staging and progression of pancreatic carcinoma. In synergy with MDCT, there has been a notable advent of avant-garde imaging techniques in recent years. These advanced methodologies, including ultrasonography, endoscopic ultrasonography, contrast-enhanced ultrasonography, and magnetic resonance imaging (MRI) conjoined with magnetic resonance cholangiopancreatography (MRCP), have broadened the horizon of tumor characterization, offering unparalleled depth and precision in oncological assessment. Other emerging diagnostic techniques, such as elastography, also hold a lot of potential and promise for the future of pancreatic imaging. Fine needle aspiration (FNA) is a quick, minimally invasive procedure to evaluate lumps using a thin needle to extract tissue for analysis. It is less invasive than surgical biopsies and usually performed as an outpatient with quick recovery. Its accuracy depends on sample quality, and the risks include minimal bleeding or discomfort. Results, guiding further treatment, are typically available within a week. Elastography is a non-invasive medical imaging technique that maps the elastic properties and stiffness of soft tissue. This method, often used in conjunction with ultrasound or MRI, helps differentiate between hard and soft areas in tissue, providing valuable diagnostic information. It is particularly useful for assessing liver fibrosis, thyroid nodules, breast lumps, and musculoskeletal conditions. The technique is painless and involves applying gentle pressure to the area being examined. The resulting images show tissue stiffness, indicating potential abnormalities. Elastography is advantageous for its ability to detect diseases in early stages and monitor treatment effectiveness. The procedure is quick, safe, and requires no special preparation, with results typically available immediately. Results: The assembled and gathered data shows the efficacy of various techniques in discerning the nature and extent of neoplastic lesions within the pancreas. Conclusions: The most common imaging modalities currently used in diagnosing pancreatic neoplasms are multidetector computed tomography (MDCT), endoscopic ultrasound (EUS), and magnetic resonance imaging (MRI), alongside new technologies, such as elastography.
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Affiliation(s)
- Sabina Florina Șolea
- Doctoral School of Biological and Biomedical Sciences, University of Oradea, 410087 Oradea, Romania; (S.F.Ș.); (A.O.); (F.C.V.); (R.M.Ș.); (A.V.); (C.B.)
- Bihor Clinical County Emergency Hospital, 410169 Oradea, Romania
| | - Mihaela Cristina Brisc
- Bihor Clinical County Emergency Hospital, 410169 Oradea, Romania
- Department of Medical Disciplines, Faculty of Medicine and Pharmacy, University of Oradea, 410073 Oradea, Romania
| | - Alexandra Orășeanu
- Doctoral School of Biological and Biomedical Sciences, University of Oradea, 410087 Oradea, Romania; (S.F.Ș.); (A.O.); (F.C.V.); (R.M.Ș.); (A.V.); (C.B.)
- Bihor Clinical County Emergency Hospital, 410169 Oradea, Romania
| | - Florian Ciprian Venter
- Doctoral School of Biological and Biomedical Sciences, University of Oradea, 410087 Oradea, Romania; (S.F.Ș.); (A.O.); (F.C.V.); (R.M.Ș.); (A.V.); (C.B.)
- Bihor Clinical County Emergency Hospital, 410169 Oradea, Romania
| | - Ciprian Mihai Brisc
- Faculty of Medicine and Pharmacy, University of Oradea, 410068 Oradea, Romania; (C.M.B.); (L.D.)
| | - Răzvan Mihai Șolea
- Doctoral School of Biological and Biomedical Sciences, University of Oradea, 410087 Oradea, Romania; (S.F.Ș.); (A.O.); (F.C.V.); (R.M.Ș.); (A.V.); (C.B.)
| | - Lavinia Davidescu
- Faculty of Medicine and Pharmacy, University of Oradea, 410068 Oradea, Romania; (C.M.B.); (L.D.)
| | - Amina Venter
- Doctoral School of Biological and Biomedical Sciences, University of Oradea, 410087 Oradea, Romania; (S.F.Ș.); (A.O.); (F.C.V.); (R.M.Ș.); (A.V.); (C.B.)
| | - Ciprian Brisc
- Doctoral School of Biological and Biomedical Sciences, University of Oradea, 410087 Oradea, Romania; (S.F.Ș.); (A.O.); (F.C.V.); (R.M.Ș.); (A.V.); (C.B.)
- Bihor Clinical County Emergency Hospital, 410169 Oradea, Romania
- Department of Medical Disciplines, Faculty of Medicine and Pharmacy, University of Oradea, 410073 Oradea, Romania
- Faculty of Medicine and Pharmacy, University of Oradea, 410068 Oradea, Romania; (C.M.B.); (L.D.)
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19
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Gu X, Minko T. Targeted Nanoparticle-Based Diagnostic and Treatment Options for Pancreatic Cancer. Cancers (Basel) 2024; 16:1589. [PMID: 38672671 PMCID: PMC11048786 DOI: 10.3390/cancers16081589] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/29/2024] [Revised: 04/17/2024] [Accepted: 04/19/2024] [Indexed: 04/28/2024] Open
Abstract
Pancreatic ductal adenocarcinoma (PDAC), one of the deadliest cancers, presents significant challenges in diagnosis and treatment due to its aggressive, metastatic nature and lack of early detection methods. A key obstacle in PDAC treatment is the highly complex tumor environment characterized by dense stroma surrounding the tumor, which hinders effective drug delivery. Nanotechnology can offer innovative solutions to these challenges, particularly in creating novel drug delivery systems for existing anticancer drugs for PDAC, such as gemcitabine and paclitaxel. By using customization methods such as incorporating conjugated targeting ligands, tumor-penetrating peptides, and therapeutic nucleic acids, these nanoparticle-based systems enhance drug solubility, extend circulation time, improve tumor targeting, and control drug release, thereby minimizing side effects and toxicity in healthy tissues. Moreover, nanoparticles have also shown potential in precise diagnostic methods for PDAC. This literature review will delve into targeted mechanisms, pathways, and approaches in treating pancreatic cancer. Additional emphasis is placed on the study of nanoparticle-based delivery systems, with a brief mention of those in clinical trials. Overall, the overview illustrates the significant advances in nanomedicine, underscoring its role in transcending the constraints of conventional PDAC therapies and diagnostics.
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Affiliation(s)
- Xin Gu
- Department of Pharmaceutics, Ernest Mario School of Pharmacy, Rutgers, The State University of New Jersey, Piscataway, NJ 08554, USA
| | - Tamara Minko
- Department of Pharmaceutics, Ernest Mario School of Pharmacy, Rutgers, The State University of New Jersey, Piscataway, NJ 08554, USA
- Rutgers Cancer Institute of New Jersey, Rutgers, The State University of New Jersey, New Brunswick, NJ 08901, USA
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20
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Watcharanurak P, Mutirangura A, Aksornkitti V, Bhummaphan N, Puttipanyalears C. The high FKBP1A expression in WBCs as a potential screening biomarker for pancreatic cancer. Sci Rep 2024; 14:7888. [PMID: 38570626 PMCID: PMC10991374 DOI: 10.1038/s41598-024-58324-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2024] [Accepted: 03/27/2024] [Indexed: 04/05/2024] Open
Abstract
Given the limitation of current routine approaches for pancreatic cancer screening and detection, the mortality rate of pancreatic cancer cases is still critical. The development of blood-based molecular biomarkers for pancreatic cancer screening and early detection which provide less-invasive, high-sensitivity, and cost-effective, is urgently needed. The goal of this study is to identify and validate the potential molecular biomarkers in white blood cells (WBCs) of pancreatic cancer patients. Gene expression profiles of pancreatic cancer patients from NCBI GEO database were analyzed by CU-DREAM. Then, mRNA expression levels of three candidate genes were determined by quantitative RT-PCR in WBCs of pancreatic cancer patients (N = 27) and healthy controls (N = 51). ROC analysis was performed to assess the performance of each candidate gene. A total of 29 upregulated genes were identified and three selected genes were performed gene expression analysis. Our results revealed high mRNA expression levels in WBCs of pancreatic cancer patients in all selected genes, including FKBP1A (p < 0.0001), PLD1 (p < 0.0001), and PSMA4 (p = 0.0002). Among candidate genes, FKBP1A mRNA expression level was remarkably increased in the pancreatic cancer samples and also in the early stage (p < 0.0001). Moreover, FKBP1A showed the greatest performance to discriminate patients with pancreatic cancer from healthy individuals than other genes with the 88.9% sensitivity, 84.3% specificity, and 90.1% accuracy. Our findings demonstrated that the alteration of FKBP1A gene in WBCs serves as a novel valuable biomarker for patients with pancreatic cancer. Detection of FKBP1A mRNA expression level in circulating WBCs, providing high-sensitive, less-invasive, and cost-effective, is simple and feasible for routine clinical setting that can be applied for pancreatic cancer screening and early detection.
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Affiliation(s)
| | - Apiwat Mutirangura
- Department of Anatomy, Faculty of Medicine, Chulalongkorn University, 1873 Rama IV Road, Pathumwan, Bangkok, 10330, Thailand
- Center of Excellence in Molecular Genetics of Cancer and Human Diseases, Department of Anatomy, Faculty of Medicine, Chulalongkorn University, Bangkok, 10330, Thailand
| | - Vitavat Aksornkitti
- Department of Anatomy, Faculty of Medicine, Chulalongkorn University, 1873 Rama IV Road, Pathumwan, Bangkok, 10330, Thailand
| | - Narumol Bhummaphan
- College of Public Health Sciences, Chulalongkorn University, Sabbasastravicaya Building, Phayathai Road. Wangmai, Pathumwan, Bangkok, 10330, Thailand.
| | - Charoenchai Puttipanyalears
- Department of Anatomy, Faculty of Medicine, Chulalongkorn University, 1873 Rama IV Road, Pathumwan, Bangkok, 10330, Thailand.
- Center of Excellence in Molecular Genetics of Cancer and Human Diseases, Department of Anatomy, Faculty of Medicine, Chulalongkorn University, Bangkok, 10330, Thailand.
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21
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Asghar A, Narayan RK, Pushpa NB, Patra A, Ravi KS, Tubbs RS. Exploring the variations of the pancreatic ductal system: a systematic review and meta-analysis of observational studies. Anat Cell Biol 2024; 57:31-44. [PMID: 38351473 PMCID: PMC10968189 DOI: 10.5115/acb.23.148] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2023] [Revised: 12/09/2023] [Accepted: 12/24/2023] [Indexed: 03/23/2024] Open
Abstract
The exocrine part of the pancreas has a duct system called the pancreatic ductal system (PDS). Its mechanism of development is complex, and any reorganization during early embryogenesis can give rise to anatomical variants. The aim of this study is to collect, classify, and analyze published evidence on the importance of anatomical variants of the PDS, addressing gaps in our understanding of such variations. The MEDLINE, Web of Science, Embase, and Google Scholar databases were searched to identify publications relevant to this review. R studio with meta-package was used for data extraction, risk of bias estimation, and statistical analysis. A total of 64 studies out of 1,778 proved suitable for this review and metanalysis. The meta-analysis computed the prevalence of normal variants of the PDS (92% of 10,514 subjects). Type 3 variants and "descending" subtypes of the main pancreatic duct (MPD) predominated in the pooled samples. The mean lengths of the MPD and accessory pancreatic duct (APD) were 16.53 cm and 3.36 cm, respectively. The mean diameters of the MPD at the head and the APD were 3.43 mm and 1.69 mm, respectively. The APD was present in only 41% of samples, and the long type predominated. The pancreatic ductal anatomy is highly variable, and the incorrect identification of variants may be challenging for surgeons during ductal anastomosis with gut, failure to which may often cause ductal obstruction or pseudocysts formation.
