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Matsumoto M, Tsunematsu M, Hamura R, Haruki K, Furukawa K, Shirai Y, Uwagawa T, Onda S, Taniai T, Tanji Y, Yanagaki M, Ikegami T. The minimum apparent diffusion coefficient value on preoperative magnetic resonance imaging in resectable pancreatic cancer: a new prognostic factor for biologically borderline resectable pancreatic cancer. Surg Today 2025:10.1007/s00595-025-03050-w. [PMID: 40301166 DOI: 10.1007/s00595-025-03050-w] [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: 11/17/2024] [Accepted: 04/03/2025] [Indexed: 05/01/2025]
Abstract
PURPOSE To identify the prognostic factors that can define biologically borderline resectable pancreatic cancer (BRPC) in resectable pancreatic cancer (RPC) patients. METHODS This retrospective study included 121 R/BRPC patients who underwent upfront surgery. Univariate and multivariate analyses were conducted to investigate the relationship between preoperative factors and overall survival (OS) for RPC. The OS of RPC patients was stratified based on a score, with each independent prognostic factor receiving 1 point. The OS of the R/BRPC patients was compared based on their scores. RESULTS Overall, 113 and eight patients had RPC and BRPC. Serum CA19-9 > 500 U/mL (p = 0.048), maximum tumor diameter > 30 mm (p = 0.01), superior mesenteric/portal vein contact < 180° (p = 0.04), and minimum apparent diffusion coefficient (ADCmin) ≤ 1020 × 10-6 mm2/s (p = 0.01) were identified as independent prognostic factors in RPC patients. RPC patients with a score of 0 had a significantly better prognosis than those with scores of 1 and 2-4 and BRPC patients (median OS: 99.3, 35.1, 19.0, and 8.4 months; p = 0.007, p < 0.001, and p = 0.003, respectively). No significant difference in the prognosis was observed between BRPC and RPC patients with scores of 1 and 2-4. CONCLUSIONS Preoperative ADCmin in RPC may be a new prognostic factor for biological BRPC.
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Affiliation(s)
- Michinori Matsumoto
- Department of Surgery, The Jikei University School of Medicine, 3-25-8 Nishi-Shinbashi, Minato-Ku, Tokyo, 105-8461, Japan.
| | - Masashi Tsunematsu
- Department of Surgery, The Jikei University School of Medicine, 3-25-8 Nishi-Shinbashi, Minato-Ku, Tokyo, 105-8461, Japan
| | - Ryoga Hamura
- Department of Surgery, The Jikei University School of Medicine, 3-25-8 Nishi-Shinbashi, Minato-Ku, Tokyo, 105-8461, Japan
| | - Koichiro Haruki
- Department of Surgery, The Jikei University School of Medicine, 3-25-8 Nishi-Shinbashi, Minato-Ku, Tokyo, 105-8461, Japan
| | - Kenei Furukawa
- Department of Surgery, The Jikei University School of Medicine, 3-25-8 Nishi-Shinbashi, Minato-Ku, Tokyo, 105-8461, Japan
| | - Yoshihiro Shirai
- Department of Surgery, The Jikei University School of Medicine, 3-25-8 Nishi-Shinbashi, Minato-Ku, Tokyo, 105-8461, Japan
| | - Tadashi Uwagawa
- Department of Surgery, The Jikei University School of Medicine, 3-25-8 Nishi-Shinbashi, Minato-Ku, Tokyo, 105-8461, Japan
| | - Shinji Onda
- Department of Surgery, The Jikei University School of Medicine, 3-25-8 Nishi-Shinbashi, Minato-Ku, Tokyo, 105-8461, Japan
| | - Tomohiko Taniai
- Department of Surgery, The Jikei University School of Medicine, 3-25-8 Nishi-Shinbashi, Minato-Ku, Tokyo, 105-8461, Japan
| | - Yoshiaki Tanji
- Department of Surgery, The Jikei University School of Medicine, 3-25-8 Nishi-Shinbashi, Minato-Ku, Tokyo, 105-8461, Japan
| | - Mitsuru Yanagaki
- Department of Surgery, The Jikei University School of Medicine, 3-25-8 Nishi-Shinbashi, Minato-Ku, Tokyo, 105-8461, Japan
| | - Toru Ikegami
- Department of Surgery, The Jikei University School of Medicine, 3-25-8 Nishi-Shinbashi, Minato-Ku, Tokyo, 105-8461, Japan
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Qu C, Zeng P, Li C, Hu W, Yang D, Wang H, Yuan H, Cao J, Xiu D. A machine learning model based on preoperative multiparametric quantitative DWI can effectively predict the survival and recurrence risk of pancreatic ductal adenocarcinoma. Insights Imaging 2025; 16:38. [PMID: 39962007 PMCID: PMC11833029 DOI: 10.1186/s13244-025-01915-9] [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: 10/21/2024] [Accepted: 01/26/2025] [Indexed: 02/20/2025] Open
Abstract
PURPOSE To develop a machine learning (ML) model combining preoperative multiparametric diffusion-weighted imaging (DWI) and clinical features to better predict overall survival (OS) and recurrence-free survival (RFS) following radical surgery for pancreatic ductal adenocarcinoma (PDAC). MATERIALS AND METHODS A retrospective analysis was conducted on 234 PDAC patients who underwent radical resection at two centers. Among 101 ML models tested for predicting postoperative OS and RFS, the best-performing model was identified based on comprehensive evaluation metrics, including C-index, Brier scores, AUC curves, clinical decision curves, and calibration curves. This model's risk stratification capability was further validated using Kaplan-Meier survival analysis. RESULTS The random survival forest model achieved the highest C-index (0.828/0.723 for OS and 0.781/0.747 for RFS in training/validation cohorts). Incorporating nine key factors-D value, T-stage, ADC-value, postoperative 7th day CA19-9 level, AJCC stage, tumor differentiation, type of operation, tumor location, and age-optimized the model's predictive accuracy. The model had integrated Brier score below 0.13 and C/D AUC values above 0.85 for both OS and RFS predictions. It also outperformed traditional models in predictive ability and clinical benefit, as shown by clinical decision curves. Calibration curves confirmed good predictive consistency. Using cut-off scores of 16.73/29.05 for OS/RFS, Kaplan-Meier analysis revealed significant prognostic differences between risk groups (p < 0.0001), highlighting the model's robust risk prediction and stratification capabilities. CONCLUSION The random survival forest model, combining DWI and clinical features, accurately predicts survival and recurrence risk after radical resection of PDAC and effectively stratifies risk to guide clinical treatment. CRITICAL RELEVANCE STATEMENT The construction of 101 ML models based on multiparametric quantitative DWI combined with clinical variables has enhanced the prediction performance for survival and recurrence risks in patients undergoing radical resection for PDAC. KEY POINTS This study first develops DWI-based radiological-clinical ML models predicting PDAC prognosis. Among 101 models, RFS is the best and outperforms other traditional models. Multiparametric DWI is the key prognostic predictor, with model interpretations through SurvSHAP.
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Affiliation(s)
- Chao Qu
- Department of Hepatobiliary and Pancreatic Surgery, The Affiliated Hospital of Qingdao University, Qingdao, China
- Department of General Surgery, Peking University Third Hospital, Beijing, China
| | - Piaoe Zeng
- Department of Radiology, Peking University Third Hospital, Beijing, China
| | - Changlei Li
- Department of Hepatobiliary and Pancreatic Surgery, The Affiliated Hospital of Qingdao University, Qingdao, China
| | - Weiyu Hu
- Department of Hepatobiliary and Pancreatic Surgery, The Affiliated Hospital of Qingdao University, Qingdao, China
| | - Dongxia Yang
- Department of Hepatobiliary and Pancreatic Surgery, The Affiliated Hospital of Qingdao University, Qingdao, China
| | - Hangyan Wang
- Department of General Surgery, Peking University Third Hospital, Beijing, China
| | - Huishu Yuan
- Department of Radiology, Peking University Third Hospital, Beijing, China
| | - Jingyu Cao
- Department of Hepatobiliary and Pancreatic Surgery, The Affiliated Hospital of Qingdao University, Qingdao, China.
| | - Dianrong Xiu
- Department of General Surgery, Peking University Third Hospital, Beijing, China.
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Shi S, Liu R, Zhou J, Liu J, Lin H, Mo J, Zhang J, Diao X, Luo Y, Huang B, Feng ST. Development and validation of a CT-based radiomics model to predict survival-graded fibrosis in pancreatic ductal adenocarcinoma. Int J Surg 2025; 111:950-961. [PMID: 39172712 PMCID: PMC11745594 DOI: 10.1097/js9.0000000000002059] [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: 02/19/2024] [Accepted: 08/11/2024] [Indexed: 08/24/2024]
Abstract
BACKGROUND Tumor fibrosis plays an important role in chemotherapy resistance in pancreatic ductal adenocarcinoma (PDAC); however, there remains a contradiction in the prognostic value of fibrosis. The authors aimed to investigate the relationship between tumor fibrosis and survival in patients with PDAC, classify patients into high- and low-fibrosis groups, and develop and validate a CT-based radiomics model to non-invasively predict fibrosis before treatment. MATERIALS AND METHODS This retrospective, bicentric study included 295 patients with PDAC without any treatments before surgery. Tumor fibrosis was assessed using the collagen fraction (CF). Cox regression analysis was used to evaluate the associations of CF with overall survival (OS) and disease-free survival (DFS). Receiver operating characteristic (ROC) analyses were used to determine the rounded threshold of CF. An integrated model (IM) was developed by incorporating selected radiomic features and clinical-radiological characteristics. The predictive performance was validated in the test cohort (Center 2). RESULTS The CFs were 38.22±6.89% and 38.44±8.66% in center 1 (131 patients, 83 males) and center 2 (164 patients, 100 males), respectively ( P =0.814). Multivariable Cox regression revealed that CF was an independent risk factor in the OS and DFS analyses at both centers. ROCs revealed that 40% was the rounded cut-off value of CF. IM predicted CF with areas under the curves (AUCs) of 0.829 (95% CI: 0.753-0.889) and 0.751 (95% CI: 0.677-0.815) in the training and test cohorts, respectively. Decision curve analyses revealed that IM outperformed radiomics model and clinical-radiological model for CF prediction in both cohorts. CONCLUSIONS Tumor fibrosis was an independent risk factor for survival of patients with PDAC, and a rounded cut-off value of 40% provided a good differentiation of patient prognosis. The model combining CT-based radiomics and clinical-radiological features can satisfactorily predict survival-grade fibrosis in patients with PDAC.
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Affiliation(s)
- Siya Shi
- Department of Radiology, The First Affiliated Hospital, Sun Yat-sen University
| | - Ruihao Liu
- Marshall Laboratory of Biomedical Engineering, Shenzhen University
- Medical AI Lab, School of Biomedical Engineering, Shenzhen University Medical School, Shenzhen University
- National-Regional Key Technology Engineering Laboratory for Medical Ultrasound, Guangdong Key Laboratory for Biomedical Measurements and Ultrasound Imaging, Medical School, Shenzhen University, Shenzhen, Guangdong, China
| | - Jian Zhou
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Department of Radiology, Sun Yat-sen University Cancer Center, Guangzhou
- South China Hospital, Medical School, Shenzhen University
| | - Jiawei Liu
- Department of Radiology, The First Affiliated Hospital, Sun Yat-sen University
| | - Hongxin Lin
- Marshall Laboratory of Biomedical Engineering, Shenzhen University
- Medical AI Lab, School of Biomedical Engineering, Shenzhen University Medical School, Shenzhen University
| | - Junyang Mo
- Marshall Laboratory of Biomedical Engineering, Shenzhen University
- Medical AI Lab, School of Biomedical Engineering, Shenzhen University Medical School, Shenzhen University
| | - Jian Zhang
- Shenzhen-Hong Kong Institute of Brain Science-Shenzhen Fundamental Research Institutions
- Shenzhen University Medical School, Shenzhen University
| | - Xianfen Diao
- Marshall Laboratory of Biomedical Engineering, Shenzhen University
- Medical AI Lab, School of Biomedical Engineering, Shenzhen University Medical School, Shenzhen University
- National-Regional Key Technology Engineering Laboratory for Medical Ultrasound, Guangdong Key Laboratory for Biomedical Measurements and Ultrasound Imaging, Medical School, Shenzhen University, Shenzhen, Guangdong, China
| | - Yanji Luo
- Department of Radiology, The First Affiliated Hospital, Sun Yat-sen University
| | - Bingsheng Huang
- Marshall Laboratory of Biomedical Engineering, Shenzhen University
- Medical AI Lab, School of Biomedical Engineering, Shenzhen University Medical School, Shenzhen University
- Shenzhen-Hong Kong Institute of Brain Science-Shenzhen Fundamental Research Institutions
| | - Shi-Ting Feng
- Department of Radiology, The First Affiliated Hospital, Sun Yat-sen University
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Fukukura Y, Kanki A. Quantitative Magnetic Resonance Imaging for the Pancreas: Current Status. Invest Radiol 2024; 59:69-77. [PMID: 37433065 DOI: 10.1097/rli.0000000000001002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/13/2023]
Abstract
ABSTRACT Magnetic resonance imaging (MRI) is important for evaluating pancreatic disorders, and anatomical landmarks play a major role in the interpretation of results. Quantitative MRI is an effective diagnostic modality for various pathologic conditions, as it allows the investigation of various physical parameters. Recent advancements in quantitative MRI techniques have significantly improved the accuracy of pancreatic MRI. Consequently, this method has become an essential tool for the diagnosis, treatment, and monitoring of pancreatic diseases. This comprehensive review article presents the currently available evidence on the clinical utility of quantitative MRI of the pancreas.
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Affiliation(s)
- Yoshihiko Fukukura
- From the Department of Radiology, Kawasaki Medical School, Kurashiki City, Okayama, Japan
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Miller FH, Lopes Vendrami C, Hammond NA, Mittal PK, Nikolaidis P, Jawahar A. Pancreatic Cancer and Its Mimics. Radiographics 2023; 43:e230054. [PMID: 37824413 DOI: 10.1148/rg.230054] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/14/2023]
Abstract
Pancreatic ductal adenocarcinoma (PDAC) is the most common primary pancreatic malignancy, ranking fourth in cancer-related mortality in the United States. Typically, PDAC appears on images as a hypovascular mass with upstream pancreatic duct dilatation and abrupt duct cutoff, distal pancreatic atrophy, and vascular encasement, with metastatic involvement including lymphadenopathy. However, atypical manifestations that may limit detection of the underlying PDAC may also occur. Atypical PDAC features include findings related to associated conditions such as acute or chronic pancreatitis, a mass that is isointense to the parenchyma, multiplicity, diffuse tumor infiltration, associated calcifications, and cystic components. Several neoplastic and inflammatory conditions can mimic PDAC, such as paraduodenal "groove" pancreatitis, autoimmune pancreatitis, focal acute and chronic pancreatitis, neuroendocrine tumors, solid pseudopapillary neoplasms, metastases, and lymphoma. Differentiation of these conditions from PDAC can be challenging due to overlapping CT and MRI features; however, certain findings can help in differentiation. Diffusion-weighted MRI can be helpful but also can be nonspecific. Accurate diagnosis is pivotal for guiding therapeutic planning and potential outcomes in PDAC and avoiding biopsy or surgical treatment of some of these mimics. Biopsy may still be required for diagnosis in some cases. The authors describe the typical and atypical imaging findings of PDAC and features that may help to differentiate PDAC from its mimics. ©RSNA, 2023 Online supplemental material is available for this article. Quiz questions for this article are available through the Online Learning Center. See the invited commentary by Zins in this issue.
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Affiliation(s)
- Frank H Miller
- From the Department of Radiology, Northwestern Memorial Hospital, Northwestern University Feinberg School of Medicine, 676 N St. Clair St, Ste 800, Chicago, IL 60611 (F.H.M., C.L.V., N.A.H., P.N., A.J.); and Department of Radiology and Imaging, Medical College of Georgia, Augusta, GA (P.K.M.)
| | - Camila Lopes Vendrami
- From the Department of Radiology, Northwestern Memorial Hospital, Northwestern University Feinberg School of Medicine, 676 N St. Clair St, Ste 800, Chicago, IL 60611 (F.H.M., C.L.V., N.A.H., P.N., A.J.); and Department of Radiology and Imaging, Medical College of Georgia, Augusta, GA (P.K.M.)
| | - Nancy A Hammond
- From the Department of Radiology, Northwestern Memorial Hospital, Northwestern University Feinberg School of Medicine, 676 N St. Clair St, Ste 800, Chicago, IL 60611 (F.H.M., C.L.V., N.A.H., P.N., A.J.); and Department of Radiology and Imaging, Medical College of Georgia, Augusta, GA (P.K.M.)
| | - Pardeep K Mittal
- From the Department of Radiology, Northwestern Memorial Hospital, Northwestern University Feinberg School of Medicine, 676 N St. Clair St, Ste 800, Chicago, IL 60611 (F.H.M., C.L.V., N.A.H., P.N., A.J.); and Department of Radiology and Imaging, Medical College of Georgia, Augusta, GA (P.K.M.)
| | - Paul Nikolaidis
- From the Department of Radiology, Northwestern Memorial Hospital, Northwestern University Feinberg School of Medicine, 676 N St. Clair St, Ste 800, Chicago, IL 60611 (F.H.M., C.L.V., N.A.H., P.N., A.J.); and Department of Radiology and Imaging, Medical College of Georgia, Augusta, GA (P.K.M.)
| | - Anugayathri Jawahar
- From the Department of Radiology, Northwestern Memorial Hospital, Northwestern University Feinberg School of Medicine, 676 N St. Clair St, Ste 800, Chicago, IL 60611 (F.H.M., C.L.V., N.A.H., P.N., A.J.); and Department of Radiology and Imaging, Medical College of Georgia, Augusta, GA (P.K.M.)
