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Rho S, Martin S, Nigogosyan Z, Kushnir V, Mintz AJ, Hu ZI. Pancreatic tail cancer in the setting of pancreatitis with a review of the literature: A case report. Clin Case Rep 2023; 11:e8023. [PMID: 37830064 PMCID: PMC10565090 DOI: 10.1002/ccr3.8023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2023] [Revised: 08/26/2023] [Accepted: 09/25/2023] [Indexed: 10/14/2023] Open
Abstract
Environmental risk factors for pancreatic cancer include acute and chronic pancreatitis, obesity, and tobacco use. Differentiating a pancreatic neoplasm in a patient with pancreatitis can be challenging due to their similar presentations. A 57-year-old African American man with a history of congestive heart failure, pancreatitis, and incomplete pancreas divisum presented with an epigastric abdominal pain that radiated to his back. Imaging showed necrotizing pancreatitis, a developing splenic infarct, and a mass at the pancreas tail. The patient was discharged with pain medications and was recommended follow-up imaging after resolution of his pancreatitis. He was readmitted to the emergency department 2 weeks later with recurrent acute abdominal pain. Computed tomography scan of abdomen and pelvis followed by magnetic resonance imaging and endoscopic ultrasound revealed an infiltrative pancreatic tail mass. Biopsy of the mass confirmed a locally advanced pancreatic tail adenocarcinoma. Chronic pancreatitis is associated with pancreatic cancer. Practitioners should be aware of the co-existence of chronic pancreatitis and pancreatic cancer, and the initial steps to evaluate a malignancy in chronic pancreatitis.
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Affiliation(s)
- Shinji Rho
- School of MedicineWashington University School of MedicineSt. LouisMissouriUSA
| | - Sooyoung Martin
- Department of RadiologyWashington University School of MedicineSt. LouisMissouriUSA
| | - Zack Nigogosyan
- Department of RadiologyWashington University School of MedicineSt. LouisMissouriUSA
| | - Vladimir Kushnir
- Department of GastroenterologyWashington University School of MedicineSt. LouisMissouriUSA
| | - Aaron J. Mintz
- Department of RadiologyWashington University School of MedicineSt. LouisMissouriUSA
| | - Zishuo Ian Hu
- Department of Medicine, Division of Oncology, Section of Medical OncologyWashington University School of MedicineSt. LouisMissouriUSA
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2
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Yang J, Huang J, Zhang Y, Zeng K, Liao M, Jiang Z, Bao W, Lu Q. Contrast-enhanced ultrasound and contrast-enhanced computed tomography for differentiating mass-forming pancreatitis from pancreatic ductal adenocarcinoma: a meta-analysis. Chin Med J (Engl) 2023; 136:2028-2036. [PMID: 36728948 PMCID: PMC10476799 DOI: 10.1097/cm9.0000000000002300] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2022] [Indexed: 02/03/2023] Open
Abstract
BACKGROUND Patients with mass-forming pancreatitis (MFP) or pancreatic ductal adenocarcinoma (PDAC) presented similar clinical symptoms, but required different treatment approaches and had different survival outcomes. This meta-analysis aimed to compare the diagnostic performance of contrast-enhanced ultrasound (CEUS) and contrast-enhanced computed tomography (CECT) in differentiating MFP from PDAC. METHODS A literature search was performed in the PubMed, EMBASE (Ovid), Cochrane Library (CENTRAL), China National Knowledge Infrastructure (CNKI), Weipu (VIP), and WanFang databases to identify original studies published from inception to August 20, 2021. Studies reporting the diagnostic performances of CEUS and CECT for differentiating MFP from PDAC were included. The meta-analysis was performed with Stata 15.0 software. The outcomes included the pooled sensitivity, specificity, positive likelihood ratio (+LR), negative likelihood ratio (-LR), diagnostic odds ratio (DOR), and summary receiver operating characteristic (SROC) curves of CEUS and CECT. Meta-regression was conducted to investigate heterogeneity. Bayesian network meta-analysis was conducted to indirectly compare the overall diagnostic performance. RESULTS Twenty-six studies with 2115 pancreatic masses were included. The pooled sensitivity and specificity of CEUS for MFP were 82% (95% confidence interval [CI], 73%-88%; I2 = 0.00%) and 95% (95% CI, 90%-97%; I2 = 63.44%), respectively; the overall +LR, -LR, and DOR values were 15.12 (95% CI, 7.61-30.01), 0.19 (95% CI, 0.13-0.29), and 78.91 (95% CI, 30.94-201.27), respectively; and the area under the SROC curve (AUC) was 0.90 (95% CI, 0.87-92). However, the overall sensitivity and specificity of CECT were 81% (95% CI, 75-85%; I2 = 66.37%) and 94% (95% CI, 90-96%; I2 = 74.87%); the overall +LR, -LR, and DOR values were 12.91 (95% CI, 7.86-21.20), 0.21 (95% CI, 0.16-0.27), and 62.53 (95% CI, 34.45-113.51), respectively; and, the SROC AUC was 0.92 (95% CI, 0.90-0.94). The overall diagnostic accuracy of CEUS was comparable to that of CECT for the differential diagnosis of MFP and PDAC (relative DOR 1.26, 95% CI [0.42-3.83], P > 0.05). CONCLUSIONS CEUS and CECT have comparable diagnostic performance for differentiating MFP from PDAC, and should be considered as mutually complementary diagnostic tools for suspected focal pancreatic lesions.
