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Babapour S, Chen A, Li G, Phan L. Pancreatic Neuroendocrine Diagnostic Imaging Order and Reader Evaluation over Two Decades in a Tertiary Academic Center. Diagnostics (Basel) 2025; 15:960. [PMID: 40310338 PMCID: PMC12026277 DOI: 10.3390/diagnostics15080960] [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: 01/25/2025] [Revised: 03/03/2025] [Accepted: 03/04/2025] [Indexed: 05/02/2025] Open
Abstract
Background/Objective: Identifying patterns of diagnostic imaging workflow parallel to the influence of certain variables, such as pathology guidelines over time, provides valuable insight for clinical decision making. This study presents a recurring trend of initial imaging orders and follow-ups, up to the diagnosis of pancreatic neuroendocrine tumors (pNETs), across two decades, with scans which led to pathological investigation. Methods: Three readers evaluated common conventional imaging among initial and follow-up studies for lesion detection and localization. Inter-reader and intra-reader analyses were controlled as contributing factors to the imaging diagnostic trend. Results: Our results show that CT was the prominent initial scan in pNET workup, likely due to their wide availability, high spatial resolution, and rapid acquisition, with a sufficient detection rate throughout both decades, regardless of technical advances. However, MRI scans also gained soaring popularity, especially among syndromic patients, likely due to follow-up and anatomical surgery precision. Conclusions: Newer modalities may be eventually useful and only requested for pNETs staging and further treatment.
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Affiliation(s)
- Sara Babapour
- Radiological Sciences, Clinical Research, David Geffen School of Medicine, University of California, Los Angeles, 10833 Le Conte Ave, Los Angeles, CA 90095, USA; (A.C.); (G.L.); (L.P.)
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Lu X, Dai Y, Liu X, Jiang L, Zhang K, Wu J, Gao W, Jiang K, Dai C, Miao Y, Li M, Wei J. Differences in the Clinicopathologic and Radiological Characteristics of Patients With Microcystic and Macrocystic Serous Cystadenoma of the Pancreas. Pancreas 2025; 54:e317-e323. [PMID: 39999293 PMCID: PMC12017593 DOI: 10.1097/mpa.0000000000002436] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/19/2024] [Accepted: 11/06/2024] [Indexed: 02/27/2025]
Abstract
OBJECTIVES The aims of the study were to elucidate the clinicopathological characteristics, imaging features, and surgical outcomes of patients with serous cystic neoplasms (SCNs) and to compare the features between microcystic (MiC) and macrocystic (MaC) SCNs. MATERIALS AND METHODS In this single-center retrospective study, information of patients with SCN between 2016 and 2022 at our institution was collected and analyzed. RESULTS A total of 105 patients with SCNs were identified, including 58 (55.2%) with MiC type and 47 (44.8%) with MaC type. Patient age and American Society of Anesthesiologists grade in the MiC group were significantly higher than those in the MaC group. The overall preoperative diagnostic accuracy was 7.6%, with no patients in the MaC group correctly diagnosed before surgery. In imaging examinations, almost all (97.1%) exhibited a lobulated pattern. Internal septation, honeycomb pattern, central scar, and calcification were common, with a significantly higher incidence in the MiC group. No in-hospital deaths occurred, and the incidence of major complications were comparable in both groups. CONCLUSIONS Although many patients presented with typical imaging features, accurate diagnosis of SCN remained difficult. Except for older age and higher American Society of Anesthesiologists grade in the MiC group, there were no significant differences in the clinicopathological characteristics between MiC and MaC SCN patients.
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Affiliation(s)
- Xiaozhi Lu
- Pancreas Center, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Yuran Dai
- Pancreas Center, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Xinchun Liu
- Department of Gastrointestinal and Anal Surgery, Affiliated Hangzhou First People's Hospital, Hangzhou, China
- School of Medicine, Westlake University, Hangzhou, China
| | - Lei Jiang
- Pancreas Center, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Kai Zhang
- Pancreas Center, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Junli Wu
- Pancreas Center, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Wentao Gao
- Pancreas Center, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Kuirong Jiang
- Pancreas Center, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Cuncai Dai
- Pancreas Center, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Yi Miao
- Pancreas Center, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Mingna Li
- Department of Pathology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Jishu Wei
- Pancreas Center, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
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Zhou XP, Sun LB, Liu WH, Song XY, Gao Y, Xing JP, Gao SH. Development and validation of predictive models for distant metastasis and prognosis of gastroenteropancreatic neuroendocrine neoplasms. Sci Rep 2025; 15:9510. [PMID: 40108260 PMCID: PMC11923110 DOI: 10.1038/s41598-025-92974-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2024] [Accepted: 03/04/2025] [Indexed: 03/22/2025] Open
Abstract
Imaging examinations exhibit a certain rate of missed detection for distant metastases of gastroenteropancreatic neuroendocrine neoplasms (GEP-NENs). This study aims to develop and validate a risk prediction model for the distant metastases and prognosis of GEP-NENs. This study included patients diagnosed with gastroenteropancreatic neuroendocrine neoplasms (GEP-NENs) from the Surveillance, Epidemiology, and End Results (SEER) database between 2010 and 2015. External validation was performed with patients from the China-Japan Union Hospital of Jilin University. Univariate and multivariate logistic regression analyses were conducted on the selected data to identify independent risk factors for distant metastasis in GEP-NENs. A nomogram was subsequently developed using these variables to estimate the probability of distant metastasis in patients with GEP-NENs. Subsequently, patients with distant metastasis from GEP-NENs were selected for univariate and multivariate Cox regression analyses to identify prognostic risk factors. A nomogram was subsequently developed to predict overall survival (OS) in patients with GEP-NENs. Finally, the developed nomogram was validated using Receiver Operating Characteristic (ROC) curves, calibration curves, and Decision Curve Analysis (DCA). Kaplan-Meier analysis was employed to evaluate survival differences between high-risk and low-risk groups. A total of 11,207 patients with GEP-NENs were selected from the SEER database, and 152 patients from the China-Japan Union Hospital of Jilin University were utilized as an independent external validation cohort. Univariate and multivariate logistic regression analyses revealed that the primary tumor site, tumor grade, pathological type, tumor size, T stage, and N stage are independent predictors of distant metastasis in GEP-NENs. Additionally, among the 1732 patients with distant metastasis of GEP-NENs, univariate and multivariate Cox regression analyses identified N stage, tumor size, pathological type, primary site surgery, and tumor grade as independent prognostic factors. Based on the results of the regression analyses, a nomogram model was developed. Both internal and external validation results demonstrated that the nomogram models exhibited high predictive accuracy and significant clinical utility. In summary, we developed an effective predictive model to assess distant metastasis and prognosis in GEP-NENs. This model assists clinicians in evaluating the risk of distant metastasis and in assessing patient prognosis.
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Affiliation(s)
- Xuan-Peng Zhou
- China-Japan Union Hospital of Jilin University, Changchun, 130000, Jilin, People's Republic of China
| | - Luan-Biao Sun
- China-Japan Union Hospital of Jilin University, Changchun, 130000, Jilin, People's Republic of China
| | - Wen-Hao Liu
- China-Japan Union Hospital of Jilin University, Changchun, 130000, Jilin, People's Republic of China
| | - Xin-Yuan Song
- The Chinese University of Hong Kong, New Territories, 999077, Hong Kong Special Administrative Region, People's Republic of China
| | - Yang Gao
- Zhalute Banner People's Hospital, Tongliao, 029100, Inner Mongolia Autonomous Region, People's Republic of China
| | - Jian-Peng Xing
- China-Japan Union Hospital of Jilin University, Changchun, 130000, Jilin, People's Republic of China.
| | - Shuo-Hui Gao
- China-Japan Union Hospital of Jilin University, Changchun, 130000, Jilin, People's Republic of China.
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Shen K, Su W, Liang C, Shi D, Sun J, Yu R. Differentiating small (< 2 cm) pancreatic ductal adenocarcinoma from neuroendocrine tumors with multiparametric MRI-based radiomic features. Eur Radiol 2024; 34:7553-7563. [PMID: 38869639 DOI: 10.1007/s00330-024-10837-x] [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: 03/19/2024] [Revised: 04/08/2024] [Accepted: 05/02/2024] [Indexed: 06/14/2024]
Abstract
OBJECTIVES To assess MR-based radiomic analysis in preoperatively discriminating small (< 2 cm) pancreatic ductal adenocarcinomas (PDACs) from neuroendocrine tumors (PNETs). METHODS A total of 197 patients (146 in the training cohort, 51 in the validation cohort) from two centers were retrospectively collected. A total of 7338 radiomics features were extracted from T2-weighted, diffusion-weighted, T1-weighted, arterial phase, portal venous phase and delayed phase imaging. The optimal features were selected by the Mann-Whitney U test, Spearman's rank correlation test and least absolute shrinkage and selection operator method and used to construct the radiomic score (Rad-score). Conventional radiological and clinical features were also assessed. Multivariable logistic regression was used to construct a radiological model, a radiomic model and a fusion model. RESULTS Nine optimal features were identified and used to build the Rad-score. The radiomic model based on the Rad-score achieved satisfactory results with AUCs of 0.905 and 0.930, sensitivities of 0.780 and 0.800, specificities of 0.906 and 0.952 and accuracies of 0.836 and 0.863 for the training and validation cohorts, respectively. The fusion model, incorporating CA19-9, tumor margins, pancreatic duct dilatation and the Rad-score, exhibited the best performance with AUCs of 0.977 and 0.941, sensitivities of 0.914 and 0.852, specificities of 0.954 and 0.950, and accuracies of 0.932 and 0.894 for the training and validation cohorts, respectively. CONCLUSIONS The MR-based Rad-score is a novel image biomarker for discriminating small PDACs from PNETs. A fusion model combining radiomic, radiological and clinical features performed very well in differentially diagnosing these two tumors. CLINICAL RELEVANCE STATEMENT A fusion model combining MR-based radiomic, radiological, and clinical features could help differentiate between small pancreatic ductal adenocarcinomas and pancreatic neuroendocrine tumors. KEY POINTS Preoperatively differentiating small pancreatic ductal adenocarcinomas (PDACs) and pancreatic neuroendocrine tumors (PNETs) is challenging. Multiparametric MRI-based Rad-score can be used for discriminating small PDACs from PNETs. A fusion model incorporating radiomic, radiological, and clinical features differentiated small PDACs from PNETs well.
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Affiliation(s)
- Keren Shen
- Department of Radiology, the Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310009, China
| | - Weijie Su
- Department of Radiology, the Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310009, China
| | - Chunmiao Liang
- Department of Radiology, the Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310009, China
| | - Dan Shi
- Department of Radiology, the Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310009, China
| | - Jihong Sun
- Department of Radiology, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, 310016, China
| | - Risheng Yu
- Department of Radiology, the Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310009, China.
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Xu Q, Zhao H, Gao R, Wang X, Xu J, Sun G, Xue K, Yang Y, Li E, Zhu L, Wu W, Feng F. Insulinoma detection and surgery planning: a comparative study of 5.0T MRI versus 3.0T MRI and MDCT. Abdom Radiol (NY) 2024:10.1007/s00261-024-04680-3. [PMID: 39514101 DOI: 10.1007/s00261-024-04680-3] [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: 09/20/2024] [Revised: 10/30/2024] [Accepted: 11/02/2024] [Indexed: 11/16/2024]
Abstract
PURPOSE To compare the ability among 5.0T MRI, 3.0T MRI and MDCT in identifying insulinomas and determining the tumor-to-duct relationship. METHODS A consecutive series of patients highly suspected of insulinomas were enrolled between October 2021 and February 2024, who underwent 5.0T MRI preoperatively, as well as 3.0T MRI or MDCT. The subjective and objective image quality, lesion-to-pancreas contrast, clarity of main pancreatic duct (MPD) and tumor-to-duct relationship at 5.0T, 3.0T MRI and MDCT were evaluated by three observers. The correlation between tumor-duct distance and clinically relevant postoperative pancreatic fistula (CR-POPF) risk was analyzed. RESULTS Forty patients (14 men; mean age, 46.4 ± 16.5 years) with insulinomas were included in this study. 21 of them underwent both 5.0T and 3.0T MRI; and 38 of them underwent 5.0T MRI and MDCT. The intra- and inter-observer agreement of 5.0T MRI were good to excellent. 5.0T showed significantly higher subjective and objective image quality on T1WI and DWI compared to 3.0T (p < 0.05). Lesion-to-pancreas contrast was superior across all sequences at 5.0T compared to 3.0T(p < 0.05). A head-to-head comparison of patients who received both 5.0T and 3.0T MRI demonstrated that tumor detection was superior with 5.0T MRI (5.0T: 100%; 3.0 T: 92.0%, p < 0.05). Feasibility of tumor-to-duct relationship assessment was superior at 5.0T, compared to 3.0T and MDCT (93.2%, 64.0% and 52.3%, respectively, p < 0.05). Tumor-duct distance could predict CR-POPF after enucleation surgery (areas under the ROC curve 0.79, p = 0.01). CONCLUSION 5.0T MRI exhibits certain superiority in detecting insulinomas and assessing tumor-to-duct relationship compared to 3.0T MRI and MDCT.
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Affiliation(s)
- Qiang Xu
- Department of General Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Science and Peking Union Medical College, Beijing, China
- State Key Laboratory of Complex Severe and Rare Diseases, Beijing, China
| | - Huijia Zhao
- Department of General Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Science and Peking Union Medical College, Beijing, China
- State Key Laboratory of Complex Severe and Rare Diseases, Beijing, China
| | - Ruichen Gao
- Department of General Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Science and Peking Union Medical College, Beijing, China
- State Key Laboratory of Complex Severe and Rare Diseases, Beijing, China
| | - Xuan Wang
- State Key Laboratory of Complex Severe and Rare Diseases, Beijing, China
- Department of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Science and Peking Union Medical College, Beijing, China
| | - Jia Xu
- State Key Laboratory of Complex Severe and Rare Diseases, Beijing, China
- Department of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Science and Peking Union Medical College, Beijing, China
| | - Gan Sun
- Theranostics and Translational Research Center, National Infrastructures for Translational Medicine, Institute of Clinical Medicine, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Beijing, China
| | - Ke Xue
- United Imaging Research Institute of Intelligent Imaging, Beijing, China
| | - Yuxin Yang
- United Imaging Research Institute of Intelligent Imaging, Beijing, China
| | - Enhui Li
- United Imaging Research Institute of Intelligent Imaging, Beijing, China
| | - Liang Zhu
- State Key Laboratory of Complex Severe and Rare Diseases, Beijing, China.
- Department of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Science and Peking Union Medical College, Beijing, China.
| | - Wenming Wu
- Department of General Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Science and Peking Union Medical College, Beijing, China.
- State Key Laboratory of Complex Severe and Rare Diseases, Beijing, China.
| | - Feng Feng
- State Key Laboratory of Complex Severe and Rare Diseases, Beijing, China
- Department of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Science and Peking Union Medical College, Beijing, China
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Hu M, Lv L, Dong H. A CT-based diagnostic nomogram and survival analysis for differentiating grade 3 pancreatic neuroendocrine tumors from pancreatic ductal adenocarcinomas. Front Oncol 2024; 14:1443213. [PMID: 39267841 PMCID: PMC11391483 DOI: 10.3389/fonc.2024.1443213] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2024] [Accepted: 08/06/2024] [Indexed: 09/15/2024] Open
Abstract
Objective To construct a CT-based diagnostic nomogram for distinguishing grade 3 pancreatic neuroendocrine tumors (G3 PNETs) from pancreatic ductal adenocarcinomas (PDACs) and assess their respective survival outcomes. Methods Patients diagnosed with G3 PNETs (n = 30) and PDACs (n = 78) through surgery or biopsy from two medical centers were retrospectively identified. Demographic and radiological information, including age, gender, tumor diameter, shape, margin, dilatation of pancreatic duct, and invasive behavior, were carefully collected. A nomogram was established after univariate and multivariate logistic regression analyses. The Kaplan-Meier survival was performed to analyze their survival outcomes. Results Factors with a p-value <0.05, including age, CA 19-9, pancreatic duct dilatation, irregular shape, ill-defined margin, pancreatic atrophy, combined pancreatitis, arterial/portal enhancement ratio, were included in the multivariate logistic analysis. The independent predictive factors, including age (OR, 0.91; 95% CI, 0.85-0.98), pancreatic duct dilatation (OR, 0.064; 95% CI, 0.01-0.32), and portal enhancement ratio (OR, 1,178.08; 95% CI, 5.96-232,681.2) were determined to develop a nomogram. The internal calibration curve and decision curve analysis demonstrate that the nomogram exhibits good consistency and discriminative capacity in distinguishing G3 PNETs from PDACs. Patients diagnosed with G3 PNETs exhibited considerably better overall survival outcomes compared to those diagnosed with PDACs (median survival months, 42 vs. 9 months, p < 0.001). Conclusions The nomogram model based on age, pancreatic duct dilatation, and portal enhancement ratio demonstrates good accuracy and discriminative ability effectively predicting the probability of G3 PNETs from PDACs. Furthermore, patients with G3 PNETs exhibit better prognosis than PDACs.
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Affiliation(s)
- Miaomiao Hu
- Department of Radiology, The First People's Hospital of Huzhou, Huzhou, China
| | - Lulu Lv
- Department of Radiology, Xuzhou Central Hospital, Xuzhou, China
| | - Hongfeng Dong
- Department of Radiology, The First People's Hospital of Huzhou, Huzhou, China
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Hesami M, Blake M, Anderson MA, Asmundo L, Kilcoyne A, Najmi Z, Caravan PD, Catana C, Czawlytko C, Esfahani SA, Kambadakone AR, Samir A, McDermott S, Domachevsky L, Ursprung S, Catalano OA. Diagnostic Anatomic Imaging for Neuroendocrine Neoplasms: Maximizing Strengths and Mitigating Weaknesses. J Comput Assist Tomogr 2024; 48:521-532. [PMID: 38657156 PMCID: PMC11245376 DOI: 10.1097/rct.0000000000001615] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/26/2024]
Abstract
ABSTRACT Neuroendocrine neoplasms are a heterogeneous group of gastrointestinal and lung tumors. Their diverse clinical manifestations, variable locations, and heterogeneity present notable diagnostic challenges. This article delves into the imaging modalities vital for their detection and characterization. Computed tomography is essential for initial assessment and staging. At the same time, magnetic resonance imaging (MRI) is particularly adept for liver, pancreatic, osseous, and rectal imaging, offering superior soft tissue contrast. The article also highlights the limitations of these imaging techniques, such as MRI's inability to effectively evaluate the cortical bone and the questioned cost-effectiveness of computed tomography and MRI for detecting specific gastric lesions. By emphasizing the strengths and weaknesses of these imaging techniques, the review offers insights into optimizing their utilization for improved diagnosis, staging, and therapeutic management of neuroendocrine neoplasms.