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Qu C, Zeng P, Wang H, Guo L, Zhang L, Yuan C, Yuan H, Xiu D. Preoperative Multiparametric Quantitative Magnetic Resonance Imaging Correlates with Prognosis and Recurrence Patterns in Pancreatic Ductal Adenocarcinoma. Cancers (Basel) 2022; 14:cancers14174243. [PMID: 36077777 PMCID: PMC9454581 DOI: 10.3390/cancers14174243] [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: 06/04/2022] [Revised: 08/19/2022] [Accepted: 08/28/2022] [Indexed: 11/17/2022] Open
Abstract
Simple Summary Magnetic resonance imaging (MRI) has been considered a noninvasive prognostic biomarker in some cancers; however, the correlation with pancreatic ductal adenocarcinoma (PDAC) remains inconclusive. The aim of our study was to identify quantitative MRI parameters associated with prognosis and recurrence patterns. In an analysis of data from the 136 patients ultimately included in this study, we found that the value of the pure diffusion coefficient D in intravoxel incoherent MRI is an independent risk factor for overall survival (OS) and recurrence-free survival (RFS), while a low value of D is significantly associated with a higher risk of local recurrence. All the patients have been operated on with histopathology for further evaluation. Based on the results of our research, we believe that it is possible in clinical practice to stratify patients based on quantitative MRI data in order to guide treatment strategies, reduce the risk of local tumor recurrence, and improve patients’ prognosis. Abstract Magnetic resonance imaging (MRI) has been shown to be associated with prognosis in some tumors; however, the correlation in pancreatic ductal adenocarcinoma (PDAC) remains inconclusive. In this retrospective study, we ultimately included 136 patients and analyzed quantitative MRI parameters that are associated with prognosis and recurrence patterns in PDAC using survival analysis and competing risks models; all the patients have been operated on with histopathology and immunohistochemical staining for further evaluation. In intravoxel incoherent motion diffusion-weighted imaging (DWI), we found that pure-diffusion coefficient D value was an independent risk factor for overall survival (OS) (HR: 1.696, 95% CI: 1.003–2.869, p = 0.049) and recurrence-free survival (RFS) (HR: 2.066, 95% CI: 1.252–3.409, p = 0.005). A low D value (≤1.08 × 10−3 mm2/s) was significantly associated with a higher risk of local recurrence (SHR: 5.905, 95% CI: 2.107–16.458, p = 0.001). Subgroup analysis revealed that patients with high D and f values had significantly better outcomes with adjuvant chemotherapy. Distant recurrence patients in the high-D value group who received chemotherapy may significantly improve their OS and RFS. It was found that preoperative multiparametric quantitative MRI correlates with prognosis and recurrence patterns in PDAC. Diffusion coefficient D value can be used as a noninvasive biomarker for predicting prognosis and recurrence patterns in PDAC.
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Affiliation(s)
- Chao Qu
- Department of General Surgery, Peking University Third Hospital, Beijing 100191, China
| | - Piaoe Zeng
- Department of Radiology, Peking University Third Hospital, Beijing 100191, China
| | - Hangyan Wang
- Department of General Surgery, Peking University Third Hospital, Beijing 100191, China
| | - Limei Guo
- Department of Pathology, School of Basic Medical Sciences, Peking University Third Hospital, Peking University Health Science Center, Beijing 100191, China
| | - Lingfu Zhang
- Department of General Surgery, Peking University Third Hospital, Beijing 100191, China
| | - Chunhui Yuan
- Department of General Surgery, Peking University Third Hospital, Beijing 100191, China
| | - Huishu Yuan
- Department of Radiology, Peking University Third Hospital, Beijing 100191, China
- Correspondence: (H.Y.); (D.X.)
| | - Dianrong Xiu
- Department of General Surgery, Peking University Third Hospital, Beijing 100191, China
- Correspondence: (H.Y.); (D.X.)
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Qu C, Zeng PE, Wang HY, Yuan CH, Yuan HS, Xiu DR. Application of Magnetic Resonance Imaging in Neoadjuvant Treatment of Pancreatic Ductal Adenocarcinoma. J Magn Reson Imaging 2022; 55:1625-1632. [PMID: 35132729 DOI: 10.1002/jmri.28096] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2021] [Revised: 01/18/2022] [Accepted: 01/22/2022] [Indexed: 12/11/2022] Open
Abstract
Pancreatic ductal adenocarcinoma (PDAC) is one of the deadliest malignant tumors of the human digestive system. Due to its insidious onset, many patients have already lost the opportunity for radical resection upon tumor diagnosis. In recent years, neoadjuvant treatment for patients with borderline resectable PDAC has been recommended by multiple guidelines to increase the resection rate of radical surgery and improve the postoperative survival. However, further developments are required to accurately assess the tumor response to neoadjuvant therapy and to select the population suitable for such treatment. Reductions in drug toxicity and the number of neoadjuvant cycles are also critical. At present, the clinical evaluation of neoadjuvant treatment is mainly based on several serological and imaging indicators; however, the unique characteristics of PDAC and the insufficient sensitivity and specificity of the markers render this system ineffective. The imaging evaluation system, magnetic resonance imaging (MRI), has its own unique imaging advantages compared with computed tomography (CT) and other imaging examinations. One key advantage is the ability to reflect the changes more rapidly in tumor tissue components, such as the degree of fibrosis, microvessel density, and tissue hypoxia. It can also perform multiparameter quantitative analysis of tumor tissue and changes, attributing to its increasingly important role in imaging evaluation, and potentially the evaluation of neoadjuvant treatment of pancreatic cancer, as several current articles have studied. At the same time, owing to the complexity of MRI and some of its limitations, its wider application is limited. Compared with CT imaging, few relevant studies have been conducted. In this review article, we will investigate and summarize the advantages, limitations, and future development of MRI in the evaluation of neoadjuvant treatment of PDAC. EVIDENCE LEVEL: 3 TECHNICAL EFFICACY: Stage 2.
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Affiliation(s)
- Chao Qu
- Department of General Surgery, Peking University Third Hospital, Beijing, China
| | - Piao-E Zeng
- Department of Radiology, Peking University Third Hospital, Beijing, China
| | - Hang-Yan Wang
- Department of General Surgery, Peking University Third Hospital, Beijing, China
| | - Chun-Hui Yuan
- Department of General Surgery, Peking University Third Hospital, Beijing, China
| | - Hui-Shu Yuan
- Department of Radiology, Peking University Third Hospital, Beijing, China
| | - Dian-Rong Xiu
- Department of General Surgery, Peking University Third Hospital, Beijing, China
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Cystic Lesions of the Pancreas: Is Apparent Diffusion Coefficient Value Useful at 3 T Magnetic Resonance Imaging? J Comput Assist Tomogr 2022; 46:363-370. [PMID: 35405726 DOI: 10.1097/rct.0000000000001302] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
OBJECTIVE The objective of this study is to determine the role of apparent diffusion coefficient (ADC) value at 3T magnetic resonance imaging (MRI) in the characterization of pancreatic cystic lesions. METHODS We retrospectively selected a total number of 223 patients with a conclusive diagnosis of pancreatic cystic lesion, previously undergoing MR examination on a 3 T system. The MRI protocol first included axial T1/T2-weighted sequences and magnetic resonance cholangiopancreatography. Diffusion-weighted MRI was performed using a spin-echo echo-planar sequence with multiple b values (0, 150, 500, 1000, and 1500 s/mm2) in all diffusion directions, obtaining an ADC map. Contrast-enhanced T1-weighted sequences were performed during the initial work-up of a pancreatic cystic lesion and when signs of malignancy were suspected during the MRI follow-up. The ADC value of each pancreatic lesion was measured using a monoexponential curve fitting with all the multiple b. RESULTS The final diagnosis of our study group included the following: serous cystadenomas (n = 42), mucinous cystadenomas (n = 14), intraductal papillary mucinous neoplasms (IPMNs) (n = 121), IPMNs with signs of malignancy at histopathologic examination (n = 24), pseudocysts (n = 9), other cystic lesions (n = 13). A statistically significant difference was observed between the ADC values of malignant IPMNs and those of each other group of pancreatic lesions (P < 0.001). The ADC value of benign IPMN was significantly higher than that of serous cystadenomas (P = 0.024). A statistically significant difference was observed between the ADCs of all mucinous cystic tumors (benign IPMNs together to mucinous cystadenomas) and the ADCs of serous cystadenomas (P = 0.014). CONCLUSIONS Fitted ADC value obtained at 3T MRI may be helpful in the characterization of pancreatic cystic lesions with particular regards of differential diagnosis between mucinous and serous cystic tumors and between malignant and benign IPMNs.
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Non-Invasive Monitoring of Increased Fibrotic Tissue and Hyaluronan Deposition in the Tumor Microenvironment in the Advanced Stages of Pancreatic Ductal Adenocarcinoma. Cancers (Basel) 2022; 14:cancers14040999. [PMID: 35205746 PMCID: PMC8870395 DOI: 10.3390/cancers14040999] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2021] [Revised: 02/06/2022] [Accepted: 02/11/2022] [Indexed: 02/04/2023] Open
Abstract
Simple Summary Pancreatic ductal adenocarcinoma (PDAC) is a deadly disease with a poor prognosis. A better understanding of the tumor microenvironment may help better treat the disease. Magnetic resonance imaging may be a great tool for monitoring the tumor microenvironment at different stages of tumor evolution. Here, we used multi-parametric magnetic resonance imaging techniques to monitor underlying pathophysiologic processes during the advanced stages of tumor development and correlated with histologic measurements. Abstract Pancreatic ductal adenocarcinomas are characterized by a complex and robust tumor microenvironment (TME) consisting of fibrotic tissue, excessive levels of hyaluronan (HA), and immune cells. We utilized quantitative multi-parametric magnetic resonance imaging (mp-MRI) methods at 14 Tesla in a genetically engineered KPC (KrasLSL-G12D/+, Trp53LSL-R172H/+, Cre) mouse model to assess the complex TME in advanced stages of tumor development. The whole tumor, excluding cystic areas, was selected as the region of interest for data analysis and subsequent statistical analysis. Pearson correlation was used for statistical inference. There was a significant correlation between tumor volume and T2 (r = −0.66), magnetization transfer ratio (MTR) (r = 0.60), apparent diffusion coefficient (ADC) (r = 0.48), and Glycosaminoglycan-chemical exchange saturation transfer (GagCEST) (r = 0.51). A subset of mice was randomly selected for histological analysis. There were positive correlations between tumor volume and fibrosis (0.92), and HA (r = 0.76); GagCEST and HA (r = 0.81); and MTR and CD31 (r = 0.48). We found a negative correlation between ADC low-b (perfusion) and Ki67 (r = −0.82). Strong correlations between mp-MRI and histology results suggest that mp-MRI can be used as a non-invasive tool to monitor the tumor microenvironment.
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Hussien N, Hussien RS, Saad DHA, El Kassas M, Elkhatib WF, Ezz El Din M. The Role of MRI Pancreatic Protocol in Assessing Response to Neoadjuvant Therapy for Patients With Borderline Resectable Pancreatic Cancer. Front Oncol 2022; 11:796317. [PMID: 35096596 PMCID: PMC8792857 DOI: 10.3389/fonc.2021.796317] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2021] [Accepted: 12/06/2021] [Indexed: 12/30/2022] Open
Abstract
BACKGROUND Borderline Resectable Pancreatic Cancer (BRPC) remains a unique entity that is difficult to categorize due to variance in definitions and the small number of patients. The ultimate goal is to achieve a free resection (R0) after a favorable response to neoadjuvant therapy that is somewhat difficult to assess by current radiological parameters. AIM To evaluate the role of Magnetic Resonance Imaging (MRI) pancreatic protocol, including Diffusion-Weighted Imaging (DWI), in patients with BRPC receiving neoadjuvant therapy, and further compare it to RECIST criteria and outcome. METHODS Histologically confirmed BRPC patients were prospectively included. DWI-MRI was performed pre- and post-therapy. Clinical characteristics with ensuing operability were recorded and correlated to radiological RECIST/apparent diffusion coefficient (ADC) change, preoperative therapy administrated, surgical resection status, and survival. RESULTS Out of 30 BRPC cases, only 11 (36.7%) ultimately underwent pancreaticoduodenectomy. Attaining a stationary or stable disease via ADC/RECIST was achieved in the majority of cases (60%/53.3% respectively). Of the 12 patients (40%) who achieved a regression by ADC, 11 underwent surgery with an R0 status. These surgical cases showed variable RECIST responses (PR=5, SD=4, PD=3). Responders by ADC to neoadjuvant therapy were significantly associated to presenting with abdominal pain (p =0.07), a decline in post-therapy CA19-9 (p<0.001), going through surgery (p<0.001), and even achieving better survival (p<0.001 vs. 0.66). CONCLUSION DWI-MRI ADC picked up patients most likely to undergo a successful operative procedure better than traditional RECIST criteria. An algorithm incorporating novel radiological advances with CA19-9 deserves further assessment in future studies.
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Affiliation(s)
- Nervana Hussien
- Department of Clinical Oncology, Faculty of Medicine, Helwan University, Cairo, Egypt
| | - Rasha S. Hussien
- Department of Radiology, Faculty of Medicine, Ain Shams University, Cairo, Egypt
| | | | - Mohamed El Kassas
- Department of Endemic Medicine, Faculty of Medicine, Helwan University, Cairo, Egypt
| | - Walid F. Elkhatib
- Department of Microbiology and Immunology, Faculty of Pharmacy, Ain Shams University, Cairo, Egypt
- Department of Microbiology & Immunology, Faculty of Pharmacy, Galala University, Suez, Egypt
| | - Mai Ezz El Din
- Department of Clinical Oncology, Faculty of Medicine, Ain Shams University, Cairo, Egypt
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11
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Identification of intratumoral fluid-containing area by magnetic resonance imaging to predict prognosis in patients with pancreatic ductal adenocarcinoma after curative resection. Eur Radiol 2021; 32:2518-2528. [PMID: 34671833 DOI: 10.1007/s00330-021-08328-4] [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: 05/25/2021] [Revised: 08/14/2021] [Accepted: 09/12/2021] [Indexed: 10/20/2022]
Abstract
OBJECTIVES To compare the prognosis of pancreatic ductal adenocarcinoma (PDAC) after curative resection according to the type of intratumoral fluid-containing area identified on MRI. METHODS This retrospective study included 112 consecutive patients who underwent upfront surgery with margin-negative resection between 2012 and 2019. All patients underwent MRI within 1 month before surgery. Three radiologists independently assessed the MRI findings, determined whether intratumoral fluid-containing areas were present, and classified all intratumoral fluid-containing areas by type (i.e., imaging necrosis or neoplastic mucin cysts). Recurrence-free survival (RFS) and overall survival (OS) were evaluated by the Kaplan-Meier method and the Cox proportional hazards model. Histopathological differences according to the type of intratumoral fluid-containing area were assessed. RESULTS Of the 112 PDAC patients, intratumoral fluid-containing areas were identified on MRI in 33 (29.5%), among which 18 were classified as imaging necrosis and 15 as neoplastic mucin cysts. PDAC patients with imaging necrosis demonstrated significantly shorter RFS (mean 6.1 months versus 47.3 months; p < .001) and OS (18.4 months versus 55.0 months, p = .001) than those with neoplastic mucin cysts. Multivariable analysis showed that only the type of intratumoral fluid-containing area was significantly associated with RFS (hazard ratio, 2.25 and 0.38; p = .009 and p = .046 for imaging necrosis and neoplastic mucin cysts, respectively). PDAC with imaging necrosis had more frequent histological necrosis, more aggressive tumor differentiation, and higher tumor cellularity than PDAC with neoplastic mucin cysts (p ≤ .02). CONCLUSION The detection and discrimination of intratumoral fluid-containing areas on preoperative MRI may be useful in predicting the prognosis of PDAC patients after curative resection. KEY POINTS • Pancreatic ductal adenocarcinoma (PDAC) patients with imaging necrosis demonstrated significantly shorter survival than those with neoplastic mucin cysts after curative resection. • Multivariable analysis showed that only the type of intratumoral fluid-containing area identified on MRI was significantly associated with recurrence-free survival. • PDAC with imaging necrosis had more frequent histological necrosis, more aggressive tumor differentiation, and higher tumor cellularity than PDAC with neoplastic mucin cysts.