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Affiliation(s)
- Adil Asghar
- Department of Anatomy, All India Institute of Medical Sciences, Patna, India
| | - Ravi Kant Narayan
- Department of Anatomy, ESIC Medical College & Hospital, Patna, India
| | | | - Apurba Patra
- All India Institute of Medical Sciences, Bathinda, India
| | | | - R. Shane Tubbs
- Tulane University School of Medicine, New Orleans, LA, USA
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22
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Tian XF, Yu LY, Yang DH, Zuo D, Cao JY, Wang Y, Yang ZY, Lou WH, Wang WP, Gong W, Dong Y. Contrast-enhanced ultrasound (CEUS) and shear wave elastography (SWE) features for characterizing serous microcystic adenomas (SMAs): In comparison to pancreatic neuroendocrine tumors (pNETs). Heliyon 2024; 10:e25185. [PMID: 38327470 PMCID: PMC10847598 DOI: 10.1016/j.heliyon.2024.e25185] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2023] [Revised: 01/19/2024] [Accepted: 01/22/2024] [Indexed: 02/09/2024] Open
Abstract
OBJECTIVES Serous microcystic adenoma (SMA), a primary benign pancreatic tumor which can be clinically followed-up instead of undergoing surgery, are sometimes mis-distinguished as pancreatic neuroendocrine tumor (pNET) in regular preoperative imaging examinations. This study aimed to analyze preoperative contrast-enhanced ultrasound (CEUS) and shear wave elastography (SWE) features of SMAs in comparison to pNETs. MATERIAL AND METHODS In this retrospective study, patients with imaging-diagnosed pancreatic lesions were screened between October 2020 to October 2022 (ethical approval No. B2020-309R). Performing by a Siemens Sequoia (Siemens Medical Solutions, Mountain View, CA, USA) equipped with a 5C-1 curved array transducer (3.0-4.5 MHz), CEUS examination was conducted to observe the microvascular perfusion patterns of pancreatic lesions in arterial phase, venous/late phases (VLP) using SonoVue® (Bracco Imaging Spa, Milan, Italy) as the contrast agent. Virtual touch tissue imaging and quantification (VTIQ) - SWE was used to measure the shear wave velocity (SWV, m/s) value to represent the quantitative stiffness of pancreatic lesions. Multivariate logistic regression was performed to analyze potential ultrasound and clinical features in discriminating SMAs and pNETs. RESULTS Finally, 30 SMA and 40 pNET patients were included. All pancreatic lesions were pathologically proven via biopsy or surgery. During the arterial phase of CEUS, most SMAs and pNETs showed iso- or hyperenhancement (29/30, 97 % and 31/40, 78 %), with a specific early honeycomb enhancement pattern appeared in 14/30 (47 %) SMA lesions. During the VLP, while most of the SMA lesions remained iso- or hyperenhancement (25/30, 83 %), nearly half of the pNET lesions revealed an attenuated hypoenhancement (17/40, 43 %). The proportion of hypoenhancement pattern during the VLP of CEUS differed significantly between SMAs and pNETs (P = 0.021). The measured SWV value of SMAs was significantly higher than pNETs (2.04 ± 0.70 m/s versus 1.42 ± 0.44 m/s, P = 0.002). Taking a SWV value > 1.83 m/s as a cutoff in differentiating SMAs and pNETs, the area under the receiver operating characteristic curve (AUROC) was 0.825, with sensitivity, specificity and likelihood ratio (+) of 85.71 %, 72.73 % and 3.143, respectively. Multivariate logistic regression revealed that SWV value (m/s) of the pancreatic lesion was an independent variable in discriminating SMA and pNET. CONCLUSION By comprehensively evaluating CEUS patterns and SWE features, SMA and pNET may be well differentiated before the operation. While SMA typically presents as harder lesion in VTIQ-SWE, exhibiting a specific honeycomb hyperenhancement pattern during the arterial phase of CEUS, pNET is characterized by relative softness, occasionally displaying a wash-out pattern during the VLP of CEUS.
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Affiliation(s)
- Xiao-Fan Tian
- Department of Ultrasound, Xinhua Hospital Affiliated to Shanghai Jiaotong University School of Medicine, 200092, Shanghai, China
| | - Ling-Yun Yu
- Department of Ultrasound, Xiamen Branch, Zhongshan Hospital, Fudan University, 361006, Xiamen, China
| | - Dao-Hui Yang
- Department of Ultrasound, Xiamen Branch, Zhongshan Hospital, Fudan University, 361006, Xiamen, China
| | - Dan Zuo
- Department of Ultrasound, Zhongshan Hospital, Fudan University, 200032, Shanghai, China
| | - Jia-Ying Cao
- Department of Ultrasound, Xinhua Hospital Affiliated to Shanghai Jiaotong University School of Medicine, 200092, Shanghai, China
| | - Ying Wang
- Department of Ultrasound, Xinhua Hospital Affiliated to Shanghai Jiaotong University School of Medicine, 200092, Shanghai, China
| | - Zi-Yi Yang
- Department of Surgery, Xinhua Hospital Affiliated to Shanghai Jiaotong University School of Medicine, 1665 Kongjiang Road, Shanghai, 200092, China
| | - Wen-Hui Lou
- Department of Pancreatic Surgery, Zhongshan Hospital, Fudan University, 200032, Shanghai, China
| | - Wen-Ping Wang
- Department of Ultrasound, Zhongshan Hospital, Fudan University, 200032, Shanghai, China
| | - Wei Gong
- Department of Surgery, Xinhua Hospital Affiliated to Shanghai Jiaotong University School of Medicine, 1665 Kongjiang Road, Shanghai, 200092, China
| | - Yi Dong
- Department of Ultrasound, Xinhua Hospital Affiliated to Shanghai Jiaotong University School of Medicine, 200092, Shanghai, China
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23
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Sok CP, Polireddy K, Kooby DA. Molecular pathology and protein markers for pancreatic cancer: relevance in staging, in adjuvant therapy, in determination of minimal residual disease, and follow-up. Hepatobiliary Surg Nutr 2024; 13:56-70. [PMID: 38322203 PMCID: PMC10839718 DOI: 10.21037/hbsn-22-628] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/28/2022] [Accepted: 05/10/2023] [Indexed: 02/08/2024]
Abstract
The diagnosis and monitoring of disease through the detection of circulating protein biomarkers is a growing field in the practice of oncology. The search for more effective protein biomarkers to aid in the diagnosis and treatment of patients with pancreatic ductal adenocarcinoma (PDAC) remains a valuable area of study, given the aggressive and often occult nature of this malignancy. Liquid biopsies are attractive, as they offer a minimally invasive and cost-effective approach when compared to traditional biopsy methods and imaging modalities used for diagnosis and surveillance. Carbohydrate antigen (CA) 19-9 is currently the most commonly used serum protein biomarker for the diagnosis and monitoring of patients with PDAC, but due to its sensitivity and specificity, its utility remains limited. In this review, we examine how circulating protein biomarkers are used in the diagnosis, prognostication, and surveillance of PDAC. We also highlight protein biomarkers that are currently under investigation that have the potential to enhance our ability to detect early-stage malignancies, predict response to therapy, and monitor for recurrence, but these markers require larger prospective validation studies before they can be widely implemented. Continued efforts to identify and validate novel biomarkers will be crucial for improving the management and outcomes of patients with this challenging disease.
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Affiliation(s)
- Caitlin P. Sok
- Department of Surgery, Emory University School of Medicine, Atlanta, GA, USA
| | - Karunesh Polireddy
- Department of Surgery, Emory University School of Medicine, Atlanta, GA, USA
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24
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Tripathi S, Tabari A, Mansur A, Dabbara H, Bridge CP, Daye D. From Machine Learning to Patient Outcomes: A Comprehensive Review of AI in Pancreatic Cancer. Diagnostics (Basel) 2024; 14:174. [PMID: 38248051 PMCID: PMC10814554 DOI: 10.3390/diagnostics14020174] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2023] [Revised: 12/28/2023] [Accepted: 12/29/2023] [Indexed: 01/23/2024] Open
Abstract
Pancreatic cancer is a highly aggressive and difficult-to-detect cancer with a poor prognosis. Late diagnosis is common due to a lack of early symptoms, specific markers, and the challenging location of the pancreas. Imaging technologies have improved diagnosis, but there is still room for improvement in standardizing guidelines. Biopsies and histopathological analysis are challenging due to tumor heterogeneity. Artificial Intelligence (AI) revolutionizes healthcare by improving diagnosis, treatment, and patient care. AI algorithms can analyze medical images with precision, aiding in early disease detection. AI also plays a role in personalized medicine by analyzing patient data to tailor treatment plans. It streamlines administrative tasks, such as medical coding and documentation, and provides patient assistance through AI chatbots. However, challenges include data privacy, security, and ethical considerations. This review article focuses on the potential of AI in transforming pancreatic cancer care, offering improved diagnostics, personalized treatments, and operational efficiency, leading to better patient outcomes.
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Affiliation(s)
- Satvik Tripathi
- Department of Radiology, Massachusetts General Hospital, Boston, MA 02114, USA; (S.T.); (A.T.); (A.M.); (C.P.B.)
- Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA 02129, USA
- Harvard Medical School, Boston, MA 02115, USA
| | - Azadeh Tabari
- Department of Radiology, Massachusetts General Hospital, Boston, MA 02114, USA; (S.T.); (A.T.); (A.M.); (C.P.B.)
- Harvard Medical School, Boston, MA 02115, USA
| | - Arian Mansur
- Department of Radiology, Massachusetts General Hospital, Boston, MA 02114, USA; (S.T.); (A.T.); (A.M.); (C.P.B.)
- Harvard Medical School, Boston, MA 02115, USA
| | - Harika Dabbara
- Boston University Chobanian & Avedisian School of Medicine, Boston, MA 02118, USA;
| | - Christopher P. Bridge
- Department of Radiology, Massachusetts General Hospital, Boston, MA 02114, USA; (S.T.); (A.T.); (A.M.); (C.P.B.)
- Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA 02129, USA
- Harvard Medical School, Boston, MA 02115, USA
| | - Dania Daye
- Department of Radiology, Massachusetts General Hospital, Boston, MA 02114, USA; (S.T.); (A.T.); (A.M.); (C.P.B.)
- Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA 02129, USA
- Harvard Medical School, Boston, MA 02115, USA
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25
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Zhang X, Detering L, Heo GS, Sultan D, Luehmann H, Li L, Somani V, Lesser J, Tao J, Kang LI, Li A, Lahad D, Rho S, Ruzinova MB, DeNardo DG, Dehdashti F, Lim KH, Liu Y. Chemokine Receptor 2 Targeted PET/CT Imaging Distant Metastases in Pancreatic Ductal Adenocarcinoma. ACS Pharmacol Transl Sci 2024; 7:285-293. [PMID: 38230294 PMCID: PMC10789124 DOI: 10.1021/acsptsci.3c00303] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2023] [Revised: 11/15/2023] [Accepted: 11/16/2023] [Indexed: 01/18/2024]
Abstract
Pancreatic ductal adenocarcinoma (PDAC) is one of the most aggressive and treatment-refractory malignancies. The lack of an effective screening tool results in the majority of patients being diagnosed at late stages, which underscores the urgent need to develop more sensitive and specific imaging modalities, particularly in detecting occult metastases, to aid clinical decision-making. The tumor microenvironment of PDAC is heavily infiltrated with myeloid-derived suppressor cells (MDSCs) that express C-C chemokine receptor type 2 (CCR2). These CCR2-expressing MDSCs accumulate at a very early stage of metastasis and greatly outnumber PDAC cells, making CCR2 a promising target for detecting early, small metastatic lesions that have scant PDAC cells. Herein, we evaluated a CCR2 targeting PET tracer (68Ga-DOTA-ECL1i) for PET imaging on PDAC metastasis in two mouse models. Positron emission tomography/computed tomography (PET/CT) imaging of 68Ga-DOTA-ECL1i was performed in a hemisplenic injection metastasis model (KI) and a genetically engineered orthotopic PDAC model (KPC), which were compared with 18F-FDG PET concurrently. Autoradiography, hematoxylin and eosin (H&E), and CCR2 immunohistochemical staining were performed to characterize the metastatic lesions. PET/CT images visualized the PDAC metastases in the liver/lung of KI mice and in the liver of KPC mice. Quantitative uptake analysis revealed increased metastasis uptake during disease progression in both models. In comparison, 18F-FDG PET failed to detect any metastases during the time course studies. H&E staining showed metastases in the liver and lung of KI mice, within which immunostaining clearly demonstrated the overexpression of CCR2 as well as CCR2+ cell infiltration into the normal liver. H&E staining, CCR2 staining, and autoradiography also confirmed the expression of CCR2 and the uptake of 68Ga-DOTA-ECL1i in the metastatic foci in KPC mice. Using our novel CCR2 targeted radiotracer 68Ga-DOTA-ECL1i and PET/CT, we demonstrated the sensitive and specific detection of CCR2 in the early PDAC metastases in two mouse models, indicating its potential in future clinical translation.
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Affiliation(s)
- Xiaohui Zhang
- Department
of Radiology, Washington University in St.
Louis, St. Louis, Missouri 63110, United States
| | - Lisa Detering
- Department
of Radiology, Washington University in St.
Louis, St. Louis, Missouri 63110, United States
| | - Gyu Seong Heo
- Department
of Radiology, Washington University in St.
Louis, St. Louis, Missouri 63110, United States
| | - Deborah Sultan
- Department
of Radiology, Washington University in St.
Louis, St. Louis, Missouri 63110, United States
| | - Hannah Luehmann
- Department
of Radiology, Washington University in St.
Louis, St. Louis, Missouri 63110, United States
| | - Lin Li
- Division
of Oncology, Department of Medicine, Washington
University in St. Louis, St. Louis, Missouri 63110, United States
| | - Vikas Somani
- Division
of Oncology, Department of Medicine, Washington
University in St. Louis, St. Louis, Missouri 63110, United States
| | - Josie Lesser
- Department
of Anthropology, Washington University in
St. Louis, St. Louis, Missouri 63110, United States
| | - Joan Tao
- Department
of Medicine, University of Missouri, Columbia, Missouri 65211, United States
| | - Liang-I. Kang
- Department
of Pathology and Immunology, Washington
University in St. Louis, St. Louis, Missouri 63110, United States
| | - Alexandria Li
- Department
of Radiology, Washington University in St.
Louis, St. Louis, Missouri 63110, United States
| | - Divangana Lahad
- Department
of Radiology, Washington University in St.
Louis, St. Louis, Missouri 63110, United States
| | - Shinji Rho
- Department
of Medicine, Washington University in St.