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Affiliation(s)
- Mina Hesami
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA
| | - Michael Blake
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA
| | - Mark A. Anderson
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA
| | - Luigi Asmundo
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA
- Postgraduation School in Radiodiagnostics, Università degli Studi di Milano, Milan, Italy
| | - Aoife Kilcoyne
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA
| | - Zahra Najmi
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA
| | - Peter D. Caravan
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA
| | - Ciprian Catana
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA
| | - Cynthia Czawlytko
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA
| | - Shadi Abdar Esfahani
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA
| | - Avinash R. Kambadakone
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA
| | - Anthony Samir
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA
| | - Shaunagh McDermott
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA
| | - Liran Domachevsky
- Department of Nuclear Medicine, The Chaim Sheba Medical Center, Tel Hashomer, Israel
| | - Stephan Ursprung
- Department of Radiology, University Hospital Tuebingen, Tuebingen, Germany
| | - Onofrio A. Catalano
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA
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Asmundo L, Rizzetto F, Blake M, Anderson M, Mojtahed A, Bradley W, Shenoy-Bhangle A, Fernandez-del Castillo C, Qadan M, Ferrone C, Clark J, Ambrosini V, Picchio M, Mapelli P, Evangelista L, Leithner D, Nikolaou K, Ursprung S, Fanti S, Vanzulli A, Catalano OA. Advancements in Neuroendocrine Neoplasms: Imaging and Future Frontiers. J Clin Med 2024; 13:3281. [PMID: 38892992 PMCID: PMC11172657 DOI: 10.3390/jcm13113281] [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: 04/27/2024] [Revised: 05/23/2024] [Accepted: 05/30/2024] [Indexed: 06/21/2024] Open
Abstract
Neuroendocrine neoplasms (NENs) are a diverse group of tumors with varying clinical behaviors. Their incidence has risen due to increased awareness, improved diagnostics, and aging populations. The 2019 World Health Organization classification emphasizes integrating radiology and histopathology to characterize NENs and create personalized treatment plans. Imaging methods like CT, MRI, and PET/CT are crucial for detection, staging, treatment planning, and monitoring, but each of them poses different interpretative challenges and none are immune to pitfalls. Treatment options include surgery, targeted therapies, and chemotherapy, based on the tumor type, stage, and patient-specific factors. This review aims to provide insights into the latest developments and challenges in NEN imaging, diagnosis, and management.
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Affiliation(s)
- Luigi Asmundo
- Postgraduation School in Radiodiagnostics, Università degli Studi di Milano, Via Festa del Perdono 7, 20122 Milan, Italy;
- Department of Radiology, Harvard Medical School, Massachusetts General Hospital, 55 Fruit Street, Boston, MA 02114, USA; (M.B.); (M.A.); (A.M.); (W.B.); (A.S.-B.)
| | - Francesco Rizzetto
- Postgraduation School in Radiodiagnostics, Università degli Studi di Milano, Via Festa del Perdono 7, 20122 Milan, Italy;
- Department of Radiology, ASST Grande Ospedale Metropolitano Niguarda, Piazza Ospedale Maggiore 3, 20162 Milan, Italy;
| | - Michael Blake
- Department of Radiology, Harvard Medical School, Massachusetts General Hospital, 55 Fruit Street, Boston, MA 02114, USA; (M.B.); (M.A.); (A.M.); (W.B.); (A.S.-B.)
| | - Mark Anderson
- Department of Radiology, Harvard Medical School, Massachusetts General Hospital, 55 Fruit Street, Boston, MA 02114, USA; (M.B.); (M.A.); (A.M.); (W.B.); (A.S.-B.)
| | - Amirkasra Mojtahed
- Department of Radiology, Harvard Medical School, Massachusetts General Hospital, 55 Fruit Street, Boston, MA 02114, USA; (M.B.); (M.A.); (A.M.); (W.B.); (A.S.-B.)
| | - William Bradley
- Department of Radiology, Harvard Medical School, Massachusetts General Hospital, 55 Fruit Street, Boston, MA 02114, USA; (M.B.); (M.A.); (A.M.); (W.B.); (A.S.-B.)
| | - Anuradha Shenoy-Bhangle
- Department of Radiology, Harvard Medical School, Massachusetts General Hospital, 55 Fruit Street, Boston, MA 02114, USA; (M.B.); (M.A.); (A.M.); (W.B.); (A.S.-B.)
| | - Carlos Fernandez-del Castillo
- Department of Surgery, Harvard Medical School, Massachusetts General Hospital, 55 Fruit Street, Boston, MA 02114, USA; (C.F.-d.C.); (M.Q.)
| | - Motaz Qadan
- Department of Surgery, Harvard Medical School, Massachusetts General Hospital, 55 Fruit Street, Boston, MA 02114, USA; (C.F.-d.C.); (M.Q.)
| | - Cristina Ferrone
- Department of Surgery, Cedars-Sinai Medical Center, 8700 Beverly Boulevard, Los Angeles, CA 90048, USA;
| | - Jeffrey Clark
- Department of Oncology, Harvard Medical School, Massachusetts General Hospital, 55 Fruit Street, Boston, MA 02114, USA;
| | - Valentina Ambrosini
- Nuclear Medicine, IRCCS Azienda Ospedaliero-Universitaria di Bologna, Via Massarenti 9, 40138 Bologna, Italy; (V.A.); (S.F.)
- Nuclear Medicine, Alma Mater Studiorum University of Bologna, 40126 Bologna, Italy
| | - Maria Picchio
- Department of Nuclear Medicine, IRCCS San Raffaele Scientific Institute, Vita-Salute San Raffaele University, 20132 Milan, Italy; (M.P.); (P.M.)
| | - Paola Mapelli
- Department of Nuclear Medicine, IRCCS San Raffaele Scientific Institute, Vita-Salute San Raffaele University, 20132 Milan, Italy; (M.P.); (P.M.)
| | - Laura Evangelista
- Department of Biomedical Sciences, Humanitas University, Via Rita Levi Montalcini 4, Pieve Emanuele, 20072 Milan, Italy;
| | - Doris Leithner
- Department of Diagnostic and Interventional Radiology, University Hospital Frankfurt, Theodor-Stern-Kai 7, 60596 Frankfurt am Main, Germany;
| | - Konstantin Nikolaou
- Department of Radiology, University Hospital Tuebingen, Osianderstraße 5, 72076 Tübingen, Germany; (K.N.); (S.U.)
| | - Stephan Ursprung
- Department of Radiology, University Hospital Tuebingen, Osianderstraße 5, 72076 Tübingen, Germany; (K.N.); (S.U.)
| | - Stefano Fanti
- Nuclear Medicine, IRCCS Azienda Ospedaliero-Universitaria di Bologna, Via Massarenti 9, 40138 Bologna, Italy; (V.A.); (S.F.)
- Nuclear Medicine, Alma Mater Studiorum University of Bologna, 40126 Bologna, Italy
| | - Angelo Vanzulli
- Department of Radiology, ASST Grande Ospedale Metropolitano Niguarda, Piazza Ospedale Maggiore 3, 20162 Milan, Italy;
- Department of Oncology and Hemato-Oncology, Università Degli Studi di Milano, Via Festa del Perdono 7, 20122 Milan, Italy
| | - Onofrio Antonio Catalano
- Department of Radiology, Harvard Medical School, Massachusetts General Hospital, 55 Fruit Street, Boston, MA 02114, USA; (M.B.); (M.A.); (A.M.); (W.B.); (A.S.-B.)
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Noda Y, Ando T, Kaga T, Yamda N, Seko T, Ishihara T, Kawai N, Miyoshi T, Ito A, Naruse T, Hyodo F, Kato H, Kambadakone AR, Matsuo M. Pancreatic cancer detection with dual-energy CT: diagnostic performance of 40 keV and 70 keV virtual monoenergetic images. LA RADIOLOGIA MEDICA 2024; 129:677-686. [PMID: 38512626 DOI: 10.1007/s11547-024-01806-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/05/2023] [Accepted: 02/14/2024] [Indexed: 03/23/2024]
Abstract
PURPOSE To compare the diagnostic performance of 40 keV and 70 keV virtual monoenergetic images (VMIs) generated from dual-energy CT in the detection of pancreatic cancer. METHODS This retrospective study included patients who underwent pancreatic protocol dual-energy CT from January 2019 to August 2022. Four radiologists (1-11 years of experience), who were blinded to the final diagnosis, independently and randomly interpreted 40 keV and 70 keV VMIs and graded the presence or absence of pancreatic cancer. For each image set (40 keV and 70 keV VMIs), the sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy were calculated. The diagnostic performance of each image set was compared using generalized estimating equations. RESULTS Overall, 137 patients (median age, 71 years; interquartile range, 63-78 years; 77 men) were included. Among them, 62 patients (45%) had pathologically proven pancreatic cancer. The 40 keV VMIs had higher specificity (75% vs. 67%; P < .001), PPV (76% vs. 71%; P < .001), and accuracy (85% vs. 81%; P = .001) than the 70 keV VMIs. On the contrary, 40 keV VMIs had lower sensitivity (96% vs. 98%; P = .02) and NPV (96% vs. 98%; P = .004) than 70 keV VMIs. However, the diagnostic confidence in patients with (P < .001) and without (P = .001) pancreatic cancer was improved in 40 keV VMIs than in 70 keV VMIs. CONCLUSIONS The 40 keV VMIs showed better diagnostic performance in diagnosing pancreatic cancer than the 70 keV VMIs, along with higher reader confidence.
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Affiliation(s)
- Yoshifumi Noda
- Department of Radiology, Gifu University, 1-1 Yanagido, Gifu, 501-1194, Japan.
| | - Tomohiro Ando
- Department of Radiology, Gifu University, 1-1 Yanagido, Gifu, 501-1194, Japan
| | - Tetsuro Kaga
- Department of Radiology, Gifu University, 1-1 Yanagido, Gifu, 501-1194, Japan
| | - Nao Yamda
- Department of Radiology, Gifu University, 1-1 Yanagido, Gifu, 501-1194, Japan
| | - Takuya Seko
- Department of Radiology, Gifu University, 1-1 Yanagido, Gifu, 501-1194, Japan
| | - Takuma Ishihara
- Innovative and Clinical Research Promotion Center, Gifu University Hospital, 1-1 Yanagido, Gifu, 501-1194, Japan
| | - Nobuyuki Kawai
- Department of Radiology, Gifu University, 1-1 Yanagido, Gifu, 501-1194, Japan
| | - Toshiharu Miyoshi
- Department of Radiology Services, Gifu University Hospital, 1-1 Yanagido, Gifu, 501-1194, Japan
| | - Akio Ito
- Department of Radiology, Gifu University, 1-1 Yanagido, Gifu, 501-1194, Japan
| | - Takuya Naruse
- Department of Radiology, Gifu University, 1-1 Yanagido, Gifu, 501-1194, Japan
| | - Fuminori Hyodo
- Center for One Medicine Innovative Translational Research (COMIT), Institute for Advanced Study, Gifu University, 1-1 Yanagido, Gifu, 501-1194, Japan
- Department of Pharmacology, Graduate School of Medicine, Gifu University, Gifu, Japan
| | - Hiroki Kato
- Department of Radiology, Gifu University, 1-1 Yanagido, Gifu, 501-1194, Japan
| | - Avinash R Kambadakone
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, 55 Fruit Street, White 270, Boston, MA, 02114, USA
| | - Masayuki Matsuo
- Department of Radiology, Gifu University, 1-1 Yanagido, Gifu, 501-1194, Japan
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10
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Hu X, Shi S, Wang Y, Yuan J, Chen M, Wei L, Deng W, Feng ST, Peng Z, Luo Y. Dual-energy CT improves differentiation of non-hypervascular pancreatic neuroendocrine neoplasms from CA 19-9-negative pancreatic ductal adenocarcinomas. LA RADIOLOGIA MEDICA 2024; 129:1-13. [PMID: 37861978 DOI: 10.1007/s11547-023-01733-3] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/16/2023] [Accepted: 09/28/2023] [Indexed: 10/21/2023]
Abstract
PURPOSE To evaluate the utility of dual-energy CT (DECT) in differentiating non-hypervascular pancreatic neuroendocrine neoplasms (PNENs) from pancreatic ductal adenocarcinomas (PDACs) with negative carbohydrate antigen 19-9 (CA 19-9). METHODS This retrospective study included 26 and 39 patients with pathologically confirmed non-hypervascular PNENs and CA 19-9-negative PDACs, respectively, who underwent contrast-enhanced DECT before treatment between June 2019 and December 2021. The clinical, conventional CT qualitative, conventional CT quantitative, and DECT quantitative parameters of the two groups were compared using univariate analysis and selected by least absolute shrinkage and selection operator regression (LASSO) analysis. Multivariate logistic regression analyses were performed to build qualitative, conventional CT quantitative, DECT quantitative, and comprehensive models. The areas under the receiver operating characteristic curve (AUCs) of the models were compared using DeLong's test. RESULTS The AUCs of the DECT quantitative (based on normalized iodine concentrations [nICs] in the arterial and portal venous phases: 0.918; 95% confidence interval [CI] 0.852-0.985) and comprehensive (based on tumour location and nICs in the arterial and portal venous phases: 0.966; 95% CI 0.889-0.995) models were higher than those of the qualitative (based on tumour location: 0.782; 95% CI 0.665-0.899) and conventional CT quantitative (based on normalized conventional CT attenuation in the arterial phase: 0.665; 95% CI 0.533-0.797; all P < 0.05) models. The DECT quantitative and comprehensive models had comparable performances (P = 0.076). CONCLUSIONS Higher nICs in the arterial and portal venous phases were associated with higher blood supply improving the identification of non-hypervascular PNENs.
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Affiliation(s)
- Xuefang Hu
- Department of Radiology, The First Affiliated Hospital, Sun Yat-Sen University, 58 Zhongshan Road 2, Guangzhou, 510080, Guangdong, China
- Department of Radiology, Huazhong University of Science and Technology Union Shenzhen Hospital, Shenzhen, 518000, Guangdong, China
| | - Siya Shi
- Department of Radiology, The First Affiliated Hospital, Sun Yat-Sen University, 58 Zhongshan Road 2, Guangzhou, 510080, Guangdong, China
| | - Yangdi Wang
- Department of Radiology, The First Affiliated Hospital, Sun Yat-Sen University, 58 Zhongshan Road 2, Guangzhou, 510080, Guangdong, China
| | - Jiaxin Yuan
- Department of Radiology, The First Affiliated Hospital, Sun Yat-Sen University, 58 Zhongshan Road 2, Guangzhou, 510080, Guangdong, China
| | - Mingjie Chen
- Department of Radiology, The First Affiliated Hospital, Sun Yat-Sen University, 58 Zhongshan Road 2, Guangzhou, 510080, Guangdong, China
| | - Luyong Wei
- Department of Radiology, The First Affiliated Hospital, Sun Yat-Sen University, 58 Zhongshan Road 2, Guangzhou, 510080, Guangdong, China
| | - Weiwei Deng
- Clinical and Technical Support, Philips Healthcare China, Shanghai, 200072, China
| | - Shi-Ting Feng
- Department of Radiology, The First Affiliated Hospital, Sun Yat-Sen University, 58 Zhongshan Road 2, Guangzhou, 510080, Guangdong, China
| | - Zhenpeng Peng
- Department of Radiology, The First Affiliated Hospital, Sun Yat-Sen University, 58 Zhongshan Road 2, Guangzhou, 510080, Guangdong, China.
| | - Yanji Luo
- Department of Radiology, The First Affiliated Hospital, Sun Yat-Sen University, 58 Zhongshan Road 2, Guangzhou, 510080, Guangdong, China.
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11
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Kim DH, Kim B, Chung DJ, Kim KA, Lee SL, Choi MH, Kim H, Rha SE. Predicting resection margin status of pancreatic neuroendocrine tumors on CT: performance of NCCN resectability criteria. Br J Radiol 2023; 96:20230503. [PMID: 37750830 PMCID: PMC10646654 DOI: 10.1259/bjr.20230503] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2023] [Revised: 07/18/2023] [Accepted: 08/21/2023] [Indexed: 09/27/2023] Open
Abstract
OBJECTIVE To test the performance of the National Comprehensive Cancer Network (NCCN) CT resectability criteria for predicting the surgical margin status of pancreatic neuroendocrine tumor (PNET) and to identify factors associated with margin-positive resection. METHODS Eighty patients with pre-operative CT and upfront surgery were retrospectively enrolled. Two radiologists assessed the CT resectability (resectable [R], borderline resectable [BR], unresectable [UR]) of the PNET according to NCCN criteria. Logistic regression was used to identify factors associated with resection margin status. κ statistics were used to evaluate interreader agreements. Kaplan-Meier method with log-rank test was used to estimate and compare recurrence-free survival (RFS). RESULTS Forty-five patients (56.2%) received R0 resection and 35 (43.8%) received R1 or R2 resection. R0 resection rates were 63.6-64.2%, 20.0-33.3%, and 0% for R, BR, and UR diseases, respectively (all p ≤ 0.002), with a good interreader agreement (κ, 0.74). Tumor size (<2 cm, 2-4 cm, and >4 cm; odds ratio (OR), 9.042-18.110; all p ≤ 0.007) and NCCN BR/UR diseases (OR, 5.918; p = 0.032) were predictors for R1 or R2 resection. The R0 resection rate was 91.7% for R disease <2 cm and decreased for larger R disease. R0 resection and smaller tumor size in R disease improved RFS. CONCLUSION NCCN resectability criteria can stratify patients with PNET into distinct groups of R0 resectability. Adding tumor size to R disease substantially improves the prediction of R0 resection, especially for PNETs <2 cm. ADVANCES IN KNOWLEDGE Tumor size and radiologic resectability independently predicted margin status of PNETs.