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12
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Jeon SK, Jang JY, Kwon W, Kim H, Han Y, Kim D, Park D, Kim JH. Diffusion-weighted MR imaging in pancreatic ductal adenocarcinoma: prediction of next-generation sequencing-based tumor cellularity and prognosis after surgical resection. Abdom Radiol (NY) 2021; 46:4787-4799. [PMID: 34143259 DOI: 10.1007/s00261-021-03177-7] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2021] [Revised: 06/08/2021] [Accepted: 06/10/2021] [Indexed: 11/28/2022]
Abstract
PURPOSE To identify features on preoperative MR imaging with diffusion-weighted imaging (DWI) for predicting next-generation sequencing (NGS)-based tumor cellularity and patient outcome after surgical resection of pancreatic ductal adenocarcinoma (PDAC). METHODS This retrospective study included 105 patients with surgically resected PDAC who underwent preoperative MR imaging with DWI. Tumor cellularity was measured using molecular techniques and bioinformatics methods. Clinico-pathologic findings including tumor T stage for predicting disease-free survival (DFS) and overall survival (OS) were identified using Cox proportional hazards model. Important MR imaging findings including apparent diffusion coefficient (ADC) value of PDAC and modified ADC value (the ratio of the ADC value of PDAC to the ADC value of the spleen) for predicting higher tumor cellularity (≥ 30%) and poor prognosis were also identified. RESULTS The median DFS and OS were 12.0 months [95% confidence interval (CI), 8.0-17.0] and 22.0 months (95% CI, 18.0-29.0), respectively. Higher T stage (T3/4) [hazard ratio (HR), 7.720, (95% CI 1.072, 55.612); p = 0.048] and higher tumor cellularity [HR, 1.599 (95% CI, 1.003-2.548); p = 0.048] were significantly associated with worse DFS. Among MR imaging features, the modified ADC value was significantly associated with tumor cellularity [odds ratio, 0.068 (95% CI, 0.012-0.372); p = 0.002], and PDAC with lower modified ADC value [≤ 1.40 (cutoff value)] showed significantly shorter median DFS than PDAC with higher modified ADC value [8 months (95% CI, 4-12) vs. 16 months (95% CI, 10-29); HR, 1.713 (95% CI, 1.073-2.735), log-rank p = 0.024]. CONCLUSION Higher NGS-based tumor cellularity may be a negative prognostic factor in pancreatic cancer after resection, and modified ADC value derived from DWI could be helpful in predicting tumor cellularity and patient surgical outcome with regard to recurrence.
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Affiliation(s)
- Sun Kyung Jeon
- Department of Radiology, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul, 03080, Republic of Korea
| | - Jin-Young Jang
- Department of Surgery and Cancer Research Institute, Seoul National University Hospital, 101 Daehangno, Jongno-gu, Seoul, 03080, Korea
| | - Wooil Kwon
- Department of Surgery and Cancer Research Institute, Seoul National University Hospital, 101 Daehangno, Jongno-gu, Seoul, 03080, Korea
| | - Hongbeom Kim
- Department of Surgery and Cancer Research Institute, Seoul National University Hospital, 101 Daehangno, Jongno-gu, Seoul, 03080, Korea
| | - Youngmin Han
- Department of Surgery and Cancer Research Institute, Seoul National University Hospital, 101 Daehangno, Jongno-gu, Seoul, 03080, Korea
| | - Daeun Kim
- Department of Biological Sciences, College of Natural Sciences, Ajou University, Suwon, 16499, Republic of Korea
| | - Daechan Park
- Department of Biological Sciences, College of Natural Sciences, Ajou University, Suwon, 16499, Republic of Korea
| | - Jung Hoon Kim
- Department of Radiology, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul, 03080, Republic of Korea.
- Department of Radiology, Seoul National University College of Medicine, 103 Daehak-ro, Jongno-gu, Seoul, 03080, Republic of Korea.
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13
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Liu Q, Zhang J, Jiang M, Zhang Y, Chen T, Zhang J, Li B, Chen J, Xing W. Evaluating the Histopathology of Pancreatic Ductal Adenocarcinoma by Intravoxel Incoherent Motion-Diffusion Weighted Imaging Comparing With Diffusion-Weighted Imaging. Front Oncol 2021; 11:670085. [PMID: 34249707 PMCID: PMC8261286 DOI: 10.3389/fonc.2021.670085] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2021] [Accepted: 05/21/2021] [Indexed: 01/05/2023] Open
Abstract
Objectives To explore the differences between intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) and diffusion-weighted imaging (DWI) in evaluating the histopathological characters of pancreatic ductal adenocarcinoma (PDAC). Methods This retrospective study enrolled 50 patients with PDAC confirmed by pathology from December 2018 to May 2020. All patients underwent DWI and IVIM-DWI before surgeries. Patients were classified into low- and high-fibrosis groups. Apparent diffusion coefficient (ADC), diffusion coefficient (D), false diffusion coefficient (D*), and perfusion fraction (f) were measured by two radiologists, respectively in GE AW 4.7 post-processing station, wherein ADC values were derived by mono-exponential fits and f, D, D* values were derived by biexponential fits. The tumor tissue was stained with Sirius red, CD34, and CK19 to evaluate fibrosis, microvascular density (MVD), and tumor cell density. Furthermore, the correlation between ADC, D, D*, and f values and histopathological results was analyzed. Results The D values were lower in the high-fibrosis group than in the low-fibrosis group, while the f values were opposite. Further, no statistically significant differences were detected in ADC and D* values between the high- and low-fibrosis groups. The AUC of D and f values had higher evaluation efficacy in the high- and low-fibrosis groups than ADC values. A significant negative correlation was established between D values, and fibrosis and a significant positive correlation were observed between f values and fibrosis. No statistical difference was detected between DWI/IVIM parameters values and MVD or tumor cell density except for the positive correlation between D* values and tumor cell density. Conclusions D and f values derived from the IVIM model had higher sensitivity and diagnostic performance for grading fibrosis in PDAC compared to the conventional DWI model. IVIM-DWI may have the potential as an imaging biomarker for predicting the fibrosis grade of PDAC.
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Affiliation(s)
- Qi Liu
- Department of Radiology, The Third Affiliated Hospital of Soochow University, Changzhou, China
| | - Jinggang Zhang
- Department of Radiology, The Third Affiliated Hospital of Soochow University, Changzhou, China
| | - Man Jiang
- Department of Radiology, The Third Affiliated Hospital of Soochow University, Changzhou, China
| | - Yue Zhang
- Department of Hepatobiliary and Pancreatic Surgery, The Third Affiliated Hospital of Soochow University, Changzhou, China
| | - Tongbing Chen
- Department of Pathology, The Third Affiliated Hospital of Soochow University, Changzhou, China
| | - Jilei Zhang
- Clinical Science, Philips Healthcare, Shanghai, China
| | - Bei Li
- Department of Radiology, The Third Affiliated Hospital of Soochow University, Changzhou, China
| | - Jie Chen
- Department of Radiology, The Third Affiliated Hospital of Soochow University, Changzhou, China
| | - Wei Xing
- Department of Radiology, The Third Affiliated Hospital of Soochow University, Changzhou, China
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14
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Geng R, Zhang Y, Starekova J, Rutkowski DR, Estkowski L, Roldán-Alzate A, Hernando D. Characterization and correction of cardiovascular motion artifacts in diffusion-weighted imaging of the pancreas. Magn Reson Med 2021; 86:1956-1969. [PMID: 34142375 DOI: 10.1002/mrm.28846] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2020] [Revised: 04/23/2021] [Accepted: 04/26/2021] [Indexed: 02/01/2023]
Abstract
PURPOSE To assess the effects of cardiovascular-induced motion on conventional DWI of the pancreas and to evaluate motion-robust DWI methods in a motion phantom and healthy volunteers. METHODS 3T DWI was acquired using standard monopolar and motion-compensated gradient waveforms, including in an anatomically accurate pancreas phantom with controllable compressive motion and healthy volunteers (n = 8, 10). In volunteers, highly controlled single-slice DWI using breath-holding and cardiac gating and whole-pancreas respiratory-triggered DWI were acquired. For each acquisition, the ADC variability across volunteers, as well as ADC differences across parts of the pancreas were evaluated. RESULTS In motion phantom scans, conventional DWI led to biased ADC, whereas motion-compensated waveforms produced consistent ADC. In the breath-held, cardiac-triggered study, conventional DWI led to heterogeneous DW signals and highly variable ADC across the pancreas, whereas motion-compensated DWI avoided these artifacts. In the respiratory-triggered study, conventional DWI produced heterogeneous ADC across the pancreas (head: 1756 ± 173 × 10-6 mm2 /s; body: 1530 ± 338 × 10-6 mm2 /s; tail: 1388 ± 267 × 10-6 mm2 /s), with ADCs in the head significantly higher than in the tail (P < .05). Motion-compensated ADC had lower variability across volunteers (head: 1277 ± 102 × 10-6 mm2 /s; body: 1204 ± 169 × 10-6 mm2 /s; tail: 1235 ± 178 × 10-6 mm2 /s), with no significant difference (P ≥ .19) across the pancreas. CONCLUSION Cardiovascular motion introduces artifacts and ADC bias in pancreas DWI, which are addressed by motion-robust DWI.
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Affiliation(s)
- Ruiqi Geng
- Department of Radiology, University of Wisconsin-Madison, Madison, Wisconsin, USA.,Department of Medical Physics, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - Yuxin Zhang
- Department of Radiology, University of Wisconsin-Madison, Madison, Wisconsin, USA.,Department of Medical Physics, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - Jitka Starekova
- Department of Radiology, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - David R Rutkowski
- Department of Radiology, University of Wisconsin-Madison, Madison, Wisconsin, USA.,Department of Mechanical Engineering, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | | | - Alejandro Roldán-Alzate
- Department of Radiology, University of Wisconsin-Madison, Madison, Wisconsin, USA.,Department of Mechanical Engineering, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - Diego Hernando
- Department of Radiology, University of Wisconsin-Madison, Madison, Wisconsin, USA.,Department of Medical Physics, University of Wisconsin-Madison, Madison, Wisconsin, USA
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15
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Yang J, Eresen A, Shangguan J, Ma Q, Yaghmai V, Zhang Z. Irreversible electroporation ablation overcomes tumor-associated immunosuppression to improve the efficacy of DC vaccination in a mice model of pancreatic cancer. Oncoimmunology 2021; 10:1875638. [PMID: 33643692 PMCID: PMC7872063 DOI: 10.1080/2162402x.2021.1875638] [Citation(s) in RCA: 30] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023] Open
Abstract
Pancreatic ductal adenocarcinoma (PDAC) is associated with highly immunosuppressive tumor microenvironment (TME) that can limit the efficacy of dendritic cell (DC) vaccine immunotherapy. Irreversible electroporation (IRE) is a local ablation approach. Herein, we test the hypothesis that IRE ablation can overcome TME immunosuppression to improve the efficacy of DC vaccination using KrasLSL-G12D-p53LSL-R172H-Pdx-1-Cre (KPC) orthotopic mouse model of PDAC. The median survival for mice treated with the combined IRE and DC vaccination was 77 days compared with sham control (35 days), DC vaccination (49 days), and IRE (44 days) groups (P = .006). Thirty-six percent of the mice treated with combination IRE and DC vaccination were still survival at the end of the study period (90 days) without visible tumor. The changes of tumor apparent diffusion coefficient (ΔADC) were higher in mice treated with combination IRE and DC vaccination than that of other groups (all P < .001); tumor ΔADC value positively correlated with tumor fibrosis fraction (R = 0.707, P < .001). IRE induced immunogenic cell death and alleviation of immunosuppressive components in PDAC TME when combined with DC vaccination, including increased tumor infiltration of CD8+ T cells and Granzyme B+ cells (P = .001, and P = .007, respectively). Our data show that IRE ablation can overcome TME immunosuppression to improve the efficacy of DC vaccination in PDAC. Combination IRE ablation and DC vaccination may enhance therapeutic efficacy for PDAC.
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Affiliation(s)
- Jia Yang
- Department of Radiology, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
| | - Aydin Eresen
- Department of Radiology, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
| | - Junjie Shangguan
- Department of Radiology, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
| | - Quanhong Ma
- Department of Radiology, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
| | - Vahid Yaghmai
- Department of Radiology, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA.,Department of Radiological Sciences, School of Medicine, University of California, Irvine, CA, USA
| | - Zhuoli Zhang
- Department of Radiology, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA.,Department of Radiological Sciences, School of Medicine, University of California, Irvine, CA, USA.,Chao Family Comprehensive Cancer Center, University of California, Irvine, CA, USA
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16
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Onal Y, Samanci C. The Role of Diffusion-weighted Imaging in Patients with Gastric Wall Thickening. Curr Med Imaging 2020; 15:965-971. [PMID: 32013813 DOI: 10.2174/1573405614666181115120109] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2018] [Revised: 10/18/2018] [Accepted: 10/26/2018] [Indexed: 01/20/2023]
Abstract
BACKGROUND Gastric cancer is the second leading cause of cancer death worldwide. AIMS In the benign and malign gastric pathologies, we measured the Apparent Diffusion Coefficient (ADC) value from the thickened section of the stomach wall. We assessed the diagnostic value of ADC and we wanted to see whether this value could be used to diagnose gastric pathologies. STUDY DESIGN This study has a prospective study design. METHODS A total of 90 patients, 27 with malign gastric pathologies 63 with benign gastric pathologies with Gastric Wall (GW) thickening in multidector CT, were evaluated by T2 weighted axial MR imaging and Diffusion-Weighted Imaging (DWI). Measurements were made both from the thickened wall and from the normal GW. Also, a new method called GW/spine ADC ratio was performed in image analysis. The value found after ADC measurement from the GW was proportioned to the spinal cord ADC value in the same section. RESULTS The ADC values measured from the pathological wall in patients with gastric malignancy (1.115 ± 0.156 x10-3 mm2/s) were significantly lower than the healthy wall measurements (1.621 ± 0.292 × 10-3 mm2/s) and benign gastric diseases (1.790± 0.359 x10-3 mm2/s). GW/spine ADC ratio was also lower in gastric malignancy group. CONCLUSION ADC measurement in DWI can be used to distinguish between benign and malign gastric pathologies.
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Affiliation(s)
- Yilmaz Onal
- Department of Radiology, Sultan Abdulhamid Han Training and Research Hospital, Haydarpasa, Istanbul, Turkey
| | - Cesur Samanci
- Department of Radiology, Sultan Abdulhamid Han Training and Research Hospital, Haydarpasa, Istanbul, Turkey
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17
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Rhee H, Park MS. The Role of Imaging in Current Treatment Strategies for Pancreatic Adenocarcinoma. Korean J Radiol 2020; 22:23-40. [PMID: 32901458 PMCID: PMC7772381 DOI: 10.3348/kjr.2019.0862] [Citation(s) in RCA: 30] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2019] [Revised: 04/30/2020] [Accepted: 05/18/2020] [Indexed: 02/06/2023] Open
Abstract
In pancreatic cancer, imaging plays an essential role in surveillance, diagnosis, resectability evaluation, and treatment response evaluation. Pancreatic cancer surveillance in high-risk individuals has been attempted using endoscopic ultrasound (EUS) or magnetic resonance imaging (MRI). Imaging diagnosis and resectability evaluation are the most important factors influencing treatment decisions, where computed tomography (CT) is the preferred modality. EUS, MRI, and positron emission tomography play a complementary role to CT. Treatment response evaluation is of increasing clinical importance, especially in patients undergoing neoadjuvant therapy. This review aimed to comprehensively review the role of imaging in relation to the current treatment strategy for pancreatic cancer, including surveillance, diagnosis, evaluation of resectability and treatment response, and prediction of prognosis.
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Affiliation(s)
- Hyungjin Rhee
- Department of Radiology, Severance Hospital, Yonsei University College of Medicine, Seoul, Korea
| | - Mi Suk Park
- Department of Radiology, Severance Hospital, Yonsei University College of Medicine, Seoul, Korea.
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18
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Baek DW, Cho HJ, Bae JH, Sohn SK, Moon JH. Apparent diffusion coefficient as a valuable quantitative parameter for predicting clinical outcomes in patients with newly diagnosed primary CNS lymphoma. Blood Res 2020; 55:99-106. [PMID: 32408414 PMCID: PMC7343555 DOI: 10.5045/br.2020.2020032] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2020] [Revised: 03/27/2020] [Accepted: 04/16/2020] [Indexed: 12/11/2022] Open
Abstract
Background This study attempted to identify novel prognostic factors in patients with newly diagnosed primary central nervous system lymphoma (PCNSL) using magnetic resonance imaging (MRI). Methods We retrospectively evaluated 67 patients diagnosed with central nervous system (CNS) tumors. The enrollment criteria were as follows: i) pathologic diagnosis of CNS lymphoma, ii) no evidence of systemic involvement, iii) no evidence of human immunodeficiency virus-1 infection or other immunodeficiencies, and iv) MRI scans available at diagnosis. Fifty-two patients met these criteria and were enrolled. Results The 3-year overall survival (OS) and failure-free survival rates were 69.7% and 45.6%, respectively, with a median follow-up duration of 36.2 months. OS of patients with low apparent diffusion coefficient (ADC) was lower than those with higher ADC. Multivariate analysis revealed that old age (>60 yr) [hazard ratio (HR), 20.372; P=0.001], Eastern Cooperative Oncology Group performance status (ECOG PS) ≥2 (HR, 10.429; P<0.001), higher lactate dehydrogenase (LDH) levels (HR, 7.408; P=0.001), and low ADC (HR, 0.273; P=0.009) were associated with lower OS. We modified the conventional prognostic scoring system using low ADC, old age (>60 yr), ECOG PS ≥2, and higher LDH. The risk of death was categorized as high (score 3-4), intermediate-2 (score 2), intermediate-1 (score 1), and low (score 0), with three-year OS rates of 33.5%, 55.4%, 88.9%, and 100%, respectively. Conclusion ADC demonstrated significant prognostic value for long-term survival in patients with newly diagnosed PCNSL. Low ADC was an independent unfavorable prognostic factor, suggesting that ADC obtained from MRI can improve the current prognostic scoring system.