Louis, St. Louis, Missouri 63110, United States
| | - Marianna B. Ruzinova
- Department
of Pathology and Immunology, Washington
University in St. Louis, St. Louis, Missouri 63110, United States
| | - David G. DeNardo
- Division
of Oncology, Department of Medicine, Washington
University in St. Louis, St. Louis, Missouri 63110, United States
- Department
of Pathology and Immunology, Washington
University in St. Louis, St. Louis, Missouri 63110, United States
| | - Farrokh Dehdashti
- Department
of Radiology, Washington University in St.
Louis, St. Louis, Missouri 63110, United States
| | - Kian-Huat Lim
- Division
of Oncology, Department of Medicine, Washington
University in St. Louis, St. Louis, Missouri 63110, United States
| | - Yongjian Liu
- Department
of Radiology, Washington University in St.
Louis, St. Louis, Missouri 63110, United States
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26
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Lee DH, Lee SS, Lee JM, Choi JY, Lee CH, Ha HI, Kang BK, Yu MH, Chang W, Park SJ. Pancreas CT assessment for pancreatic ductal adenocarcinoma resectability: effect of tube voltage and slice thickness on image quality and diagnostic performance. Cancer Imaging 2023; 23:126. [PMID: 38111054 PMCID: PMC10729459 DOI: 10.1186/s40644-023-00637-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2023] [Accepted: 11/22/2023] [Indexed: 12/20/2023] Open
Abstract
OBJECTIVES To assess the resectability of pancreatic ductal adenocarcinoma (PDAC), the evaluation of tumor vascular contact holds paramount significance. This study aimed to compare the image quality and diagnostic performance of high-resolution (HR) pancreas computed tomography (CT) using an 80 kVp tube voltage and a thin slice (1 mm) for assessing PDAC resectability, in comparison with the standard protocol CT using 120 kVp. METHODS This research constitutes a secondary analysis originating from a multicenter prospective study. All participants underwent both the standard protocol pancreas CT using 120 kVp with 3 mm slice thickness (ST) and HR-CT utilizing an 80 kVp tube voltage and 1 mm ST. The contrast-to-noise ratio (CNR) between parenchyma and tumor, along with the degree of enhancement of the abdominal aorta and main portal vein (MPV), were measured and subsequently compared. Additionally, the likelihood of margin-negative resection (R0) was evaluated using a five-point scale. The diagnostic performance of both CT protocols in predicting R0 resection was assessed through the area under the receiver operating characteristic curve (AUC). RESULTS A total of 69 patients (37 males and 32 females; median age, 66.5 years) were included in the study. The median CNR of PDAC was 10.4 in HR-CT, which was significantly higher than the 7.1 in the standard CT (P=0.006). Furthermore, HR-CT demonstrated notably higher median attenuation values for both the abdominal aorta (579.5 HU vs. 327.2 HU; P=0.002) and the MPV (263.0 HU vs. 175.6 HU; P=0.004) in comparison with standard CT. Following surgery, R0 resection was achieved in 51 patients. The pooled AUC for HR-CT in predicting R0 resection was 0.727, slightly exceeding the 0.699 of standard CT, albeit lacking a significant statistical distinction (P=0.128). CONCLUSION While HR pancreas CT using 80 kVp offered a notably greater degree of contrast enhancement in vessels and a higher CNR for PDAC compared to standard CT, its diagnostic performance in predicting R0 resection remained statistically comparable.
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Affiliation(s)
- Dong Ho Lee
- Department of Radiology, Seoul National University Hospital, Seoul, South Korea
| | - Seung Soo Lee
- Department of Radiology and Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, South Korea
| | - Jeong Min Lee
- Department of Radiology, Seoul National University Hospital, Seoul, South Korea.
- Department of Radiology, Seoul National University College of Medicine, National University College of Medicine, 101 Daehak-ro, Jongno-gu, Seoul, 03080, South Korea.
| | - Jin-Young Choi
- Department of Radiology and Research Institute of Radiological Science, Severance Hospital, Yonsei University College of Medicine, Seoul, South Korea
| | - Chang Hee Lee
- Department of Radiology, Korea University Guro Hospital, South Korea University Medicine, Seoul, South Korea
| | - Hong Il Ha
- Department of Radiology, Hallym University Sacred Heart Hospital, Anyang, South Korea
| | - Bo-Kyeong Kang
- Department of Radiology, Hanyang University College of Medicine, Seoul, South Korea
| | - Mi Hye Yu
- Department of Radiology, Konkuk University College of Medicine, Seoul, South Korea
| | - Won Chang
- Department of Radiology, Seoul National University Bundang Hospital, Seoul, South Korea
| | - Sae Jin Park
- Department of Radiology, Seoul National University Hospital, Seoul, South Korea
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27
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Watabe T, Kabayama K, Naka S, Yamamoto R, Kaneda K, Serada S, Ooe K, Toyoshima A, Wang Y, Haba H, Kurimoto K, Kobayashi T, Shimosegawa E, Tomiyama N, Fukase K, Naka T. Immuno-PET and Targeted α-Therapy Using Anti-Glypican-1 Antibody Labeled with 89Zr or 211At: A Theranostic Approach for Pancreatic Ductal Adenocarcinoma. J Nucl Med 2023; 64:1949-1955. [PMID: 37827841 PMCID: PMC10690121 DOI: 10.2967/jnumed.123.266313] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2023] [Revised: 09/06/2023] [Indexed: 10/14/2023] Open
Abstract
Glypican-1 (GPC1) is overexpressed in several solid cancers and is associated with tumor progression, whereas its expression is low in normal tissues. This study aimed to evaluate the potential of an anti-GPC1 monoclonal antibody (GPC1 mAb) labeled with 89Zr or 211At as a theranostic target in pancreatic ductal adenocarcinoma. Methods: GPC1 mAb clone 01a033 was labeled with 89Zr or 211At with a deferoxamine or decaborane linker, respectively. The internalization ability of GPC1 mAb was evaluated by fluorescence conjugation using a confocal microscope. PANC-1 xenograft mice (n = 6) were intravenously administered [89Zr]GPC1 mAb (0.91 ± 0.10 MBq), and PET/CT scanning was performed for 7 d. Uptake specificity was confirmed through a comparative study using GPC1-positive (BxPC-3) and GPC1-negative (BxPC-3 GPC1-knockout) xenografts (each n = 3) and a blocking study. DNA double-strand breaks were evaluated using the γH2AX antibody. The antitumor effect was evaluated by administering [211At]GPC1 mAb (∼100 kBq) to PANC-1 xenograft mice (n = 10). Results: GPC1 mAb clone 01a033 showed increased internalization ratios over time. One day after administration, a high accumulation of [89Zr]GPC1 mAb was observed in the PANC-1 xenograft (SUVmax, 3.85 ± 0.10), which gradually decreased until day 7 (SUVmax, 2.16 ± 0.30). The uptake in the BxPC-3 xenograft was significantly higher than in the BxPC-3 GPC1-knockout xenograft (SUVmax, 4.66 ± 0.40 and 2.36 ± 0.36, respectively; P = 0.05). The uptake was significantly inhibited in the blocking group compared with the nonblocking group (percentage injected dose per gram, 7.3 ± 1.3 and 12.4 ± 3.0, respectively; P = 0.05). DNA double-strand breaks were observed by adding 150 kBq of [211At]GPC1 and were significantly suppressed by the internalization inhibitor (dynasore), suggesting a substantial contribution of the internalization ability to the antitumor effect. Tumor growth suppression was observed in PANC-1 mice after the administration of [211At]GPC1 mAb. Internalization inhibitors (prochlorperazine) significantly inhibited the therapeutic effect of [211At]GPC1 mAb, suggesting an essential role in targeted α-therapy. Conclusion: [89Zr]GPC1 mAb PET showed high tumoral uptake in the early phase after administration, and targeted α-therapy using [211At]GPC1 mAb showed tumor growth suppression. GPC1 is a promising target for future applications for the precise diagnosis of pancreatic ductal adenocarcinoma and GPC1-targeted theranostics.
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Affiliation(s)
- Tadashi Watabe
- Department of Nuclear Medicine and Tracer Kinetics, Graduate School of Medicine, Osaka University, Suita, Japan;
- Institute for Radiation Sciences, Osaka University, Suita, Japan
| | - Kazuya Kabayama
- Institute for Radiation Sciences, Osaka University, Suita, Japan
- Department of Chemistry, Graduate School of Science, Osaka University, Toyonaka, Japan
- Forefront Research Center, Graduate School of Science, Osaka University, Toyonaka, Japan
| | - Sadahiro Naka
- Department of Pharmacy, Osaka University Hospital, Suita, Japan
| | - Ryuku Yamamoto
- Department of Chemistry, Graduate School of Science, Osaka University, Toyonaka, Japan
| | - Kazuko Kaneda
- Institute for Radiation Sciences, Osaka University, Suita, Japan
- Forefront Research Center, Graduate School of Science, Osaka University, Toyonaka, Japan
| | - Satoshi Serada
- Institute for Biomedical Sciences Molecular Pathophysiology, Iwate Medical University, Yahaba, Japan
| | - Kazuhiro Ooe
- Institute for Radiation Sciences, Osaka University, Suita, Japan
| | | | - Yang Wang
- Nishina Center for Accelerator-Based Science, RIKEN, Saitama, Japan
| | - Hiromitsu Haba
- Nishina Center for Accelerator-Based Science, RIKEN, Saitama, Japan
| | - Kenta Kurimoto
- Department of Pharmacy, Osaka University Hospital, Suita, Japan
| | - Takanori Kobayashi
- Department of Nuclear Medicine and Tracer Kinetics, Graduate School of Medicine, Osaka University, Suita, Japan
| | - Eku Shimosegawa
- Department of Molecular Imaging in Medicine, Graduate School of Medicine, Osaka University, Suita, Japan
| | - Noriyuki Tomiyama
- Institute for Radiation Sciences, Osaka University, Suita, Japan
- Department of Radiology, Graduate School of Medicine, Osaka University, Suita, Japan; and
| | - Koichi Fukase
- Institute for Radiation Sciences, Osaka University, Suita, Japan
- Department of Chemistry, Graduate School of Science, Osaka University, Toyonaka, Japan
- Forefront Research Center, Graduate School of Science, Osaka University, Toyonaka, Japan
| | - Tetsuji Naka
- Institute for Biomedical Sciences Molecular Pathophysiology, Iwate Medical University, Yahaba, Japan
- Division of Allergy and Rheumatology, Department of Internal Medicine, School of Medicine, Iwate Medical University, Yahaba, Japan
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Abi Nader C, Vetil R, Wood LK, Rohe MM, Bône A, Karteszi H, Vullierme MP. Automatic Detection of Pancreatic Lesions and Main Pancreatic Duct Dilatation on Portal Venous CT Scans Using Deep Learning. Invest Radiol 2023; 58:791-798. [PMID: 37289274 DOI: 10.1097/rli.0000000000000992] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/09/2023]
Abstract
OBJECTIVES This study proposes and evaluates a deep learning method to detect pancreatic neoplasms and to identify main pancreatic duct (MPD) dilatation on portal venous computed tomography scans. MATERIALS AND METHODS A total of 2890 portal venous computed tomography scans from 9 institutions were acquired, among which 2185 had a pancreatic neoplasm and 705 were healthy controls. Each scan was reviewed by one in a group of 9 radiologists. Physicians contoured the pancreas, pancreatic lesions if present, and the MPD if visible. They also assessed tumor type and MPD dilatation. Data were split into a training and independent testing set of 2134 and 756 cases, respectively.A method to detect pancreatic lesions and MPD dilatation was built in 3 steps. First, a segmentation network was trained in a 5-fold cross-validation manner. Second, outputs of this network were postprocessed to extract imaging features: a normalized lesion risk, the predicted lesion diameter, and the MPD diameter in the head, body, and tail of the pancreas. Third, 2 logistic regression models were calibrated to predict lesion presence and MPD dilatation, respectively. Performance was assessed on the independent test cohort using receiver operating characteristic analysis. The method was also evaluated on subgroups defined based on lesion types and characteristics. RESULTS The area under the curve of the model detecting lesion presence in a patient was 0.98 (95% confidence interval [CI], 0.97-0.99). A sensitivity of 0.94 (469 of 493; 95% CI, 0.92-0.97) was reported. Similar values were obtained in patients with small (less than 2 cm) and isodense lesions with a sensitivity of 0.94 (115 of 123; 95% CI, 0.87-0.98) and 0.95 (53 of 56, 95% CI, 0.87-1.0), respectively. The model sensitivity was also comparable across lesion types with values of 0.94 (95% CI, 0.91-0.97), 1.0 (95% CI, 0.98-1.0), 0.96 (95% CI, 0.97-1.0) for pancreatic ductal adenocarcinoma, neuroendocrine tumor, and intraductal papillary neoplasm, respectively. Regarding MPD dilatation detection, the model had an area under the curve of 0.97 (95% CI, 0.96-0.98). CONCLUSIONS The proposed approach showed high quantitative performance to identify patients with pancreatic neoplasms and to detect MPD dilatation on an independent test cohort. Performance was robust across subgroups of patients with different lesion characteristics and types. Results confirmed the interest to combine a direct lesion detection approach with secondary features such as the MPD diameter, thus indicating a promising avenue for the detection of pancreatic cancer at early stages.