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Affiliation(s)
- Dong Hwan Kim
- Department of Radiology, Seoul St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | - Bohyun Kim
- Department of Radiology, Seoul St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | - Dong Jin Chung
- Department of Radiology, Yeouido St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | - Kyung Ah Kim
- Department of Radiology, St. Vincent’s Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | - Su Lim Lee
- Department of Radiology, Uijeongbu St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | - Moon Hyung Choi
- Department of Radiology, Eunpyeong St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | - Hokun Kim
- Department of Radiology, Seoul St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | - Sung Eun Rha
- Department of Radiology, Seoul St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
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12
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Juchems M, Kläsner B. [Neuroendocrine tumors of the pancreas]. RADIOLOGIE (HEIDELBERG, GERMANY) 2023; 63:894-899. [PMID: 37947864 DOI: 10.1007/s00117-023-01231-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 10/13/2023] [Indexed: 11/12/2023]
Abstract
CLINICAL/METHODOLOGICAL ISSUE Neuroendocrine tumors (NET) of the pancreas fall into the group of gastroenteropancreatic neuroendocrine neoplasms (GEP-NEN). The assignment of imaging morphological criteria to this heterogeneous group of complex tumors is often difficult. STANDARD RADIOLOGICAL METHODS Diagnostic ultrasound, computed tomography (CT), magnetic resonance imaging (MRI) and positron emission tomography-CT (PET/CT) are available for the detection of pancreatic NET (also referred to as NEN) and for the diagnosis of spread and the search for metastases. METHODOLOGICAL INNOVATIONS In particular, nuclear medicine examination methods with somatostatin analogues are of high value, since they make tumors visible with high sensitivity via radioactively labeled receptor ligands. PERFORMANCE CT and MRI have high detection rates of pancreatic NET. Further developments, such as diffusion imaging, have further improved these traditional cross-sectional imaging diagnostics. However, nuclear medicine methods are an important component in detection and are superior to CT and MRI. ACHIEVEMENTS It is important for the radiologist to be familiar with NET of the pancreas, as it is an important differential diagnosis-also with regard to prognosis-of other pancreatic lesions. PRACTICAL RECOMMENDATIONS Because NET are often hypervascularized, a biphasic examination technique after contrast administration is mandatory for cross-sectional imaging. PET/CT with somatostatin analogues should be performed for further diagnosis.
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Affiliation(s)
- Markus Juchems
- Zentrum für Diagnostische und Interventionelle Radiologie im GLKN, Klinikum Konstanz, 78464, Konstanz, Deutschland.
| | - Benjamin Kläsner
- Klinik für Nuklearmedizin, Klinikum Konstanz, Konstanz, Deutschland
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13
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Vogele D, Schmidt SA, Gnutzmann D, Thaiss WM, Ettrich TJ, Kornmann M, Beer M, Juchems MS. Gastroenteropancreatic Neuroendocrine Tumors-Current Status and Advances in Diagnostic Imaging. Diagnostics (Basel) 2023; 13:2741. [PMID: 37685279 PMCID: PMC10486652 DOI: 10.3390/diagnostics13172741] [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: 07/17/2023] [Revised: 08/16/2023] [Accepted: 08/21/2023] [Indexed: 09/10/2023] Open
Abstract
Gastroenteropancreatic neuroendocrine neoplasia (GEP-NEN) is a heterogeneous and complex group of tumors that are often difficult to classify due to their heterogeneity and varying locations. As standard radiological methods, ultrasound, computed tomography (CT), magnetic resonance imaging (MRI), and positron emission tomography-computed tomography (PET/CT) are available for both localization and staging of NEN. Nuclear medical imaging methods with somatostatin analogs are of great importance since radioactively labeled receptor ligands make tumors visible with high sensitivity. CT and MRI have high detection rates for GEP-NEN and have been further improved by developments such as diffusion-weighted imaging. However, nuclear medical imaging methods are superior in detection, especially in gastrointestinal NEN. It is important for radiologists to be familiar with NEN, as it can occur ubiquitously in the abdomen and should be identified as such. Since GEP-NEN is predominantly hypervascularized, a biphasic examination technique is mandatory for contrast-enhanced cross-sectional imaging. PET/CT with somatostatin analogs should be used as the subsequent method.
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Affiliation(s)
- Daniel Vogele
- Department of Diagnostic and Interventional Radiology, Ulm University Medical Center, Albert-Einstein-Allee 23, 89081 Ulm, Germany; (S.A.S.); (W.M.T.); (M.B.)
| | - Stefan A. Schmidt
- Department of Diagnostic and Interventional Radiology, Ulm University Medical Center, Albert-Einstein-Allee 23, 89081 Ulm, Germany; (S.A.S.); (W.M.T.); (M.B.)
| | - Daniel Gnutzmann
- Department of Diagnostic and Interventional Radiology, Konstanz Hospital, Mainaustraße 35, 78464 Konstanz, Germany; (D.G.); (M.S.J.)
| | - Wolfgang M. Thaiss
- Department of Diagnostic and Interventional Radiology, Ulm University Medical Center, Albert-Einstein-Allee 23, 89081 Ulm, Germany; (S.A.S.); (W.M.T.); (M.B.)
- Department of Nuclear Medicine, Ulm University Medical Center, Albert-Einstein-Allee 23, 89081 Ulm, Germany
| | - Thomas J. Ettrich
- Department of Internal Medicine I, Ulm University Medical Center, Albert-Einstein-Allee 23, 89081 Ulm, Germany;
- i2SouI—Innovative Imaging in Surgical Oncology Ulm, University Hospital of Ulm, Albert-Einstein-Allee 23, 89081 Ulm, Germany;
| | - Marko Kornmann
- i2SouI—Innovative Imaging in Surgical Oncology Ulm, University Hospital of Ulm, Albert-Einstein-Allee 23, 89081 Ulm, Germany;
- Department of General and Visceral Surgery, Ulm University Medical Center, Albert-Einstein-Allee 23, 89081 Ulm, Germany
| | - Meinrad Beer
- Department of Diagnostic and Interventional Radiology, Ulm University Medical Center, Albert-Einstein-Allee 23, 89081 Ulm, Germany; (S.A.S.); (W.M.T.); (M.B.)
- i2SouI—Innovative Imaging in Surgical Oncology Ulm, University Hospital of Ulm, Albert-Einstein-Allee 23, 89081 Ulm, Germany;
| | - Markus S. Juchems
- Department of Diagnostic and Interventional Radiology, Konstanz Hospital, Mainaustraße 35, 78464 Konstanz, Germany; (D.G.); (M.S.J.)
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14
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Lin X, Wang M, Li F, Xu Z, Chen J, Chen X, Yuan C, Wu S, Luo Y, Shen J, Feng ST, Huang B. Improving Tumor Classification by Reusing Self-predicted Segmentation of Medical Images as Guiding Knowledge. IEEE J Biomed Health Inform 2023; PP:122-133. [PMID: 37410638 DOI: 10.1109/jbhi.2023.3293009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/08/2023]
Abstract
Differential diagnosis of tumors is important for computer-aided diagnosis. In computer-aided diagnosis systems, expert knowledge of lesion segmentation masks is limited as it is only used during preprocessing or as supervision to guide feature extraction. To improve the utilization of lesion segmentation masks, this study proposes a simple and effective multitask learning network that improves medical image classification using self-predicted segmentation as guiding knowledge; we call this network RS 2-net. In RS 2-net, the predicted segmentation probability map obtained from the initial segmentation inference is added to the original image to form a new input, which is then reinput to the network for the final classification inference. We validated the proposed RS 2-net using three datasets: the pNENs-Grade dataset, which tested the prediction of pancreatic neuroendocrine neoplasm grading, and the HCC-MVI dataset, which tested the prediction of microvascular invasion of hepatocellular carcinoma, and ISIC 2017 public skin lesion dataset. The experimental results indicate that the proposed strategy of reusing self-predicted segmentation is effective, and RS 2-net outperforms other popular networks and existing state-of-the-art studies. Interpretive analytics based on feature visualization demonstrates that the improved classification performance of our reuse strategy is due to the semantic information that can be acquired in advance in a shallow network.
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15
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Sulciner ML, Clancy TE. Surgical Management of Pancreatic Neuroendocrine Tumors. Cancers (Basel) 2023; 15:2006. [PMID: 37046665 PMCID: PMC10093271 DOI: 10.3390/cancers15072006] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2023] [Revised: 03/23/2023] [Accepted: 03/24/2023] [Indexed: 03/30/2023] Open
Abstract
Pancreatic neuroendocrine tumors (PNETs) are relatively uncommon malignancies, characterized as either functional or nonfunctional secondary to their secretion of biologically active hormones. A wide range of clinical behavior can be seen, with the primary prognostic indicator being tumor grade as defined by the Ki67 proliferation index and mitotic index. Surgery is the primary treatment modality for PNETs. While functional PNETs should undergo resection for symptom control as well as potential curative intent, nonfunctional PNETs are increasingly managed nonoperatively. There is increasing data to suggest small, nonfunctional PNETs (less than 2 cm) are appropriate follow with nonoperative active surveillance. Evidence supports surgical management of metastatic disease if possible, and occasionally even surgical management of the primary tumor in the setting of widespread metastases. In this review, we highlight the evolving surgical management of local and metastatic PNETs.
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Affiliation(s)
| | - Thomas E. Clancy
- Division of Surgical Oncology, Department of Surgery, Brigham and Women’s Hospital, Boston, MA 02115, USA
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16
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Gu XL, Cui Y, Zhu HT, Li XT, Pei X, He XX, Yang L, Lu M, Li ZW, Sun YS. Discrimination of Liver Metastases of Digestive System Neuroendocrine Tumors From Neuroendocrine Carcinoma by Computed Tomography-Based Radiomics Analysis. J Comput Assist Tomogr 2023; 47:361-368. [PMID: 36944109 DOI: 10.1097/rct.0000000000001443] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/23/2023]
Abstract
OBJECTIVE The aim of the study is to investigate the value of computed tomography (CT) radiomics features to discriminate the liver metastases (LMs) of digestive system neuroendocrine tumors (NETs) from neuroendocrine carcinoma (NECs). METHODS Ninety-nine patients with LMs of digestive system neuroendocrine neoplasms from 2 institutions were included. Radiomics features were extracted from the portal venous phase CT images by the Pyradiomics and then selected by using the t test, Pearson correlation analysis, and least absolute shrinkage and selection operator method. The radiomics score (Rad score) for each patient was constructed by linear combination of the selected radiomics features. The radiological model was constructed by radiological features using the multivariable logistic regression. Then, the combined model was constructed by combining Rad score and the radiological model into logistic regression. The performance of all models was evaluated by the receiver operating characteristic curves with the area under curve (AUC). RESULTS In the radiological model, only the enhancement degree (odds ratio, 8.299; 95% confidence interval, 2.070-32.703; P = 0.003) was an independent predictor for discriminating the LMs of digestive system NETs from those of NECs. The combined model constructed by the Rad score in combination with the enhancement degree showed good discrimination performance, with AUCs of 0.893, 0.841, and 0.740 in the training, testing, and external validation groups, respectively. In addition, it performed better than radiological model in the training and testing groups (AUC, 0.893 vs 0.726; AUC, 0.841 vs 0.621). CONCLUSIONS The CT radiomics might be useful for discrimination LMs of digestive system NECs from NETs.
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Affiliation(s)
- Xiao-Lei Gu
- From the Department of Radiology, Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Peking University Cancer Hospital and Institute
| | - Yong Cui
- From the Department of Radiology, Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Peking University Cancer Hospital and Institute
| | - Hai-Tao Zhu
- From the Department of Radiology, Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Peking University Cancer Hospital and Institute
| | - Xiao-Ting Li
- From the Department of Radiology, Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Peking University Cancer Hospital and Institute
| | - Xiang Pei
- Department of Radiology, Beijing Shunyi District Hospital, Beijing
| | - Xiao-Xiao He
- Department of Radiology, The Fourth Hospital of Hebei Medical University, Shijiazhuang
| | - Li Yang
- Department of Radiology, The Fourth Hospital of Hebei Medical University, Shijiazhuang
| | - Ming Lu
- Departments of Gastrointestinal Oncology and
| | - Zhong-Wu Li
- Pathology, Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Peking University Cancer Hospital and Institute, Beijing, China
| | - Ying-Shi Sun
- From the Department of Radiology, Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Peking University Cancer Hospital and Institute
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17
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Yuan J, Wang Y, Hu X, Shi S, Zhang N, Wang L, Deng W, Feng ST, Peng Z, Luo Y. Use of dual-layer spectral detector computed tomography in the diagnosis of pancreatic neuroendocrine neoplasms. Eur J Radiol 2023; 159:110660. [PMID: 36577182 DOI: 10.1016/j.ejrad.2022.110660] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2022] [Revised: 12/12/2022] [Accepted: 12/14/2022] [Indexed: 12/23/2022]
Abstract
PURPOSE To explore the optimal energy level of dual-layer spectral detector computed tomography (DLCT) images of pancreatic neuroendocrine neoplasms (pNENs) and investigate the value in their detection. METHODS This retrospective analysis included 134 pNEN patients with 136 lesions; they underwent contrast-enhanced DLCT scanning with histopathological confirmation of pNENs. Virtual monoenergetic images (VMI) of 40-100 keV, iodine concentration map (IC map), Z-effective atomic number map (Zeff map), and conventional images were analysed. The optimal energy level was obtained by comparing the signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR). The lesion detection rates of DLCT and conventional images were compared. Subjective image analysis was performed by two readers who assessed the image quality and lesion conspicuity on a 5-point scale. RESULTS The SNR of VMIs from 40 to 80 keV (arterial phase, P < 0.001; venous phase, P < 0.05) and CNR from 40 to 60 keV (arterial and venous phases, each P < 0.05) were higher than that of conventional images; VMI40keV showed the highest SNR and CNR. There was a good inter-reader agreement between the two reviewers (Kappa values > 0.61); the scores of Zeff and IC maps were higher than those of conventional images and VMI40keV (P < 0.05). The detection performance of DLCT images was better than conventional images. CONCLUSIONS The VMI40keV demonstrated the best CNR and SNR of pNENs compared to other VMIs. Zeff and IC maps improve objective image quality and reader preference compared to conventional images. These findings could possess important clinical implications in formulating treatment strategies.
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Affiliation(s)
- Jiaxin Yuan
- Department of Radiology, The First Affiliated Hospital, Sun Yat-Sen University, Guangzhou 510080, Guangdong, China
| | - Yangdi Wang
- Department of Radiology, The First Affiliated Hospital, Sun Yat-Sen University, Guangzhou 510080, Guangdong, China
| | - Xuefang Hu
- Department of Radiology, The First Affiliated Hospital, Sun Yat-Sen University, Guangzhou 510080, Guangdong, China
| | - Siya Shi
- Department of Radiology, The First Affiliated Hospital, Sun Yat-Sen University, Guangzhou 510080, Guangdong, China
| | - Ning Zhang
- Department of Gastroenterology, The First Affiliated Hospital, Sun Yat-Sen University, 58 Zhongshan Road 2, Guangzhou 510080, Guangdong, China
| | - Liqin Wang
- Department of Radiology, The First Affiliated Hospital, Sun Yat-Sen University, Guangzhou 510080, Guangdong, China
| | - Weiwei Deng
- Clinical & Technical Support, Philips Healthcare China, Shanghai 200072, China
| | - Shi-Ting Feng
- Department of Radiology, The First Affiliated Hospital, Sun Yat-Sen University, Guangzhou 510080, Guangdong, China
| | - Zhenpeng Peng
- Department of Radiology, The First Affiliated Hospital, Sun Yat-Sen University, Guangzhou 510080, Guangdong, China
| | - Yanji Luo
- Department of Radiology, The First Affiliated Hospital, Sun Yat-Sen University, Guangzhou 510080, Guangdong, China.
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18
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Marcal LP, Chuang HH, Tran Cao HS, Halperin DM. Pancreatic Neuroendocrine Tumors. ONCOLOGIC IMAGING : A MULTIDISCIPLINARY APPROACH 2023:197-217. [DOI: 10.1016/b978-0-323-69538-1.00014-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/06/2025]
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19
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Galgano SJ, Morani AC, Gopireddy DR, Sharbidre K, Bates DDB, Goenka AH, Arif-Tiwari H, Itani M, Iravani A, Javadi S, Faria S, Lall C, Bergsland E, Verma S, Francis IR, Halperin DM, Chatterjee D, Bhosale P, Yano M. Pancreatic neuroendocrine neoplasms: a 2022 update for radiologists. ABDOMINAL RADIOLOGY (NEW YORK) 2022; 47:3962-3970. [PMID: 35244755 DOI: 10.1007/s00261-022-03466-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/25/2022] [Revised: 02/17/2022] [Accepted: 02/18/2022] [Indexed: 01/18/2023]
Abstract
Pancreatic neuroendocrine neoplasms (PaNENs) are a unique group of pancreatic neoplasms with a wide range of clinical presentations and behaviors. Given their heterogeneous appearance and increasing detection on cross-sectional imaging, it is essential that radiologists understand the variable presentation and distinctions PaNENs display compared to other pancreatic neoplasms. Additionally, some of these neoplasms may be hormonally functional, and it is imperative that radiologists be aware of the common clinical presentations of hormonally active PaNENs. Knowledge of PaNEN pathology and treatments may influence which imaging modality is optimal for each patient. Each imaging modality used for PaNENs has distinct advantages and disadvantages, particularly in different treatment settings. Thus, the focus of this manuscript is to provide an update for the radiologist on PaNEN pathology, imaging, and treatments.