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Affiliation(s)
- Dong Won Baek
- Department of Hematology/Oncology, Kyungpook National University Hospital, School of Medicine, Kyungpook National University, Daegu, Korea
| | - Hee Jeong Cho
- Department of Hematology/Oncology, Kyungpook National University Hospital, School of Medicine, Kyungpook National University, Daegu, Korea
| | - Jae Heung Bae
- Department of Radiology, Kyungpook National University Hospital, School of Medicine, Kyungpook National University, Daegu, Korea
| | - Sang Kyun Sohn
- Department of Hematology/Oncology, Kyungpook National University Hospital, School of Medicine, Kyungpook National University, Daegu, Korea
| | - Joon Ho Moon
- Department of Hematology/Oncology, Kyungpook National University Hospital, School of Medicine, Kyungpook National University, Daegu, Korea
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19
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Elsherif SB, Virarkar M, Javadi S, Ibarra-Rovira JJ, Tamm EP, Bhosale PR. Pancreatitis and PDAC: association and differentiation. Abdom Radiol (NY) 2020; 45:1324-1337. [PMID: 31705251 DOI: 10.1007/s00261-019-02292-w] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
The discrimination of mass-forming chronic pancreatitis (MFCP) from pancreatic ductal adenocarcinoma (PDAC) is a central diagnostic dilemma. It is important to differentiate these entities since they have markedly different prognoses and management. Importantly, the appearance of these two entities significantly overlaps on a variety of imaging modalities. However, there are imaging features that may be suggestive of one entity more than the other. MFCP and PDAC may show different enhancement patterns on perfusion computed tomography (CT) and/or dynamic contrast-enhanced MRI (DCE-MRI). The duct-penetrating sign on magnetic resonance cholangiopancreatography (MRCP) is more often associated with MFCP, whereas abrupt cutoff with upstream dilatation of the main pancreatic duct and the double-duct sign (obstruction/cutoff of both the common bile duct and pancreatic duct) are more often associated with PDAC. Nevertheless, tissue sampling is the most reliable method to differentiate between these entities and is currently generally necessary for management.
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Affiliation(s)
- Sherif B Elsherif
- The Department of Diagnostic Radiology, The University of Texas M. D. Anderson Cancer Center, 1400 Pressler St., Houston, TX, 77030, USA.
- The Department of Internal Medicine, Weiss Memorial Hospital, Affiliate of the University of Illinois at Chicago, Chicago, USA.
| | - Mayur Virarkar
- The Department of Diagnostic Radiology, The University of Texas M. D. Anderson Cancer Center, 1400 Pressler St., Houston, TX, 77030, USA
| | - Sanaz Javadi
- The Department of Diagnostic Radiology, The University of Texas M. D. Anderson Cancer Center, 1400 Pressler St., Houston, TX, 77030, USA
| | - Juan J Ibarra-Rovira
- The Department of Diagnostic Radiology, The University of Texas M. D. Anderson Cancer Center, 1400 Pressler St., Houston, TX, 77030, USA
| | - Eric P Tamm
- The Department of Diagnostic Radiology, The University of Texas M. D. Anderson Cancer Center, 1400 Pressler St., Houston, TX, 77030, USA
| | - Priya R Bhosale
- The Department of Diagnostic Radiology, The University of Texas M. D. Anderson Cancer Center, 1400 Pressler St., Houston, TX, 77030, USA
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20
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Harrington KA, Shukla-Dave A, Paudyal R, Do RKG. MRI of the Pancreas. J Magn Reson Imaging 2020; 53:347-359. [PMID: 32302044 DOI: 10.1002/jmri.27148] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2019] [Revised: 03/01/2020] [Accepted: 03/02/2020] [Indexed: 02/06/2023] Open
Abstract
MRI has played a critical role in the evaluation of patients with pancreatic pathologies, from screening of patients at high risk for pancreatic cancer to the evaluation of pancreatic cysts and indeterminate pancreatic lesions. The high mortality associated with pancreatic adenocarcinomas has spurred much interest in developing effective screening tools, with MRI using magnetic resonance cholangiopancreatography (MRCP) playing a central role in the hopes of identifying cancers at earlier stages amenable to curative resection. Ongoing efforts to improve the resolution and robustness of imaging of the pancreas using MRI may thus one day reduce the mortality of this deadly disease. However, the increasing use of cross-sectional imaging has also generated a concomitant clinical conundrum: How to manage incidental pancreatic cystic lesions that are found in over a quarter of patients who undergo MRCP. Efforts to improve the specificity of MRCP for patients with pancreatic cysts and with indeterminate pancreatic masses may be achieved with continued technical advances in MRI, including diffusion-weighted and T1 -weighted dynamic contrast-enhanced MRI. However, developments in quantitative MRI of the pancreas remain challenging, due to the small size of the pancreas and its upper abdominal location, adjacent to bowel and below the diaphragm. Further research is needed to improve MRI of the pancreas as a clinical tool, to positively affect the lives of patients with pancreatic abnormalities. This review focuses on various MR techniques such as MRCP, quantitative imaging, and dynamic contrast-enhanced imaging and their clinical applicability in the imaging of the pancreas, with an emphasis on pancreatic malignant and premalignant lesions. Level of Evidence 5 Technical Efficacy Stage 3 J. MAGN. RESON. IMAGING 2021;53:347-359.
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Affiliation(s)
- Kate A Harrington
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Amita Shukla-Dave
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, USA.,Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Ramesh Paudyal
- Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Richard K G Do
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, USA
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21
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Wang L, Gaddam S, Wang N, Xie Y, Deng Z, Zhou Z, Fan Z, Jiang T, Christodoulou AG, Han F, Lo SK, Wachsman AM, Hendifar AE, Pandol SJ, Li D. Multiparametric Mapping Magnetic Resonance Imaging of Pancreatic Disease. Front Physiol 2020; 11:8. [PMID: 32153416 PMCID: PMC7047169 DOI: 10.3389/fphys.2020.00008] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2019] [Accepted: 01/09/2020] [Indexed: 12/13/2022] Open
Abstract
Background Current magnetic resonance imaging (MRI) of pancreatic disease is qualitative in nature. Quantitative imaging offers several advantages, including increased reproducibility and sensitivity to detect mild or diffuse disease. The role of multiparametric mapping MRI in characterizing various tissue types in pancreatic disease such as chronic pancreatitis (CP) and pancreatic ductal adenocarcinoma (PDAC) has rarely been evaluated. Purpose To evaluate the feasibility of multiparametric mapping [T1, T2, and apparent diffusion coefficient (ADC)] in defining tissue characteristics that occur in CP and PDAC to improve disease diagnosis. Materials and Methods: Pancreatic MRI was performed in 17 patients with PDAC undergoing therapy, 7 patients with CP, and 29 healthy volunteers with no pancreatic disease. T1 modified Look-Locker Inversion Recovery (T1 MOLLI), T2-prepared gradient-echo, and multi-slice single-shot echo-planar diffusion weighted imaging (SS-EPI DWI) sequences were used for data acquisition. Regions of interest (ROIs) of pancreas in PDAC, CP, and control subjects were outlined by an experienced radiologist. One-way analysis of variance (ANOVA) was used to compare the difference between groups and regions of the pancreas, and Tukey tests were used for multiple comparison testing within groups. Receiver operator characteristic (ROC) curves were analyzed, and the areas under the curves (AUCs) were calculated using single parameter and combined parameters, respectively. Results T1, T2, and ADC values of the entire pancreas among PDAC, CP, and control subjects; and between upstream and downstream portions of the pancreas in PDAC patients were all significantly different (p < 0.05). The AUC values were 0.90 for T1, 0.55 for T2, and 0.71 for ADC for independent prediction of PDAC. By combining T1, T2, and ADC, the AUC value was 0.94 (sensitivity 91.54%, specificity 85.81%, 95% CI: 0.92–0.96), which yielded higher accuracy than any one parameter only (p < 0.001). Conclusion Multiparametric mapping MRI is feasible for the evaluation of the differences between PDAC, CP, and normal pancreas tissues. The combination of multiple parameters of T1, T2, and ADC provides a higher accuracy than any single parameter alone in tissue characterization of the pancreas.
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Affiliation(s)
- Lixia Wang
- Department of Radiology, Beijing Chaoyang Hospital, Capital Medical University, Beijing, China
| | - Srinivas Gaddam
- Division of Digestive and Liver Diseases, Cedars-Sinai Medical Center, Los Angeles, CA, United States
| | - Nan Wang
- Department of Bioengineering, University of California, Los Angeles, Los Angeles, CA, United States.,Cedars-Sinai Biomedical Imaging Research Institute, Los Angeles, CA, United States
| | - Yibin Xie
- Cedars-Sinai Biomedical Imaging Research Institute, Los Angeles, CA, United States
| | - Zixin Deng
- Cedars-Sinai Biomedical Imaging Research Institute, Los Angeles, CA, United States
| | - Zhengwei Zhou
- Cedars-Sinai Biomedical Imaging Research Institute, Los Angeles, CA, United States
| | - Zhaoyang Fan
- Cedars-Sinai Biomedical Imaging Research Institute, Los Angeles, CA, United States
| | - Tao Jiang
- Department of Radiology, Beijing Chaoyang Hospital, Capital Medical University, Beijing, China
| | | | - Fei Han
- Department of Nuclear Science and Engineering, Siemens Healthineers, Princeton, NJ, United States
| | - Simon K Lo
- Division of Digestive and Liver Diseases, Cedars-Sinai Medical Center, Los Angeles, CA, United States
| | - Ashley M Wachsman
- Cedars-Sinai Biomedical Imaging Research Institute, Los Angeles, CA, United States
| | - Andrew Eugene Hendifar
- Department of Gastrointestinal Malignancies, Cedars-Sinai Medical Center, Los Angeles, CA, United States
| | - Stephen J Pandol
- Division of Digestive and Liver Diseases, Cedars-Sinai Medical Center, Los Angeles, CA, United States
| | - Debiao Li
- Cedars-Sinai Biomedical Imaging Research Institute, Los Angeles, CA, United States
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22
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Shangguan A, Shang N, Figini M, Pan L, Yang J, Ma Q, Hu S, Eresen A, Sun C, Wang B, Velichko Y, Yaghmai V, Zhang Z. Prophylactic dendritic cell vaccination controls pancreatic cancer growth in a mouse model. Cytotherapy 2020; 22:6-15. [PMID: 32005355 DOI: 10.1016/j.jcyt.2019.12.001] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2019] [Revised: 11/29/2019] [Accepted: 12/01/2019] [Indexed: 12/18/2022]
Abstract
PURPOSE Pancreatic ductal adenocarcinoma (PDAC) is the fourth leading cause of cancer-related deaths with high recurrence after surgery due to a paucity of effective post-surgical adjuvant treatments. DC vaccines can activate multiple anti-tumor immune responses but have not been explored for post-surgery PDAC recurrence. Intraperitoneal (IP) delivery may allow increased DC vaccine dosage and migration to lymph nodes. Here, we investigated the role of prophylactic DC vaccination controlling PDAC tumor growth with IP delivery as an administration route for DC vaccination. METHODS DC vaccines were generated using ex vivo differentiation and maturation of bone marrow-derived precursors. Twenty mice were divided into four groups (n = 5) and treated with DC vaccines, unpulsed mature DCs, Panc02 lysates or no treatment. After tumor induction, mice underwent three magnetic resonance imaging scans to track tumor growth. Apparent diffusion coefficient (ADC), a quantitative magnetic resonance imaging measurement of tumor microstructure, was calculated. Survival was tracked. Tumor tissue was collected after death and stained with hematoxylin and eosin, Masson's trichrome, terminal deoxynucleotidyl transferase dUTP nick end labeling and anti-CD8 stains for histology. RESULTS DC-vaccinated mice demonstrated stronger anti-tumor cytotoxicity compared with control groups on lactate dehydrogenase assay. DC vaccine mice also demonstrated decreased tumor volume, prolonged survival and increased ΔADC compared with control groups. On histology, the DC vaccine group had increased apoptosis, increased CD8+ T cells and decreased collagen. ΔADC negatively correlated with % collagen in tumor tissues. DISCUSSION Prophylactic DC vaccination may inhibit PDAC tumor growth during recurrence and prolong survival. ΔADC may be a potential imaging biomarker that correlates with tumor histological features.
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Affiliation(s)
- Anna Shangguan
- Department of Radiology, Feinberg School of Medicine, Northwestern University, Chicago, Illinois, USA; Medical Student Training Program, Northwestern University, Chicago, Illinois, USA
| | - Na Shang
- Department of Radiology, Feinberg School of Medicine, Northwestern University, Chicago, Illinois, USA
| | - Matteo Figini
- Department of Radiology, Feinberg School of Medicine, Northwestern University, Chicago, Illinois, USA
| | - Liang Pan
- Department of Radiology, Feinberg School of Medicine, Northwestern University, Chicago, Illinois, USA; Department of Radiology, The Third Affiliated Hospital of Suzhou University, Changzhou, Jiangsu, China
| | - Jia Yang
- Department of Radiology, Feinberg School of Medicine, Northwestern University, Chicago, Illinois, USA
| | - Quanhong Ma
- Department of Radiology, Feinberg School of Medicine, Northwestern University, Chicago, Illinois, USA
| | - Su Hu
- Department of Radiology, Feinberg School of Medicine, Northwestern University, Chicago, Illinois, USA; Department of Radiology, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu, China
| | - Aydin Eresen
- Department of Radiology, Feinberg School of Medicine, Northwestern University, Chicago, Illinois, USA
| | - Chong Sun
- Department of Radiology, Feinberg School of Medicine, Northwestern University, Chicago, Illinois, USA; Department of Orthopaedics, The Affiliated Hospital of Qingdao University, Qingdao, Shandong, China
| | - Bin Wang
- Department of Radiology, Feinberg School of Medicine, Northwestern University, Chicago, Illinois, USA; Department of General Surgery, Nanfang Hospital, Southern Medical University, Guangdong Provincial Engineering Technology Research Center of Minimally Invasive Surgery, Guangzhou, China
| | - Yuri Velichko
- Department of Radiology, Feinberg School of Medicine, Northwestern University, Chicago, Illinois, USA; Robert H. Lurie Comprehensive Cancer Center, Northwestern University, Chicago, Illinois, USA
| | - Vahid Yaghmai
- Department of Radiology, Feinberg School of Medicine, Northwestern University, Chicago, Illinois, USA; Robert H. Lurie Comprehensive Cancer Center, Northwestern University, Chicago, Illinois, USA
| | - Zhuoli Zhang
- Department of Radiology, Feinberg School of Medicine, Northwestern University, Chicago, Illinois, USA; Robert H. Lurie Comprehensive Cancer Center, Northwestern University, Chicago, Illinois, USA.
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23
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Baboli M, Zhang J, Kim SG. Advances in Diffusion and Perfusion MRI for Quantitative Cancer Imaging. CURRENT PATHOBIOLOGY REPORTS 2019; 7:129-141. [PMID: 33344067 PMCID: PMC7747414 DOI: 10.1007/s40139-019-00204-7] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
PURPOSE OF REVIEW This article is to review recent technical developments and their clinical applications in cancer imaging quantitative measurement of cellular and vascular properties of the tumors. RECENT FINDINGS Rapid development of fast Magnetic Resonance Imaging (MRI) technologies over last decade brought new opportunities in quantitative MRI methods to measure both cellular and vascular properties of tumors simultaneously. SUMMARY Diffusion MRI (dMRI) and dynamic contrast enhanced (DCE)-MRI have become widely used to assess the tissue structural and vascular properties, respectively. However, the ultimate potential of these advanced imaging modalities has not been fully exploited. The dependency of dMRI on the diffusion weighting gradient strength and diffusion time can be utilized to measure tumor perfusion, cellular structure, and cellular membrane permeability. Similarly, DCE-MRI can be used to measure vascular and cellular membrane permeability along with cellular compartment volume fractions. To facilitate the understanding of these potentially important methods for quantitative cancer imaging, we discuss the basic concepts and recent developments, as well as future directions for further development.