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Affiliation(s)
- Jie Yang
- Department of Ultrasound, West China Hospital, Sichuan University, Chengdu, Sichuan 610041, China
| | - Jiayan Huang
- Laboratory of Ultrasound Medicine, West China Hospital, Sichuan University, Chengdu, Sichuan 610041, China
| | - Yonggang Zhang
- The Chinese Centre of Evidence-Based Medicine, West China Hospital, Sichuan University, Chengdu, Sichuan 610041, China
| | - Keyu Zeng
- Department of Ultrasound, West China Hospital, Sichuan University, Chengdu, Sichuan 610041, China
| | - Min Liao
- Department of Ultrasound, West China Hospital, Sichuan University, Chengdu, Sichuan 610041, China
| | - Zhenpeng Jiang
- Department of Ultrasound, West China Hospital, Sichuan University, Chengdu, Sichuan 610041, China
| | - Wuyongga Bao
- Department of Ultrasound, West China Hospital, Sichuan University, Chengdu, Sichuan 610041, China
| | - Qiang Lu
- Department of Ultrasound, West China Hospital, Sichuan University, Chengdu, Sichuan 610041, China
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Tornel-Avelar AI, Velarde Ruiz-Velasco JA, Pelaez-Luna M. Pancreatic cancer, autoimmune or chronic pancreatitis, beyond tissue diagnosis: Collateral imaging and clinical characteristics may differentiate them. World J Gastrointest Oncol 2023; 15:925-942. [PMID: 37389107 PMCID: PMC10302998 DOI: 10.4251/wjgo.v15.i6.925] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/20/2023] [Revised: 04/21/2023] [Accepted: 04/28/2023] [Indexed: 06/14/2023] Open
Abstract
Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal malignancies and is developing into the 2nd leading cause of cancer-related death. Often, the clinical and radiological presentation of PDAC may be mirrored by other inflammatory pancreatic masses, such as autoimmune pancreatitis (AIP) and mass-forming chronic pancreatitis (MFCP), making its diagnosis challenging. Differentiating AIP and MFCP from PDAC is vital due to significant therapeutic and prognostic implications. Current diagnostic criteria and tools allow the precise differentiation of benign from malignant masses; however, the diagnostic accuracy is imperfect. Major pancreatic resections have been performed in AIP cases under initial suspicion of PDAC after a diagnostic approach failed to provide an accurate diagnosis. It is not unusual that after a thorough diagnostic evaluation, the clinician is confronted with a pancreatic mass with uncertain diagnosis. In those cases, a re-evaluation must be entertained, preferably by an experienced multispecialty team including radiologists, pathologists, gastroenterologists, and surgeons, looking for disease-specific clinical, imaging, and histological hallmarks or collateral evidence that could favor a specific diagnosis. Our aim is to describe current diagnostic limitations that hinder our ability to reach an accurate diagnosis among AIP, PDAC, and MFCP and to highlight those disease-specific clinical, radiological, serological, and histological characteristics that could support the presence of any of these three disorders when facing a pancreatic mass with uncertain diagnosis after an initial diagnostic approach has been unsuccessful.