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Affiliation(s)
- Samuel J Galgano
- Department of Radiology, University of Alabama at Birmingham, Birmingham, AL, USA.
| | | | - Dheeraj R Gopireddy
- Department of Radiology, University of Florida-Jacksonville, Jacksonville, FL, USA
| | - Kedar Sharbidre
- Department of Radiology, University of Alabama at Birmingham, Birmingham, AL, USA
| | - David D B Bates
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Ajit H Goenka
- Department of Radiology, Mayo Clinic, Rochester, MN, USA
| | - Hina Arif-Tiwari
- Department of Radiology, University of Arizona-Tuscon, Tuscon, AZ, USA
| | - Malak Itani
- Mallinckrodt Institute of Radiology, Washington University in St. Louis, St. Louis, MO, USA
| | - Amir Iravani
- Mallinckrodt Institute of Radiology, Washington University in St. Louis, St. Louis, MO, USA
| | - Sanaz Javadi
- Department of Radiology, M.D. Anderson Cancer Center, Houston, TX, USA
| | - Silvana Faria
- Department of Radiology, M.D. Anderson Cancer Center, Houston, TX, USA
| | - Chandana Lall
- Department of Radiology, University of Florida-Jacksonville, Jacksonville, FL, USA
| | - Emily Bergsland
- Department of Medicine, University of California San Francisco, San Francisco, CA, USA
| | - Sadhna Verma
- Department of Radiology, University of Cincinnati, Cincinnati, OH, USA
| | - Isaac R Francis
- Department of Radiology, Michigan Medicine, Ann Arbor, MI, USA
| | - Daniel M Halperin
- Department of Gastrointestinal Medical Oncology, M.D. Anderson Cancer Center, Houston, TX, USA
| | - Deyali Chatterjee
- Department of Pathology, M.D. Anderson Cancer Center, Houston, TX, USA
| | - Priya Bhosale
- Department of Radiology, M.D. Anderson Cancer Center, Houston, TX, USA
| | - Motoyo Yano
- Department of Radiology, Mayo Clinic Arizona, Scottsdale, AZ, USA
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20
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Prosperi D, Gentiloni Silveri G, Panzuto F, Faggiano A, Russo VM, Caruso D, Polici M, Lauri C, Filice A, Laghi A, Signore A. Nuclear Medicine and Radiological Imaging of Pancreatic Neuroendocrine Neoplasms: A Multidisciplinary Update. J Clin Med 2022; 11:jcm11226836. [PMID: 36431313 PMCID: PMC9694730 DOI: 10.3390/jcm11226836] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2022] [Revised: 11/14/2022] [Accepted: 11/16/2022] [Indexed: 11/22/2022] Open
Abstract
Pancreatic neuroendocrine neoplasms (panNENs) are part of a large family of tumors arising from the neuroendocrine system. PanNENs show low-intermediate tumor grade and generally high somatostatin receptor (SSTR) expression. Therefore, panNENs benefit from functional imaging with 68Ga-somatostatin analogues (SSA) for diagnosis, staging, and treatment choice in parallel with morphological imaging. This narrative review aims to present conventional imaging techniques and new perspectives in the management of panNENs, providing the clinicians with useful insight for clinical practice. The 68Ga-SSA PET/CT is the most widely used in panNENs, not only fr diagnosis and staging purpose but also to characterize the biology of the tumor and its responsiveness to SSAs. On the contrary, the 18F-Fluordeoxiglucose (FDG) PET/CT is not employed systematically in all panNEN patients, being generally preferred in G2-G3, to predict aggressiveness and progression rate. The combination of 68Ga-SSA PET/CT and 18F-FDG PET/CT can finally suggest the best therapeutic strategy. Other radiopharmaceuticals are 68Ga-exendin-4 in case of insulinomas and 18F-dopamine (DOPA), which can be helpful in SSTR-negative tumors. New promising but still-under-investigation radiopharmaceuticals include radiolabeled SSTR antagonists and 18F-SSAs. Conventional imaging includes contrast enhanced CT and multiparametric MRI. There are now enriched by radiomics, a new non-invasive imaging approach, very promising to early predict tumor response or progression.
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Affiliation(s)
- Daniela Prosperi
- Nuclear Medicine Unit, Department of Medical-Surgical Sciences and of Translational Medicine, Sant’Andrea University Hospital, Sapienza University of Rome, 00189 Roma, Italy
| | - Guido Gentiloni Silveri
- Nuclear Medicine Unit, Department of Medical-Surgical Sciences and of Translational Medicine, Sant’Andrea University Hospital, Sapienza University of Rome, 00189 Roma, Italy
| | - Francesco Panzuto
- Digestive Disease Unit, Department of Medical-Surgical Sciences and Translational Medicine, Sant’Andrea University Hospital, ENETS Center of Excellence, Sapienza University of Rome, 00189 Roma, Italy
| | - Antongiulio Faggiano
- Endocrinology Unit, Department of Clinical and Molecular Medicine, Sant’Andrea University Hospital, ENETS Center of Excellence, Sapienza University of Rome, 00189 Roma, Italy
| | - Vincenzo Marcello Russo
- Nuclear Medicine Unit, Department of Medical-Surgical Sciences and of Translational Medicine, Sant’Andrea University Hospital, Sapienza University of Rome, 00189 Roma, Italy
| | - Damiano Caruso
- Radiology Unit, Department of Medical Surgical Sciences and Translational Medicine, Sant’Andrea University Hospital, Sapienza University of Rome, 00189 Roma, Italy
| | - Michela Polici
- Radiology Unit, Department of Medical Surgical Sciences and Translational Medicine, Sant’Andrea University Hospital, Sapienza University of Rome, 00189 Roma, Italy
| | - Chiara Lauri
- Nuclear Medicine Unit, Department of Medical-Surgical Sciences and of Translational Medicine, Sant’Andrea University Hospital, Sapienza University of Rome, 00189 Roma, Italy
- Correspondence:
| | - Angelina Filice
- Nucler Medicine Unit, AUSL-IRCCS di Reggio Emilia, 42123 Reggio Emilia, Italy
| | - Andrea Laghi
- Radiology Unit, Department of Medical Surgical Sciences and Translational Medicine, Sant’Andrea University Hospital, Sapienza University of Rome, 00189 Roma, Italy
| | - Alberto Signore
- Nuclear Medicine Unit, Department of Medical-Surgical Sciences and of Translational Medicine, Sant’Andrea University Hospital, Sapienza University of Rome, 00189 Roma, Italy
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21
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Saleh M, Bhosale PR, Yano M, Itani M, Elsayes AK, Halperin D, Bergsland EK, Morani AC. New frontiers in imaging including radiomics updates for pancreatic neuroendocrine neoplasms. Abdom Radiol (NY) 2022; 47:3078-3100. [PMID: 33095312 DOI: 10.1007/s00261-020-02833-8] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2020] [Revised: 10/07/2020] [Accepted: 10/12/2020] [Indexed: 01/18/2023]
Abstract
OBJECTIVE To illustrate the applications of various imaging tools including conventional MDCT, MRI including DWI, CT & MRI radiomics, FDG & DOTATATE PET-CT for diagnosis, staging, grading, prognostication, treatment planning and assessing treatment response in cases of pancreatic neuroendocrine neoplasms (PNENs). BACKGROUND Gastroenteropancreatic neuroendocrine neoplasms (GEP NENs) are very diverse clinically & biologically. Their treatment and prognosis depend on staging and primary site, as well as histological grading, the importance of which is also reflected in the recently updated WHO classification of GEP NENs. Grade 3 poorly differentiated neuroendocrine carcinomas (NECs) are aggressive & nearly always advanced at diagnosis with poor prognosis; whereas Grades-1 and 2 well-differentiated neuroendocrine tumors (NETs) can be quite indolent. Grade 3 well-differentiated NETs represent a new category of neoplasm with an intermediate prognosis. Importantly, the evidence suggest grade heterogeneity can occur within a given tumor and even grade progression can occur over time. Emerging evidence suggests that several non-invasive qualitative and quantitative imaging features on CT, dual-energy CT (DECT), MRI, PET and somatostatin receptor imaging with new tracers, as well as texture analysis, may be useful to grade, prognosticate, and accurately stage primary NENs. Imaging features may also help to inform choice of treatment and follow these neoplasms post-treatment. CONCLUSION GEP NENs treatment and prognosis depend on the stage as well as histological grade of the tumor. Traditional ways of imaging evaluation for diagnosis and staging does not yet yield sufficient information to replace operative and histological evaluation. Recognition of important qualitative imaging features together with quantitative features and advanced imaging tools including functional imaging with DWI MRI, DOTATATE PET/CT, texture analysis with radiomics and radiogenomic features appear promising for more accurate staging, tumor risk stratification, guiding management and assessing treatment response.
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Affiliation(s)
- Mohammed Saleh
- Department of Radiology, The University of Texas MD Anderson Cancer Center, 1515 Holocombe Blvd, Houston, TX, 77030, USA
| | - Priya R Bhosale
- Department of Radiology, The University of Texas MD Anderson Cancer Center, 1515 Holocombe Blvd, Houston, TX, 77030, USA
| | - Motoyo Yano
- Department of Radiology, Mayo Clinic Hospital, Phoenix, AZ, 77030, USA
| | - Malak Itani
- Mallinckrodt Institute of Radiology, Washington University School of Medicine in St. Louis, St. Louis, MO, USA
| | - Ahmed K Elsayes
- Department of Radiology, The University of Texas MD Anderson Cancer Center, 1515 Holocombe Blvd, Houston, TX, 77030, USA
| | - Daniel Halperin
- GI Medical Oncology, The University of Texas MD Anderson Cancer Center, 1515 Holocombe Blvd, Houston, TX, 77030, USA
| | - Emily K Bergsland
- University of California San Francisco, San Francisco, CA, 94143, USA
| | - Ajaykumar C Morani
- Department of Radiology, The University of Texas MD Anderson Cancer Center, 1515 Holocombe Blvd, Houston, TX, 77030, USA.
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22
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La Salvia A, Persano I, Parlagreco E, Audisio A, Cani M, Brizzi MP. Pancreatic adenocarcinoma and pancreatic high-grade neuroendocrine carcinoma: two sides of the moon. Med Oncol 2022; 39:168. [PMID: 35972607 DOI: 10.1007/s12032-022-01764-2] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2022] [Accepted: 06/09/2022] [Indexed: 06/15/2023]
Abstract
Pancreatic adenocarcinoma is the seventh leading cause of cancer death in the world and the most common type pf pancreatic cancer. Unfortunately, less than 20% of patients are surgically resectable and the great majority of cases are treated with palliative chemotherapy with unsatisfactory results. No targeted agents or personalized approaches have been validated in the last decades. On the other side, neuroendocrine neoplasms of the pancreas are generally considered indolent tumours. However, high-grade neuroendocrine carcinoma is a rare subtype of neuroendocrine neoplasm of the pancreas (accounting up to 10% of the neuroendocrine neoplasms of the pancreas), with particularly aggressive behaviour and poor prognosis. Even in this case, the treatment is represented by palliative chemotherapy with dismal results and no personalized therapies are available, so far. Notably, the quality of life of these patients is disappointingly low and the future perspectives of more personalized diagnostic and therapeutic strategies are scarce. In this review, we discuss relevant and current information on epidemiology, pathology, diagnosis, clinical presentation, treatment and ongoing clinical trials of these two entities, in order to illustrate the two sides of the moon.
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Affiliation(s)
- Anna La Salvia
- Division of Medical Oncology 2, IRCCS Regina Elena National Cancer Institute, Rome, Italy.
| | - Irene Persano
- Department of Oncology, San Luigi Gonzaga Hospital, Orbassano, Italy
| | - Elena Parlagreco
- Department of Oncology, San Luigi Gonzaga Hospital, Orbassano, Italy
| | | | - Massimiliano Cani
- Department of Oncology, San Luigi Gonzaga Hospital, Orbassano, Italy
| | - Maria Pia Brizzi
- Department of Oncology, San Luigi Gonzaga Hospital, Orbassano, Italy
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23
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Wang Y, Huang B, Fu Q, Wang J, Ye M, Hu M, Qu K, Liu K, Hu X, Wei S, Sun K, Xiao W, Zhang B, Li H, Li J, Zhang Q, Liang T. Comprehensive Clinical Analysis of Gallbladder Neuroendocrine Neoplasms: A Large-Volume Multicenter Study During One Decade. Ann Surg Oncol 2022; 29:7619-7630. [PMID: 35849293 DOI: 10.1245/s10434-022-12107-w] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2022] [Accepted: 06/05/2022] [Indexed: 02/06/2023]
Abstract
BACKGROUND This study aimed to comprehensively investigate the clinicopathologic characteristics and therapeutic situations of gallbladder neuroendocrine neoplasms (GB-NENs) in the real world via a multicenter, large-scale cohort study. METHODS The study searched for patients in 143 hospitals in China and enrolled 154 patients with GB-NENs diagnosed in 40 hospitals between 2004 and 2021. Clinicopathologic characteristics and therapeutic approaches were analyzed retrospectively. RESULTS The median age at the initial diagnosis of the patients with GB-NENs was 63 years (range 33-83 years), and 61.7% of the patients were women. Tumor-node-metastasis staging classified 92 patients as stage 3 or above. Based on the 2019 World Health Organization classification, 96 cases (62.3%) were confirmed pathologically as poorly differentiated neuroendocrine carcinomas, 13 cases (8.4%) as well-differentiated neuroendocrine tumors, and 45 cases as mixed neuroendocrine-non-neuroendocrine neoplasms. The liver was the most frequent metastatic site. Immunohistochemistry showed that synaptophysin was most frequently positive (80.4%), followed by chromogranin A (61.7%), and CD56 (58.4%). Computed tomography and magnetic resonance imaging showed more common clear boundaries (25/39 cases) and invasive growth features (27 cases). None of these cases had an accurate diagnosis before surgery, with a misdiagnosis rate of 100%. Surgical resection is the main treatment, and platinum-based chemotherapeutic regimens were preferred as adjuvant therapies for patients with GB-NENs. The available survival data for 74 patients showed an overall survival rate of 59% at 1 year, 33% at 3 years, and 29% at 5 years. No significant difference was found between the patients treated with and those treated without adjuvant chemotherapy. CONCLUSIONS Gallbladder neuroendocrine neoplasms have high malignancy and a poor prognosis. Importantly, this large-scale cohort study significantly improves our understanding of GB-NENs and will benefit the exploration of its mechanism and treatment modes. Further investigation is necessary to explore the management of this disease.
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Affiliation(s)
- Yangyang Wang
- Department of Hepatobiliary and Pancreatic Surgery, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.,Zhejiang Provincial Key Laboratory of Pancreatic Disease, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Bingfeng Huang
- Department of Hepatobiliary and Pancreatic Surgery, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Qihan Fu
- Zhejiang Clinical Research Center of Hepatobiliary and Pancreatic Diseases, Hangzhou, China.,Zhejiang University Cancer Center, Hangzhou, China.,Department of Medical Oncology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Jianing Wang
- Department of Hepatobiliary and Pancreatic Surgery, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.,Zhejiang Provincial Key Laboratory of Pancreatic Disease, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Mao Ye
- Department of Hepatobiliary and Pancreatic Surgery, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.,Zhejiang Provincial Key Laboratory of Pancreatic Disease, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Manyi Hu
- Department of Hepatobiliary and Pancreatic Surgery, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Kai Qu
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Kai Liu
- Department of Hepatobiliary and Pancreatic Surgery, The First Hospital of Jilin University, Changchun, China
| | - Xiao Hu
- Department of Hepatobiliary Pancreatic Surgery, The Affiliated Hospital of Qingdao University, Qingdao, China
| | - Shumei Wei
- Department of Pathology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Ke Sun
- Department of Pathology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Wenbo Xiao
- Department of Radiology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Bo Zhang
- Department of General Surgery, Shenzhen University Luohu People's Hospital, Shenzhen, China
| | - Haijun Li
- Department of General Surgery, Shenzhen University Luohu People's Hospital, Shenzhen, China
| | - Jingsong Li
- The Engineering Research Center of EMR and Intelligent Expert System, Ministry of Education, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, China.,Research Center for Healthcare Data Science, Zhejiang Lab, Hangzhou, China
| | - Qi Zhang
- Department of Hepatobiliary and Pancreatic Surgery, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China. .,Zhejiang Provincial Key Laboratory of Pancreatic Disease, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China. .,Zhejiang Clinical Research Center of Hepatobiliary and Pancreatic Diseases, Hangzhou, China. .,Zhejiang University Cancer Center, Hangzhou, China.
| | - Tingbo Liang
- Department of Hepatobiliary and Pancreatic Surgery, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China. .,Zhejiang Provincial Key Laboratory of Pancreatic Disease, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China. .,Zhejiang Clinical Research Center of Hepatobiliary and Pancreatic Diseases, Hangzhou, China. .,Zhejiang University Cancer Center, Hangzhou, China.