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Affiliation(s)
- Mehran Baboli
- Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, NY 10016, USA
| | - Jin Zhang
- Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, NY 10016, USA
| | - Sungheon Gene Kim
- Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, NY 10016, USA
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24
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Tang W, Liu W, Li HM, Wang QF, Fu CX, Wang XH, Zhou LP, Peng WJ. Quantitative dynamic contrast-enhanced MR imaging for the preliminary prediction of the response to gemcitabine-based chemotherapy in advanced pancreatic ductal carcinoma. Eur J Radiol 2019; 121:108734. [PMID: 31743881 DOI: 10.1016/j.ejrad.2019.108734] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2019] [Revised: 08/15/2019] [Accepted: 10/27/2019] [Indexed: 02/07/2023]
Abstract
PURPOSE To investigate the role of the quantitative parameters of dynamic contrast-enhanced MR imaging (DCE-MRI) in the prediction of the response to chemotherapy in pancreatic ductal carcinoma (PDC). METHOD Forty patients with histologically confirmed PDC who underwent quantitative DCE-MRI were retrospectively analyzed. All patients were divided into groups of responders and nonresponders. DCE-MRI parameters, including the volume transfer constant (Ktrans), the extracellular extravascular volume fraction (ve), the rate constant (kep) and the initial area under the concentration curve in 60 s (iAUC60), were measured and compared. DCE-MRI parameters were obtained from different ROIs. RESULTS The values of Ktrans in responders with peripheral, whole tumor slice, and adjacent non-tumorous region ROIs were significantly higher than those in nonresponders (P = 0.015, 0.043, and 0.025, respectively). Responders showed a significantly higher kep with peripheral area ROI compared with nonresponders (P = 0.013). Ve and iAUC60 with all ROIs were not significantly different between responders and nonresponders (P = 0.140-0.968). Kep with periphery ROI showed the highest area under the ROC curve (AUC) of 0.806, but there were no statistical differences when compared with values of Ktrans.There were statistically significant differences for DCE-MRI parameters among four ROIs (all P < 0.05). All parameters showed good to excellent intra and interobserver agreement. CONCLUSIONS Quantitative parameters derived from DCE-MRI might be a potential predictor of response to gemcitabine in patients with PDC. Perfusion parameters were diverse depending on the location of the ROI on different tumoral and peritumoral areas.
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Affiliation(s)
- Wei Tang
- Department of Radiology, Fudan University Shanghai Cancer Center, Department of Oncology, Shanghai Medical College, Fudan University, 270 Dongan Road, Xuhui District, Shanghai, 200032, China
| | - Wei Liu
- Department of Radiology, Fudan University Shanghai Cancer Center, Department of Oncology, Shanghai Medical College, Fudan University, 270 Dongan Road, Xuhui District, Shanghai, 200032, China
| | - Hai-Ming Li
- Department of Radiology, Fudan University Shanghai Cancer Center, Department of Oncology, Shanghai Medical College, Fudan University, 270 Dongan Road, Xuhui District, Shanghai, 200032, China
| | - Qi-Feng Wang
- Department of Pathology, Fudan University Shanghai Cancer Center, Department of Oncology, Shanghai Medical College, Fudan University, 270 Dongan Road, Xuhui District, Shanghai, 200032, China
| | - Cai-Xia Fu
- MR Applications Development, Siemens Shenzhen Magnetic Resonance Ltd., Shenzhen, China
| | - Xiao-Hong Wang
- Department of Radiology, Fudan University Shanghai Cancer Center, Department of Oncology, Shanghai Medical College, Fudan University, 270 Dongan Road, Xuhui District, Shanghai, 200032, China
| | - Liang-Ping Zhou
- Department of Radiology, Fudan University Shanghai Cancer Center, Department of Oncology, Shanghai Medical College, Fudan University, 270 Dongan Road, Xuhui District, Shanghai, 200032, China.
| | - Wei-Jun Peng
- Department of Radiology, Fudan University Shanghai Cancer Center, Department of Oncology, Shanghai Medical College, Fudan University, 270 Dongan Road, Xuhui District, Shanghai, 200032, China.
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25
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Ma W, Wei M, Han Z, Tang Y, Pan Q, Zhang G, Ren J, Huan Y, Li N. The added value of intravoxel incoherent motion diffusion weighted imaging parameters in differentiating high-grade pancreatic neuroendocrine neoplasms from pancreatic ductal adenocarcinoma. Oncol Lett 2019; 18:5448-5458. [PMID: 31612053 PMCID: PMC6781772 DOI: 10.3892/ol.2019.10863] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2018] [Accepted: 08/16/2019] [Indexed: 12/13/2022] Open
Abstract
The aim of the present study was to investigate the potential significance of intravoxel incoherent motion (IVIM)-diffusion weighted imaging (DWI) in differentiating high-grade pancreatic neuroendocrine neoplasms (pNENs) from pancreatic ductal adenocarcinoma (PDAC). A total of 50 patients, including 37 patients with PDAC and 13 patients with high-grade pNENs, underwent pancreatic multiple b-values DWI with 15 b-values including 0, 10, 20, 40, 60, 80, 100, 150, 200, 400, 800, 1,000, 1,200, 1,500 and 2,000 sec/mm2. Standard apparent diffusion coefficient (ADCstandard) and IVIM parameter [slow apparent diffusion coefficient (Dslow), fast apparent diffusion coefficient (Dfast), fraction of fast apparent diffusion coefficient (ƒ)] values of PDAC and pNENs were compared. P<0.05 was considered to indicate a statistically significant difference. Receiver operating characteristics analysis was performed in order to evaluate the diagnostic potential of IVIM parameters for differentiating high-grade pNENs from PDAC. Dslow of pNENs was significantly lower compared with that of PDAC (0.460 vs. 0.579×10−3 mm2/sec; P=0.001). Dfast of pNENs was significantly higher compared with that of PDAC (13.361 vs. 4.985×10−3 mm2/sec; P<0.001). Area under the curve of Dslow, Dfast and combined Dslow and Dfast was 0.793, 0.863 and 0.885 respectively. The specificity and sensitivity of Dslow≤0.472×10−3 mm2/sec were 97.3 and 53.9%, respectively, for differentiating high-grade pNENs from PDAC. The specificity and sensitivity of Dfast >9.58×10−3 mm2/sec were 91.9 and 69.2%, respectively, for differentiating high-grade pNENs from PDAC. When Dslow and Dfast were combined, the specificity and sensitivity for differentiating high-grade pNENs from PDAC were 76.9 and 100%, respectively. Taken together, these results indicated that the diffusion-associated parameter Dslow and the perfusion-associated parameter Dfast of IVIM-DWI may differentiate high-grade pNENs from PDAC with high diagnostic accuracy, and that IVIM-DWI may be a valuable biomarker in differentiating pancreatic neoplasms.
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Affiliation(s)
- Wanling Ma
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, Shaanxi 710032, P.R. China
| | - Mengqi Wei
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, Shaanxi 710032, P.R. China
| | - Zhiwei Han
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, Shaanxi 710032, P.R. China
| | - Yongqiang Tang
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, Shaanxi 710032, P.R. China
| | - Qi Pan
- Department of Radiology, Second Affiliated Hospital of Xi'an Medical Collage, Xi'an, Shaanxi 710038, P.R. China
| | - Guangwen Zhang
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, Shaanxi 710032, P.R. China
| | - Jing Ren
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, Shaanxi 710032, P.R. China
| | - Yi Huan
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, Shaanxi 710032, P.R. China
| | - Na Li
- Department of Radiology, Ninth Hospital of Xi'an City, Xi'an, Shaanxi 710068, P.R. China
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26
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Kovač JD, Đurić-Stefanović A, Dugalić V, Lazić L, Stanisavljević D, Galun D, Mašulović D. CT perfusion and diffusion-weighted MR imaging of pancreatic adenocarcinoma: can we predict tumor grade using functional parameters? Acta Radiol 2019; 60:1065-1073. [PMID: 30428264 DOI: 10.1177/0284185118812202] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/01/2023]
Affiliation(s)
- Jelena Djokić Kovač
- Center for Radiology and Magnetic Resonance Imaging, Clinical Center of Serbia, Faculty of Medicine, University of Belgrade, Belgrade, Serbia
| | - Aleksandra Đurić-Stefanović
- Center for Radiology and Magnetic Resonance Imaging, Clinical Center of Serbia, Faculty of Medicine, University of Belgrade, Belgrade, Serbia
| | - Vladimir Dugalić
- First Surgical Clinic, Clinical Center of Serbia, Faculty of Medicine, University of Belgrade, Belgrade, Serbia
| | - Ljubica Lazić
- Center for Radiology and Magnetic Resonance Imaging, Clinical Center of Serbia, Faculty of Medicine, University of Belgrade, Belgrade, Serbia
| | - Dejana Stanisavljević
- Institute for Medical Statistics, Faculty of Medicine, University of Belgrade, Belgrade, Serbia
| | - Danijel Galun
- First Surgical Clinic, Clinical Center of Serbia, Faculty of Medicine, University of Belgrade, Belgrade, Serbia
| | - Dragan Mašulović
- Center for Radiology and Magnetic Resonance Imaging, Clinical Center of Serbia, Faculty of Medicine, University of Belgrade, Belgrade, Serbia
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27
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Kaissis G, Braren R. Pancreatic cancer detection and characterization-state of the art cross-sectional imaging and imaging data analysis. Transl Gastroenterol Hepatol 2019; 4:35. [PMID: 31231702 DOI: 10.21037/tgh.2019.05.04] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/03/2019] [Accepted: 05/07/2019] [Indexed: 12/12/2022] Open
Abstract
Pancreatic ductal adenocarcinoma (PDAC) represents a deadly disease, prognosticated to become the 2nd most common cause of cancer related death in the western world by 2030. State of the art radiologic high-resolution cross-sectional imaging by computed tomography (CT) and magnetic resonance imaging (MRI) represent advanced techniques for early lesion detection, pre-therapeutic patient staging and therapy response monitoring. In light of molecular taxonomies currently under development, the implementation of advanced imaging data post-processing pipelines and the integration of imaging and clinical data for the development of risk assessment and clinical decision support tools are required. This review will present the current state of cross-sectional radiologic imaging and image post-processing related to PDAC.
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Affiliation(s)
- Georgios Kaissis
- Institute of Diagnostic and Interventional Radiology, Faculty of Medicine, Technical University of Munich, Translational Oncology and Quantitative Imaging/Data Science Laboratory, Munich, Germany
| | - Rickmer Braren
- Institute of Diagnostic and Interventional Radiology, Faculty of Medicine, Technical University of Munich, Translational Oncology and Quantitative Imaging/Data Science Laboratory, Munich, Germany
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28
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Siddiqui N, Vendrami CL, Chatterjee A, Miller FH. Advanced MR Imaging Techniques for Pancreas Imaging. Magn Reson Imaging Clin N Am 2019; 26:323-344. [PMID: 30376973 DOI: 10.1016/j.mric.2018.03.002] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
Advances in MR imaging with optimization of hardware, software, and techniques have allowed for an increased role of MR in the identification and characterization of pancreatic disorders. Diffusion-weighted imaging improves the detection and staging of pancreatic neoplasms and aides in the evaluation of acute, chronic and autoimmune pancreatitis. The use of secretin-enhanced MR cholangiography improves the detection of morphologic ductal anomalies, and assists in the characterization of pancreatic cystic lesions and evaluation of acute and chronic pancreatitis. Emerging MR techniques such as MR perfusion, T1 mapping/relaxometry, and MR elastography show promise in further evaluating pancreatic diseases.
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Affiliation(s)
- Nasir Siddiqui
- Department of Radiology, DuPage Medical Group, 430 Warrenville Road, Lisle, IL 60532, USA
| | - Camila Lopes Vendrami
- Department of Radiology, Northwestern Memorial Hospital, Northwestern University Feinberg School of Medicine, 676 North St. Clair Street Suite 800, Chicago, IL 60611, USA
| | - Argha Chatterjee
- Department of Radiology, Northwestern Memorial Hospital, Northwestern University Feinberg School of Medicine, 676 North St. Clair Street Suite 800, Chicago, IL 60611, USA
| | - Frank H Miller
- Department of Radiology, Northwestern Memorial Hospital, Northwestern University Feinberg School of Medicine, 676 North St. Clair Street Suite 800, Chicago, IL 60611, USA.
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29
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Li J, Liang L, Yu H, Shen Y, Hu Y, Hu D, Tang H, Li Z. Whole-tumor histogram analysis of non-Gaussian distribution DWI parameters to differentiation of pancreatic neuroendocrine tumors from pancreatic ductal adenocarcinomas. Magn Reson Imaging 2019; 55:52-59. [PMID: 30240758 DOI: 10.1016/j.mri.2018.09.017] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2018] [Revised: 09/11/2018] [Accepted: 09/16/2018] [Indexed: 01/15/2023]
Abstract
PURPOSE To evaluate the utility of volumetric histogram analysis of monoexponential and non-Gaussian distribution DWI models for discriminating pancreatic ductal adenocarcinoma (PDAC) and neuroendocrine tumor (pNET). MATERIALS AND METHODS A total of 340 patients were retrospectively reviewed. Finally, 62 patients with histopathological confirmed PDAC (n = 42) and pNET (n = 20) were enrolled in the study. All the patients accepted magnetic resonance imaging (MRI) at 3 T (including multi-b value DWI, 0-1000 s/mm2). Isotropic apparent diffusion coefficient (ADC), true molecular diffusion (Dt), perfusion-related diffusion (Dp), perfusion fraction (f), distributed diffusion coefficient (DDC) and alpha (α) were obtained from different DWI models. Then, mean value, median value, 10th and 90th percentiles were obtained from histogram analysis of each DWI parameter. RESULTS Histogram metrics derived from ADC, Dp, f and DDC were significantly lower in PDAC than pNET group (P < 0.05). In contrast, histogram metrics derived from α were observed significantly higher in the PDAC than pNET group (P < 0.05). No significant difference was found in Dt (P ≥ 0.05) between PDAC and pNET patients. Among all parameters, f-median had the highest diagnostic performance (AUC 0.91, cutoff value 0.188, sensitivity 97.62%, specificity 80%). CONCLUSIONS f-Median derived from IVIM DWI model may be potentially more valuable parameter than ADC, Dp, DDC and α for discriminating PDAC and pNET. Histogram analysis based on the entire tumor was an emerging and valuable tool.
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Affiliation(s)
- Jiali Li
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Lili Liang
- Department of Radiology, The first affiliated hospital of Nanyang Medical College, China
| | - Hao Yu
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yaqi Shen
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yao Hu
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Daoyu Hu
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Hao Tang
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Zhen Li
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
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30
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Intravoxel incoherent motion diffusion-weighted MR imaging of solid pancreatic masses: reliability and usefulness for characterization. Abdom Radiol (NY) 2019; 44:131-139. [PMID: 29951899 DOI: 10.1007/s00261-018-1684-z] [Citation(s) in RCA: 29] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
PURPOSE IVIM-DW imaging has shown potential usefulness in the study of pancreatic lesions. Controversial results are available regarding the reliability of the measurements of IVIM-derived parameters. The aim of this study was to evaluate the reliability and the diagnostic potential of IVIM-derived parameters in differentiation among focal solid pancreatic lesions and normal pancreas (NP). METHODS Fifty-seven patients (34 carcinomas-PDACs, 18 neuroendocrine neoplasms-panNENs, and 5 autoimmune pancreatitis-AIP) and 50 subjects with NP underwent 1.5-T MR imaging including IVIM-DWI. Images were analyzed by two independent readers. Apparent diffusion coefficient (ADC), slow component of diffusion (D), incoherent microcirculation (Dp), and perfusion fraction (f) were calculated. Interobserver reliability was assessed with intraclass correlation coefficient (ICC). A Kruskal-Wallis H test with Steel-Dwass post hoc test was used for comparison. The diagnostic performance of each parameter was evaluated through receiver operating characteristic (ROC) curve analysis. RESULTS Overall interobserver agreement was excellent (ICC = 0.860, 0.937, 0.968, and 0.983 for ADC, D, Dp, and f). D, Dp, and f significantly differed among PDACs and panNENs (p = 0.002, < 0.001, and < 0.001), albeit without significant difference at the pairwise comparison of ROC curves (p = 0.08-0.74). Perfusion fraction was higher in AIP compared with PDACs (p = 0.024; AUC = 0.735). Dp and f were higher in panNENs compared with AIP (p = 0.029 and 0.023), without differences at ROC analysis (p = 0.07). CONCLUSIONS IVIM-derived parameters have excellent reliability and could help in differentiation among solid pancreatic lesions and NP.