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Affiliation(s)
| | | | | | | | | | | | - Marie-Pierre Vullierme
- Department of Radiology, Hospital of Annecy-Genevois, Université Paris-Cité, Paris, France
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29
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Song C, Min JH, Jeong WK, Kim SH, Heo JS, Han IW, Shin SH, Yoon SJ, Choi SY, Moon S. Use of individualized 3D-printed models of pancreatic cancer to improve surgeons' anatomic understanding and surgical planning. Eur Radiol 2023; 33:7646-7655. [PMID: 37231071 DOI: 10.1007/s00330-023-09756-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2022] [Revised: 03/21/2023] [Accepted: 03/27/2023] [Indexed: 05/27/2023]
Abstract
OBJECTIVES Three-dimensional (3D) printing has been increasingly used to create accurate patient-specific 3D-printed models from medical imaging data. We aimed to evaluate the utility of 3D-printed models in the localization and understanding of pancreatic cancer for surgeons before pancreatic surgery. METHODS Between March and September 2021, we prospectively enrolled 10 patients with suspected pancreatic cancer who were scheduled for surgery. We created an individualized 3D-printed model from preoperative CT images. Six surgeons (three staff and three residents) evaluated the CT images before and after the presentation of the 3D-printed model using a 7-item questionnaire (understanding of anatomy and pancreatic cancer [Q1-4], preoperative planning [Q5], and education for trainees or patients [Q6-7]) on a 5-point scale. Survey scores on Q1-5 before and after the presentation of the 3D-printed model were compared. Q6-7 assessed the 3D-printed model's effects on education compared to CT. Subgroup analysis was performed between staff and residents. RESULTS After the 3D-printed model presentation, survey scores improved in all five questions (before 3.90 vs. after 4.56, p < 0.001), with a mean improvement of 0.57‒0.93. Staff and resident scores improved after a 3D-printed model presentation (p < 0.05), except for Q4 in the resident group. The mean difference was higher among the staff than among the residents (staff: 0.50‒0.97 vs. residents: 0.27‒0.90). The scores of the 3D-printed model for education were high (trainees: 4.47 vs. patients: 4.60) compared to CT. CONCLUSION The 3D-printed model of pancreatic cancer improved surgeons' understanding of individual patients' pancreatic cancer and surgical planning. CLINICAL RELEVANCE STATEMENT The 3D-printed model of pancreatic cancer can be created using a preoperative CT image, which not only assists surgeons in surgical planning but also serves as a valuable educational resource for patients and students. KEY POINTS • A personalized 3D-printed pancreatic cancer model provides more intuitive information than CT, allowing surgeons to better visualize the tumor's location and relationship to neighboring organs. • In particular, the survey score was higher among staff who performed the surgery than among residents. • Individual patient pancreatic cancer models have the potential to be used for personalized patient education as well as resident education.
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Affiliation(s)
- Chorog Song
- Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-ro Gangnam-gu, Seoul, 06351, Republic of Korea
| | - Ji Hye Min
- Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-ro Gangnam-gu, Seoul, 06351, Republic of Korea.
| | - Woo Kyoung Jeong
- Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-ro Gangnam-gu, Seoul, 06351, Republic of Korea
| | - Seong Hyun Kim
- Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-ro Gangnam-gu, Seoul, 06351, Republic of Korea
| | - Jin Seok Heo
- Division of Hepatobiliary-Pancreatic Surgery, Department of Surgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
| | - In Woong Han
- Division of Hepatobiliary-Pancreatic Surgery, Department of Surgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
| | - Sang Hyun Shin
- Division of Hepatobiliary-Pancreatic Surgery, Department of Surgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
| | - So Jeong Yoon
- Division of Hepatobiliary-Pancreatic Surgery, Department of Surgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
| | - Seo-Youn Choi
- Department of Radiology, Soonchunhyang University Bucheon Hospital, Soonchunhyang University College of Medicine, Bucheon, Republic of Korea
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30
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Sindayigaya R, Barat M, Tzedakis S, Dautry R, Dohan A, Belle A, Coriat R, Soyer P, Fuks D, Marchese U. Modified Appleby procedure for locally advanced pancreatic carcinoma: A primer for the radiologist. Diagn Interv Imaging 2023; 104:455-464. [PMID: 37301694 DOI: 10.1016/j.diii.2023.05.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2023] [Accepted: 05/31/2023] [Indexed: 06/12/2023]
Abstract
Pancreatic ductal adenocarcinoma (PDAC) is the most prevalent pancreatic neoplasm accounting for more than 90% of pancreatic malignancies. Surgical resection with adequate lymphadenectomy remains the only available curative strategy for patients with PDAC. Despite improvements in both chemotherapy regimen and surgical care, body/neck PDAC still conveys a poor prognosis because of the vicinity of major vascular structures, including celiac trunk, which favors insidious disease spread at the time of diagnosis. Body/neck PDAC involving the celiac trunk is considered locally advanced PDAC in most guidelines and therefore not eligible for upfront resection. However, a more aggressive surgical approach (i.e., distal pancreatectomy with splenectomy and en-bloc celiac trunk resection [DP-CAR]) was recently proposed to offer hope for cure in selected patients with locally advanced body/neck PDAC responsive to induction therapy at the cost of higher morbidity. The so-called "modified Appleby procedure" is highly demanding and requires optimal preoperative staging as well as appropriate patient preparation for surgery (i.e., preoperative arterial embolization). Herein, we review current evidence regarding DP-CAR indications and outcomes as well as the critical role of diagnostic and interventional radiology in patient preparation before DP-CAR, and early identification and management of DP-CAR complications.
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Affiliation(s)
- Rémy Sindayigaya
- Department of Digestive, Pancreatic, Hepato-biliary and Endocrine Surgery, Hôpital Cochin, Assistance Publique-Hôpitaux de Paris, 75014, Paris, France; Université Paris Cité, Faculté de Médecine, 75006 Paris, France.
| | - Maxime Barat
- Université Paris Cité, Faculté de Médecine, 75006 Paris, France; Department of Radiology, Hôpital Cochin, Assistance Publique-Hôpitaux de Paris, 75014 Paris, France
| | - Stylianos Tzedakis
- Department of Digestive, Pancreatic, Hepato-biliary and Endocrine Surgery, Hôpital Cochin, Assistance Publique-Hôpitaux de Paris, 75014, Paris, France; Université Paris Cité, Faculté de Médecine, 75006 Paris, France
| | - Raphael Dautry
- Department of Radiology, Hôpital Cochin, Assistance Publique-Hôpitaux de Paris, 75014 Paris, France
| | - Anthony Dohan
- Université Paris Cité, Faculté de Médecine, 75006 Paris, France; Department of Radiology, Hôpital Cochin, Assistance Publique-Hôpitaux de Paris, 75014 Paris, France
| | - Arthur Belle
- Department of Gastroenterology, Hôpital Cochin, Assistance Publique-Hôpitaux de Paris, 75014 Paris, France
| | - Romain Coriat
- Université Paris Cité, Faculté de Médecine, 75006 Paris, France; Department of Gastroenterology, Hôpital Cochin, Assistance Publique-Hôpitaux de Paris, 75014 Paris, France
| | - Philippe Soyer
- Université Paris Cité, Faculté de Médecine, 75006 Paris, France; Department of Radiology, Hôpital Cochin, Assistance Publique-Hôpitaux de Paris, 75014 Paris, France
| | - David Fuks
- Department of Digestive, Pancreatic, Hepato-biliary and Endocrine Surgery, Hôpital Cochin, Assistance Publique-Hôpitaux de Paris, 75014, Paris, France; Université Paris Cité, Faculté de Médecine, 75006 Paris, France
| | - Ugo Marchese
- Department of Digestive, Pancreatic, Hepato-biliary and Endocrine Surgery, Hôpital Cochin, Assistance Publique-Hôpitaux de Paris, 75014, Paris, France; Université Paris Cité, Faculté de Médecine, 75006 Paris, France
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31
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Freed IM, Kasi A, Fateru O, Hu M, Gonzalez P, Weatherington N, Pathak H, Hyter S, Sun W, Al-Rajabi R, Baranda J, Hupert ML, Chalise P, Godwin AK, A. Witek M, Soper SA. Circulating Tumor Cell Subpopulations Predict Treatment Outcome in Pancreatic Ductal Adenocarcinoma (PDAC) Patients. Cells 2023; 12:2266. [PMID: 37759489 PMCID: PMC10526802 DOI: 10.3390/cells12182266] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2023] [Revised: 09/06/2023] [Accepted: 09/09/2023] [Indexed: 09/29/2023] Open
Abstract
There is a high clinical unmet need to improve outcomes for pancreatic ductal adenocarcinoma (PDAC) patients, either with the discovery of new therapies or biomarkers that can track response to treatment more efficiently than imaging. We report an innovative approach that will generate renewed interest in using circulating tumor cells (CTCs) to monitor treatment efficacy, which, in this case, used PDAC patients receiving an exploratory new therapy, poly ADP-ribose polymerase inhibitor (PARPi)-niraparib-as a case study. CTCs were enumerated from whole blood using a microfluidic approach that affinity captures epithelial and mesenchymal CTCs using anti-EpCAM and anti-FAPα monoclonal antibodies, respectively. These antibodies were poised on the surface of two separate microfluidic devices to discretely capture each subpopulation for interrogation. The isolated CTCs were enumerated using immunophenotyping to produce a numerical ratio consisting of the number of mesenchymal to epithelial CTCs (denoted "Φ"), which was used as an indicator of response to therapy, as determined using computed tomography (CT). A decreasing value of Φ during treatment was indicative of tumor response to the PARPi and was observed in 88% of the enrolled patients (n = 31). Changes in Φ during longitudinal testing were a better predictor of treatment response than the current standard CA19-9. We were able to differentiate between responders and non-responders using ΔΦ (p = 0.0093) with higher confidence than CA19-9 (p = 0.033). For CA19-9 non-producers, ΔΦ correctly predicted the outcome in 72% of the PDAC patients. Sequencing of the gDNA extracted from affinity-selected CTC subpopulations provided information that could be used for patient enrollment into the clinical trial based on their tumor mutational status in DNA repair genes.
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Affiliation(s)
- Ian M. Freed
- Department of Chemistry, The University of Kansas, Lawrence, KS 66047, USA; (I.M.F.); (O.F.); (M.H.); (P.G.); (N.W.); (M.A.W.)
- Center of Bio-Modular Multiscale Systems for Precision Medicine (CBM), The University of Kansas, Lawrence, KS 66047, USA;
| | - Anup Kasi
- Division of Medical Oncology, University of Kansas Medical Center, Kansas City, KS 66160, USA; (W.S.); (R.A.-R.); (J.B.); (P.C.)
| | - Oluwadamilola Fateru
- Department of Chemistry, The University of Kansas, Lawrence, KS 66047, USA; (I.M.F.); (O.F.); (M.H.); (P.G.); (N.W.); (M.A.W.)
- Center of Bio-Modular Multiscale Systems for Precision Medicine (CBM), The University of Kansas, Lawrence, KS 66047, USA;
| | - Mengjia Hu
- Department of Chemistry, The University of Kansas, Lawrence, KS 66047, USA; (I.M.F.); (O.F.); (M.H.); (P.G.); (N.W.); (M.A.W.)
- Center of Bio-Modular Multiscale Systems for Precision Medicine (CBM), The University of Kansas, Lawrence, KS 66047, USA;
- Kansas Institute for Precision Medicine, University of Kansas Medical Center, Kansas City, KS 66160, USA; (H.P.); (S.H.)
- Department of Cancer Biology, The University of Kansas Medical Center, Cancer Center, Kansas City, KS 66160, USA
| | - Phasin Gonzalez
- Department of Chemistry, The University of Kansas, Lawrence, KS 66047, USA; (I.M.F.); (O.F.); (M.H.); (P.G.); (N.W.); (M.A.W.)
- Center of Bio-Modular Multiscale Systems for Precision Medicine (CBM), The University of Kansas, Lawrence, KS 66047, USA;
| | - Nyla Weatherington
- Department of Chemistry, The University of Kansas, Lawrence, KS 66047, USA; (I.M.F.); (O.F.); (M.H.); (P.G.); (N.W.); (M.A.W.)
- Center of Bio-Modular Multiscale Systems for Precision Medicine (CBM), The University of Kansas, Lawrence, KS 66047, USA;
| | - Harsh Pathak
- Kansas Institute for Precision Medicine, University of Kansas Medical Center, Kansas City, KS 66160, USA; (H.P.); (S.H.)
- Department of Pathology and Laboratory Medicine, University of Kansas Medical Center, Kansas City, KS 66160, USA
| | - Stephen Hyter
- Kansas Institute for Precision Medicine, University of Kansas Medical Center, Kansas City, KS 66160, USA; (H.P.); (S.H.)