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24
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Chen HY, Pan Y, Chen JY, Liu LL, Yang YB, Li K, Yu RS, Shao GL. Quantitative analysis of enhanced CT in differentiating well-differentiated pancreatic neuroendocrine tumors and poorly differentiated neuroendocrine carcinomas. Eur Radiol 2022; 32:8317-8325. [PMID: 35759016 DOI: 10.1007/s00330-022-08891-4] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2022] [Revised: 05/02/2022] [Accepted: 05/18/2022] [Indexed: 11/29/2022]
Abstract
OBJECTIVE To identify quantitative CT features for distinguishing well-differentiated pancreatic neuroendocrine tumors (PNETs) from poorly differentiated pancreatic neuroendocrine carcinomas (PNECs). MATERIALS AND METHODS Seventeen patients with PNECs and 131 patients with PNETs confirmed by biopsy or surgery were retrospectively included. General demographic (sex, age) and CT quantitative parameters (arterial/portal absolute enhancement, arterial/portal relative enhancement ratio, arterial/portal enhancement ratio) were collected. Univariate and multivariate logistic regression analyses were performed to confirm independent variables for differentiating PNECs from PNETs. Receiver operating characteristic (ROC) curves for each quantitative parameter were generated to determine their diagnostic ability. RESULTS PNECs had a much lower mean arterial/portal absolute enhancement value (19.5 ± 11.0 vs. 78.8 ± 47.2; 28.1 ± 15.8 vs. 77.0 ± 39.4), arterial/portal relative enhancement ratio (0.57 ± 0.36 vs. 2.03 ± 1.31; 0.80 ± 0.52 vs. 1.99 ± 1.13), and arterial/portal enhancement ratio (0.62 ± 0.27 vs. 1.22 ± 0.49; 0.74 ± 0.19 vs. 1.21 ± 0.36) than PNETs (all p < 0.001). After multivariable analysis, arterial absolute enhancement (odds ratio [OR]: 0.96, 95% confidence interval [CI]: 0.93, 0.99) and portal absolute enhancement (OR: 0.96, 95% CI: 0.92, 0.99) were independent factors for differentiating PNECs from PNETs. For each quantitative parameter, arterial lesion enhancement yielded the highest diagnostic performance, with an area under the curve (AUC) of 0.922 (95% CI: 0.867-0.960), followed by portal absolute enhancement. CONCLUSIONS Arterial/portal absolute enhancements were independent predictors with good diagnostic accuracy for differentiating between PNETs and PNECs. Quantitative parameters of enhanced CT can distinguish PNECs from PNETs. KEY POINTS • PNECs were hypovascular and had a much lower enhanced CT attenuation in both arterial and portal phases than well-differentiated PNETs. • Quantitative parameters derived from enhanced CT can be used to distinguish PNECs from PNETs. • Arterial absolute enhancement and portal absolute enhancement were independent predictive factors for differentiating between PNETs and PNECs.
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Affiliation(s)
- Hai-Yan Chen
- Department of Radiology, Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), Hangzhou, 310022, China.,Institue of Cancer and Basic Medicine (ICBM), Chinese Academy of Sciences, Hangzhou, 310018, China
| | - Yao Pan
- Department of Radiology, Second Affiliated Hospital, Zhejiang University School of Medicine, Jiefang Road 88#, Hangzhou, 310009, China
| | - Jie-Yu Chen
- Department of Radiology, Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), Hangzhou, 310022, China.,Institue of Cancer and Basic Medicine (ICBM), Chinese Academy of Sciences, Hangzhou, 310018, China
| | - Lu-Lu Liu
- Department of Radiology, Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), Hangzhou, 310022, China.,Institue of Cancer and Basic Medicine (ICBM), Chinese Academy of Sciences, Hangzhou, 310018, China
| | - Yong-Bo Yang
- Department of Radiology, Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), Hangzhou, 310022, China.,Institue of Cancer and Basic Medicine (ICBM), Chinese Academy of Sciences, Hangzhou, 310018, China
| | - Kai Li
- Department of Radiology, Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), Hangzhou, 310022, China.,Institue of Cancer and Basic Medicine (ICBM), Chinese Academy of Sciences, Hangzhou, 310018, China
| | - Ri-Sheng Yu
- Department of Radiology, Second Affiliated Hospital, Zhejiang University School of Medicine, Jiefang Road 88#, Hangzhou, 310009, China.
| | - Guo-Liang Shao
- Institue of Cancer and Basic Medicine (ICBM), Chinese Academy of Sciences, Hangzhou, 310018, China. .,Department of Interventional Radiology, Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), Hangzhou, 310022, China. .,Clinical Research Center of Hepatobiliary and Pancreatic Diseases of Zhejiang Province, Qingchun Road 79#, Hangzhou, 310006, China.
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25
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Zeng P, Ma L, Liu J, Song Z, Liu J, Yuan H. The diagnostic value of intravoxel incoherent motion diffusion-weighted imaging for distinguishing nonhypervascular pancreatic neuroendocrine tumors from pancreatic ductal adenocarcinomas. Eur J Radiol 2022; 150:110261. [PMID: 35316674 DOI: 10.1016/j.ejrad.2022.110261] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2021] [Revised: 02/19/2022] [Accepted: 03/14/2022] [Indexed: 12/12/2022]
Abstract
PURPOSE To primarily evaluate the diagnostic performance of the monoexponential and intravoxel incoherent motion (IVIM) diffusion weighted imaging (DWI) models for differentiating between nonhypervascular pancreatic neuroendocrine tumors (PNETs) and pancreatic ductal adenocarcinomas (PDACs). METHODS 63 patients with PNETs (35 nonhypervascular PNETs and 28 hypervascular PNETs) and 164 patients with PDACs were retrospectively enrolled in the study and underwent multiple b-value DWI. Intraobserver and interobserver reliabilities of DWI parameters were assessed by using the intraclass correlation coefficient (ICC). The parameters of apparent diffusion coefficient (ADC), true diffusion coefficient (D), pseudo-diffusion coefficient (D*), and perfusion fraction (f) of nonhypervascular PNETs were compared with PDACs and hypervascular PNETs using the independent sample t test or the Mann-Whitney U test. The diagnostic performance was evaluated using receiver operating characteristic (ROC) analysis. RESULTS All DWI parameters values showed good to excellent intra- and interobserver agreements (ICC = 0.743-0.873). Nonhypervascular PNETs had significantly lower ADC and D, but significantly higher f than PDACs (P = 0.005, P < 0.001 and P < 0.001, respectively). ADC, D and f of nonhypervascular PNETs were lower than hypervascular PNETs (P = 0.001, <0.001 and 0.093, respectively). D* of nonhypervascular PNETs showed no statistically significant differences with PDACs and hypervascular PNETs (P = 0.809 and 0.420). D showed a higher area under the curve (AUC), followed by ADC and f (AUC = 0.885, 0.665 and 0.740, respectively) in differentiating nonhypervascular PNETs from PDACs. CONCLUSION Monoexponential and IVIM diffusion models are valuable to differentiate nonhypervascular PNETs from PDACs. D showed better performance than f and ADC.
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Affiliation(s)
- Piaoe Zeng
- Department of Radiology, Peking University Third Hospital, 49 North Garden Road, Haidian District, Beijing 100191, Beijing, China
| | - Lu Ma
- Department of Radiology, Tsinghua University Hospital, 30 Shuangqing Road, Beijing 100084, Beijing, China
| | - Jianfang Liu
- Department of Radiology, Peking University Third Hospital, 49 North Garden Road, Haidian District, Beijing 100191, Beijing, China
| | - Zixiu Song
- Department of Pathology, Peking University Third Hospital, 49 North Garden Road, Haidian District, Beijing 100191, Beijing, China
| | - Jianyu Liu
- Department of Radiology, Peking University Third Hospital, 49 North Garden Road, Haidian District, Beijing 100191, Beijing, China
| | - Huishu Yuan
- Department of Radiology, Peking University Third Hospital, 49 North Garden Road, Haidian District, Beijing 100191, Beijing, China.
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26
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Han S, Kim JH, Yoo J, Jang S. Prediction of recurrence after surgery based on preoperative MRI features in patients with pancreatic neuroendocrine tumors. Eur Radiol 2021; 32:2506-2517. [PMID: 34647178 DOI: 10.1007/s00330-021-08316-8] [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: 07/16/2021] [Revised: 09/01/2021] [Accepted: 09/04/2021] [Indexed: 10/20/2022]
Abstract
OBJECTIVES To investigate useful MRI features in pancreatic neuroendocrine tumor (PNET) patients for predicting recurrence and its timing after surgery. METHODS A total of 99 patients with PNET who underwent MRI and surgery from 2000 to 2018 were enrolled. Two radiologists independently assessed MRI findings, including size, location, margin, T1 and T2 signal intensity, enhancement patterns, common bile duct (CBD) or main pancreatic duct (MPD) dilatation, vascular invasion, lymph node enlargement, DWI, and ADC value. Imaging findings associated with recurrence and disease-free survival (DFS) were assessed using logistic regression analysis and Cox proportional hazard regression analysis. RESULTS The median follow-up period was 40.4 months, and recurrence after surgery occurred in 12.1% (12/99). Among them, 6 patients experienced recurrence within 1 year, and 9 patients experienced recurrence within 2 years after surgery. In multivariate analysis, major venous invasion (OR 10.76 [1.14-101.85], p = 0.04) was associated with recurrence within 1 year, and portal phase iso- to hypoenhancement (OR 51.89 [1.73-1557.89], p = 0.02), CBD or MPD dilatation (OR 10.49 [1.35-81.64], p = 0.03) and larger size (OR 1.05 [1.00-1.10], p = 0.046) were associated with recurrence within 2 years. The mean DFS was 116.4 ± 18.5 months, and the 5-year DFS rate was 85.7%. In multivariate analysis, portal phase iso- to hypoenhancement (HR 21.36 [2.01-197.77], p = 0.01), ductal dilatation (HR 5.22 [1.46-18.68], p = 0.01), major arterial invasion (HR 42.90 [3.66-502.48], p = 0.003), and larger size (HR 1.04 [1.01-1.06], p = 0.01) showed a significant effect on poor DFS. CONCLUSION MRI features, including size, enhancement pattern, vascular invasion, and ductal dilatation, are useful in predicting recurrence and poor DFS after surgery in PNET. Key Points • MRI features are useful for predicting prognosis in patients with PNET after surgery. • PV or SMV invasion (OR 10.49 [1.35-81.64], p = 0.04) was significantly associated with 1-year recurrence. • Portal phase iso- to hypoenhancement (HR 21.36), CBD or MPD dilatation (HR 5.22), arterial invasion (HR 42.90), and larger size (HR 1.04) had significant effects on poor DFS (p < 0.05).
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Affiliation(s)
- Seungchul Han
- Department of Radiology, Seoul National University Hospital, Seoul, Republic of Korea.,Department of Radiology, Seoul National University College of Medicine, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul, 03080, Republic of Korea
| | - Jung Hoon Kim
- Department of Radiology, Seoul National University Hospital, Seoul, Republic of Korea. .,Department of Radiology, Seoul National University College of Medicine, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul, 03080, Republic of Korea. .,Institute of Radiation Medicine, Seoul National University Medical Research Center, Seoul, Republic of Korea.
| | - Jeongin Yoo
- Department of Radiology, Seoul National University Hospital, Seoul, Republic of Korea.,Department of Radiology, Seoul National University College of Medicine, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul, 03080, Republic of Korea
| | - Siwon Jang
- Department of Radiology, Seoul National University Hospital, Seoul, Republic of Korea.,Department of Radiology, Seoul National University College of Medicine, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul, 03080, Republic of Korea.,Department of Radiology, Seoul National University Boramae Hospital, Seoul, Republic of Korea
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Imaging of Pancreatic Neuroendocrine Neoplasms. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2021; 18:ijerph18178895. [PMID: 34501485 PMCID: PMC8430610 DOI: 10.3390/ijerph18178895] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/07/2021] [Revised: 08/16/2021] [Accepted: 08/22/2021] [Indexed: 12/25/2022]
Abstract
Pancreatic neuroendocrine neoplasms (panNENs) represent the second most common pancreatic tumors. They are a heterogeneous group of neoplasms with varying clinical expression and biological behavior, from indolent to aggressive ones. PanNENs can be functioning or non-functioning in accordance with their ability or not to produce metabolically active hormones. They are histopathologically classified according to the 2017 World Health Organization (WHO) classification system. Although the final diagnosis of neuroendocrine tumor relies on histologic examination of biopsy or surgical specimens, both morphologic and functional imaging are crucial for patient care. Morphologic imaging with ultrasonography (US), computed tomography (CT) and magnetic resonance imaging (MRI) is used for initial evaluation and staging of disease, as well as surveillance and therapy monitoring. Functional imaging techniques with somatostatin receptor scintigraphy (SRS) and positron emission tomography (PET) are used for functional and metabolic assessment that is helpful for therapy management and post-therapeutic re-staging. This article reviews the morphological and functional imaging modalities now available and the imaging features of panNENs. Finally, future imaging challenges, such as radiomics analysis, are illustrated.
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Huang J, Chen J, Xu M, Zheng Y, Lin M, Huang G, Xie X, Xie X. Contrast-Enhanced Ultrasonography Findings Correlate with Pathologic Grades of Pancreatic Neuroendocrine Tumors. ULTRASOUND IN MEDICINE & BIOLOGY 2021; 47:2097-2106. [PMID: 33934943 DOI: 10.1016/j.ultrasmedbio.2021.02.013] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/29/2020] [Revised: 01/22/2021] [Accepted: 02/17/2021] [Indexed: 06/12/2023]
Abstract
The correlation of sonographic findings with pathologic grades of pancreatic neuroendocrine tumors (PNETs) remains unclear. This study aimed to evaluate the usefulness of sonographic features in diagnosing the pathologic grade of PNETs. Conventional and contrast-enhanced ultrasonography findings of PNETs diagnosed by surgical pathology from July 2010 to June 2020 were retrospectively reviewed. Sonographic features were compared among three pathologic grades of PNETs according to the World Health Organization 2010 classification. Ordinal regression models were constructed to evaluate the usefulness of the sonographic features in diagnosing the pathologic grade of PNETs. This study enrolled 93 participants with PNETs: 50 grade 1, 31 grade 2 and 12 grade 3. Multivariate ordinal regression analysis suggested that tumor size ≥2 cm (odds ratio [OR], 0.110; 95% confidence interval [CI], 0.020-0.606; p = 0.011), dilation of the main pancreatic duct (OR, 0.103; 95% CI, 0.025-0.430; p = 0.002), hepatic metastases (OR, 0.250; 95% CI, 0.072-0.869; p = 0.029) and hyper-enhancement in arterial phase (OR, 4.676; 95% CI, 1.656-13.206; p = 0.004) were significantly associated with the pathologic grades of PNETs. The accuracy of the ordinal logistic regression model in identifying grade 1, 2 and 3 PNETs was 77.4%, 67.7% and 90.3%, respectively. The findings suggest that sonographic features, including tumor size, pancreatic duct dilation and hepatic metastasis, as well as the enhancement level in arterial phase, may help identify different pathologic grades of PNETs.
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Affiliation(s)
- Jingzhi Huang
- Department of Medical Ultrasound, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Jie Chen
- Department of Gastroenterology, The First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, China
| | - Ming Xu
- Department of Medical Ultrasound, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Yanling Zheng
- Department of Medical Ultrasound, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Manxia Lin
- Department of Medical Ultrasound, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Guangliang Huang
- Department of Medical Ultrasound, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Xiaoyan Xie
- Department of Medical Ultrasound, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Xiaohua Xie
- Department of Medical Ultrasound, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.
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Dioguardi Burgio M, Cros J, Panvini N, Depoilly T, Couvelard A, Ruszniewski P, de Mestier L, Hentic O, Sauvanet A, Dokmak S, Faccinetto A, Ronot M, Vilgrain V. Serotonin immunoreactive pancreatic neuroendocrine neoplasm associated with main pancreatic duct dilation: a recognizable entity with excellent long-term outcome. Eur Radiol 2021; 31:8671-8681. [PMID: 33977308 DOI: 10.1007/s00330-021-08007-4] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2020] [Revised: 03/19/2021] [Accepted: 04/20/2021] [Indexed: 12/14/2022]
Abstract
OBJECTIVES Dilatation of the main pancreatic duct (MPD) is rare in pancreatic neuroendocrine neoplasm (panNEN) and may be due to different mechanisms. We compared the imaging and pathological characteristics as well as the outcome after resection of positive (S+) and negative (S-) serotonin immunoreactive panNENs causing MPD dilatation. METHODS This retrospective study included patients with panNEN, with MPD dilatation (≥ 4 mm) on preoperative CT/MRI and resected between 2005 and 2019. Clinical, radiological, and pathological features were compared between S+ and S- panNENs. Imaging features associated with S+ panNEN were identified using logistic regression analysis. The diagnostic performance of imaging for the differentiation of S+ and S- panNENs was assessed by ROC curve analysis. Recurrence-free survival (RFS) was compared between the two groups. RESULTS The final population of 60 panNENs included 20/60 (33%) S+ panNENs. S+ panNENs were smaller (median 12.5 mm vs. 33 mm; p < 0.01), more frequently hyperattenuating/intense on portal venous phase at CT/MRI (95% vs. 25%, p < 0.01), and presented with more fibrotic stroma on pathology (60.7 ± 16% vs. 40.7 ± 12.8%; p < 0.01) than S- panNENs. Tumor size was the only imaging factor associated with S+ panNEN on multivariate analysis. A tumor size ≤ 20 mm had 95% sensitivity and 90% specificity for the diagnosis of S+ panNEN. Among 52 patients without synchronous liver metastases, recurrence occurred in 1/20 (5%) with S+ panNEN and 18/32 (56%) with S- panNEN (p < 0.01). Median RFS was not reached in S+ panNENs and was 31.3 months in S- panNENs (p < 0.01). CONCLUSIONS In panNENs with MPD dilatation, serotonin positivity is associated with smaller size, extensive fibrotic stroma, and better long-term outcomes. KEY POINTS • S+ panNENs showed a higher percentage of fibrotic stroma, higher microvessel density, and lower proliferation index (Ki-67) compared to S- panNENs. • Radiologically, S+ panNENs causing dilatation of the MPD were characterized by a small size (< = 20 mm) and a persistent enhancement on portal phase on both CT and MRI. • Patients with S+ panNENs presented with longer RFS when compared to those with S- panNENs.
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Affiliation(s)
- Marco Dioguardi Burgio
- Université de Paris, INSERM U1149 "centre de recherche sur l'inflammation," CRI, F-75018, Paris, France.