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Li J, Lu J, Liang P, Li A, Hu Y, Shen Y, Hu D, Li Z. Differentiation of atypical pancreatic neuroendocrine tumors from pancreatic ductal adenocarcinomas: Using whole-tumor CT texture analysis as quantitative biomarkers. Cancer Med 2018; 7:4924-4931. [PMID: 30151864 PMCID: PMC6198241 DOI: 10.1002/cam4.1746] [Citation(s) in RCA: 37] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2018] [Revised: 07/29/2018] [Accepted: 07/30/2018] [Indexed: 12/19/2022] Open
Abstract
Background To explore the application value of computed tomography (CT) texture analysis in differentiating atypical pancreatic neuroendocrine tumors (pNET) from pancreatic ductal adenocarcinomas (PDAC). Materials and methods This single‐center retrospective study was approved by local institutional review board, and the requirement for informed consent was waived. We retrospectively analyzed 127 patients with 50 PDACs and 77 pNETs in pathology database between January 2012 and May 2017.These patients successfully finished preoperative contrast‐enhanced CT test. Texture parameters (mean, median, 5th, 10th, 25th, 75th, 90th percentiles, skewness, kurtosis and entropy) were extracted from portal images and compared between PDAC and 77 pNET groups using proper statistical method. The optimal parameters for differentiating PDACs and atypical pNETs were gained through receiver operating characteristic (ROC) curves. Results On the basis of arterial enhancement, 52 pNETs (67%, 52/77) were typical hypervascular and 25 pNETs (32%, 25/77) were atypical hypovascular. Compared with PDACs, atypical pNETs had statistically higher mean, median, 5th, 10th, and 25th percentiles (P = 0.006, 0.024, 0.000, 0.001, 0.021, respectively) and statistically lower skewness (P = 0.017). However, there were no difference for 75th, 90th percentiles, kurtosis and entropy between these two tumors (P = 0.232, 0.415, 0.143, 0.291, respectively). For differentiating PDACs and atypical pNETs, 5th percentile and 5th+skewness were optimal parameters for alone and combined diagnosis, respectively. Conclusion Volumetric CT texture features, especially combined diagnosis of 5th+skewness can be used as a quantitative tool to distinguish atypical pNETs from PDACs.
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Affiliation(s)
- Jiali Li
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Jingyu Lu
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Ping Liang
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Anqin Li
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yao Hu
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yaqi Shen
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Daoyu Hu
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Zhen Li
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
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Lee S, Kim SH, Park HK, Jang KT, Hwang JA, Kim S. Pancreatic Ductal Adenocarcinoma: Rim Enhancement at MR Imaging Predicts Prognosis after Curative Resection. Radiology 2018; 288:456-466. [DOI: 10.1148/radiol.2018172331] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Affiliation(s)
- Sunyoung Lee
- From the Department of Radiology and Center for Imaging Science (S.L., S.H.K., J.A.H.), Department of Pathology (H.K.P., K.T.J.), and Department of Statistics and Data Center (S.K.), Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-Ro, Gangnam-gu, Seoul 06351, Korea
| | - Seong Hyun Kim
- From the Department of Radiology and Center for Imaging Science (S.L., S.H.K., J.A.H.), Department of Pathology (H.K.P., K.T.J.), and Department of Statistics and Data Center (S.K.), Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-Ro, Gangnam-gu, Seoul 06351, Korea
| | - Hyung Kyu Park
- From the Department of Radiology and Center for Imaging Science (S.L., S.H.K., J.A.H.), Department of Pathology (H.K.P., K.T.J.), and Department of Statistics and Data Center (S.K.), Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-Ro, Gangnam-gu, Seoul 06351, Korea
| | - Kee Taek Jang
- From the Department of Radiology and Center for Imaging Science (S.L., S.H.K., J.A.H.), Department of Pathology (H.K.P., K.T.J.), and Department of Statistics and Data Center (S.K.), Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-Ro, Gangnam-gu, Seoul 06351, Korea
| | - Jeong Ah Hwang
- From the Department of Radiology and Center for Imaging Science (S.L., S.H.K., J.A.H.), Department of Pathology (H.K.P., K.T.J.), and Department of Statistics and Data Center (S.K.), Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-Ro, Gangnam-gu, Seoul 06351, Korea
| | - Seonwoo Kim
- From the Department of Radiology and Center for Imaging Science (S.L., S.H.K., J.A.H.), Department of Pathology (H.K.P., K.T.J.), and Department of Statistics and Data Center (S.K.), Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-Ro, Gangnam-gu, Seoul 06351, Korea
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Abstract
Computed tomography is the first-line imaging modality for suspected pancreatic cancer. Magnetic resonance cholangiopancreatography is a second-line modality for suspected pancreatic cancer and is usually reserved for equivocal cases. Both computed tomography and MR are highly sensitive in the detection of pancreatic cancer, with up to 96% and 93.5% sensitivity, respectively. Computed tomography is superior to MR in the assessment of tumor resectability, with accuracy rates of up to 86.8% and 78.9%, respectively. Close attention to secondary signs of pancreatic cancer, such as pancreatic duct dilatation, abrupt pancreatic duct caliber change, and parenchymal atrophy, are critical in the diagnosis of pancreatic cancer. Emerging techniques such as radiomics and molecular imaging have the potential of identifying malignant precursors and lead to earlier disease diagnosis. The results of these promising techniques need to be validated in larger clinical studies.
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Rong D, Mao Y, Hu W, Xu S, Wang J, He H, Li S, Zhang R. Intravoxel incoherent motion magnetic resonance imaging for differentiating metastatic and non-metastatic lymph nodes in pancreatic ductal adenocarcinoma. Eur Radiol 2018; 28:2781-2789. [PMID: 29404768 DOI: 10.1007/s00330-017-5259-0] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2017] [Revised: 11/14/2017] [Accepted: 12/20/2017] [Indexed: 01/27/2023]
Abstract
OBJECTIVES To evaluate the diagnostic potential of intravoxel incoherent motion (IVIM) DWI for differentiating metastatic and non-metastatic lymph node stations (LNS) in pancreatic ductal adenocarcinoma (PDAC). METHODS 59 LNS histologically diagnosed following surgical resection from 15 patients were included. IVIM DWI with 12 b values was added to the standard MRI protocol. Evaluation of parameters was performed pre-operatively and included the apparent diffusion coefficient (ADC), pure diffusion coefficient (D), pseudo-diffusion coefficient (D*) and perfusion fraction (f). Diagnostic performance of ADC, D, D* and f for differentiating between metastatic and non-metastatic LNS was evaluated using ROC analysis. RESULTS Metastatic LNS had significantly lower D, D*, f and ADC values than the non-metastatic LNS (p< 0.01). The best diagnostic performance was found in D, with an area under the ROC curve of 0.979, while the area under the ROC curve values of D*, f and ADC were 0.867, 0.855 and 0.940, respectively. The optimal cut-off values for distinguishing metastatic and non-metastatic lymph nodes were D = 1.180 × 10-3 mm2/s; D* = 14.750 × 10-3 mm2/s, f = 20.65 %, and ADC = 1.390 × 10-3 mm2/s. CONCLUSION IVIM DWI is useful for differentiating between metastatic and non-metastatic LNS in PDAC. KEY POINTS • IVIM DWI is feasible for diagnosing LN metastasis in PDAC. • Metastatic LNS has lower D, D*, f, ADC values than non-metastatic LNS. • D-value from IVIM model has best diagnostic performance, followed by ADC value. • D* has the lowest AUC value.
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Affiliation(s)
- Dailin Rong
- State Key Laboratory of Oncology in Southern China, Guangzhou, 510060, China
- Department of Radiology, Sun Yat-sen University Cancer Center, No. 651 Dongfeng Road East, Guangzhou, 510060, China
| | - Yize Mao
- State Key Laboratory of Oncology in Southern China, Guangzhou, 510060, China
- Department of Hepato-Biliary-Pancreatic Oncology, Sun Yat-Sen University Cancer Center, No. 651 Dongfeng Road East, Guangzhou, 510060, China
| | - Wanming Hu
- State Key Laboratory of Oncology in Southern China, Guangzhou, 510060, China
- Department of Pathology, Sun Yat-sen University Cancer Center, No. 651 Dongfeng Road East, Guangzhou, 510060, China
| | - Shuhang Xu
- Department of Ultrasound, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, 510630, Guangdong Province, People's Republic of China
| | - Jun Wang
- State Key Laboratory of Oncology in Southern China, Guangzhou, 510060, China
- Department of Hepato-Biliary-Pancreatic Oncology, Sun Yat-Sen University Cancer Center, No. 651 Dongfeng Road East, Guangzhou, 510060, China
- Department of Ultrasound, Sun Yat-sen University Cancer Center, No. 651 Dongfeng Road East, Guangzhou, 510060, China
| | - Haoqiang He
- State Key Laboratory of Oncology in Southern China, Guangzhou, 510060, China
- Department of Radiology, Sun Yat-sen University Cancer Center, No. 651 Dongfeng Road East, Guangzhou, 510060, China
| | - Shengping Li
- State Key Laboratory of Oncology in Southern China, Guangzhou, 510060, China.
- Department of Hepato-Biliary-Pancreatic Oncology, Sun Yat-Sen University Cancer Center, No. 651 Dongfeng Road East, Guangzhou, 510060, China.
| | - Rong Zhang
- State Key Laboratory of Oncology in Southern China, Guangzhou, 510060, China.
- Department of Radiology, Sun Yat-sen University Cancer Center, No. 651 Dongfeng Road East, Guangzhou, 510060, China.
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Rong D, Mao Y, Hu W, Xu S, Wang J, He H, Li S, Zhang R. Intravoxel incoherent motion magnetic resonance imaging for differentiating metastatic and non-metastatic lymph nodes in pancreatic ductal adenocarcinoma. Eur Radiol 2018; 28:2781-2789. [DOI: 29404768 10.1007/s00330-017-5259-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2017] [Revised: 11/14/2017] [Accepted: 12/20/2017] [Indexed: 05/20/2025]
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Shi Z, Li X, You R, Li Y, Zheng X, Ramen K, Loosa VS, Cao D, Chen Q. Homogenously isoattenuating insulinoma on biphasic contrast-enhanced computed tomography: Little benefits of diffusion-weighted imaging for lesion detection. Oncol Lett 2018; 16:3117-3125. [PMID: 30127903 PMCID: PMC6096136 DOI: 10.3892/ol.2018.9037] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2017] [Accepted: 05/30/2018] [Indexed: 12/15/2022] Open
Abstract
The aim of the present study was to evaluate the diagnostic benefit of diffusion-weighted imaging (DWI) in the detection of homogenous isoattenuating insulinoma on biphasic contrast-enhanced computed tomography (CT) preoperatively and to determine which magnetic resonance (MR) sequences exhibited the best diagnostic performance. A total of 44 consecutive patients who underwent biphasic contrast-enhanced CT and conventional MR imaging (MRI), including DWI on a 3T scanner, were identified retrospectively. Apparent diffusion coefficient (ADC) values of insulinomas and the surrounding pancreatic parenchyma were compared using a Wilcoxon signed-rank test. Receiver operating characteristic analysis was used to compare the diagnostic accuracy of four randomized image sets [T2-weighted image (WI), axial T1WI, DWI and T2WI + DWI] for each reader. Axial T1-weighted MRI exhibited the highest relative sensitivity for each reader; DWI alone exhibited the lowest relative sensitivity and the lower inter-reader agreement. There was no significant difference in lesion detection between T2WI and T2WI + DWI image sets for each reader. The ADC values of the insulinoma were significantly lower compared with those of the surrounding parenchyma. In conclusion, DWI does not benefit the detection of homogenous isoattenuating insulinoma. Axial T1WI is the optimal pulse sequence. Quantitative assessment of the tumor ADC values may be a useful tool to characterize identified pancreatic neoplasms.
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Affiliation(s)
- Zhenshan Shi
- Department of Radiology, First Affiliated Hospital of Fujian Medical University, Fuzhou, Fujian 350005, P.R. China
| | - Xiumei Li
- Department of Radiology, First Affiliated Hospital of Fujian Medical University, Fuzhou, Fujian 350005, P.R. China
| | - Ruixiong You
- Department of Radiology, First Affiliated Hospital of Fujian Medical University, Fuzhou, Fujian 350005, P.R. China
| | - Yueming Li
- Department of Radiology, First Affiliated Hospital of Fujian Medical University, Fuzhou, Fujian 350005, P.R. China
| | - Xianying Zheng
- Department of Radiology, First Affiliated Hospital of Fujian Medical University, Fuzhou, Fujian 350005, P.R. China
| | - Kamisha Ramen
- Department of Radiology, Fujian Medical University, Fuzhou, Fujian 350001, P.R. China
| | - Vikash Sahadeo Loosa
- Department of Radiology, Fujian Medical University, Fuzhou, Fujian 350001, P.R. China
| | - Dairong Cao
- Department of Radiology, First Affiliated Hospital of Fujian Medical University, Fuzhou, Fujian 350005, P.R. China
| | - Qunlin Chen
- Department of Radiology, First Affiliated Hospital of Fujian Medical University, Fuzhou, Fujian 350005, P.R. China
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Yun G, Kim YH, Lee YJ, Kim B, Hwang JH, Choi DJ. Tumor heterogeneity of pancreas head cancer assessed by CT texture analysis: association with survival outcomes after curative resection. Sci Rep 2018; 8:7226. [PMID: 29740111 PMCID: PMC5940761 DOI: 10.1038/s41598-018-25627-x] [Citation(s) in RCA: 84] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2017] [Accepted: 04/25/2018] [Indexed: 12/12/2022] Open
Abstract
The value of image based texture features as a powerful method to predict prognosis and assist clinical management in cancer patients has been established recently. However, texture analysis using histograms and grey-level co-occurrence matrix in pancreas cancer patients has rarely been reported. We aimed to analyze the association of survival outcomes with texture features in pancreas head cancer patients. Eighty-eight pancreas head cancer patients who underwent preoperative CT images followed by curative resection were included. Texture features using different filter values were obtained. The texture features of average, contrast, correlation, and standard deviation with no filter, and fine to medium filter values as well as the presence of nodal metastasis were significantly different between the recurred (n = 70, 79.5%) and non-recurred group (n = 18, 20.5%). In the multivariate Cox regression analysis, lower standard deviation and contrast and higher correlation with lower average value representing homogenous texture were significantly associated with poorer DFS (disease free survival), along with the presence of lymph node metastasis. Texture parameters from routinely performed pre-operative CT images could be used as an independent imaging tool for predicting the prognosis in pancreas head cancer patients who underwent curative resection.
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Affiliation(s)
- Gabin Yun
- Seoul National University Bundang Hospital, Department of Radiology, Seongnam, 13620, Korea
| | - Young Hoon Kim
- Seoul National University Bundang Hospital, Department of Radiology, Seongnam, 13620, Korea.
| | - Yoon Jin Lee
- Seoul National University Bundang Hospital, Department of Radiology, Seongnam, 13620, Korea
| | - Bohyoung Kim
- Seoul National University Bundang Hospital, Department of Radiology, Seongnam, 13620, Korea.,Hankuk University of Foreign Studies, Division of Biomedical Engineering, Yongin, 17035, Korea
| | - Jin-Hyeok Hwang
- Seoul National University Bundang Hospital, Department of Internal Medicine, Seongnam, 13620, Korea
| | - Dong Joon Choi
- Seoul National University Bundang Hospital, Department of Radiology, Seongnam, 13620, Korea
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Ma W, Zhang G, Ren J, Pan Q, Wen D, Zhong J, Zhang Z, Huan Y. Quantitative parameters of intravoxel incoherent motion diffusion weighted imaging (IVIM-DWI): potential application in predicting pathological grades of pancreatic ductal adenocarcinoma. Quant Imaging Med Surg 2018; 8:301-310. [PMID: 29774183 DOI: 10.21037/qims.2018.04.08] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Background The aim of this study was to compare intravoxel incoherent motion diffusion weighted imaging (IVIM-DWI) parameters such as standard apparent diffusion coefficient (ADCstandard), pure diffusion coefficient (Dslow), pseudodiffusion coefficient (Dfast) and perfusion fraction (ƒ) for differentiating pancreatic ductal adenocarcinoma (PDAC) with different pathological grades. Methods Institutional Review Board of our hospital approved this study protocol. Subjects comprised 38 PDACs confirmed by pathology. Pancreatic multiple b values DWI with 15 b values of 0, 10, 20, 40, 60, 80, 100, 150, 200, 400, 800, 1,000, 1200, 1,500, and 2,000 s/mm2 was performed using GE Discovery MR750 3.0T scanner. ADCstandard, Dslow, Dfast and ƒ values of all PDACs were calculated using mono- and bi-exponential models. Parameters of well/moderately differentiated and poorly differentiated PDAC were compared using Independent Sample t-test. P values <0.05 were considered significant. Results Mean Dslow value of well/moderately differentiated PDAC was significantly lower than that of poorly differentiated PDAC (0.540×10-3vs. 0.676×10-3 mm2/s, P<0.001). Mean ƒ value of well/moderately differentiated PDAC was significantly higher than that of poorly differentiated PDAC (60.3% vs. 38.4%, P<0.001). The area under curve value of ƒ in differentiating well/moderately differentiated PDAC from poorly differentiated PDAC was slightly higher than that of Dslow (0.894>0.865). When the Dslow value was less than or equal to 0.599×10-3 mm2/s, the sensitivity and specificity were 100% and 84.6% respectively. When ƒ value was greater than 49.6%, the sensitivity and specificity were 92.0% and 84.6% respectively. Conclusions Dslow and ƒ derived from IVIM-DWI model can be used to distinguish well/moderately differentiated PDAC from poorly differentiated PDAC. And to serve this purpose, Dslow and ƒ have high diagnostic performance. IVIM-DWI is a promising and non-invasive tool for predicting pathological grade of PDAC.