- Department of Pathology and Laboratory Medicine, University of Kansas Medical Center, Kansas City, KS 66160, USA
| | - Weijing Sun
- Division of Medical Oncology, University of Kansas Medical Center, Kansas City, KS 66160, USA; (W.S.); (R.A.-R.); (J.B.); (P.C.)
| | - Raed Al-Rajabi
- Division of Medical Oncology, University of Kansas Medical Center, Kansas City, KS 66160, USA; (W.S.); (R.A.-R.); (J.B.); (P.C.)
| | - Joaquina Baranda
- Division of Medical Oncology, University of Kansas Medical Center, Kansas City, KS 66160, USA; (W.S.); (R.A.-R.); (J.B.); (P.C.)
| | | | - Prabhakar Chalise
- Division of Medical Oncology, University of Kansas Medical Center, Kansas City, KS 66160, USA; (W.S.); (R.A.-R.); (J.B.); (P.C.)
| | - Andrew K. Godwin
- Center of Bio-Modular Multiscale Systems for Precision Medicine (CBM), The University of Kansas, Lawrence, KS 66047, USA;
- Kansas Institute for Precision Medicine, University of Kansas Medical Center, Kansas City, KS 66160, USA; (H.P.); (S.H.)
- Department of Pathology and Laboratory Medicine, University of Kansas Medical Center, Kansas City, KS 66160, USA
| | - Malgorzata A. Witek
- Department of Chemistry, The University of Kansas, Lawrence, KS 66047, USA; (I.M.F.); (O.F.); (M.H.); (P.G.); (N.W.); (M.A.W.)
- Center of Bio-Modular Multiscale Systems for Precision Medicine (CBM), The University of Kansas, Lawrence, KS 66047, USA;
- Kansas Institute for Precision Medicine, University of Kansas Medical Center, Kansas City, KS 66160, USA; (H.P.); (S.H.)
| | - Steven A. Soper
- Department of Chemistry, The University of Kansas, Lawrence, KS 66047, USA; (I.M.F.); (O.F.); (M.H.); (P.G.); (N.W.); (M.A.W.)
- Center of Bio-Modular Multiscale Systems for Precision Medicine (CBM), The University of Kansas, Lawrence, KS 66047, USA;
- Kansas Institute for Precision Medicine, University of Kansas Medical Center, Kansas City, KS 66160, USA; (H.P.); (S.H.)
- Department of Cancer Biology, The University of Kansas Medical Center, Cancer Center, Kansas City, KS 66160, USA
- BioFluidica, Inc., San Diego, CA 92121, USA;
- Bioengineering Program, The University of Kansas, Lawrence, KS 66045, USA
- Department of Mechanical Engineering, The University of Kansas, Lawrence, KS 66045, USA
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Mirza-Aghazadeh-Attari M, Madani SP, Shahbazian H, Ansari G, Mohseni A, Borhani A, Afyouni S, Kamel IR. Predictive role of radiomics features extracted from preoperative cross-sectional imaging of pancreatic ductal adenocarcinoma in detecting lymph node metastasis: a systemic review and meta-analysis. Abdom Radiol (NY) 2023; 48:2570-2584. [PMID: 37202642 DOI: 10.1007/s00261-023-03940-y] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2022] [Revised: 04/20/2023] [Accepted: 04/24/2023] [Indexed: 05/20/2023]
Abstract
Lymph node metastases are associated with poor clinical outcomes in pancreatic ductal adenocarcinoma (PDAC). In preoperative imaging, conventional diagnostic modalities do not provide the desired accuracy in diagnosing lymph node metastasis. The current review aims to determine the pooled diagnostic profile of studies examining the role of radiomics features in detecting lymph node metastasis in PDAC. PubMed, Google Scholar, and Embase databases were searched for relevant articles. The quality of the studies was examined using the Radiomics Quality Score and Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2) tools. Pooled results for sensitivity, specificity, likelihood, and odds ratios with the corresponding 95% confidence intervals (CIs) were calculated using a random-effect model (DerSimonian-Liard method). No significant publication bias was detected among the studies included in this meta-analysis. The pooled sensitivity of the validation datasets included in the study was 77.4% (72.7%, 81.5%) and pooled specificity was 72.4% (63.8, 79.6%). The diagnostic odds ratio of the validation datasets was 9.6 (6.0, 15.2). No statistically significant heterogeneity was detected for sensitivity and odds ratio (P values of 0.3 and 0.08, respectively). However, there was significant heterogeneity concerning specificity (P = 0.003). The pretest probability of having lymph node metastasis in the pooled databases was 52% and a positive post-test probability was 76% after the radiomics features were used, showing a net benefit of 24%. Classifiers trained on radiomics features extracted from preoperative images can improve the sensitivity and specificity of conventional cross-sectional imaging in detecting lymph node metastasis in PDAC.
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Affiliation(s)
- Mohammad Mirza-Aghazadeh-Attari
- Russell H. Morgan Department of Radiology and Radiological Sciences, Johns Hopkins Hospital, Johns Hopkins University School of Medicine, 600 North Wolfe Street, MRI 143, Baltimore, MD, 21287, USA
| | - Seyedeh Panid Madani
- Russell H. Morgan Department of Radiology and Radiological Sciences, Johns Hopkins Hospital, Johns Hopkins University School of Medicine, 600 North Wolfe Street, MRI 143, Baltimore, MD, 21287, USA
| | - Haneyeh Shahbazian
- Russell H. Morgan Department of Radiology and Radiological Sciences, Johns Hopkins Hospital, Johns Hopkins University School of Medicine, 600 North Wolfe Street, MRI 143, Baltimore, MD, 21287, USA
| | - Golnoosh Ansari
- Russell H. Morgan Department of Radiology and Radiological Sciences, Johns Hopkins Hospital, Johns Hopkins University School of Medicine, 600 North Wolfe Street, MRI 143, Baltimore, MD, 21287, USA
| | - Alireza Mohseni
- Russell H. Morgan Department of Radiology and Radiological Sciences, Johns Hopkins Hospital, Johns Hopkins University School of Medicine, 600 North Wolfe Street, MRI 143, Baltimore, MD, 21287, USA
| | - Ali Borhani
- Russell H. Morgan Department of Radiology and Radiological Sciences, Johns Hopkins Hospital, Johns Hopkins University School of Medicine, 600 North Wolfe Street, MRI 143, Baltimore, MD, 21287, USA
| | - Shadi Afyouni
- Russell H. Morgan Department of Radiology and Radiological Sciences, Johns Hopkins Hospital, Johns Hopkins University School of Medicine, 600 North Wolfe Street, MRI 143, Baltimore, MD, 21287, USA
| | - Ihab R Kamel
- Russell H. Morgan Department of Radiology and Radiological Sciences, Johns Hopkins Hospital, Johns Hopkins University School of Medicine, 600 North Wolfe Street, MRI 143, Baltimore, MD, 21287, USA.
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Gudmundsdottir H, Yonkus JA, Alva-Ruiz R, Kendrick ML, Smoot RL, Warner SG, Starlinger P, Thiels CA, Nagorney DM, Cleary SP, Grotz TE, Truty MJ. Yield of Staging Laparoscopy for Pancreatic Cancer in the Modern Era: Analysis of More than 1,000 Consecutive Patients. J Am Coll Surg 2023; 237:49-57. [PMID: 37026837 PMCID: PMC10262988 DOI: 10.1097/xcs.0000000000000704] [Citation(s) in RCA: 22] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2023] [Revised: 02/24/2023] [Accepted: 02/27/2023] [Indexed: 04/08/2023]
Abstract
BACKGROUND Accurate staging prior to resection of pancreatic ductal adenocarcinoma (PDAC) is imperative to avoid unnecessary operative morbidity and oncologic futility in patients with occult intra-abdominal distant metastases. We aimed to determine the diagnostic yield of staging laparoscopy (SL) and to identify factors associated with increased risk of positive laparoscopy (PL) in the modern era. STUDY DESIGN Patients with radiographically localized PDAC who underwent SL from 2017 to 2021 were retrospectively reviewed. The yield of SL was defined as the proportion of patients with PL, including gross metastases and/or positive peritoneal cytology. Factors associated with PL were assessed using univariate analysis and multivariable logistic regression. RESULTS Of 1,004 patients who underwent SL, 180 (18%) had PL due to gross metastases (n = 140) and/or positive cytology (n = 96). Patients who had neoadjuvant chemotherapy prior to laparoscopy had lower rates of PL (14% vs 22%, p = 0.002). When the analysis was restricted to chemo-naive patients who had concurrent peritoneal lavage performed, 95 of 419 patients (23%) had PL. In multivariable analysis, PL was associated with younger (<60) age, indeterminate extrapancreatic lesions on preoperative imaging, body/tail tumor location, larger tumor size, and elevated serum CA 19-9 (all p < 0.05). Among patients with no indeterminate extrapancreatic lesions on preoperative imaging, the rate of PL ranged from 1.6% in patients with no risk factors to 42% in young patients with large body/tail tumors and elevated serum CA 19-9. CONCLUSIONS The rate of PL in patients with PDAC remains high in the modern era. SL with peritoneal lavage should be considered for the majority of patients prior to resection, specifically those with high-risk features, and ideally prior to neoadjuvant chemotherapy.
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Affiliation(s)
| | | | | | | | - Rory L Smoot
- From the Department of Surgery, Mayo Clinic, Rochester, MN
| | | | | | | | | | - Sean P Cleary
- From the Department of Surgery, Mayo Clinic, Rochester, MN
| | - Travis E Grotz
- From the Department of Surgery, Mayo Clinic, Rochester, MN
| | - Mark J Truty
- From the Department of Surgery, Mayo Clinic, Rochester, MN
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Viriyasaranon T, Chun JW, Koh YH, Cho JH, Jung MK, Kim SH, Kim HJ, Lee WJ, Choi JH, Woo SM. Annotation-Efficient Deep Learning Model for Pancreatic Cancer Diagnosis and Classification Using CT Images: A Retrospective Diagnostic Study. Cancers (Basel) 2023; 15:3392. [PMID: 37444502 DOI: 10.3390/cancers15133392] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2023] [Revised: 06/26/2023] [Accepted: 06/26/2023] [Indexed: 07/15/2023] Open
Abstract
The aim of this study was to develop a novel deep learning (DL) model without requiring large-annotated training datasets for detecting pancreatic cancer (PC) using computed tomography (CT) images. This retrospective diagnostic study was conducted using CT images collected from 2004 and 2019 from 4287 patients diagnosed with PC. We proposed a self-supervised learning algorithm (pseudo-lesion segmentation (PS)) for PC classification, which was trained with and without PS and validated on randomly divided training and validation sets. We further performed cross-racial external validation using open-access CT images from 361 patients. For internal validation, the accuracy and sensitivity for PC classification were 94.3% (92.8-95.4%) and 92.5% (90.0-94.4%), and 95.7% (94.5-96.7%) and 99.3 (98.4-99.7%) for the convolutional neural network (CNN) and transformer-based DL models (both with PS), respectively. Implementing PS on a small-sized training dataset (randomly sampled 10%) increased accuracy by 20.5% and sensitivity by 37.0%. For external validation, the accuracy and sensitivity were 82.5% (78.3-86.1%) and 81.7% (77.3-85.4%) and 87.8% (84.0-90.8%) and 86.5% (82.3-89.8%) for the CNN and transformer-based DL models (both with PS), respectively. PS self-supervised learning can increase DL-based PC classification performance, reliability, and robustness of the model for unseen, and even small, datasets. The proposed DL model is potentially useful for PC diagnosis.
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Affiliation(s)
- Thanaporn Viriyasaranon
- Graduate Program in System Health Science and Engineering, Division of Mechanical and Biomedical Engineering, Ewha Womans University, Seoul 03760, Republic of Korea
| | - Jung Won Chun
- Center for Liver and Pancreatobiliary Cancer, National Cancer Center, Goyang 10408, Republic of Korea
| | - Young Hwan Koh
- Center for Liver and Pancreatobiliary Cancer, National Cancer Center, Goyang 10408, Republic of Korea
| | - Jae Hee Cho
- Department of Internal Medicine, Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul 03722, Republic of Korea
| | - Min Kyu Jung
- Department of Internal Medicine, Kyungpook National University Hospital, Daegu 41944, Republic of Korea
| | - Seong-Hun Kim
- Department of Internal Medicine, Research Institute of Clinical Medicine of Jeonbuk National University-Biomedical Research Institute of Jeonbuk National University Hospital, Jeonju 54907, Republic of Korea
| | - Hyo Jung Kim
- Department of Gastroenterology, Korea University Guro Hospital, Seoul 10408, Republic of Korea
| | - Woo Jin Lee
- Center for Liver and Pancreatobiliary Cancer, National Cancer Center, Goyang 10408, Republic of Korea
| | - Jang-Hwan Choi
- Graduate Program in System Health Science and Engineering, Division of Mechanical and Biomedical Engineering, Ewha Womans University, Seoul 03760, Republic of Korea
| | - Sang Myung Woo
- Center for Liver and Pancreatobiliary Cancer, National Cancer Center, Goyang 10408, Republic of Korea
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Ramaekers M, Viviers CGA, Janssen BV, Hellström TAE, Ewals L, van der Wulp K, Nederend J, Jacobs I, Pluyter JR, Mavroeidis D, van der Sommen F, Besselink MG, Luyer MDP. Computer-Aided Detection for Pancreatic Cancer Diagnosis: Radiological Challenges and Future Directions. J Clin Med 2023; 12:4209. [PMID: 37445243 PMCID: PMC10342462 DOI: 10.3390/jcm12134209] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2023] [Revised: 06/08/2023] [Accepted: 06/19/2023] [Indexed: 07/15/2023] Open
Abstract
Radiological imaging plays a crucial role in the detection and treatment of pancreatic ductal adenocarcinoma (PDAC). However, there are several challenges associated with the use of these techniques in daily clinical practice. Determination of the presence or absence of cancer using radiological imaging is difficult and requires specific expertise, especially after neoadjuvant therapy. Early detection and characterization of tumors would potentially increase the number of patients who are eligible for curative treatment. Over the last decades, artificial intelligence (AI)-based computer-aided detection (CAD) has rapidly evolved as a means for improving the radiological detection of cancer and the assessment of the extent of disease. Although the results of AI applications seem promising, widespread adoption in clinical practice has not taken place. This narrative review provides an overview of current radiological CAD systems in pancreatic cancer, highlights challenges that are pertinent to clinical practice, and discusses potential solutions for these challenges.