- Department of Radiology, AP-HP Nord, Hôpital Beaujon, 100 Boulevard du Général Leclerc, 92110, Clichy, France.
| | - Jérome Cros
- Department of Pathology, AP-HP Nord, Hôpital Beaujon, 100 Boulevard du Général Leclerc, 92110, Clichy, France
| | - Nicola Panvini
- Department of Radiology, AP-HP Nord, Hôpital Beaujon, 100 Boulevard du Général Leclerc, 92110, Clichy, France
| | - Thomas Depoilly
- Department of Pathology, AP-HP Nord, Hôpital Beaujon, 100 Boulevard du Général Leclerc, 92110, Clichy, France
| | - Anne Couvelard
- Department of Pathology, AP-HP Nord, Hôpital Beaujon, 100 Boulevard du Général Leclerc, 92110, Clichy, France
| | - Philippe Ruszniewski
- Department of Gastroenterology-Pancreatology, ENETS Centre of Excellence AP-HP Nord, Hôpital Beaujon, 100 Boulevard du Général Leclerc, 92110, Clichy, France
| | - Louis de Mestier
- Department of Gastroenterology-Pancreatology, ENETS Centre of Excellence AP-HP Nord, Hôpital Beaujon, 100 Boulevard du Général Leclerc, 92110, Clichy, France
| | - Olivia Hentic
- Department of Gastroenterology-Pancreatology, ENETS Centre of Excellence AP-HP Nord, Hôpital Beaujon, 100 Boulevard du Général Leclerc, 92110, Clichy, France
| | - Alain Sauvanet
- Department of HBP Surgery, AP-HP Nord, Hôpital Beaujon, 100 Boulevard du Général Leclerc, 92110, Clichy, France
| | - Safi Dokmak
- Department of HBP Surgery, AP-HP Nord, Hôpital Beaujon, 100 Boulevard du Général Leclerc, 92110, Clichy, France
| | - Alex Faccinetto
- Department of Radiology, AP-HP Nord, Hôpital Beaujon, 100 Boulevard du Général Leclerc, 92110, Clichy, France
| | - Maxime Ronot
- Université de Paris, INSERM U1149 "centre de recherche sur l'inflammation," CRI, F-75018, Paris, France
- Department of Radiology, AP-HP Nord, Hôpital Beaujon, 100 Boulevard du Général Leclerc, 92110, Clichy, France
| | - Valérie Vilgrain
- Université de Paris, INSERM U1149 "centre de recherche sur l'inflammation," CRI, F-75018, Paris, France
- Department of Radiology, AP-HP Nord, Hôpital Beaujon, 100 Boulevard du Général Leclerc, 92110, Clichy, France
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Xu W, Zhang H, Feng G, Zheng Q, Shang R, Liu X. The value of MRI in identifying pancreatic neuroendocrine tumour G3 and carcinoma G3. Clin Radiol 2021; 76:551.e1-551.e9. [PMID: 33902887 DOI: 10.1016/j.crad.2021.02.031] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2020] [Accepted: 02/11/2021] [Indexed: 11/17/2022]
Abstract
AIM To explore the magnetic resonance imaging (MRI) differences between pancreatic neuroendocrine tumour grade 3 (pNET-G3) and pancreatic neuroendocrine carcinoma grade 3 (pNEC-G3). MATERIALS AND METHODS Between 2009 and 2019, 31 patients underwent pNEN-G3 resection with preoperative MRI in two local hospitals in China. The 31 patients were assigned to a pNET-G3 group (n=13) or a pNEC-G3 group (n=18). The MRI findings between the groups were compared. RESULTS There was no statistically significant difference between the two groups in lesion size, clinical characteristics, or laboratory indexes. The lesions showed high or slightly higher signal on diffusion-weighted imaging and decreased apparent diffusion coefficient (ADC) values, which differed between the two groups (p=0.013). The difference between the groups regarding positive enhancement integral, arterial phase and portal phase signal enhancement ratio were statistically significant; however, the delayed phase signal enhancement ratio was not significantly different. CONCLUSIONS pNET-G3 and pNEC-G3 showed different characteristics on MRI. In particular, the ADC value and dynamic enhanced imaging could have an important role in distinguishing between the two.
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Affiliation(s)
- W Xu
- Department of Radiology, Dezhou People's Hospital, 1166 Dong Fang Hong West Road, Dezhou, Shandong 253000, China
| | - H Zhang
- Department of Radiology, Dezhou People's Hospital, 1166 Dong Fang Hong West Road, Dezhou, Shandong 253000, China
| | - G Feng
- Department of Radiology, Yucheng People's Hospital, 753 Pioneer Road, Yucheng, Shandong 251200, China
| | - Q Zheng
- Department of Radiology, Dezhou People's Hospital, 1166 Dong Fang Hong West Road, Dezhou, Shandong 253000, China
| | - R Shang
- Department of Radiology, Dezhou People's Hospital, 1166 Dong Fang Hong West Road, Dezhou, Shandong 253000, China
| | - X Liu
- Department of Pharmacy, Dezhou People's Hospital, 1166 Dong Fang Hong West Road, Dezhou, Shandong 253000, China.
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When pancreas solid mass meets liver cystic lesion: A case report. JOURNAL OF PANCREATOLOGY 2021. [DOI: 10.1097/jp9.0000000000000065] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022] Open
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32
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Tanaka M, Heckler M, Mihaljevic AL, Probst P, Klaiber U, Heger U, Schimmack S, Büchler MW, Hackert T. Systematic Review and Metaanalysis of Lymph Node Metastases of Resected Pancreatic Neuroendocrine Tumors. Ann Surg Oncol 2021; 28:1614-1624. [PMID: 32720049 DOI: 10.1245/s10434-020-08850-7] [Citation(s) in RCA: 40] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2020] [Accepted: 06/27/2020] [Indexed: 12/15/2022]
Abstract
BACKGROUND The optimal surgical strategy for pancreatic neuroendocrine tumors (PNETs) is unknown. However, current guidelines recommend a watch-and-wait strategy for small nonfunctional PNETs (NF-PNETs). The aim of this study is to investigate the risk stratification and prognostic significance of lymph node metastasis (LNM) of PNETs to guide decision-making for lymphadenectomy. PATIENTS AND METHODS The MEDLINE and Web of Science databases were systematically searched for studies reporting either risk factors of LNM in resected PNETs or survival of patients with LNM. The weighted average incidence of LNM was calculated according to tumor characteristics. Random-effects metaanalyses were performed, and pooled hazard ratios (HR) and their 95% confidence intervals (CI) were calculated to determine the impact of LNM on overall survival (OS). In subgroup analyses, NF-PNETs were assessed. RESULTS From a total of 5883 articles, 98 retrospective studies with 13,374 patients undergoing resection for PNET were included. In all PNETs, the weighted median rates of LNM were 11.5% for small (≤ 2 cm) PNETs and 15.8% for G1 PNETs. In NF-PNETs, the rates were 11.2% for small PNETs and 10.3% for G1 PNETs. LNM of all PNETs (HR 3.87, 95% CI 3.00-4.99, P < 0.001) and NF-PNETs (HR 4.98, 95% CI 2.81-8.83, P < 0.001) was associated with worse OS. CONCLUSIONS LNM is potentially prevalent even in small and well-differentiated PNETs and is associated with worse prognosis. A watch-and-wait strategy for small NF-PNETs should be reappraised, and oncologic resection with lymphadenectomy can be considered. Prospective and controlled studies are needed in the future.
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Affiliation(s)
- Masayuki Tanaka
- Department of General, Visceral and Transplantation Surgery, University of Heidelberg, Heidelberg, Germany
- Department of Surgery, Keio University, School of Medicine, Tokyo, Japan
| | - Max Heckler
- Department of General, Visceral and Transplantation Surgery, University of Heidelberg, Heidelberg, Germany
| | - André L Mihaljevic
- Department of General, Visceral and Transplantation Surgery, University of Heidelberg, Heidelberg, Germany
| | - Pascal Probst
- Department of General, Visceral and Transplantation Surgery, University of Heidelberg, Heidelberg, Germany
| | - Ulla Klaiber
- Department of General, Visceral and Transplantation Surgery, University of Heidelberg, Heidelberg, Germany
| | - Ulrike Heger
- Department of General, Visceral and Transplantation Surgery, University of Heidelberg, Heidelberg, Germany
| | - Simon Schimmack
- Department of General, Visceral and Transplantation Surgery, University of Heidelberg, Heidelberg, Germany
| | - Markus W Büchler
- Department of General, Visceral and Transplantation Surgery, University of Heidelberg, Heidelberg, Germany
| | - Thilo Hackert
- Department of General, Visceral and Transplantation Surgery, University of Heidelberg, Heidelberg, Germany.
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Zhang T, Zhang Y, Liu X, Xu H, Chen C, Zhou X, Liu Y, Ma X. Application of Radiomics Analysis Based on CT Combined With Machine Learning in Diagnostic of Pancreatic Neuroendocrine Tumors Patient's Pathological Grades. Front Oncol 2021; 10:521831. [PMID: 33643890 PMCID: PMC7905094 DOI: 10.3389/fonc.2020.521831] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2019] [Accepted: 12/11/2020] [Indexed: 02/05/2023] Open
Abstract
Purpose To evaluate the value of multiple machine learning methods in classifying pathological grades (G1,G2, and G3), and to provide the best machine learning method for the identification of pathological grades of pancreatic neuroendocrine tumors (PNETs) based on radiomics. Materials and Methods A retrospective study was conducted on 82 patients with Pancreatic Neuroendocrine tumors. All patients had definite pathological diagnosis and grading results. Using Lifex software to extract the radiomics features from CT images manually. The sensitivity, specificity, area under the curve (AUC) and accuracy were used to evaluate the performance of the classification model. Result Our analysis shows that the CT based radiomics features combined with multi algorithm machine learning method has a strong ability to identify the pathological grades of pancreatic neuroendocrine tumors. DC + AdaBoost, DC + GBDT, and Xgboost+RF were very valuable for the differential diagnosis of three pathological grades of PNET. They showed a strong ability to identify the pathological grade of pancreatic neuroendocrine tumors. The validation set AUC of DC + AdaBoost is 0.82 (G1 vs G2), 0.70 (G2 vs G3), and 0.85 (G1 vs G3), respectively. Conclusion In conclusion, based on enhanced CT radiomics features could differentiate between different pathological grades of pancreatic neuroendocrine tumors. Feature selection method Distance Correlation + classifier method Adaptive Boosting show a good application prospect.
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Affiliation(s)
- Tao Zhang
- Department of Biotherapy, Cancer Center, West China Hospital, Sichuan University, Chengdu, China.,State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu, China
| | - YueHua Zhang
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Xinglong Liu
- West China School of Medicine, West China Hospital, Sichuan University, Chengdu, China
| | - Hanyue Xu
- West China School of Medicine, West China Hospital, Sichuan University, Chengdu, China
| | - Chaoyue Chen
- Department of Neurosurgery, West China Hospital, Sichuan University, Chengdu, China
| | - Xuan Zhou
- West China School of Medicine, West China Hospital, Sichuan University, Chengdu, China
| | - Yichun Liu
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Xuelei Ma
- Department of Biotherapy, Cancer Center, West China Hospital, Sichuan University, Chengdu, China.,State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu, China
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Wang Y, Chen X, Wang J, Cui W, Wang C, Chen X, Wang Z. Differentiation between non-hypervascular pancreatic neuroendocrine tumors and mass-forming pancreatitis using contrast-enhanced computed tomography. Acta Radiol 2021; 62:190-197. [PMID: 32375515 DOI: 10.1177/0284185120921503] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
BACKGROUND Non-hypervascular pancreatic neuroendocrine tumors (PNETs) showed slight or iso-enhancement in contrast-enhanced computed tomography (CE-CT), which shared similar imaging findings with mass-forming pancreatitis (MFPs). PURPOSE To explore the value of CT imaging features in differentiating the two diseases. MATERIAL AND METHODS Fifty-one patients with histologically proved MFPs (n = 27) or non-hypervascular PNETs (n = 24) were included. Two radiologists reviewed CT imaging findings and clinical features. Logistic regression analysis was performed to identify relevant features in differentiating non-hypervascular PNETs and MFPs. Receiver operating characteristic (ROC) curve analysis was used to show the performance of the optimal parameters in differentiating non-hypervascular PNETs and MFPs. RESULTS A well-defined margin was more common in non-hypervascular PNETs (P < 0.05) than that in MFPs. MFPs often occurred in older people (P < 0.01) and the head-neck of the pancreas compared with non-hypervascular PNETs (P < 0.05). Metastases only presented in non-hypervascular PNETs (P < 0.05). CT values at venous phase and delay phase of MFPs were higher (P = 0.010 and P = 0.029) than those in non-hypervascular PNETs. Logistic analysis showed gender, tumor margin, CT values at venous phase, and tumor components were independent predictors in differentiating the two lesions. The area under the curve (AUC) was 0.938 with a sensitivity of 87.5% and specificity of 92.6% for combined predicators. CONCLUSION Gender, tumor margin, CT values at venous phase, and tumor components were useful predicators in differentiating non-hypervascular PNETs and MFPs.
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Affiliation(s)
- Yajie Wang
- Department of Radiology, The Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, Jiangsu Province, PR China
| | - Xin Chen
- Department of Radiology, The Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, Jiangsu Province, PR China
- Department of Graduate, Bengbu Medical College, Bengbu, Anhui Province, PR China
| | - Jianhua Wang
- Department of Radiology, The Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, Jiangsu Province, PR China
| | - Wenjing Cui
- Department of Radiology, The Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, Jiangsu Province, PR China
| | - Cheng Wang
- Department of Radiology, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing, Jiangsu Province, PR China
| | - Xiao Chen
- Department of Radiology, The Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, Jiangsu Province, PR China
| | - Zhongqiu Wang
- Department of Radiology, The Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, Jiangsu Province, PR China
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Xu W, Yan H, Xu L, Li M, Gao W, Jiang K, Wu J, Miao Y. Correlation between radiologic features on contrast-enhanced CT and pathological tumor grades in pancreatic neuroendocrine neoplasms. J Biomed Res 2021; 35:179-188. [PMID: 33637654 PMCID: PMC8193709 DOI: 10.7555/jbr.34.20200039] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023] Open
Abstract
Contrast-enhanced computed tomography (CT) contributes to the increasing detection of pancreatic neuroendocrine neoplasms (PNENs). Nevertheless, its value for differentiating pathological tumor grades is not well recognized. In this report, we have conducted a retrospective study on the relationship between the 2017 World Health Organization (WHO) classification and CT imaging features in 94 patients. Most of the investigated features eventually provided statistically significant indicators for discerning PNENs G3 from PNENs G1/G2, including tumor size, shape, margin, heterogeneity, intratumoral blood vessels, vascular invasion, enhancement pattern in both contrast phases, enhancement degree in both phases, tumor-to-pancreas contrast ratio in both phases, common bile duct dilatation, lymph node metastases, and liver metastases. Ill-defined tumor margin was an independent predictor for PNENs G3 with the highest area under the curve (AUC) of 0.906 in the multivariable logistic regression and receiver operating characteristic curve analysis. The portal enhancement ratio (PER) was shown the highest AUC of 0.855 in terms of quantitative features. Our data suggest that the traditional contrast-enhanced CT still plays a vital role in differentiation of tumor grades and heterogeneity analysis prior to treatment.
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Affiliation(s)
- Wenbin Xu
- Pancreas Center, the First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu 210029, China.,Pancreas Institute of Nanjing Medical University, Nanjing, Jiangsu 210029, China
| | - Han Yan
- Pancreas Center, the First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu 210029, China.,Pancreas Institute of Nanjing Medical University, Nanjing, Jiangsu 210029, China
| | - Lulu Xu
- Department of Radiology, the First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu 210029, China
| | - Mingna Li
- Department of Pathology, the First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu 210029, China
| | - Wentao Gao
- Pancreas Center, the First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu 210029, China.,Pancreas Institute of Nanjing Medical University, Nanjing, Jiangsu 210029, China
| | - Kuirong Jiang
- Pancreas Center, the First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu 210029, China.,Pancreas Institute of Nanjing Medical University, Nanjing, Jiangsu 210029, China
| | - Junli Wu
- Pancreas Center, the First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu 210029, China.,Pancreas Institute of Nanjing Medical University, Nanjing, Jiangsu 210029, China
| | - Yi Miao
- Pancreas Center, the First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu 210029, China.,Pancreas Institute of Nanjing Medical University, Nanjing, Jiangsu 210029, China
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Ren S, Qian L, Daniels MJ, Duan S, Chen R, Wang Z. Evaluation of contrast-enhanced computed tomography for the differential diagnosis of hypovascular pancreatic neuroendocrine tumors from chronic mass-forming pancreatitis. Eur J Radiol 2020; 133:109360. [PMID: 33126171 DOI: 10.1016/j.ejrad.2020.109360] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2020] [Revised: 09/27/2020] [Accepted: 10/15/2020] [Indexed: 12/28/2022]
Abstract
PURPOSE To assess the role of contrast-enhanced computed tomography (CECT) for differentiation of hypovascular pancreatic neuroendocrine tumors (hypo-PNETs) from chronic mass-forming pancreatitis (CMFP). METHODS A retrospective study of 59 patients (27 hypo-PNETs patients vs 32 CMFP patients) who underwent preoperative CECT between July 2012 and July 2019 was performed. Qualitative and quantitative analysis was performed, including mass location, size, margin, cystic changes, calcification, pancreatic or bile duct dilatation, pancreatic atrophy, local vessels involvement, mass contrast enhancement and mass-to-pancreas enhancement ratio. Multivariate logistic regression analyses were used to identify relevant CT imaging findings in differentiation between hypo-PNETs and CMFP. RESULTS When compared to CMFP, hypo-PNETs more frequently had a well-defined margin and cystic changes and less frequently had a history of pancreatitis and calcification. CMFP had higher mass contrast enhancement and mass-to-pancreas enhancement ratio in the portal and delayed phases than hypo-PNETs. After multivariate logistic regression analyses, areas under the curve (AUCs) were 0.795 (95 % CI: 0.652-0.899), 0.752 (95 % CI: 0.604-0.866), 0.859 (95 % CI: 0.726-0.943), and 0.929 (95 % CI: 0.814-0.983) for Model 1(clinical factors), Model 2 (qualitative parameters), Model 3 (quantitative parameters), and their combinations, respectively. CONCLUSION Combined assessment of clinical factors, qualitative, and quantitative imaging characteristics can improve the differentiation between hypo-PNETs and CMFP at CECT.