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Affiliation(s)
- Wanling Ma
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an 710032, China
| | - Guangwen Zhang
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an 710032, China
| | - Jing Ren
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an 710032, China
| | - Qi Pan
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an 710032, China
| | - Didi Wen
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an 710032, China
| | - Jinman Zhong
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an 710032, China
| | - Zhuoli Zhang
- Department of Radiology, Feinberg School of Medicine, Northwestern University, Chicago, IL 60611, USA
| | - Yi Huan
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an 710032, China
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Park HJ, Jang KM, Song KD, Kim SH, Kim YK, Cha MJ, Choi SY, Min K. Value of unenhanced MRI with diffusion-weighted imaging for detection of primary small (≤20 mm) solid pancreatic tumours and prediction of pancreatic ductal adenocarcinoma. Clin Radiol 2017; 72:1076-1084. [PMID: 28784320 DOI: 10.1016/j.crad.2017.07.009] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2016] [Revised: 06/27/2017] [Accepted: 07/12/2017] [Indexed: 02/07/2023]
Abstract
AIM To determine the diagnostic performance of unenhanced magnetic resonance imaging (MRI) with diffusion-weighted imaging (DWI; NonMRI) for the detection of primary small (≤20 mm) pancreatic solid tumours and prediction of pancreatic ductal adenocarcinoma (PDAC) in comparison with pancreatic computed tomography (CT; PanCT) and pancreatic MRI with magnetic resonance cholangiopancreatography (PanMRI). METHODS AND MATERIALS The institutional review board approved this retrospective study and waived the requirement for informed consent. A total of 126 patients who underwent PanCT and PanMRI, including 94 small (≤20 mm) pancreatic tumours (51 PDACs, 34 neuroendocrine tumours [NETs], nine solid pseudopapillary tumours [SPTs]), and 32 patients with a normal pancreas, comprised the study population. Two observers assessed three sets of images: PanCT, PanMRI and NonMRI (T1- and T2-weighted images and DWI). Receiver operating characteristic curve analysis and diagnostic accuracy using the area under the receiver operating characteristic curve (Az) were used for statistical analysis. RESULTS On NonMRI and PanMRI, all of tumours except one NET were detected, but eight tumours (six NETs, one PDAC, one SPT) were not detected on PanCT (p<0.01). For prediction of PDAC, the Az value of the NonMRI (0.884 for observer 1; 0.930 for observer 2) was comparable with PanCT (0.922; 0.924; p>0.05), and inferior to PanMRI (0.930; 0.977; p<0.05), but all of 51 PDACs were considered as probable or definite PDAC on NonMRI by both observers. CONCLUSION NonMRI showed better performance than PanCT, and competitive performance to PanMRI for the detection of primary small solid pancreatic tumours, and showed reasonable sensitivity for prediction of PDACs compared with PanCT and PanMRI.
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Affiliation(s)
- H J Park
- Department of Radiology, Chung-Ang University Hospital, Chung-Ang University College of Medicine, Seoul, Republic of Korea
| | - K M Jang
- Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea.
| | - K D Song
- Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
| | - S H Kim
- Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
| | - Y K Kim
- Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
| | - M J Cha
- Department of Radiology, Chung-Ang University Hospital, Chung-Ang University College of Medicine, Seoul, Republic of Korea
| | - S-Y Choi
- Department of Radiology, Soonchunhyang University College of Medicine, Bucheon Hospital, Bucheon, Republic of Korea
| | - K Min
- Eone Pathology Laboratory, Seongnam, Republic of Korea
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Koc Z, Erbay G, Karadeli E. Internal comparison standard for abdominal diffusion-weighted imaging. Acta Radiol 2017; 58:1029-1036. [PMID: 27956463 DOI: 10.1177/0284185116681040] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/17/2023]
Abstract
Background Standards for abdominal diffusion-weighted imaging (DWI), apparent diffusion coefficient (ADC) measurements, and analysis are required for reproducibility. Purpose To identify optimal internal comparison standards for DWI to normalize the measured ADC for increased accuracy of differentiating malignant and benign abdominal lesions. Material and Methods We retrospectively studied 97 lesions (89 patients; age, 57 ± 13 years) with histopathologically confirmed abdominal disease. Seven normal body parts/contents (normal parenchyma, spleen, kidney, gallbladder bile, paraspinal muscle, spinal cord, and cerebrospinal fluid [CSF]) were assessed as internal references for possible use as comparison standards. Three observers performed ADC measurements. Statistical analyses included interclass correlation coefficients (ICCs), Mann-Whitney and Kruskal-Wallis tests, and coefficient of variation (CV). ROC analyses were performed to assess diagnostic accuracy of lesion ADC and normalized ADC for differentiating lesions. Pathology results were the reference standard. Results Mean and normalized ADCs were significantly lower for malignant lesions than for benign lesions ( P < 0.001). ICC was excellent for all internal references. Gallbladder had the lowest CV. Receiver operating characteristic (ROC) analyses showed that normalized ADCs obtained using normal parenchyma were better than lesion ADCs for differentiating malignant and benign abdominal lesions (area under the curve [AUC], 0.808 and 0.756, respectively). The normalized ADCs obtained using CSF shows higher accuracy than lesion ADCs (0.80 and 0.76, respectively) for differentiating between malignant and benign abdominal lesions. Conclusion The normal parenchyma from a lesion-detected organ can be used as an internal comparison standard for DWI. CSF can be used as a generalizable in plane reference standard.
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Affiliation(s)
- Zafer Koc
- Faculty of Medicine, Department of Radiology, Baskent University, Ankara, Turkey
| | - Gurcan Erbay
- Faculty of Medicine, Department of Radiology, Baskent University, Ankara, Turkey
| | - Elif Karadeli
- Faculty of Medicine, Department of Radiology, Baskent University, Ankara, Turkey
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Hecht EM, Liu MZ, Prince MR, Jambawalikar S, Remotti HE, Weisberg SW, Garmon D, Lopez-Pintado S, Woo Y, Kluger MD, Chabot JA. Can diffusion-weighted imaging serve as a biomarker of fibrosis in pancreatic adenocarcinoma? J Magn Reson Imaging 2017; 46:393-402. [PMID: 28152252 DOI: 10.1002/jmri.25581] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2016] [Accepted: 11/21/2016] [Indexed: 12/28/2022] Open
Abstract
PURPOSE To assess the relationship between diffusion-weighted imaging (DWI) and intravoxel incoherent motion (IVIM)-derived quantitative parameters (apparent diffusion coefficient [ADC], perfusion fraction [f], Dslow , diffusion coefficient [D], and Dfast , pseudodiffusion coefficient [D*]) and histopathology in pancreatic adenocarcinoma (PAC). MATERIALS AND METHODS Subjects with suspected surgically resectable PAC were prospectively enrolled in this Health Insurance Portability and Accountability Act (HIPAA)-compliant, Institutional Review Board-approved study. Imaging was performed at 1.5T with a respiratory-triggered echo planar DWI sequence using 10 b values. Two readers drew regions of interest (ROIs) over the tumor and adjacent nontumoral tissue. Monoexponential and biexponential fits were used to derive ADC2b , ADCall , f, D, and D*, which were compared to quantitative histopathology of fibrosis, mean vascular density, and cellularity. Two biexponential IVIM models were investigated and compared: 1) nonlinear least-square fitting based on the Levenberg-Marquardt algorithm, and 2) linear fit using a fixed D* (20 mm2 /s). Statistical analysis included Student's t-test, Pearson correlation (P < 0.05 was considered significant), intraclass correlation, and coefficients of variance. RESULTS Twenty subjects with PAC were included in the final cohort. Negative correlation between D and fibrosis (Reader 2: r = -0.57 P = 0.01; pooled P = -0.46, P = 0.04) was observed with a trend toward positive correlation between f and fibrosis (r = 0.44, P = 0.05). ADC2b was significantly lower in PAC with dense fibrosis than with loose fibrosis ADC2b (P = 0.03). Inter- and intrareader agreement was excellent for ADC, D, and f. CONCLUSION In PAC, D negatively correlates with fibrosis, with a trend toward positive correlation with f suggesting both perfusion and diffusion effects contribute to stromal desmoplasia. ADC2b is significantly lower in tumors with dense fibrosis and may serve as a biomarker of fibrosis architecture. LEVEL OF EVIDENCE 1 Technical Efficacy: Stage 2 J. MAGN. RESON. IMAGING 2017;46:393-402.
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Affiliation(s)
- Elizabeth M Hecht
- New York Presbyterian-Columbia University Medical Center, Department of Radiology, New York, New York, USA
| | - Michael Z Liu
- New York Presbyterian-Columbia University Medical Center, Department of Radiology, New York, New York, USA
| | - Martin R Prince
- New York Presbyterian-Columbia University Medical Center, Department of Radiology, New York, New York, USA
| | - Sachin Jambawalikar
- New York Presbyterian-Columbia University Medical Center, Department of Radiology, New York, New York, USA
| | - Helen E Remotti
- New York Presbyterian-Columbia University Medical Center, Department of Pathology, New York, New York, USA
| | - Stuart W Weisberg
- New York Presbyterian-Columbia University Medical Center, Department of Pathology, New York, New York, USA
| | - Donald Garmon
- New York Presbyterian-Columbia University Medical Center, Department of Surgery, New York, New York, USA
| | - Sara Lopez-Pintado
- Columbia University Mailman School of Public Heath, Department of Biostatistics, New York, New York, USA
| | - Yanghee Woo
- City of Hope, Department of Surgery, Duarte, California, USA
| | - Michael D Kluger
- New York Presbyterian-Columbia University Medical Center, Department of Surgery, New York, New York, USA
| | - John A Chabot
- New York Presbyterian-Columbia University Medical Center, Department of Surgery, New York, New York, USA
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Nissan N. Modifications of pancreatic diffusion MRI by tissue characteristics: what are we weighting for? NMR IN BIOMEDICINE 2017; 30:e3728. [PMID: 28470823 DOI: 10.1002/nbm.3728] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/05/2017] [Revised: 02/10/2017] [Accepted: 03/13/2017] [Indexed: 06/07/2023]
Abstract
Diffusion-weighted imaging holds the potential to improve the diagnosis and biological characterization of pancreatic disease, and in particular pancreatic cancer, which exhibits decreased values of the apparent diffusion coefficient (ADC). Yet, variable and overlapping ADC values have been reported for the healthy and the pathological pancreas, including for cancer and other benign conditions. This controversy reflects the complexity of probing the water-diffusion process in the pancreas, which is dependent upon multiple biological factors within this organ's unique physiological environment. In recent years, extensive studies have investigated the correlation between tissue properties including cellularity, vascularity, fibrosis, secretion and microstructure and pancreatic diffusivity. Understanding how the various physiological and pathological features and the underlying functional processes affect the diffusion measurement may serve to optimize the method for improved diagnostic gain. Therefore, the aim of the present review article is to elucidate the relationship between pancreatic tissue characteristics and diffusion MRI measurement.
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Affiliation(s)
- Noam Nissan
- Department of Diagnostic Imaging, Chaim Sheba Medical Center, Tel HaShomer 5265601, Israel
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Ma C, Guo X, Liu L, Zhan Q, Li J, Zhu C, Wang L, Zhang J, Fang X, Qu J, Chen S, Shao C, Lu JP. Effect of region of interest size on ADC measurements in pancreatic adenocarcinoma. Cancer Imaging 2017; 17:13. [PMID: 28464866 PMCID: PMC5414294 DOI: 10.1186/s40644-017-0116-6] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2017] [Accepted: 04/27/2017] [Indexed: 02/07/2023] Open
Abstract
BACKGROUND To investigate the influence of region of interest (ROI) size on tumor apparent diffusion coefficient (ADC) measurements in pancreatic cancer. METHODS The study population consisted of 64 patients with pathologically proved pancreatic ductal adenocarcinomas (PDACs), who underwent preoperative magnetic resonance imaging (MRI) examinations including diffusion-weighted imaging (DWI). The tumor ADCs were measured by two independent readers using six round ROIs with sizes ranging from 20 to 214 mm2 (9 to 97 pixels) in both the six separate measurements. The intra- and inter-observer variabilities were analyzed by using the coefficient of variance (CV), the interclass correlation coefficient (ICC) and Bland-Altman analysis. The mean ADCs measured with the 6 different-sized ROIs were compared using one-way repeated analysis of variance. The sample sizes were calculated by using 80% power and a 5% significance level to detect 10 to 25% changes in ADC measurements. RESULTS The largest ROI (ROI214) yielded the best intra-observer repeatability (CV, 6.3%; ICC, 0.93) and inter-observer reproducibility (CV, 10.1%; ICC, 0.84). The mean differences in ADC measurements ± limits of agreement between the two readers were (0.06 ± 0.47) × 10-3 mm2 for ROI20, (0.08 ± 0.46) × 10-3 mm2 for ROI46, (0.05 ± 0.37) × 10-3 mm2 for ROI82, (0.07 ± 0.42) × 10-3 mm2 for ROI115, (0.05 ± 0.43) × 10-3 mm2 for ROI152 and (-0.02 ± 0.29) × 10-3 mm2 for ROI214. CONCLUSIONS ROI size had a considerable influence on the ADC measurements of PDACs.
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Affiliation(s)
- Chao Ma
- Department of Radiology, Changhai Hospital of Shanghai, the Second Military Medical University, No.168 Changhai Road, 200433, Shanghai, China
| | - Xiaoyu Guo
- Department of Radiology, Changhai Hospital of Shanghai, the Second Military Medical University, No.168 Changhai Road, 200433, Shanghai, China
| | - Li Liu
- Department of Radiology, Changhai Hospital of Shanghai, the Second Military Medical University, No.168 Changhai Road, 200433, Shanghai, China
| | - Qian Zhan
- Department of Radiology, Changhai Hospital of Shanghai, the Second Military Medical University, No.168 Changhai Road, 200433, Shanghai, China
| | - Jing Li
- Department of Radiology, Changhai Hospital of Shanghai, the Second Military Medical University, No.168 Changhai Road, 200433, Shanghai, China
| | - Chengcheng Zhu
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, California, USA
| | - Li Wang
- Department of Radiology, Changhai Hospital of Shanghai, the Second Military Medical University, No.168 Changhai Road, 200433, Shanghai, China.
| | - Jing Zhang
- Department of Pathology, Changhai Hospital of Shanghai, the Second Military Medical University, Shanghai, China
| | - Xu Fang
- Department of Radiology, Changhai Hospital of Shanghai, the Second Military Medical University, No.168 Changhai Road, 200433, Shanghai, China
| | - Jianxun Qu
- GE Healthcare, MR Group, Shanghai, China
| | - Shiyue Chen
- Department of Radiology, Changhai Hospital of Shanghai, the Second Military Medical University, No.168 Changhai Road, 200433, Shanghai, China
| | - Chengwei Shao
- Department of Radiology, Changhai Hospital of Shanghai, the Second Military Medical University, No.168 Changhai Road, 200433, Shanghai, China
| | - Jian-Ping Lu
- Department of Radiology, Changhai Hospital of Shanghai, the Second Military Medical University, No.168 Changhai Road, 200433, Shanghai, China
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Farr N, Wang YN, D'Andrea S, Gravelle KM, Hwang JH, Lee D. Noninvasive characterization of pancreatic tumor mouse models using magnetic resonance imaging. Cancer Med 2017; 6:1082-1090. [PMID: 28390098 PMCID: PMC5430104 DOI: 10.1002/cam4.1062] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2016] [Revised: 02/23/2017] [Accepted: 02/24/2017] [Indexed: 12/19/2022] Open
Abstract
The preclinical models of pancreatic adenocarcinoma provide an alternative means for determining the mechanisms of malignancy and possibilities for treatments, thus representing a resource of immense potential for cancer treatment in medicine. To evaluate different tumor models, quantifiable magnetic resonance imaging (MRI) techniques can play a significant role in identifying valuable in vivo biomarkers of tumor characteristics. We characterized three models of pancreatic cancer with multiparametric MRI techniques. Tumor stromal density of each tumor was measured using diffusion-weighted imaging and magnetization transfer (MT-MRI). Histologic measurement showed a similar trend with tumor fibrosis levels. Results indicated that MRI measurements can serve as a valuable tool in identifying and evaluating tumor characteristics.