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Affiliation(s)
- Ana I Tornel-Avelar
- Department of Gastroenterology, Hospital Civil of Guadalajara “Fray Antonio Alcalde”, Guadalajara 44340, Jalisco, Mexico
| | | | - Mario Pelaez-Luna
- Research Division School of Medicine/Department of Gastroenterology, Universidad Nacional Autonoma de México/National Institute of Medical Sciences and Nutrition “Salvador Zubiran”, Tlalpan 14000, Mexico City, Mexico
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4
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Wang F, Guo H, Li S, Xu J, Yu D. The value of enhanced CT features and texture-signatures in assessing the inflammatory infiltration of pancreatic ductal adenocarcinoma. Front Oncol 2023; 13:1078861. [PMID: 36816950 PMCID: PMC9936180 DOI: 10.3389/fonc.2023.1078861] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2022] [Accepted: 01/16/2023] [Indexed: 02/05/2023] Open
Abstract
Purpose To explore the predictive value of computed tomography (CT) imaging features and CT-based texture analysis in assessing inflammatory infiltration in pancreatic ductal adenocarcinoma (PDAC). Methods A total of 43 patients with PDAC confirmed by surgical pathology were included in the study. The clinical, radiological, surgical, and pathological features of the patients were analyzed retrospectively using the chi-square test or Spearman's correlation. Receiver operating characteristic (ROC) curves were utilized to assess the overall predictive ability of the tumor enhancement degree on triphasic contrast-enhanced CT images for the inflammatory infiltration degree in PDAC. Furthermore, all CT data were uploaded to the RadCloud platform for region of interest (ROI) delineation and feature extraction. Then, the Variance Threshold and SelectKBest algorithms were used to find the optimal CT features. Binary logistic regression was employed to analyze the selected features in all three contrast-enhanced CT phases, and regression equations were formulated. ROC analysis was performed to evaluate the predictive effectiveness of each equation. Results The analysis revealed a statistically significant correlation between the degree of differentiation and radiological findings such as necrosis and cystic degeneration, vascular invasion, and the presence of ascites (P < 0.05). The enhancement degree of the tumor in both the arterial and venous phases was significantly correlated with the inflammatory infiltration degree (P < 0.05); however, the areas under the ROC curve (AUCs) of arterial and venous enhancement were 0.570 and 0.542, respectively. Regression equations based on the texture features of triphasic contrast-enhanced tumors were formulated, and their AUCs were 0.982, 0.643, and 0.849. Conclusion Conventional radiological features are not significantly correlated with the degree of inflammatory infiltration in PDAC. The enhancement degrees in both the arterial phase and venous phase were statistically correlated with the inflammatory infiltration level but had poor predictive value. The texture features of PDAC on contrast-enhanced CT may show a better assessment value, especially in the arterial phase.
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Affiliation(s)
- Fangqing Wang
- Department of Radiology, Qilu Hospital of Shandong University, Jinan, China
| | - Hang Guo
- Department of Radiology, Laiyang Central Hospital of Yantai, Yantai, China
| | - Shunjia Li
- Department of Radiation Oncology, Qilu Hospital of Shandong University, Jinan, China
| | - Jianwei Xu
- Department of Pancreatic Surgery, Qilu Hospital of Shandong University, Jinan, China
| | - Dexin Yu
- Department of Radiology, Qilu Hospital of Shandong University, Jinan, China,*Correspondence: Dexin Yu,
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Mass-Forming Chronic Pancreatitis: Diagnostic Performance of PET/CT. World J Nucl Med 2022; 21:239-243. [PMID: 36060080 PMCID: PMC9436516 DOI: 10.1055/s-0042-1750438] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/31/2022] Open
Abstract
AbstractMass-forming chronic pancreatitis and pancreatic ductal adenocarcinoma are most commonly located in the head of pancreas, and there is a marked overlap in clinical features and imaging findings that makes it diagnostically challenging, although prognosis and management of both these entities differ. Differentiation is made even more difficult when surgical exploratory biopsy is obtained. Radical surgical resection remains the standard of care for pancreatic ductal adenocarcinoma and conservative treatment is effective for mass-forming chronic pancreatitis. Misdiagnosis of mass-forming chronic pancreatitis as pancreatic ductal adenocarcinoma results in unnecessary surgical intervention, and misdiagnosis of pancreatic ductal adenocarcinoma as mass-forming chronic pancreatitis results in delay in surgical intervention when required. Fluorodeoxyglucose-positron emission tomography/computed tomography can reliably be used for tissue characterization of mass-forming chronic pancreatitis and for monitoring disease response following treatment. Although differentiation of mass-like lesions of pancreas is reliably made on histopathology, significant false-negative rate is a major drawback that has a negative effect on diagnosis. This case report describes a rare presentation of mass-forming chronic pancreatitis with florid dystrophic calcifications in a 60-year-old male.