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Affiliation(s)
- Mark Ramaekers
- Department of Surgery, Catharina Cancer Institute, Catharina Hospital Eindhoven, 5623 EJ Eindhoven, The Netherlands;
| | - Christiaan G. A. Viviers
- Department of Electrical Engineering, Eindhoven University of Technology, 5612 AZ Eindhoven, The Netherlands; (C.G.A.V.); (T.A.E.H.); (F.v.d.S.)
| | - Boris V. Janssen
- Department of Surgery, Amsterdam UMC, University of Amsterdam, 1105 AZ Amsterdam, The Netherlands; (B.V.J.); (M.G.B.)
- Cancer Center Amsterdam, 1081 HV Amsterdam, The Netherlands
| | - Terese A. E. Hellström
- Department of Electrical Engineering, Eindhoven University of Technology, 5612 AZ Eindhoven, The Netherlands; (C.G.A.V.); (T.A.E.H.); (F.v.d.S.)
| | - Lotte Ewals
- Department of Radiology, Catharina Cancer Institute, Catharina Hospital Eindhoven, 5623 EJ Eindhoven, The Netherlands; (L.E.); (K.v.d.W.); (J.N.)
| | - Kasper van der Wulp
- Department of Radiology, Catharina Cancer Institute, Catharina Hospital Eindhoven, 5623 EJ Eindhoven, The Netherlands; (L.E.); (K.v.d.W.); (J.N.)
| | - Joost Nederend
- Department of Radiology, Catharina Cancer Institute, Catharina Hospital Eindhoven, 5623 EJ Eindhoven, The Netherlands; (L.E.); (K.v.d.W.); (J.N.)
| | - Igor Jacobs
- Department of Hospital Services and Informatics, Philips Research, 5656 AE Eindhoven, The Netherlands;
| | - Jon R. Pluyter
- Department of Experience Design, Philips Design, 5656 AE Eindhoven, The Netherlands;
| | - Dimitrios Mavroeidis
- Department of Data Science, Philips Research, 5656 AE Eindhoven, The Netherlands;
| | - Fons van der Sommen
- Department of Electrical Engineering, Eindhoven University of Technology, 5612 AZ Eindhoven, The Netherlands; (C.G.A.V.); (T.A.E.H.); (F.v.d.S.)
| | - Marc G. Besselink
- Department of Surgery, Amsterdam UMC, University of Amsterdam, 1105 AZ Amsterdam, The Netherlands; (B.V.J.); (M.G.B.)
- Cancer Center Amsterdam, 1081 HV Amsterdam, The Netherlands
| | - Misha D. P. Luyer
- Department of Surgery, Catharina Cancer Institute, Catharina Hospital Eindhoven, 5623 EJ Eindhoven, The Netherlands;
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Harindranath S, Sundaram S. Approach to Pancreatic Head Mass in the Background of Chronic Pancreatitis. Diagnostics (Basel) 2023; 13:1797. [PMID: 37238280 PMCID: PMC10217770 DOI: 10.3390/diagnostics13101797] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2023] [Revised: 05/12/2023] [Accepted: 05/17/2023] [Indexed: 05/28/2023] Open
Abstract
Chronic pancreatitis (CP) is a known risk factor for pancreatic cancer. CP may present with an inflammatory mass, and differentiation from pancreatic cancer is often difficult. Clinical suspicion of malignancy dictates a need for further evaluation for underlying pancreatic cancer. Imaging modalities remain the mainstay of evaluation for a mass in background CP; however, they have their shortcomings. Endoscopic ultrasound (EUS) has become the go-to investigation. Adjunct modalities such as contrast-harmonic EUS and EUS elastography, as well as EUS-guided sampling using newer-generation needles are useful in differentiating inflammatory from malignant masses in the pancreas. Paraduodenal pancreatitis and autoimmune pancreatitis often masquerade as pancreatic cancer. In this narrative review, we discuss the various modalities used to differentiate inflammatory from malignant masses of the pancreas.
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Affiliation(s)
- Sidharth Harindranath
- Department of Gastroenterology, Seth GS Medical College and King Edward Memorial Hospital, Mumbai 400012, India
| | - Sridhar Sundaram
- Department of Digestive Diseases and Clinical Nutrition, Tata Memorial Hospital, Homi Bhabha National Institute, Mumbai 400012, India
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37
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Harindranath S, Sundaram S. Approach to Pancreatic Head Mass in the Background of Chronic Pancreatitis. Diagnostics (Basel) 2023; 13:1797. [DOI: https:/doi.org/10.3390/diagnostics13101797] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/13/2025] Open
Abstract
Chronic pancreatitis (CP) is a known risk factor for pancreatic cancer. CP may present with an inflammatory mass, and differentiation from pancreatic cancer is often difficult. Clinical suspicion of malignancy dictates a need for further evaluation for underlying pancreatic cancer. Imaging modalities remain the mainstay of evaluation for a mass in background CP; however, they have their shortcomings. Endoscopic ultrasound (EUS) has become the go-to investigation. Adjunct modalities such as contrast-harmonic EUS and EUS elastography, as well as EUS-guided sampling using newer-generation needles are useful in differentiating inflammatory from malignant masses in the pancreas. Paraduodenal pancreatitis and autoimmune pancreatitis often masquerade as pancreatic cancer. In this narrative review, we discuss the various modalities used to differentiate inflammatory from malignant masses of the pancreas.
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Affiliation(s)
- Sidharth Harindranath
- Department of Gastroenterology, Seth GS Medical College and King Edward Memorial Hospital, Mumbai 400012, India
| | - Sridhar Sundaram
- Department of Digestive Diseases and Clinical Nutrition, Tata Memorial Hospital, Homi Bhabha National Institute, Mumbai 400012, India
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Heiselman JS, Ecker BL, Langdon-Embry L, O’Reilly EM, Miga MI, Jarnagin WR, Do RKG, Horvat N, Wei AC, Chakraborty J. Registration-based biomarkers for neoadjuvant treatment response of pancreatic cancer via longitudinal image registration. J Med Imaging (Bellingham) 2023; 10:036002. [PMID: 37274758 PMCID: PMC10237235 DOI: 10.1117/1.jmi.10.3.036002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2022] [Revised: 04/18/2023] [Accepted: 05/15/2023] [Indexed: 06/06/2023] Open
Abstract
Purpose Pancreatic ductal adenocarcinoma (PDAC) frequently presents as hypo- or iso-dense masses with poor contrast delineation from surrounding parenchyma, which decreases reproducibility of manual dimensional measurements obtained during conventional radiographic assessment of treatment response. Longitudinal registration between pre- and post-treatment images may produce imaging biomarkers that more reliably quantify treatment response across serial imaging. Approach Thirty patients who prospectively underwent a neoadjuvant chemotherapy regimen as part of a clinical trial were retrospectively analyzed in this study. Two image registration methods were applied to quantitatively assess longitudinal changes in tumor volume and tumor burden across the neoadjuvant treatment interval. Longitudinal registration errors of the pancreas were characterized, and registration-based treatment response measures were correlated to overall survival (OS) and recurrence-free survival (RFS) outcomes over 5-year follow-up. Corresponding biomarker assessments via manual tumor segmentation, the standardized response evaluation criteria in solid tumors (RECIST), and pathological examination of post-resection tissue samples were analyzed as clinical comparators. Results Average target registration errors were 2.56 ± 2.45 mm for a biomechanical image registration algorithm and 4.15 ± 3.63 mm for a diffeomorphic intensity-based algorithm, corresponding to 1-2 times voxel resolution. Cox proportional hazards analysis showed that registration-derived changes in tumor burden were significant predictors of OS and RFS, while none of the alternative comparators, including manual tumor segmentation, RECIST, or pathological variables were associated with consequential hazard ratios. Additional ROC analysis at 1-, 2-, 3-, and 5-year follow-up revealed that registration-derived changes in tumor burden between pre- and post-treatment imaging were better long-term predictors for OS and RFS than the clinical comparators. Conclusions Volumetric changes measured by longitudinal deformable image registration may yield imaging biomarkers to discriminate neoadjuvant treatment response in ill-defined tumors characteristic of PDAC. Registration-based biomarkers may help to overcome visual limits of radiographic evaluation to improve clinical outcome prediction and inform treatment selection.
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Affiliation(s)
- Jon S. Heiselman
- Memorial Sloan Kettering Cancer Center, Department of Surgery, Hepatopancreatobiliary Unit, New York, New York, United States
- Vanderbilt University, Department of Biomedical Engineering, Nashville, Tennessee, United States
| | - Brett L. Ecker
- Rutgers Cancer Institute of New Jersey, Department of Surgery, New Brunswick, New Jersey, United States
| | - Liana Langdon-Embry
- Rutgers New Jersey Medical School, Cooperman Barnabas Medical Center, Livingston, New Jersey, United States
| | - Eileen M. O’Reilly
- Memorial Sloan Kettering Cancer Center, Department of Medicine, New York, New York, United States
| | - Michael I. Miga
- Vanderbilt University, Department of Biomedical Engineering, Nashville, Tennessee, United States
| | - William R. Jarnagin
- Memorial Sloan Kettering Cancer Center, Department of Surgery, Hepatopancreatobiliary Unit, New York, New York, United States
| | - Richard K. G. Do
- Memorial Sloan Kettering Cancer Center, Department of Radiology, New York, New York, United States
| | - Natally Horvat
- Memorial Sloan Kettering Cancer Center, Department of Radiology, New York, New York, United States
| | - Alice C. Wei
- Memorial Sloan Kettering Cancer Center, Department of Surgery, Hepatopancreatobiliary Unit, New York, New York, United States
| | - Jayasree Chakraborty
- Memorial Sloan Kettering Cancer Center, Department of Surgery, Hepatopancreatobiliary Unit, New York, New York, United States
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Myo Min KK, Ffrench CB, Jessup CF, Shepherdson M, Barreto SG, Bonder CS. Overcoming the Fibrotic Fortress in Pancreatic Ductal Adenocarcinoma: Challenges and Opportunities. Cancers (Basel) 2023; 15:2354. [PMID: 37190281 PMCID: PMC10137060 DOI: 10.3390/cancers15082354] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2023] [Revised: 04/06/2023] [Accepted: 04/14/2023] [Indexed: 05/17/2023] Open
Abstract
An overabundance of desmoplasia in the tumour microenvironment (TME) is one of the defining features that influences pancreatic ductal adenocarcinoma (PDAC) development, progression, metastasis, and treatment resistance. Desmoplasia is characterised by the recruitment and activation of fibroblasts, heightened extracellular matrix deposition (ECM) and reduced blood supply, as well as increased inflammation through an influx of inflammatory cells and cytokines, creating an intrinsically immunosuppressive TME with low immunogenic potential. Herein, we review the development of PDAC, the drivers that initiate and/or sustain the progression of the disease and the complex and interwoven nature of the cellular and acellular components that come together to make PDAC one of the most aggressive and difficult to treat cancers. We review the challenges in delivering drugs into the fortress of PDAC tumours in concentrations that are therapeutic due to the presence of a highly fibrotic and immunosuppressive TME. Taken together, we present further support for continued/renewed efforts focusing on aspects of the extremely dense and complex TME of PDAC to improve the efficacy of therapy for better patient outcomes.