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Affiliation(s)
- Shuai Ren
- Department of Radiology, Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, 210029, Jiangsu Province, China; Department of Radiology, The Eighth Affiliated Hospital, Sun Yat-Sen University, Shenzhen, 518033, Guangdong Province, China; The First School of Clinical Medicine, Nanjing University of Chinese Medicine, Nanjing, 210023, Jiangsu Province, China; Department of Diagnostic Radiology and Nuclear Medicine, School of Medicine, University of Maryland, Baltimore, MD, 21201, USA
| | - Lichao Qian
- The First School of Clinical Medicine, Nanjing University of Chinese Medicine, Nanjing, 210023, Jiangsu Province, China
| | - Marcus J Daniels
- Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | | | - Rong Chen
- Department of Diagnostic Radiology and Nuclear Medicine, School of Medicine, University of Maryland, Baltimore, MD, 21201, USA
| | - Zhongqiu Wang
- Department of Radiology, Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, 210029, Jiangsu Province, China; Department of Radiology, The Eighth Affiliated Hospital, Sun Yat-Sen University, Shenzhen, 518033, Guangdong Province, China.
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Kimura K, Tsuchiya J, Kitazume Y, Kishino M, Akahoshi K, Kudo A, Tanaka S, Tanabe M, Tateishi U. Dynamic Enhancement Pattern on CT for Predicting Pancreatic Neuroendocrine Neoplasms with Low PAX6 Expression: A Retrospective Observational Study. Diagnostics (Basel) 2020; 10:919. [PMID: 33182335 PMCID: PMC7695321 DOI: 10.3390/diagnostics10110919] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2020] [Revised: 11/05/2020] [Accepted: 11/06/2020] [Indexed: 12/20/2022] Open
Abstract
Paired box 6 (PAX6) is a transcription factor that plays a critical role in tumor suppression, implying that the downregulation of PAX6 promotes tumor growth and invasiveness. This study aimed to examine dynamic computed tomography (CT) features for predicting pancreatic neuroendocrine neoplasms (Pan-NENs) with low PAX6 expression. We retrospectively evaluated 51 patients with Pan-NENs without synchronous liver metastasis to assess the pathological expression of PAX6. Two radiologists analyzed preoperative dynamic CT images to determine morphological features and enhancement patterns. We compared the CT findings between low and high PAX6 expression groups. Pathological analysis identified 11 and 40 patients with low and high PAX6 expression, respectively. Iso- or hypoenhancement types in the arterial and portal phases were significantly associated with low PAX6 expression (p = 0.009; p = 0.001, respectively). Low PAX6 Pan-NENs showed a lower portal enhancement ratio than high PAX6 Pan-NENs (p = 0.044). The combination based on enhancement types (iso- or hypoenhancement during arterial and portal phases) and portal enhancement ratio (≤1.22) had 54.5% sensitivity, 92.5% specificity, and 84.3% accuracy in identifying low PAX6 Pan-NENs. Dynamic CT features, including iso- or hypoenhancement types in the arterial and portal phases and lower portal enhancement ratio may help predict Pan-NENs with low PAX6 expression.
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Affiliation(s)
- Koichiro Kimura
- Department of Diagnostic Radiology, Graduate School of Medicine, Tokyo Medical and Dental University, 1-5-45 Yushima, Bunkyo-ku, Tokyo 1138510, Japan; (J.T.); (Y.K.); (M.K.); (U.T.)
| | - Junichi Tsuchiya
- Department of Diagnostic Radiology, Graduate School of Medicine, Tokyo Medical and Dental University, 1-5-45 Yushima, Bunkyo-ku, Tokyo 1138510, Japan; (J.T.); (Y.K.); (M.K.); (U.T.)
| | - Yoshio Kitazume
- Department of Diagnostic Radiology, Graduate School of Medicine, Tokyo Medical and Dental University, 1-5-45 Yushima, Bunkyo-ku, Tokyo 1138510, Japan; (J.T.); (Y.K.); (M.K.); (U.T.)
| | - Mitsuhiro Kishino
- Department of Diagnostic Radiology, Graduate School of Medicine, Tokyo Medical and Dental University, 1-5-45 Yushima, Bunkyo-ku, Tokyo 1138510, Japan; (J.T.); (Y.K.); (M.K.); (U.T.)
| | - Keiichi Akahoshi
- Department of Hepatobiliary and Pancreatic Surgery, Graduate School of Medicine, Tokyo Medical and Dental University, 1-5-45 Yushima, Bunkyo-ku, Tokyo 1138510, Japan; (K.A.); (A.K.); (M.T.)
| | - Atsushi Kudo
- Department of Hepatobiliary and Pancreatic Surgery, Graduate School of Medicine, Tokyo Medical and Dental University, 1-5-45 Yushima, Bunkyo-ku, Tokyo 1138510, Japan; (K.A.); (A.K.); (M.T.)
| | - Shinji Tanaka
- Department of Molecular Oncology, Graduate School of Medicine, Tokyo Medical and Dental University, 1-5-45 Yushima, Bunkyo-ku, Tokyo 1138510, Japan;
| | - Minoru Tanabe
- Department of Hepatobiliary and Pancreatic Surgery, Graduate School of Medicine, Tokyo Medical and Dental University, 1-5-45 Yushima, Bunkyo-ku, Tokyo 1138510, Japan; (K.A.); (A.K.); (M.T.)
| | - Ukihide Tateishi
- Department of Diagnostic Radiology, Graduate School of Medicine, Tokyo Medical and Dental University, 1-5-45 Yushima, Bunkyo-ku, Tokyo 1138510, Japan; (J.T.); (Y.K.); (M.K.); (U.T.)
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Abstract
OBJECTIVE. Multiple endocrine neoplasia (MEN) syndromes are autosomal-dominant genetic disorders that predispose two or more organs of the endocrine system to tumor development. Although the diagnosis relies on clinical and serologic findings, imaging provides critical information for surgical management with the ultimate goal of complete tumor resection. CONCLUSION. This article reviews abdominal neoplasms associated with the various subtypes of MEN syndromes, with a focus on clinical presentation and characteristic imaging features.
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Pavel M, Öberg K, Falconi M, Krenning EP, Sundin A, Perren A, Berruti A. Gastroenteropancreatic neuroendocrine neoplasms: ESMO Clinical Practice Guidelines for diagnosis, treatment and follow-up. Ann Oncol 2020; 31:844-860. [PMID: 32272208 DOI: 10.1016/j.annonc.2020.03.304] [Citation(s) in RCA: 671] [Impact Index Per Article: 134.2] [Reference Citation Analysis] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2019] [Revised: 03/25/2020] [Accepted: 03/26/2020] [Indexed: 02/06/2023] Open
Affiliation(s)
- M Pavel
- Department of Medicine 1, University Hospital Erlangen, Erlangen, Germany
| | - K Öberg
- Department of Endocrine Oncology, Uppsala University, Uppsala, Sweden
| | - M Falconi
- Department of Surgery, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - E P Krenning
- Cyclotron Rotterdam BV, Erasmus Medical Centre, Rotterdam, The Netherlands
| | - A Sundin
- Department of Surgical Sciences, Uppsala University, Uppsala, Sweden
| | - A Perren
- Institute of Pathology, University of Bern, Bern, Switzerland
| | - A Berruti
- Department of Medical and Surgical Specialties, Radiological Sciences and Public Health, Medical Oncology Unit, University of Brescia, ASST Spedali Civili, Brescia, Italy
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Grade 3 Pancreatic Neuroendocrine Tumors on MDCT: Establishing a Diagnostic Model and Comparing Survival Against Pancreatic Ductal Adenocarcinoma. AJR Am J Roentgenol 2020; 215:390-397. [PMID: 32432906 DOI: 10.2214/ajr.19.21921] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
OBJECTIVE. The purpose of this study is to establish a diagnostic model for differentiating grade 3 (G3) pancreatic neuroendocrine tumors (PNETs) from pancreatic ductal adenocarcinomas (PDACs) and to analyze survival outcomes. MATERIALS AND METHODS. Twenty patients with G3 PNETs and 58 patients with PDACs confirmed by surgery or biopsy were retrospectively included. Demographic and radiologic information was collected. Univariate analyses and binary logistic regression analyses were performed to identify independent factors and establish a diagnostic model. An ROC curve was created to determine diagnostic ability. Kaplan-Meier survival analysis was performed. RESULTS. Patients with G3 PNETs were more likely to present with normal carbohydrate antigen (CA) 19-9 levels, normal pancreatic ducts, and round tumors with well-defined margins and higher portal enhancement ratios than were patients with PDAC (p < 0.05). After multivariate analysis, a normal CA 19-9 level (odds ratio, 0.0125; 95% CI, 0.0008-0.2036), round tumor shape (odds ratio, 0.0143; 95% CI, 0.0004-0.5461), and pancreatic duct dilation of 4 mm or less (odds ratio, 17.9804; 95% CI, 1.0098-320.1711) were independent predictors of G3 PNETs. The AUC of the ROC curve was 0.916, and sensitivity and specificity were 90.0% and 81.0%, respectively. Furthermore, patients with G3 PNETs had better overall survival than patients with PDACs. Among patients in the G3 PNET subgroup, patients with liver or lymph node metastases had worse overall survival than patients without metastases. CONCLUSION. A diagnostic model was established to differentiate G3 PNETs from PDACs. A normal CA 19-9 level, round tumor shape, and pancreatic duct dilation of 4 mm or less were factors that were strongly predictive of G3 PNET.
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Wang Z, Chen X, Wang J, Cui W, Ren S, Wang Z. Differentiating hypovascular pancreatic neuroendocrine tumors from pancreatic ductal adenocarcinoma based on CT texture analysis. Acta Radiol 2020; 61:595-604. [PMID: 31522519 DOI: 10.1177/0284185119875023] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
Background Hypovascular pancreatic neuroendocrine tumor is usually misdiagnosed as pancreatic ductal adenocarcinoma. Purpose To investigate the value of texture analysis in differentiating hypovascular pancreatic neuroendocrine tumors from pancreatic ductal adenocarcinoma on contrast-enhanced computed tomography (CT) images. Material and Methods Twenty-one patients with hypovascular pancreatic neuroendocrine tumors and 63 patients with pancreatic ductal adenocarcinomas were included in this study. All patients underwent preoperative unenhanced and dynamic contrast-enhanced CT examinations. Two radiologists independently and manually contoured the region of interest of each lesion using texture analysis software on pancreatic parenchymal and portal phase CT images. Multivariate logistic regression analysis was performed to identify significant features to differentiate hypovascular pancreatic neuroendocrine tumors from pancreatic ductal adenocarcinomas. Receiver operating characteristic curve analysis was performed to ascertain diagnostic ability. Results The following CT texture features were obtained to differentiate hypovascular pancreatic neuroendocrine tumors from pancreatic ductal adenocarcinomas: RMS (root mean square) (odds ratio [OR] = 0.50, P<0.001), Quantile50 (OR = 1.83, P<0.001), and sumAverage (OR = 0.92, P=0.007) in parenchymal images and “contrast” in portal phase images (OR = 6.08, P<0.001). The areas under the curves were 0.76 for RMS (sensitivity = 0.75, specificity = 0.67), 0.73 for Quantile50 (sensitivity = 0.60, specificity = 0.77), 0.70 for sumAverage (sensitivity = 0.65, specificity = 0.82), 0.85 for the combined texture features (sensitivity = 0.77, specificity = 0.85). Conclusion CT texture analysis may be helpful to differentiate hypovascular pancreatic neuroendocrine tumors from pancreatic ductal adenocarcinomas. The three combined texture features showed acceptable diagnostic performance.
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Affiliation(s)
- Zhonglan Wang
- Department of Radiology, Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, Jiangsu Province, PR China
- Department of Radiology, Nanjing Hospital of Chinese Medicine, Nanjing, Jiangsu Province, PR China
| | - Xiao Chen
- Department of Radiology, Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, Jiangsu Province, PR China
| | - Jianhua Wang
- Department of Radiology, Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, Jiangsu Province, PR China
| | - Wenjing Cui
- Department of Radiology, Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, Jiangsu Province, PR China
| | - Shuai Ren
- Department of Radiology, Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, Jiangsu Province, PR China
| | - Zhongqiu Wang
- Department of Radiology, Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, Jiangsu Province, PR China
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Armstrong EA, Beal EW, Shah M, Konda B, Abdel-Misih S, Ejaz A, Dillhoff ME, Pawlik TM, Cloyd JM. Radiographic characteristics of neuroendocrine liver metastases do not predict clinical outcomes following liver resection. Hepatobiliary Surg Nutr 2020; 9:1-12. [PMID: 32140474 DOI: 10.21037/hbsn.2019.06.02] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/27/2023]
Abstract
Background Previous research has demonstrated that specific radiographic criteria, including the presence of calcifications and the enhancement pattern on computed tomography (CT) imaging, correlates with clinicopathologic features and outcomes of patients with gastroenteropancreatic neuroendocrine tumors (NET). We sought to investigate whether these radiographic characteristics were prognostic among patients with neuroendocrine liver metastases (NELM) undergoing surgical resection. Methods The preoperative contrast-enhanced CT scans of all patients who underwent resection of NELM at a single institution between 2000-2015 were retrospectively reviewed. The presence of calcifications was determined on non-contrast phase imaging. Enhancement on the arterial phase scan was categorized as hyperenhancing, hypoenhancing, or mixed. Relevant clinicopathologic characteristics as well as recurrence-free survival (RFS) and overall survival (OS) were compared between groups. Results Among 82 patients who underwent resection of NELM, 57 had available data on calcifications while 51 had data available on arterial enhancement patterns. Among all patients, median age was 58 (IQR: 47-63) and the majority were female (N=48, 59.5%). The most common primary tumor locations were pancreas (N=25, 30.5%) and small bowel (N=27, 32.9%). The most commonly performed operations were right hepatectomy (N=29, 35.4%), bisegmentectomy (N=15, 18.3%), and segmentectomy (N=14, 17.1%). Median tumor number was 4 (IQR: 2-9), median Ki-67 was 5% (IQR: 2-10%), and median size of the largest liver metastasis was 4.5 (IQR: 2.8-7.7) cm. Twelve (21%) patients had tumor calcifications. Among patients with and without calcifications there were no differences in demographics, clinicopathologic characteristics, RFS (P=0.772) or OS (P=0.095). Arterial enhancement was hypoenhancing in 23 (45.1%), hyperenhancing in 10 (19.6%), and mixed in 18 (35.3%). Similarly, there were no differences between arterial enhancement groups in demographics, clinicopathologic characteristics, RFS (P=0.618) or OS (P=0.268). Conclusions Radiographic characteristics on contrast-enhanced CT are not associated with the outcomes of patients undergoing resection of NELM. Future investigations should evaluate the prognostic impact of functional neuroendocrine imaging.
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Affiliation(s)
| | - Eliza W Beal
- Department of Surgery, Division of Surgical Oncology, The Ohio State University Wexner Medical Center, Columbus, OH, USA
| | - Manisha Shah
- Department of Internal Medicine, Division of Medical Oncology, The Ohio State University Wexner Medical Center, Columbus, OH, USA
| | - Bhavana Konda
- Department of Internal Medicine, Division of Medical Oncology, The Ohio State University Wexner Medical Center, Columbus, OH, USA
| | - Sherif Abdel-Misih
- Department of Surgery, Division of Surgical Oncology, The Ohio State University Wexner Medical Center, Columbus, OH, USA
| | - Aslam Ejaz
- Department of Surgery, Division of Surgical Oncology, The Ohio State University Wexner Medical Center, Columbus, OH, USA
| | - Mary E Dillhoff
- Department of Surgery, Division of Surgical Oncology, The Ohio State University Wexner Medical Center, Columbus, OH, USA
| | - Timothy M Pawlik
- Department of Surgery, Division of Surgical Oncology, The Ohio State University Wexner Medical Center, Columbus, OH, USA
| | - Jordan M Cloyd
- Department of Surgery, Division of Surgical Oncology, The Ohio State University Wexner Medical Center, Columbus, OH, USA
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Yang B, Chen HY, Zhang XY, Pan Y, Lu YF, Yu RS. The prognostic value of multidetector CT features in predicting overall survival outcomes in patients with pancreatic neuroendocrine tumors. Eur J Radiol 2020; 124:108847. [PMID: 31991300 DOI: 10.1016/j.ejrad.2020.108847] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2019] [Revised: 12/03/2019] [Accepted: 01/18/2020] [Indexed: 12/14/2022]
Abstract
PURPOSE To assess the prognostic value of multidetector CT in predicting overall survival outcomes in patients with pancreatic neuroendocrine tumors (PNETs). METHOD Seventy-one patients pathologically diagnosed with PNETs were retrospectively included. The clinical and imaging information was evaluated by two radiologists. The difference between well-differentiated and poorly differentiated PNETs was analyzed. Cox proportional hazards models were created to determine the risk factors for overall survival. Kaplan-Meier survival analyses with log-rank tests were used among different subgroups of patients with PNETs. RESULTS In the whole cohort, the median survival was 36 months, and the 5-year survival rate was 84.8 %. Patients with poorly differentiated PNETs were more likely to present with symptoms, abnormal tumor markers, larger diameters, irregular shapes, ill-defined margins, invasion into nearby tissues, liver and lymph node metastases, and lower enhancement ratio than those with well-differentiated PNETs (P < 0.05). In the multivariate analysis, lymph node metastases (hazard ratio: 21.52, P = 0.009) and a portal enhancement ratio less than 1.02 (hazard ratio: 30.89, P = 0.024) were significant factors for overall survival. Overall survival decreased with an ill-defined margin, irregular shape, poor differentiation, grade 3 disease, nonfunctional status, abnormal tumor marker levels, invasion into nearby tissues, lymph node and liver metastases, and lower enhancement ratio (log-rank P < 0.05). CONCLUSIONS Poorly differentiated PNETs were more aggressiveness than well-differentiated PNETs. Lymph node metastases and a portal enhancement ratio < 1.02 were independent prognostic factors for worse overall survival outcomes in patients with PNETs.
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Affiliation(s)
- Bo Yang
- Department of Radiology, Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China; Department of Radiology, Zhejiang Prison Center Hospital (Zhejiang Youth Hospital), Hangzhou, China
| | - Hai-Yan Chen
- Department of Radiology, Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Xue-Yan Zhang
- Department of Radiology, Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China; Department of Radiology, Institute of Occupational Diseases, Zhejiang Academy of Medical Sciences, Hangzhou, China
| | - Yao Pan
- Department of Radiology, Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Yuan-Fei Lu
- Department of Radiology, Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Ri-Sheng Yu
- Department of Radiology, Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.