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Ha J, Kim DW, Choi SH. Author's reply: "ADC values from diffusion-weighted imaging may be lower for autoimmune pancreatitis than for pancreatic ductal adenocarcinoma". Dig Liver Dis 2022; 54:994-995. [PMID: 35614006 DOI: 10.1016/j.dld.2022.04.021] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/15/2022] [Revised: 04/21/2022] [Accepted: 04/26/2022] [Indexed: 12/12/2022]
Affiliation(s)
- Jiyeon Ha
- Department of Radiology, Kangdong Seong-Sim Hospital, Hallym University College of Medicine, Seoul, Korea
| | - Dong Wook Kim
- Department of Radiology and the Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Korea
| | - Sang Hyun Choi
- Department of Radiology and the Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Korea.
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Iwasa Y, Iwashita T, Ichikawa H, Mita N, Uemura S, Yoshida K, Iwata K, Mukai T, Yasuda I, Shimizu M. Efficacy of Contrast-Enhanced Harmonic Endoscopic Ultrasound for Pancreatic Solid Tumors with a Combination of Qualitative and Quantitative Analyses: A Prospective Pilot Study. Dig Dis Sci 2022; 67:1054-1064. [PMID: 33730346 DOI: 10.1007/s10620-021-06931-5] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/11/2020] [Accepted: 02/26/2021] [Indexed: 12/09/2022]
Abstract
INTRODUCTION Image evaluation of contrast-enhanced harmonic endoscopic ultrasound (CEH-EUS) and additional time-intensity curve (TIC) analysis enable qualitative and quantitative analyses of pancreatic tumor based on real-time perfusion imaging. AIMS To evaluate the efficacy of CEH-EUS with a combination of qualitative and quantitative analyses of pancreatic solid tumors. METHODS Patients were scheduled to undergo EUS-guided fine needle aspiration (FNA) for pancreatic solid tumors were prospectively enrolled between 11/2016 and 12/2018 and underwent CEH-EUS. The vascular and enhancement patterns were qualitatively evaluated and heterogeneous enhancement was defined to be indicative of malignancy. The echo intensity change during 60 s in the tumor was quantitatively evaluated by time intensity curve analysis. RESULTS In total, 100 patients were enrolled in this study. The final diagnoses were malignant lesions in 87 patients and benign legions in 13 patients. There were four categories of enhancement and patterns: hypovascular with heterogeneous, hypovascular with homogeneous, hypervascular heterogeneous, and hypervascular homogeneous enhancement. The diagnostic capability of qualitative analysis was the sensitivity, specificity, and accuracy of 89%, 62%, and 85%, respectively. With respect to time intensity curve analysis, the time to peak of malignant lesions was significantly shorter than those of benign lesions (P = 0.0009) with an optimal cutoff value of 12.81 s on the receiver operating characteristic curve analysis. With the combination of qualitative and quantitative analyses, the sensitivity, specificity, and accuracy were improved to 100%, 54%, and 94%, respectively. CONCLUSIONS CEH-EUS with combined qualitative and quantitative analyses for pancreatic tumors might be useful as a complement for EUS-FNA. The UMIN Clinical Trials Registry (UMIN000025192).
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Affiliation(s)
- Yuhei Iwasa
- First Department of Internal Medicine, Gifu University Hospital, Gifu, Japan
| | - Takuji Iwashita
- First Department of Internal Medicine, Gifu University Hospital, Gifu, Japan.