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Affiliation(s)
- Kay K. Myo Min
- Centre for Cancer Biology, University of South Australia and SA Pathology, Adelaide, SA 5000, Australia; (K.K.M.M.); (C.B.F.)
| | - Charlie B. Ffrench
- Centre for Cancer Biology, University of South Australia and SA Pathology, Adelaide, SA 5000, Australia; (K.K.M.M.); (C.B.F.)
| | - Claire F. Jessup
- College of Medicine & Public Health, Flinders University, Bedford Park, SA 5042, Australia
- Adelaide Medical School, University of Adelaide, Adelaide, SA 5000, Australia
| | - Mia Shepherdson
- College of Medicine & Public Health, Flinders University, Bedford Park, SA 5042, Australia
- Hepatopancreatobiliary & Liver Transplant Unit, Division of Surgery & Perioperative Medicine, Flinders Medical Centre, Bedford Park, SA 5042, Australia
| | - Savio George Barreto
- College of Medicine & Public Health, Flinders University, Bedford Park, SA 5042, Australia
- Hepatopancreatobiliary & Liver Transplant Unit, Division of Surgery & Perioperative Medicine, Flinders Medical Centre, Bedford Park, SA 5042, Australia
| | - Claudine S. Bonder
- Centre for Cancer Biology, University of South Australia and SA Pathology, Adelaide, SA 5000, Australia; (K.K.M.M.); (C.B.F.)
- Adelaide Medical School, University of Adelaide, Adelaide, SA 5000, Australia
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40
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Elbanna KY, Jang HJ, Kim TK. Imaging for Screening/Surveillance of Pancreatic Cancer: A Glimpse of Hope. Korean J Radiol 2023; 24:271-273. [PMID: 36907596 PMCID: PMC10067696 DOI: 10.3348/kjr.2022.1035] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/02/2023] [Revised: 02/05/2023] [Accepted: 02/08/2023] [Indexed: 03/14/2023] Open
Affiliation(s)
- Khaled Y Elbanna
- Joint Department of Medical Imaging, University of Toronto, Toronto, ON, Canada
| | - Hyun-Jung Jang
- Joint Department of Medical Imaging, University of Toronto, Toronto, ON, Canada
| | - Tae Kyoung Kim
- Joint Department of Medical Imaging, University of Toronto, Toronto, ON, Canada.
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Choi M, Yoon S, Lee Y, Han D. Evaluation of Perfusion Change According to Pancreatic Cancer and Pancreatic Duct Dilatation Using Free-Breathing Golden-Angle Radial Sparse Parallel (GRASP) Magnetic Resonance Imaging. Diagnostics (Basel) 2023; 13:731. [PMID: 36832219 PMCID: PMC9955363 DOI: 10.3390/diagnostics13040731] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2022] [Revised: 02/10/2023] [Accepted: 02/13/2023] [Indexed: 02/17/2023] Open
Abstract
PURPOSE To evaluate perfusion changes in the pancreas with pancreatic cancer and pancreatic duct dilatation using dynamic contrast-enhanced MRI (DCE-MRI). METHOD We evaluate the pancreas DCE-MRI of 75 patients. The qualitative analysis includes pancreas edge sharpness, motion artifacts, streak artifacts, noise, and overall image quality. The quantitative analysis includes measuring the pancreatic duct diameter and drawing six regions of interest (ROIs) in the three areas of the pancreas (head, body, and tail) and three vessels (aorta, celiac axis, and superior mesenteric artery) to measure the peak-enhancement time, delay time, and peak concentration. We evaluate the differences in three quantitative parameters among the ROIs and between patients with and without pancreatic cancer. The correlations between pancreatic duct diameter and delay time are also analyzed. RESULTS The pancreas DCE-MRI demonstrates good image quality, and respiratory motion artifacts show the highest score. The peak-enhancement time does not differ among the three vessels or among the three pancreas areas. The peak-enhancement time and concentrations in the pancreas body and tail and the delay time in the three pancreas areas are significantly longer (p < 0.05) in patients with pancreatic cancer than in those without pancreatic cancer. The delay time was significantly correlated with the pancreatic duct diameters in the head (p < 0.02) and body (p < 0.001). CONCLUSION DCE-MRI can display the perfusion change in the pancreas with pancreatic cancer. A perfusion parameter in the pancreas is correlated with the pancreatic duct diameter reflecting a morphological change in the pancreas.
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Affiliation(s)
- Moonhyung Choi
- Department of Radiology, Eunpyeong St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul 03312, Republic of Korea
| | - Seungbae Yoon
- Department of Internal Medicine, Eunpyeong St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul 03312, Republic of Korea
| | - Youngjoon Lee
- Department of Radiology, Eunpyeong St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul 03312, Republic of Korea
| | - Dongyeob Han
- Siemens Healthineers Ltd., Seoul 06620, Republic of Korea
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Wang F, Guo H, Li S, Xu J, Yu D. The value of enhanced CT features and texture-signatures in assessing the inflammatory infiltration of pancreatic ductal adenocarcinoma. Front Oncol 2023; 13:1078861. [PMID: 36816950 PMCID: PMC9936180 DOI: 10.3389/fonc.2023.1078861] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2022] [Accepted: 01/16/2023] [Indexed: 02/05/2023] Open
Abstract
Purpose To explore the predictive value of computed tomography (CT) imaging features and CT-based texture analysis in assessing inflammatory infiltration in pancreatic ductal adenocarcinoma (PDAC). Methods A total of 43 patients with PDAC confirmed by surgical pathology were included in the study. The clinical, radiological, surgical, and pathological features of the patients were analyzed retrospectively using the chi-square test or Spearman's correlation. Receiver operating characteristic (ROC) curves were utilized to assess the overall predictive ability of the tumor enhancement degree on triphasic contrast-enhanced CT images for the inflammatory infiltration degree in PDAC. Furthermore, all CT data were uploaded to the RadCloud platform for region of interest (ROI) delineation and feature extraction. Then, the Variance Threshold and SelectKBest algorithms were used to find the optimal CT features. Binary logistic regression was employed to analyze the selected features in all three contrast-enhanced CT phases, and regression equations were formulated. ROC analysis was performed to evaluate the predictive effectiveness of each equation. Results The analysis revealed a statistically significant correlation between the degree of differentiation and radiological findings such as necrosis and cystic degeneration, vascular invasion, and the presence of ascites (P < 0.05). The enhancement degree of the tumor in both the arterial and venous phases was significantly correlated with the inflammatory infiltration degree (P < 0.05); however, the areas under the ROC curve (AUCs) of arterial and venous enhancement were 0.570 and 0.542, respectively. Regression equations based on the texture features of triphasic contrast-enhanced tumors were formulated, and their AUCs were 0.982, 0.643, and 0.849. Conclusion Conventional radiological features are not significantly correlated with the degree of inflammatory infiltration in PDAC. The enhancement degrees in both the arterial phase and venous phase were statistically correlated with the inflammatory infiltration level but had poor predictive value. The texture features of PDAC on contrast-enhanced CT may show a better assessment value, especially in the arterial phase.
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Affiliation(s)
- Fangqing Wang
- Department of Radiology, Qilu Hospital of Shandong University, Jinan, China
| | - Hang Guo
- Department of Radiology, Laiyang Central Hospital of Yantai, Yantai, China
| | - Shunjia Li
- Department of Radiation Oncology, Qilu Hospital of Shandong University, Jinan, China
| | - Jianwei Xu
- Department of Pancreatic Surgery, Qilu Hospital of Shandong University, Jinan, China
| | - Dexin Yu
- Department of Radiology, Qilu Hospital of Shandong University, Jinan, China,*Correspondence: Dexin Yu,
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Shetty NS, Agarwal U, Choudhari A, Gupta A, PG N, Bhandare M, Gala K, Chandra D, Ramaswamy A, Ostwal V, Shrikhande SV, Kulkarni SS. Imaging Recommendations for Diagnosis, Staging, and Management of Pancreatic Cancer. Indian J Med Paediatr Oncol 2023; 44:077-083. [DOI: 10.1055/s-0042-1759521] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/08/2023] Open
Abstract
AbstractPancreatic cancer is the fourth most prevalent cause of cancer-related death worldwide, with a fatality rate equal to its incidence rate. Pancreatic cancer is a rare malignancy with a global incidence and death ranking of 14th and 7th, respectively. Pancreatic cancer cases are divided into three categories without metastatic disease: resectable, borderline resectable, or locally advanced disease. The category is determined by the tumor's location in the pancreas and whether it is abutting or encasing the adjacent arteries and/or vein/s.The stage of disease and the location of the primary tumor determine the clinical presentation: the pancreatic head, neck, or uncinate process, the body or tail, or multifocal disease. Imaging plays a crucial role in the diagnosis and follow-up of pancreatic cancers. Various imaging modalities available for pancreatic imaging are ultrasonography (USG), contrast-enhanced computed tomography (CECT), magnetic resonance imaging (MRI), and 18-fluoro-deoxy glucose positron emission tomography (FDG PET).Even though surgical resection is possible in both resectable and borderline resectable non-metastatic cases, neoadjuvant chemotherapy with or without radiotherapy has become the standard practice for borderline resectable cases as it gives a high yield of R0 resection.
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Affiliation(s)
- Nitin Sudhakar Shetty
- Department of Radio-Diagnosis, Tata Memorial Hospital, Homi Bhabha National University (HBNI), Mumbai, Maharashtra, India
| | - Ujjwal Agarwal
- Department of Radio-Diagnosis, Tata Memorial Hospital, Homi Bhabha National University (HBNI), Mumbai, Maharashtra, India
| | - Amit Choudhari
- Department of Radio-Diagnosis, Tata Memorial Hospital, Homi Bhabha National University (HBNI), Mumbai, Maharashtra, India
| | - Anurag Gupta
- Department of Radio-Diagnosis, Tata Memorial Hospital, Homi Bhabha National University (HBNI), Mumbai, Maharashtra, India
| | - Nandakumar PG
- Department of Radio-Diagnosis, Tata Memorial Hospital, Homi Bhabha National University (HBNI), Mumbai, Maharashtra, India
| | - Manish Bhandare
- Department of Surgical Oncology, Tata Memorial Hospital, Homi Bhabha National University (HBNI), Mumbai, Maharashtra, India
| | - Kunal Gala
- Department of Radio-Diagnosis, Tata Memorial Hospital, Homi Bhabha National University (HBNI), Mumbai, Maharashtra, India
| | - Daksh Chandra
- Department of Radio-Diagnosis, Tata Memorial Hospital, Homi Bhabha National University (HBNI), Mumbai, Maharashtra, India
| | - Anant Ramaswamy
- Department of Medical Oncology, Tata Memorial Hospital, Homi Bhabha National University (HBNI), Mumbai, Maharashtra, India
| | - Vikas Ostwal
- Department of Medical Oncology, Tata Memorial Hospital, Homi Bhabha National University (HBNI), Mumbai, Maharashtra, India
| | - Shailesh V. Shrikhande
- Department of Surgical Oncology, Tata Memorial Hospital, Homi Bhabha National University (HBNI), Mumbai, Maharashtra, India
| | - Suyash S. Kulkarni
- Department of Radio-Diagnosis, Tata Memorial Hospital, Homi Bhabha National University (HBNI), Mumbai, Maharashtra, India
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Koretsune Y, Sone M, Sugawara S, Wakatsuki Y, Ishihara T, Hattori C, Fujisawa Y, Kusumoto M. Validation of a convolutional neural network for the automated creation of curved planar reconstruction images along the main pancreatic duct. Jpn J Radiol 2023; 41:228-234. [PMID: 36121623 PMCID: PMC9889432 DOI: 10.1007/s11604-022-01339-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2022] [Accepted: 09/09/2022] [Indexed: 02/04/2023]
Abstract
PURPOSE To evaluate the accuracy and time-efficiency of newly developed software in automatically creating curved planar reconstruction (CPR) images along the main pancreatic duct (MPD), which was developed based on a 3-dimensional convolutional neural network, and compare them with those of conventional manually generated CPR ones. MATERIALS AND METHODS A total of 100 consecutive patients with MPD dilatation (≥ 3 mm) who underwent contrast-enhanced computed tomography between February 2021 and July 2021 were included in the study. Two radiologists independently performed blinded qualitative analysis of automated and manually created CPR images. They rated overall image quality based on a four-point scale and weighted κ analysis was employed to compare between manually created and automated CPR images. A quantitative analysis of the time required to create CPR images and the total length of the MPD measured from CPR images was performed. RESULTS The κ value was 0.796, and a good correlation was found between the manually created and automated CPR images. The average time to create automated and manually created CPR images was 61.7 s and 174.6 s, respectively (P < 0.001). The total MPD length of the automated and manually created CPR images was 110.5 and 115.6 mm, respectively (P = 0.059). CONCLUSION The automated CPR software significantly reduced reconstruction time without compromising image quality.