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Affiliation(s)
- Navid Farr
- Department of Bioengineering, University of Washington, Seattle, Washington
| | - Yak-Nam Wang
- Applied Physics Laboratory, University of Washington, Seattle, Washington
| | - Samantha D'Andrea
- Department of Medicine, University of Washington, Seattle, Washington
| | - Kayla M Gravelle
- Department of Medicine, University of Washington, Seattle, Washington
| | - Joo Ha Hwang
- Department of Medicine, University of Washington, Seattle, Washington
- Department of Radiology, University of Washington, Seattle, Washington
| | - Donghoon Lee
- Department of Radiology, University of Washington, Seattle, Washington
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Ma C, Li Y, Wang L, Wang Y, Zhang Y, Wang H, Chen S, Lu J. Intravoxel incoherent motion DWI of the pancreatic adenocarcinomas: monoexponential and biexponential apparent diffusion parameters and histopathological correlations. Cancer Imaging 2017; 17:12. [PMID: 28454564 PMCID: PMC5410078 DOI: 10.1186/s40644-017-0114-8] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2016] [Accepted: 04/19/2017] [Indexed: 02/06/2023] Open
Abstract
Background To investigate the associations between the diffusion parameters obtained from multiple-b-values diffusion weighted imaging (DWI) of pancreatic ductal adenocarcinoma (PDAC) and the aggressiveness and local stage prediction, and assess the values of the quantitative parameters for the discrimination of tumors from healthy pancreas. Methods Fifty-one patients with surgical pathology-proven PDAC (size, 35 ± 12 mm) and fifty-seven healthy volunteers were enrolled. Diffusion parameters including monoexponential apparent diffusion coefficient (ADCb and ADCtotal) and biexponential intravoxel incoherent motion (IVIM) parameters (ADCslow, ADCfast and f) based on 9 b-values (0 to 1000s/mm2) DWI were calculated for the lesions and the healthy pancreas. These parameters were compared by grades of differentiation, lymph node status, tumor stage and location. The diagnostic performances were calculated and compared by using the receiver operating characteristic curves (ROC) analyses. Results There was no statistically significant difference in ADCb, ADCtotal, ADCslow, ADCfast or f between PDAC stage T1/T2 and stage T3/T4 or moderately differentiated versus poorly differentiated PDAC (p = 0.060-0.941). In addition, no significant differences were observed for the quantitative parameters between tumors located in the pancreatic head versus other pancreatic regions (p = 0.203-0.954) or between tumors with and without metastatic peri-pancreatic lymph nodes (p = 0.313-0.917). ADC25-600, ADC1000, ADCtotal and ADCfast were significantly lower for PDAC compared the healthy pancreas (all p < 0.05). ROC analyses showed the area under curve for ADC20 was the largest (0.911) to distinguish PDAC from normal pancreas (cut-off value, 5.58 × 10−3mm2/s) and had the highest combined sensitivity (89.5%) and specificity (82.4%). Conclusions Multiple-b-values DWI derived monoexponential and biexponential parameters of PDAC do not exhibit significance dependence on tumor grade or tumor characteristics. ADC20 provided the best accuracy for differentiating PDAC from healthy pancreas in the study.
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Affiliation(s)
- Chao Ma
- Department of Radiology, Changhai Hospital of Shanghai, The Second Military Medical University, No.168 Changhai Road, Shanghai, 200433, China
| | - Yanjun Li
- Department of Radiology, Changhai Hospital of Shanghai, The Second Military Medical University, No.168 Changhai Road, Shanghai, 200433, China
| | - Li Wang
- Department of Radiology, Changhai Hospital of Shanghai, The Second Military Medical University, No.168 Changhai Road, Shanghai, 200433, China
| | - Yang Wang
- Department of Pathology, Changhai Hospital of Shanghai, The Second Military Medical University, No.168 Changhai Road, Shanghai, China
| | - Yong Zhang
- MR Group, GE Healthcare, No. 1 Huatuo Road, Shanghai, China
| | - He Wang
- MR Group, GE Healthcare, No. 1 Huatuo Road, Shanghai, China
| | - Shiyue Chen
- Department of Radiology, Changhai Hospital of Shanghai, The Second Military Medical University, No.168 Changhai Road, Shanghai, 200433, China
| | - Jianping Lu
- Department of Radiology, Changhai Hospital of Shanghai, The Second Military Medical University, No.168 Changhai Road, Shanghai, 200433, China.
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Parada Villavicencio C, Mc Carthy RJ, Miller FH. Can diffusion-weighted magnetic resonance imaging of clear cell renal carcinoma predict low from high nuclear grade tumors. Abdom Radiol (NY) 2017; 42:1241-1249. [PMID: 27904923 DOI: 10.1007/s00261-016-0981-7] [Citation(s) in RCA: 26] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
OBJECTIVE To assess the diagnostic performance of the apparent diffusion coefficient (ADC) in predicting the Fuhrman nuclear grading of clear cell renal cell carcinomas (ccRCC). MATERIALS AND METHODS A total of 129 patients who underwent partial and radical nephrectomies with pathology-proven ccRCC were retrospectively evaluated. Histopathological characteristics and nuclear grades were analyzed. In addition, conventional magnetic resonance imaging (MRI) features were assessed in consensus by two radiologists to discriminate nuclear grading. ADC values were obtained from a region of interest (ROI) measurement in the ADC maps calculated from diffusion-weighted imaging (DWI) using b values of 50, 500, and 800 s/mm2. The threshold values for predicting and differentiating low-grade cancers (Fuhrman I-II) from high grade (Fuhrman III-IV) was obtained using binary logistic regression. The ADC cut-off value for differentiating low- and high-grade tumors was determined using classification analysis. RESULTS Significant associations (P < 0.001) were found between nuclear grading, conventional MR features, and DWI. Hemorrhage, necrosis, perirenal fat invasion, enhancement homogeneity, and cystic component were identified as independent predictors of tumor grade. High-grade ccRCC had significantly lower mean ADC values compared to low-grade tumors. An ADC cut-off value of 1.6 × 10-3 mm2/s had an optimal predictive percentage of 65.5% for low-grade tumors above this threshold and 81% for high-grade ccRCC below this threshold. Overall predictive accuracy was 70.5%. CONCLUSION The addition of ADC values to a model based on MRI conventional features demonstrates increased sensitivity and high specificity improving the distinguishing accuracy between both high-grade and low-grade ccRCC.
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Affiliation(s)
- Carolina Parada Villavicencio
- Department of Radiology, Northwestern Memorial Hospital, Northwestern University Feinberg School of Medicine, 676 North Saint Clair St. Suite 800, Chicago, IL, USA
| | - Robert J Mc Carthy
- Department of Anesthesiology, Northwestern Memorial Hospital, Northwestern University Feinberg School of Medicine, 676 North Saint Clair St. Suite 1050, Chicago, IL, USA
| | - Frank H Miller
- Department of Radiology, Northwestern Memorial Hospital, Northwestern University Feinberg School of Medicine, 676 North Saint Clair St. Suite 800, Chicago, IL, USA.
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Zhang TT, Wang L, Liu HH, Zhang CY, Li XM, Lu JP, Wang DB. Differentiation of pancreatic carcinoma and mass-forming focal pancreatitis: qualitative and quantitative assessment by dynamic contrast-enhanced MRI combined with diffusion-weighted imaging. Oncotarget 2017; 8:1744-1759. [PMID: 27661003 PMCID: PMC5352094 DOI: 10.18632/oncotarget.12120] [Citation(s) in RCA: 29] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2016] [Accepted: 09/13/2016] [Indexed: 12/18/2022] Open
Abstract
Differentiation between pancreatic carcinoma (PC) and mass-forming focal pancreatitis (FP) is invariably difficult. For the differential diagnosis, we qualitatively and quantitatively assessed the value of dynamic contrast-enhanced MRI (DCE-MRI) and diffusion-weighted imaging (DWI) in PC and FP in the present study. This study included 32 PC and 18 FP patients with histological confirmation who underwent DCE-MRI and DWI. The time-signal intensity curve (TIC) of PC and FP were classified into 5 types according to the time of reaching the peak, namely, type I, II, III, IV, and V, respectively, and two subtypes, namely, subtype-a (washout type) and subtype-b (plateau type) according to the part of the TIC profile after the peak. Moreover, the mean and relative apparent diffusion coefficient (ADC) value between PC and FP on DWI were compared. The type V TIC was only recognized in PC group (P < 0.01). Type IV b were more frequently observed in PC (P = 0.036), while type- IIa (P < 0.01), type- Ia (P = 0.037) in FP. We also found a significant difference in the mean and relative ADC value between PC and FP. The combined image set of DCE-MRI and DWI yielded an excellent sensitivity, specificity, and diagnostic accuracy (96.9%, 94.4%, and 96.0%). The TIC of DCE-MRI and ADC value of DWI for pancreatic mass were found to provide reliable information in differentiating PC from FP, and the combination of DCE-MRI and DWI can achieve a higher sensitivity, specificity, and diagnostic accuracy.
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Affiliation(s)
- Ting-Ting Zhang
- Department of Radiology, Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Li Wang
- Department of Radiology, Changhai Hospital, Second Military Medical University, Shanghai, China
| | - Huan-huan Liu
- Department of Radiology, Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Cai-yuan Zhang
- Department of Radiology, Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Xiao-ming Li
- Department of Radiology, Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Jian-ping Lu
- Department of Radiology, Changhai Hospital, Second Military Medical University, Shanghai, China
| | - Deng-bin Wang
- Department of Radiology, Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
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Lim G, Horowitz JM, Berggruen S, Ernst LM, Linn RL, Hewlett B, Kim J, Chalifoux LA, McCarthy RJ. Correlation of probability scores of placenta accreta on magnetic resonance imaging with hemorrhagic morbidity. J Clin Anesth 2016; 34:261-9. [DOI: 10.1016/j.jclinane.2016.04.046] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2015] [Revised: 03/28/2016] [Accepted: 04/24/2016] [Indexed: 11/25/2022]
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Fukukura Y, Shindo T, Hakamada H, Takumi K, Umanodan T, Nakajo M, Kamimura K, Umanodan A, Ideue J, Yoshiura T. Diffusion-weighted MR imaging of the pancreas: optimizing b-value for visualization of pancreatic adenocarcinoma. Eur Radiol 2016; 26:3419-27. [PMID: 26738506 DOI: 10.1007/s00330-015-4174-5] [Citation(s) in RCA: 25] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2015] [Revised: 11/05/2015] [Accepted: 12/15/2015] [Indexed: 01/17/2023]
Abstract
OBJECTIVES To determine the optimal b-value of 3.0-T diffusion-weighted imaging (DWI) for visualizing pancreatic adenocarcinomas METHODS Fifty-five patients with histologically confirmed pancreatic adenocarcinoma underwent DWI with different b-values (b = 500, 1000, 1500, and 2000 s/mm(2)) at 3.0 T. For each b-value, we retrospectively evaluated DWI findings of pancreatic adenocarcinomas (clear hyperintensity relative to the surrounding pancreas, hyperintensity with an unclear distal border, and isointensity) and image quality, and measured tumour-to-pancreas signal intensity (SI) ratios. DWI findings, image quality, and tumour-to-pancreas SI ratios were compared between the four b-values. RESULTS There was a significantly higher incidence of tumours showing clear hyperintensity on DWI with b-value of 1500 s/mm(2) than on that with b-value of 1000 s/mm(2) (P < 0.001), and on DWI with b-value of 1000 s/mm(2) than on that with b-value of 500 s/mm(2) (P < 0.001). The tumour-to-distal pancreas SI ratio was higher with b-value of 1500 s/mm(2) than with b-value of 1000 s/mm(2) (P < 0.001), and with b-value of 1000 s/mm(2) than with b-value of 500 s/mm(2) (P < 0.001). A lower image quality was obtained at increasing b-values (P < 0.001); the lowest scores were observed with b-value of 2000 s/mm(2). CONCLUSIONS The use of b = 1500 s/mm(2) for 3.0-T DWI can improve the delineation of pancreatic adenocarcinomas. KEY POINTS • Diffusion-weighted imaging (DWI) has been used for diagnosing pancreatic adenocarcinoma • The techniques for DWI, including the choice of b-values, vary considerably • DWI often fails to delineate pancreatic adenocarcinomas because of hyperintense pancreas • DWI with a higher b-value can improve the tumour delineation • The lowest image quality was obtained on DWI with b-value = 2000 s/mm (2).
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Affiliation(s)
- Yoshihiko Fukukura
- Department of Radiology, Kagoshima University Graduate School of Medical and Dental Sciences, 8-35-1 Sakuragaoka, Kagoshima City, 890-8544, Japan.
| | - Toshikazu Shindo
- Department of Radiology, Kagoshima University Graduate School of Medical and Dental Sciences, 8-35-1 Sakuragaoka, Kagoshima City, 890-8544, Japan
| | - Hiroto Hakamada
- Department of Radiology, Kagoshima University Graduate School of Medical and Dental Sciences, 8-35-1 Sakuragaoka, Kagoshima City, 890-8544, Japan
| | - Koji Takumi
- Department of Radiology, Kagoshima University Graduate School of Medical and Dental Sciences, 8-35-1 Sakuragaoka, Kagoshima City, 890-8544, Japan
| | - Tomokazu Umanodan
- Department of Radiology, Kagoshima University Graduate School of Medical and Dental Sciences, 8-35-1 Sakuragaoka, Kagoshima City, 890-8544, Japan
| | - Masanori Nakajo
- Department of Radiology, Kagoshima University Graduate School of Medical and Dental Sciences, 8-35-1 Sakuragaoka, Kagoshima City, 890-8544, Japan
| | - Kiyoshisa Kamimura
- Department of Radiology, Kagoshima University Graduate School of Medical and Dental Sciences, 8-35-1 Sakuragaoka, Kagoshima City, 890-8544, Japan
| | - Aya Umanodan
- Department of Radiology, Kagoshima University Graduate School of Medical and Dental Sciences, 8-35-1 Sakuragaoka, Kagoshima City, 890-8544, Japan
| | - Junnichi Ideue
- Department of Radiology, Kagoshima University Graduate School of Medical and Dental Sciences, 8-35-1 Sakuragaoka, Kagoshima City, 890-8544, Japan
| | - Takashi Yoshiura
- Department of Radiology, Kagoshima University Graduate School of Medical and Dental Sciences, 8-35-1 Sakuragaoka, Kagoshima City, 890-8544, Japan
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Wegner CS, Gaustad JV, Andersen LMK, Simonsen TG, Rofstad EK. Diffusion-weighted and dynamic contrast-enhanced MRI of pancreatic adenocarcinoma xenografts: associations with tumor differentiation and collagen content. J Transl Med 2016; 14:161. [PMID: 27268062 PMCID: PMC4897888 DOI: 10.1186/s12967-016-0920-y] [Citation(s) in RCA: 30] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2016] [Accepted: 05/20/2016] [Indexed: 01/22/2023] Open
Abstract
PURPOSE The aggressiveness of pancreatic ductal adenocarcinoma (PDAC) is highly dependent on the level of differentiation and the composition of the stroma. In this preclinical study, we investigated the potential of diffusion-weighted magnetic resonance imaging (DW-MRI) and dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) as noninvasive methods for providing information on the differentiation and the stroma of PDACs. METHODS Xenografted tumors initiated from four PDAC cell lines (BxPC-3, Capan-2, MIAPaCa-2, and Panc-1) were included in the study. DW-MRI and DCE-MRI were carried out on a 7.05-T MR scanner, and tumor images of ADC (the apparent diffusion coefficient), K (trans) (the volume transfer constant of Gd-DOTA), and v e (the fractional distribution volume of Gd-DOTA) were produced. The level of differentiation and the amount and structure of collagen I and collagen IV were determined by examining histological preparations. RESULTS Differentiated tumors showed lower levels of collagen I and collagen IV than non-differentiated tumors. Significant correlations were found between ADC and v e, and both parameters differentiated clearly between collagen-rich non-differentiated tumors and differentiated tumors containing less collagen. CONCLUSION Differentiated PDAC xenografts show higher ADC values and higher v e values than their non-differentiated counterparts. This observation supports the application of parametric MR images as tumor biomarkers in PDAC. Patients showing low values of ADC and v e most likely have non-differentiated tumors with extensive stroma and, hence, poor prognosis.
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Affiliation(s)
- Catherine S. Wegner
- Group of Radiation Biology and Tumor Physiology, Department of Radiation Biology, Institute for Cancer Research, Norwegian Radium Hospital, Oslo University Hospital, Box 4953, Nydalen, 0424 Oslo, Norway
| | - Jon-Vidar Gaustad
- Group of Radiation Biology and Tumor Physiology, Department of Radiation Biology, Institute for Cancer Research, Norwegian Radium Hospital, Oslo University Hospital, Box 4953, Nydalen, 0424 Oslo, Norway
| | - Lise Mari K. Andersen
- Group of Radiation Biology and Tumor Physiology, Department of Radiation Biology, Institute for Cancer Research, Norwegian Radium Hospital, Oslo University Hospital, Box 4953, Nydalen, 0424 Oslo, Norway
| | - Trude G. Simonsen
- Group of Radiation Biology and Tumor Physiology, Department of Radiation Biology, Institute for Cancer Research, Norwegian Radium Hospital, Oslo University Hospital, Box 4953, Nydalen, 0424 Oslo, Norway
| | - Einar K. Rofstad
- Group of Radiation Biology and Tumor Physiology, Department of Radiation Biology, Institute for Cancer Research, Norwegian Radium Hospital, Oslo University Hospital, Box 4953, Nydalen, 0424 Oslo, Norway
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