| | - Hironao Ichikawa
- First Department of Internal Medicine, Gifu University Hospital, Gifu, Japan
| | - Naoki Mita
- First Department of Internal Medicine, Gifu University Hospital, Gifu, Japan
| | - Shinya Uemura
- First Department of Internal Medicine, Gifu University Hospital, Gifu, Japan
| | - Kensaku Yoshida
- Department of Gastroenterology, Gifu Prefectural General Medical Center, Gifu, Japan
| | - Keisuke Iwata
- Department of Gastroenterology, Gifu Prefectural General Medical Center, Gifu, Japan
| | - Tsuyoshi Mukai
- Department of Gastroenterology, Gifu Municipal Hospital, Gifu, Japan
| | - Ichiro Yasuda
- Third Department of Internal Medicine, University of Toyama Hospital, Toyama, Japan
| | - Masahito Shimizu
- First Department of Internal Medicine, Gifu University Hospital, Gifu, Japan
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Tikhonova VS, Gruzdev IS, Kondratyev EV, Mikhaylyuk KA, Kаrmаzаnovsky GG. Texture analysis of contrast enhancement СT in the differential diagnosis of mass-forming pancreatitis and pancreatic ductal adenocarcinoma. MEDICAL VISUALIZATION 2022. [DOI: 10.24835/1607-0763-1068] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/05/2025]
Abstract
Purpose. Improving the efficiency of CT in the differential diagnosis of mass-forming pancreatitis (MFP) and pancreatic ductal adenocarcinoma (PDAC) making a diagnostic model based using a combination of texture features and contrast enhancement features.Methods and materials. 45 patients with histologically confirmed non-metastatic locally advanced PDAC and 13 patients with MFP where underwent CT examination with contrast enhancement. For each group, the ratio of the densities of intact pancreatic tissue and tumors, the relative tumor enhancement ratio (RTE) in all enhanced phases of CT, 94 texture features for each phase of the study were calculated and compared. The selection of predictors in the logistic model was carried out in 2 stages: 1) selection of predictors based on one-factor logistic models, the selection criterion was p@adj <0.2; 2) selection of predictors using LASSO-regression after standardization of variables. The selected predictors were included in a logistic regression model without interactions.>Results. There were statistically significant differences in 14, 17, 4 out of 94 for the unenhanced, arterial, and venous phases of the study, respectively (p < 0.05). After selection, the final diagnostic model included the texture features CONVENTIONAL HUQ2 and DISCRETIZED HUQ1 for the unenhanced phase, DISCRETIZED HUQ1 and GLRLM RLNU for the arterial phase, DISCRETIZED Skewness for the venous phase, RTE for the delayed CT phase. The diagnostic model was built showed an accuracy of 81% in the diagnosis of MFP.Conclusion. We have developed a diagnostic model, including textural parameters and contrast enhancement features, which allows preoperatively distinguish MFP and PDAC, the developed model will increase the accuracy of preoperative diagnosis.
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Affiliation(s)
- V. S. Tikhonova
- Vishnevsky National Medical Research Center of Surgery of the Ministry of Health of the Russian Federation
| | - I. S. Gruzdev
- Vishnevsky National Medical Research Center of Surgery of the Ministry of Health of the Russian Federation
| | - E. V. Kondratyev
- Vishnevsky National Medical Research Center of Surgery of the Ministry of Health of the Russian Federation
| | - K. A. Mikhaylyuk
- Vishnevsky National Medical Research Center of Surgery of the Ministry of Health of the Russian Federation
| | - G. G. Kаrmаzаnovsky
- Vishnevsky National Medical Research Center of Surgery of the Ministry of Health of the Russian Federation; Russian National Research Medical University named after N. I. Pirogov
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Ma X, Wang YR, Zhuo LY, Yin XP, Ren JL, Li CY, Xing LH, Zheng TT. Retrospective Analysis of the Value of Enhanced CT Radiomics Analysis in the Differential Diagnosis Between Pancreatic Cancer and Chronic Pancreatitis. Int J Gen Med 2022; 15:233-241. [PMID: 35023961 PMCID: PMC8747707 DOI: 10.2147/ijgm.s337455] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2021] [Accepted: 12/13/2021] [Indexed: 12/12/2022] Open
Abstract
Purpose To investigate the feasibility of enhanced computed tomography (CT) radiomics analysis to differentiate between pancreatic cancer (PC) and chronic pancreatitis. Methods and materials The CT images of 151 PCs and 24 chronic pancreatitis were retrospectively analyzed in the three-dimensional regions of interest on arterial phase (AP) and venous phase (VP) and segmented by MITK software. A multivariable logistic regression model was established based on the selected radiomics features. The radiomics score was calculated, and the nomogram was established. The discrimination of each model was analyzed by the receiver operating characteristic curve (ROC). Decision curve analysis (DCA) was used to evaluate clinical utility. The precision recall curve (PRC) was used to evaluate whether the model is affected by data imbalance. The Delong test was adopted to compare the diagnostic efficiency of each model. Results Significant differences were observed in the distribution of gender (P = 0.034), carbohydrate antigen 19-9 (P < 0.001), and carcinoembryonic antigen (P < 0.001) in patients with PC and chronic pancreatitis. The area under the ROC curve (AUC) value of AP multivariate regression model, VP multivariate regression model, AP combined with VP features model (Radiomics), clinical feature model, and radiomics combined with clinical feature model (COMB) was 0.905, 0.941, 0.941, 0.822, and 0.980, respectively. The sensitivity and specificity of the COMB model were 0.947 and 0.917, respectively. The results of DCA showed that the COMB model exhibited net clinical benefits and PRC shows that COMB model have good precision and recall (sensitivity). Conclusion The COMB model could be a potential tool to distinguish PC from chronic pancreatitis and aid in clinical decisions.