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Coriat R. Les nouvelles techniques diagnostiques des tumeurs neuroendocrines pancréatiques. ONCOLOGIE 2020. [DOI: 10.3166/onco-2019-0046] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022]
Abstract
Les tumeurs neuroendocrines pancréatiques (TNEp) sont des tumeurs développées aux dépens du pancréas et nécessitent un bilan diagnostique spécifique. Le bilan d’imagerie d’une TNEp est utile pour le diagnostic ainsi que pour le traitement chirurgical/médical. Récemment, un certain nombre de progrès ont été réalisés dans le domaine de l’imagerie des TNEp, en particulier en ce qui concerne l’imagerie fonctionnelle utilisant des analogues de la somatostatine radiomarqués. Dans cette mise au point, nous abordons les progrès diagnostiques en nous focalisant sur les avancées des dernières années. Ainsi, il est abordé l’intérêt de l’imagerie conventionnelle (scanner, échographie abdominale, imagerie par résonance magnétique), de l’échoendoscopie et la place de l’imagerie fonctionnelle, principalement avec des analogues de la somatostatine radiomarqués.
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Lee L, Ito T, Jensen RT. Prognostic and predictive factors on overall survival and surgical outcomes in pancreatic neuroendocrine tumors: recent advances and controversies. Expert Rev Anticancer Ther 2019; 19:1029-1050. [PMID: 31738624 PMCID: PMC6923565 DOI: 10.1080/14737140.2019.1693893] [Citation(s) in RCA: 48] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2019] [Accepted: 11/13/2019] [Indexed: 02/06/2023]
Abstract
Introduction: Recent advances in diagnostic modalities and therapeutic agents have raised the importance of prognostic factors in predicting overall survival, as well as predictive factors for surgical outcomes, in tailoring therapeutic strategies of patients with pancreatic neuroendocrine neoplasms (panNENs).Areas covered: Numerous recent studies of panNEN patients report the prognostic values of a number of clinically related factors (clinical, laboratory, imaging, treatment-related factors), pathological factors (histological, classification, grading) and molecular factors on long-term survival. In addition, an increasing number of studies showed the usefulness of various factors, specifically biomarkers and molecular makers, in predicting recurrence and mortality related to surgical treatment. Recent findings (from the last 3 years) in each of these areas, as well as recent controversies, are reviewed.Expert commentary: The clinical importance of prognostic and predictive factors for panNENs is markedly increased for both overall outcome and post resection, as a result of recent advances in all aspects of the diagnosis, management and treatment of panNENs. Despite the proven prognostic utility of routinely used tumor grading/classification and staging systems, further studies are required to establish these novel prognostic factors to support their routine clinical use.
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Affiliation(s)
- Lingaku Lee
- Digestive Diseases Branch, NIDDK, NIH, Bethesda, MD, 20892-1804, USA
- Department of Hepato-Biliary-Pancreatology, National Kyushu Cancer Center, Fukuoka, 811-1395, Japan
| | - Tetsuhide Ito
- Neuroendocrine Tumor Centre, Fukuoka Sanno Hospital, International University of Health and Welfare, Fukuoka, 814-0001, Japan
| | - Robert T. Jensen
- Digestive Diseases Branch, NIDDK, NIH, Bethesda, MD, 20892-1804, USA
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Xiao B, Jiang ZQ, Hu JX, Zhang XM, Xu HB. Differentiating pancreatic neuroendocrine tumors from pancreatic ductal adenocarcinomas by the "Duct-Road Sign": A preliminary magnetic resonance imaging study. Medicine (Baltimore) 2019; 98:e16960. [PMID: 31464937 PMCID: PMC6736419 DOI: 10.1097/md.0000000000016960] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/06/2019] [Revised: 07/23/2019] [Accepted: 08/02/2019] [Indexed: 01/12/2023] Open
Abstract
To assess the duct-road sign and tumor-to-duct ratio (TDR) in MRI for differentiating pancreatic neuroendocrine tumors (PNETs) from pancreatic ductal-adenocarcinomas (PDACs).Retrospectively reviewed MRI characteristics of 78 pancreatic masses (histopathology-proven 25 PNETs and 53 PDACs). Receiver operating characteristics with TDR and diagnostic performance of the duct-road sign for differential diagnosis were performed.The prevalence of duct-road sign in PNETs was higher than that for PDACs (84% vs 0%; P < .001). A strong correlation (r = 0.884, P < .001) was observed between MRI for PNETs and the frequency of this sign. Performance characteristics of the duct-road sign in MRI for PNET diagnosis were sensitivity (84%, [21 of 25]), specificity (100%, [53 of 53]), positive predictive value (100%, [21 of 21]), negative predictive value (92.9%, [53 of 57]), and accuracy (94.8%, [74 of 78]). In the intention-to-diagnose analysis, the corresponding values were 67.7% (21 of 31), 100% (53 of 53), 100% (21 of 21), 84.1% (53 of 63), and 88.1% (74 of 84). The TDR in PNETs was observed to be greater than that in PDACs (14.6 ± 9.3 vs 6.9 ± 3.8, P = .001). TDR with a cut-off value of 7.7 had high sensitivity (84%) and specificity (66%) with area under curve (0.802, 95% CI: 0.699, 0.904; P < .001) for distinguishing PNETs from PDACs.The presence of duct-road sign and TDR > 7.7 on MRI may assist in diagnosis for PNET instead of PDAC.
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Affiliation(s)
- Bo Xiao
- Department of Radiology, Zhongnan Hospital of Wuhan University, Wuhan University, Wuhan
- Sichuan Key Laboratory of Medical Imaging, Department of Radiology
| | - Zhi-Qiong Jiang
- Department of Geratology, Affiliated Hospital of North Sichuan Medical College, Nanchong, PR China
| | - Jin-Xiang Hu
- Department of Radiology, Zhongnan Hospital of Wuhan University, Wuhan University, Wuhan
| | - Xiao-Ming Zhang
- Sichuan Key Laboratory of Medical Imaging, Department of Radiology
| | - Hai-Bo Xu
- Department of Radiology, Zhongnan Hospital of Wuhan University, Wuhan University, Wuhan
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He M, Liu Z, Lin Y, Wan J, Li J, Xu K, Wang Y, Jin Z, Tian J, Xue H. Differentiation of atypical non-functional pancreatic neuroendocrine tumor and pancreatic ductal adenocarcinoma using CT based radiomics. Eur J Radiol 2019; 117:102-111. [PMID: 31307634 DOI: 10.1016/j.ejrad.2019.05.024] [Citation(s) in RCA: 26] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2018] [Revised: 04/04/2019] [Accepted: 05/30/2019] [Indexed: 12/18/2022]
Abstract
PURPOSE To develop and validate an effective model to differentiate NF-pNET from PDAC. MATERIALS AND METHODS Between July 2014 and December 2017, 147 patients (80 patients with PDAC and 67 patients with atypical NF-pNET) with pathology results and enhanced CT were consecutively enrolled and chronologically divided into primary and validation cohorts. Three models were built to differentiate atypical NF-pNET from PDAC, including a model based on radiomic signature alone, one based on clinicoradiological features alone and one that integrated the two. The diagnostic performance of the three models was estimated and compared with the area under the receiver operating characteristic curve (AUC) in the validation cohort. A nomogram was used to represent the model with the best performance, and the associated calibration was also assessed. RESULTS In the validation cohort, the AUC for differential diagnosis was 0.884 with the integrated model, which was significantly improved over that of the model based on clinicoradiological features (AUC = 0.775, p value = 0.004) and was comparable to that of the model based on the radiomic signature (AUC = 0.873, p value = 0.512). The nomogram representing the integrated model achieved good discrimination performances in both the primary and validation cohorts, with C-indices of 0.960 and 0.884, respectively. CONCLUSION The integrated model outperformed the model based on clinicoradiological features alone and was comparable to the model based on the radiomic signature alone with respect to the differential diagnosis of atypical NF-pNET and PDAC. The nomogram achieved an optimal preoperative, noninvasive differential diagnosis between atypical pNET and PDAC, which can better inform therapeutic choice in clinical practice.
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Affiliation(s)
- Ming He
- From the Department of Radiology, Peking Union Medical College Hospital Beijing, China
| | - Zhenyu Liu
- From CAS Key Laboratory of Molecular Imaging, Beijing Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing and China and University of Chinese Academy of Sciences, Beijing, 100049, China; University of Chinese Academy of Sciences, Beijing, 100080, China
| | - Yusong Lin
- From the Software Technology School of Zhengzhou University, Zhengzhou, China
| | - Jianzhong Wan
- From the Software Technology School of Zhengzhou University, Zhengzhou, China
| | - Juan Li
- From the Department of Radiology, Peking Union Medical College Hospital Beijing, China
| | - Kai Xu
- From the Department of Radiology, Peking Union Medical College Hospital Beijing, China
| | - Yun Wang
- From the Department of Radiology, Peking Union Medical College Hospital Beijing, China
| | - Zhengyu Jin
- From the Department of Radiology, Peking Union Medical College Hospital Beijing, China
| | - Jie Tian
- From CAS Key Laboratory of Molecular Imaging, Beijing Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing and China and University of Chinese Academy of Sciences, Beijing, 100049, China; University of Chinese Academy of Sciences, Beijing, 100080, China; Beijing Advanced Innovation Center for Big Data-Based Precision Medicine, School of Medicine, Beihang University, Beijing, 100191, China; Engineering Research Center of Molecular and Neuro Imaging of Ministry of Education, School of Life Science and Technology, Xidian University, Xi'an, Shaanxi, 710126, China.
| | - Huadan Xue
- From the Department of Radiology, Peking Union Medical College Hospital Beijing, China.
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Guo CG, Ren S, Chen X, Wang QD, Xiao WB, Zhang JF, Duan SF, Wang ZQ. Pancreatic neuroendocrine tumor: prediction of the tumor grade using magnetic resonance imaging findings and texture analysis with 3-T magnetic resonance. Cancer Manag Res 2019; 11:1933-1944. [PMID: 30881119 PMCID: PMC6407516 DOI: 10.2147/cmar.s195376] [Citation(s) in RCA: 48] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022] Open
Abstract
PURPOSE The purpose of this study was to evaluate the performance of magnetic resonance imaging (MRI) findings and texture parameters for prediction of the histopathologic grade of pancreatic neuroendocrine tumors (PNETs) with 3-T magnetic resonance. PATIENTS AND METHODS PNETs are classified into Grade 1 (G1), Grade 2 (G2), and Grade 3 (G3) tumors based on the Ki-67 proliferation index and the mitotic activity. A total of 77 patients with pathologically confirmed PNETs met the inclusion criteria. Texture analysis (TA) was applied to T2-weighted imaging (T2WI) and diffusion-weighted imaging (DWI) maps. Patient demographics, MRI findings, and texture parameters were compared among three different histopathologic subtypes by using Fisher's exact tests or Kruskal-Wallis test. Then, logistic regression analysis was adopted to predict tumor grades. ROC curves and AUCs were calculated to assess the diagnostic performance of MRI findings and texture parameters in prediction of tumor grades. RESULTS There were 31 G1, 29 G2, and 17 G3 patients. Compared with G1, G2/G3 tumors showed higher frequencies of an ill-defined margin, a predominantly solid tumor type, local invasion or metastases, hypo-enhancement at the arterial phase, and restriction diffusion. Four T2-based (inverse difference moment, energy, correlation, and differenceEntropy) and five DWI-based (correlation, contrast, inverse difference moment, maxintensity, and entropy) TA parameters exhibited statistical significance among PNETs (P<0.001). The AUCs of six predicting models on T2WI and DWI ranged from 0.703-0.989. CONCLUSION Our data indicate that MRI findings, including tumor margin, texture, local invasion or metastases, tumor enhancement, and diffusion restriction, as well as texture parameters can aid the prediction of PNETs grading.
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Affiliation(s)
- Chuan-Gen Guo
- Department of Radiology, The First Affiliated Hospital, College of Medicine Zhejiang University, Hangzhou 310003, China
| | - Shuai Ren
- Department of Radiology, The Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing 210029, China,
| | - Xiao Chen
- Department of Radiology, The Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing 210029, China,
| | - Qi-Dong Wang
- Department of Radiology, The First Affiliated Hospital, College of Medicine Zhejiang University, Hangzhou 310003, China
| | - Wen-Bo Xiao
- Department of Radiology, The First Affiliated Hospital, College of Medicine Zhejiang University, Hangzhou 310003, China
| | - Jing-Feng Zhang
- Department of Radiology, The First Affiliated Hospital, College of Medicine Zhejiang University, Hangzhou 310003, China
| | | | - Zhong-Qiu Wang
- Department of Radiology, The Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing 210029, China,
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Ren S, Chen X, Wang J, Zhao R, Song L, Li H, Wang Z. Differentiation of duodenal gastrointestinal stromal tumors from hypervascular pancreatic neuroendocrine tumors in the pancreatic head using contrast-enhanced computed tomography. Abdom Radiol (NY) 2019; 44:867-876. [PMID: 30293109 DOI: 10.1007/s00261-018-1803-x] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
PURPOSE To determine useful contrast-enhanced computed tomography (CE-CT) features in differentiating duodenal gastrointestinal stromal tumors (duodenal GISTs) from hypervascular pancreatic neuroendocrine tumors in the pancreatic head (pancreatic head NETs). METHODS Seventeen patients with pathologically confirmed duodenal GISTs and 25 with pancreatic NETs underwent preoperative CE-CT. CT image analysis included tumor size, morphology, and contrast enhancement. Receiver operating characteristic curves were performed, and cutoff values were calculated to determine CT findings with high sensitivity and specificity. RESULTS CT imaging showed duodenal GISTs with higher frequencies of tumor central location close to the duodenum and a predominantly solid tumor type when compared with pancreatic head NETs (p < 0.05 for both). Duodenal GISTs were larger than pancreatic head NETs (3.3 ± 0.9 cm vs. 2.5 ± 1.1 cm, p = 0.03). Duodenal GISTs had significantly lower CT attenuation values (112.9 ± 17.9HU vs. 137.4 ± 32.1HU, p < 0.01) at the arterial phase and higher CT attenuation values at the delayed phase (94.3 ± 7.9HU vs. 84.9 ± 10.4HU, p < 0.01) when compared with pancreatic head NETs. A CT attenuation value of ≤ 135 HU at the arterial phase (30 s) was 76% sensitive, 94.1% specific, and 83.3% accurate for the diagnosis of duodenal GISTs, while a CT attenuation value of ≥ 89.5 HU at the delayed phase (120 s) was 93.3% sensitive, 81.8% specific, and 76.2% accurate for the diagnosis of duodenal GISTs. CONCLUSION Tumor central location, size, texture, and contrast enhancement are valuable characteristics for the differentiation between duodenal GISTs and hypervascular pancreatic head NETs during preoperative examination.
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Affiliation(s)
- Shuai Ren
- Department of Radiology, The Affiliated Hospital of Nanjing University of Chinese Medicine, No. 155 Hanzhong Road, Nanjing, 210029, Jiangsu Province, China
| | - Xiao Chen
- Department of Radiology, The Affiliated Hospital of Nanjing University of Chinese Medicine, No. 155 Hanzhong Road, Nanjing, 210029, Jiangsu Province, China
| | - Jianhua Wang
- Department of Radiology, The Affiliated Hospital of Nanjing University of Chinese Medicine, No. 155 Hanzhong Road, Nanjing, 210029, Jiangsu Province, China
| | - Rui Zhao
- Department of Radiology, The Affiliated Hospital of Nanjing University of Chinese Medicine, No. 155 Hanzhong Road, Nanjing, 210029, Jiangsu Province, China
| | - Lina Song
- Department of Radiology, The Affiliated Hospital of Nanjing University of Chinese Medicine, No. 155 Hanzhong Road, Nanjing, 210029, Jiangsu Province, China
| | - Hui Li
- Department of Pathology, The Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, 210029, Jiangsu Province, China
| | - Zhongqiu Wang
- Department of Radiology, The Affiliated Hospital of Nanjing University of Chinese Medicine, No. 155 Hanzhong Road, Nanjing, 210029, Jiangsu Province, China.
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Pancreatic neuroendocrine tumors: MR imaging features preoperatively predict lymph node metastasis. Abdom Radiol (NY) 2019; 44:1000-1009. [PMID: 30539251 DOI: 10.1007/s00261-018-1863-y] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
PURPOSES Predictive factors of lymph node metastasis (LNM) in pancreatic neuroendocrine tumors (pNETs) are not well established. We sought to identify the value of MR imaging features in preoperatively predicting the lymph node metastasis of pNETs. MATERIALS AND METHODS In this study, we enrolled 108 consecutive patients with pNETs between January 2009 and June 2018. MR morphologic features and quantitative data were evaluated. Predictors of LNM were evaluated using univariate and multivariate logistic regression models. RESULTS A total of 108 patients with pNETs were finally enrolled, including 82 LNM-negative and 26 LNM-positive patients. Features significantly related to the LNM of pNETs at univariate analysis were tumor size > 2 cm (P = 0.003), Ki-67 > 5% (P = 0.002), non-enhancement pattern (P < 0.001), apparent diffusion coefficient value (P < 0.001), main pancreatic duct dilation (P < 0.001) and pancreatic atrophy (P = 0.032) and extrapancreatic tumor spread (P = 0.001), CNRs during arterial, portal and delay phase (P = 0.005, 0.047, and 0.045, respectively), and histological classification (P = 0.006). At multivariate analysis, non-enhancement pattern (P = 0.019; odds ratio, 6.652; 95% CI 1.369, 32.321) and main pancreatic duct dilation (P = 0.018; odds ratio, 6.745; 95% CI 1.379, 32.991) were independent risk factors for predicting the LNM of pNETs. CONCLUSION The non-enhancement characteristic and main pancreatic duct dilation appear to be linked with LNM in pNETs. These radiological predictors can be easily obtained preoperatively, and may help to avoid missing pNETs with a high risk of LNM.
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