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Affiliation(s)
- Yuji Koretsune
- grid.136593.b0000 0004 0373 3971Department of Diagnostic and Interventional Radiology, Osaka University, 2-15 Yamadaoka, Suita, Osaka 565-0871 Japan
| | - Miyuki Sone
- grid.272242.30000 0001 2168 5385Department of Diagnostic Radiology, National Cancer Center Hospital, Chuo City, Japan
| | - Shunsuke Sugawara
- grid.272242.30000 0001 2168 5385Department of Diagnostic Radiology, National Cancer Center Hospital, Chuo City, Japan
| | - Yusuke Wakatsuki
- grid.272242.30000 0001 2168 5385Department of Diagnostic Technology, National Cancer Center Hospital, Chuo City, Japan
| | - Toshihiro Ishihara
- grid.272242.30000 0001 2168 5385Department of Diagnostic Technology, National Cancer Center Hospital, Chuo City, Japan
| | - Chihiro Hattori
- grid.471046.00000 0001 0671 5048Canon Medical Systems Corp., Otawara, Japan
| | - Yasuko Fujisawa
- grid.471046.00000 0001 0671 5048Canon Medical Systems Corp., Otawara, Japan
| | - Masahiko Kusumoto
- grid.272242.30000 0001 2168 5385Department of Diagnostic Radiology, National Cancer Center Hospital, Chuo City, Japan
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Hinzpeter R, Kulanthaivelu R, Kohan A, Avery L, Pham NA, Ortega C, Metser U, Haider M, Veit-Haibach P. CT Radiomics and Whole Genome Sequencing in Patients with Pancreatic Ductal Adenocarcinoma: Predictive Radiogenomics Modeling. Cancers (Basel) 2022; 14:cancers14246224. [PMID: 36551709 PMCID: PMC9776865 DOI: 10.3390/cancers14246224] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2022] [Revised: 12/02/2022] [Accepted: 12/12/2022] [Indexed: 12/23/2022] Open
Abstract
We investigate whether computed tomography (CT) derived radiomics may correlate with driver gene mutations in patients with pancreatic ductal adenocarcinoma (PDAC). In this retrospective study, 47 patients (mean age 64 ± 11 years; range: 42-86 years) with PDAC, who were treated surgically and who underwent preoperative CT imaging at our institution were included in the study. Image segmentation and feature extraction was performed semi-automatically with a commonly used open-source software platform. Genomic data from whole genome sequencing (WGS) were collected from our institution's web-based resource. Two statistical models were then built, in order to evaluate the predictive ability of CT-derived radiomics feature for driver gene mutations in PDAC. 30/47 of all tumor samples harbored 2 or more gene mutations. Overall, 81% of tumor samples demonstrated mutations in KRAS, 68% of samples had alterations in TP53, 26% in SMAD4 and 19% in CDKN2A. Extended statistical analysis revealed acceptable predictive ability for KRAS and TP53 (Youden Index 0.56 and 0.67, respectively) and mild to acceptable predictive signal for SMAD4 and CDKN2A (Youden Index 0.5, respectively). Our study establishes acceptable correlation of radiomics features and driver gene mutations in PDAC, indicating an acceptable prognostication of genomic profiles using CT-derived radiomics. A larger and more homogenous cohort may further enhance the predictive ability.
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Affiliation(s)
- Ricarda Hinzpeter
- Joint Department of Medical Imaging, Princess Margaret Hospital, University Health Network, University of Toronto, Toronto, ON M5G 2C1, Canada
- Correspondence: ; Tel.: +1-416-340-4800
| | - Roshini Kulanthaivelu
- Joint Department of Medical Imaging, Princess Margaret Hospital, University Health Network, University of Toronto, Toronto, ON M5G 2C1, Canada
| | - Andres Kohan
- Joint Department of Medical Imaging, Princess Margaret Hospital, University Health Network, University of Toronto, Toronto, ON M5G 2C1, Canada
| | - Lisa Avery
- Department of Biostatistics, Princess Margaret Cancer Centre, University Health Network, University of Toronto, Toronto, ON M5G 2C1, Canada
- Division of Biostatistics, Dalla Lana School of Public Health, University of Toronto, Toronto, ON M5T 3M7, Canada
| | - Nhu-An Pham
- Princess Margaret Cancer Centre, University Health Network, Toronto, ON M5G 2C1, Canada
| | - Claudia Ortega
- Joint Department of Medical Imaging, Princess Margaret Hospital, University Health Network, University of Toronto, Toronto, ON M5G 2C1, Canada
| | - Ur Metser
- Joint Department of Medical Imaging, Princess Margaret Hospital, University Health Network, University of Toronto, Toronto, ON M5G 2C1, Canada
| | - Masoom Haider
- Joint Department of Medical Imaging, Princess Margaret Hospital, University Health Network, University of Toronto, Toronto, ON M5G 2C1, Canada
| | - Patrick Veit-Haibach
- Joint Department of Medical Imaging, Princess Margaret Hospital, University Health Network, University of Toronto, Toronto, ON M5G 2C1, Canada
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Druk IV. Pancreatic cancer, pancreatogenic diabetes, type 2 diabetes mellitus. EXPERIMENTAL AND CLINICAL GASTROENTEROLOGY 2022:171-182. [DOI: 10.31146/1682-8658-ecg-205-9-171-182] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/03/2025]
Abstract
Pancreatic cancer (PC) is the fourth leading cause of death among all types of cancer. PC is very aggressive with a low 5-year overall survival rate. The highest prevalence of diabetes mellitus (DM), significantly exceeding the average population, is registered among patients with prostate cancer Recommendations for systemic screening of patients with diabetes for the detection of PC are not standardized. The purpose of this review is to present an analysis of current literature data on pathogenetic relationships between DM and PC and prospects for PC screening. Research data indicate that there is a bidirectional relationship between DM and PC, in which DM can act either as a risk factor for PC or as a marker of paraneoplastic syndrome of PC. In the differential diagnosis of type 2 diabetes, pancreatogenic diabetes and diabetes associated with PC, a set of clinical signs can be used. Patients with DM who have additional signs/symptoms of increased risk can be considered as a group subject to mandatory screening. Numerous studies of various proteomic, metabolomic, genetic and transcriptomic biomarkers PC have been published. The search for an easy-to-use clinically useful and cost-effective PC marker is still ongoing.
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Prejac J, Tomek Hamzić D, Librenjak N, Goršić I, Kekez D, Pleština S. The effectiveness of nab-paclitaxel plus gemcitabine and gemcitabine monotherapy in first-line metastatic pancreatic cancer treatment: A real-world evidence. Medicine (Baltimore) 2022; 101:e30566. [PMID: 36181099 PMCID: PMC9524920 DOI: 10.1097/md.0000000000030566] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/05/2023] Open
Abstract
Pancreatic cancer is one of the most lethal malignancies with a rise in mortality rates. FOLFIRINOX and nab-paclitaxel plus gemcitabine demonstrated a survival benefit compared to gemcitabine alone. Both protocols are now considered the standard of first-line treatment with no significant difference between them, primarily based on observational studies. Although new therapeutic options have emerged recently, the prognosis remains poor. We conducted a retrospective single-center study on 139 patients treated for metastatic pancreatic adenocarcinoma (mPDAC) with gemcitabine monotherapy (Gem) or nab-paclitaxel + gemcitabine (Nab-P/Gem) in the first line. The aim of our study was to evaluate the effectiveness in terms of overall survival (OS) and progression-free survival (PFS) as well as the influence of patient and disease characteristics on outcomes. Nab-P/Gem resulted in OS of 13.87 months compared to 8.5 months in patients receiving Gem. The same trend was achieved in PFS, 5.37 versus 2.80 months, respectively, but without reaching statistical significance. Furthermore, the 6-month survival in the Nab-P/Gem group was also higher, 78.1% versus 47.8%. In terms of survival, the group of elderly patients, patients of poorer performance, with higher metastatic burden and liver involvement, benefited the most from combination therapy. In our analysis ECOG performance status (p.s.), previous primary tumor surgery, and liver involvement were found to be independent prognostic factors. The addition of nab-paclitaxel to gemcitabine resulted in a significant improvement in the OS of patients with mPDAC. Subgroup analysis demonstrated that patients with some unfavorable prognostic factors benefited the most.
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Affiliation(s)
- Juraj Prejac
- University Hospital Centre Zagreb, Department of Oncology, Zagreb, Croatia
- University of Zagreb, School of Dental Medicine, Zagreb, Croatia
| | - Dora Tomek Hamzić
- University Hospital Centre Zagreb, Department of Oncology, Zagreb, Croatia
| | - Nikša Librenjak
- University Hospital Centre Zagreb, Department of Oncology, Zagreb, Croatia
| | - Irma Goršić
- University Hospital Centre Zagreb, Department of Oncology, Zagreb, Croatia
| | - Domina Kekez
- University Hospital Centre Zagreb, Department of Oncology, Zagreb, Croatia
- University of Zagreb, School of Dental Medicine, Zagreb, Croatia
| | - Stjepko Pleština
- University Hospital Centre Zagreb, Department of Oncology, Zagreb, Croatia
- University of Zagreb, School of Medicine, Zagreb, Croatia
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Khristenko E, Hank T, Gaida MM, Kauczor HU, Hackert T, Klauß M, Mayer P. Imaging features of intraductal tubulopapillary neoplasm of the pancreas and its differentiation from conventional pancreatic ductal adenocarcinoma. Sci Rep 2022; 12:15557. [PMID: 36114217 PMCID: PMC9481632 DOI: 10.1038/s41598-022-19517-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2021] [Accepted: 08/30/2022] [Indexed: 11/19/2022] Open
Abstract
Intraductal tubulopapillary neoplasms (ITPN) are rare pancreatic tumors (< 1% of exocrine neoplasms) and are considered to have better prognosis than classical pancreatic ductal adenocarcinoma (PDAC). The present study aimed to evaluate imaging features of ITPN in computed tomography (CT) and magnetic resonance (MR) imaging. We performed monocentric retrospective analysis of 14 patients with histopathologically verified ITPN, operated in 2003–2018. Images were available for 12 patients and were analysed independently by two radiologists, blinded to reports. Imaging features were compared to a matched control group consisting of 43 patients with PDAC, matched for sex and age. Histopathologic analysis showed invasive carcinoma component in all ITPN patients. CT-attenuation values of ITPN were higher in arterial and venous phases (62.3 ± 14.6 HU and 68 ± 15.6 HU) than in unenhanced phase (39.2 ± 7.9 HU), compatible with solid lesion enhancement. Compared to PDAC, ITPN lesions had significantly higher HU-values in both arterial and venous phases (arterial and venous phases, p < 0.001). ITPN were significantly larger than PDAC (4.1 ± 2.0 cm versus 2.6 ± 0.84 cm, p = 0.021). ITPN lesions were more often well-circumscribed (p < 0.002). Employing a multiple logistic regression analysis with forward stepwise method, higher HU density in the arterial phase (p = 0.012) and well-circumscribed lesion margins (p = 0.047) were found to be significant predictors of ITPN versus PDAC. Our study identified key imaging features for differentiation of ITPN and PDAC. Isodensity or moderate hypodensity and well-circumscribed margins favor the diagnosis of ITPN over PDAC. Being familiar with CT-features of these rare pancreatic tumors is essential for radiologists to accelerate the diagnosis and narrow the differentials.
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Deshpande SS, Joshi AR, Mankar D. Pancreatic Neoplasms: CT Evaluation of the Uncommon Presentations of Common Lesions and Common Presentations of the Uncommon Lesions! Indian J Radiol Imaging 2022; 32:531-539. [DOI: 10.1055/s-0042-1754359] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/14/2022] Open
Abstract
AbstractPancreatic masses are commonly encountered entities in radiology practice. Pancreatic ductal adenocarcinomas (PDAC) are the commonest pancreatic malignancies that typically present as infiltrative hypodense focal masses in the pancreatic head, which are hypoattenuating to the pancreatic parenchyma on pancreatic parenchymal and venous phases. However, there are various atypical imaging features of PDACs that create a diagnostic dilemma like tumor in body or tail, diffuse glandular involvement, isoattenuating tumors, cystic changes, or calcifications. Also, few relatively uncommon pancreatic malignancies like pancreatic neuroendocrine tumors, cystic pancreatic tumors, pancreatic lymphoma, and pancreatic metastases present with overlapping features. Accurate radiological characterization of pancreatic masses is important for optimal management and prognostication. Thus, it is imperative for radiologists to be aware of all the uncommon presentations of common pancreatic lesions and common presentations of uncommon pancreatic lesions to avoid erroneous interpretations and establishing the correct diagnosis.
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Affiliation(s)
- Sneha Satish Deshpande
- Department of Radiology, Lokmanya Tilak Municipal Medical College and General Hospital, Sion, Mumbai, Maharashtra, India
| | - Anagha Rajeev Joshi
- Department of Radiology, Lokmanya Tilak Municipal Medical College and General Hospital, Sion, Mumbai, Maharashtra, India
| | - Diksha Mankar
- Department of Radiology, Lokmanya Tilak Municipal Medical College and General Hospital, Sion, Mumbai, Maharashtra, India
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Pancreatic Incidentaloma. J Clin Med 2022; 11:jcm11164648. [PMID: 36012893 PMCID: PMC9409921 DOI: 10.3390/jcm11164648] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2022] [Revised: 08/03/2022] [Accepted: 08/08/2022] [Indexed: 11/16/2022] Open
Abstract
Pancreatic incidentalomas (PIs) represent a clinical entity increasingly recognized due to advances in and easier access to imaging techniques. By definition, PIs should be detected during abdominal imaging performed for indications other than a pancreatic disease. They range from small cysts to invasive cancer. The incidental diagnosis of pancreatic cancer can contribute to early diagnosis and treatment. On the other hand, inadequate management of PIs may result in overtreatment and unneeded morbidity. Therefore, there is a strong need to evaluate the nature and clinical features of individual PIs. In this review, we summarize the major characteristics related to PIs and present suggestions for their management.
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