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Affiliation(s)
- Xi Ma
- CT/MRI Room, Affiliated Hospital of Hebei University, Baoding, Hebei Province, 071000, People's Republic of China
| | - Yu-Rui Wang
- Department of Computed Tomography, Tangshan Gongren Hospital, Tangshan, Hebei Province, 063000, People's Republic of China
| | - Li-Yong Zhuo
- CT/MRI Room, Affiliated Hospital of Hebei University, Baoding, Hebei Province, 071000, People's Republic of China
| | - Xiao-Ping Yin
- CT/MRI Room, Affiliated Hospital of Hebei University, Baoding, Hebei Province, 071000, People's Republic of China
| | - Jia-Liang Ren
- GE Healthcare[Shanghai] Co Ltd, Shanghai, 210000, People's Republic of China
| | - Cai-Ying Li
- Department of Radiology, The Second Hospital of Hebei Medical University, Shijiazhuang, Hebei Province, 050000, People's Republic of China
| | - Li-Hong Xing
- CT/MRI Room, Affiliated Hospital of Hebei University, Baoding, Hebei Province, 071000, People's Republic of China
| | - Tong-Tong Zheng
- Department of Radiology, The Second Hospital of Hebei Medical University, Shijiazhuang, Hebei Province, 050000, People's Republic of China
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Marya NB, Powers PD, Chari ST, Gleeson FC, Leggett CL, Abu Dayyeh BK, Chandrasekhara V, Iyer PG, Majumder S, Pearson RK, Petersen BT, Rajan E, Sawas T, Storm AC, Vege SS, Chen S, Long Z, Hough DM, Mara K, Levy MJ. Utilisation of artificial intelligence for the development of an EUS-convolutional neural network model trained to enhance the diagnosis of autoimmune pancreatitis. Gut 2021; 70:1335-1344. [PMID: 33028668 DOI: 10.1136/gutjnl-2020-322821] [Citation(s) in RCA: 71] [Impact Index Per Article: 17.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/13/2020] [Revised: 09/10/2020] [Accepted: 09/15/2020] [Indexed: 02/06/2023]
Abstract
OBJECTIVE The diagnosis of autoimmune pancreatitis (AIP) is challenging. Sonographic and cross-sectional imaging findings of AIP closely mimic pancreatic ductal adenocarcinoma (PDAC) and techniques for tissue sampling of AIP are suboptimal. These limitations often result in delayed or failed diagnosis, which negatively impact patient management and outcomes. This study aimed to create an endoscopic ultrasound (EUS)-based convolutional neural network (CNN) model trained to differentiate AIP from PDAC, chronic pancreatitis (CP) and normal pancreas (NP), with sufficient performance to analyse EUS video in real time. DESIGN A database of still image and video data obtained from EUS examinations of cases of AIP, PDAC, CP and NP was used to develop a CNN. Occlusion heatmap analysis was used to identify sonographic features the CNN valued when differentiating AIP from PDAC. RESULTS From 583 patients (146 AIP, 292 PDAC, 72 CP and 73 NP), a total of 1 174 461 unique EUS images were extracted. For video data, the CNN processed 955 EUS frames per second and was: 99% sensitive, 98% specific for distinguishing AIP from NP; 94% sensitive, 71% specific for distinguishing AIP from CP; 90% sensitive, 93% specific for distinguishing AIP from PDAC; and 90% sensitive, 85% specific for distinguishing AIP from all studied conditions (ie, PDAC, CP and NP). CONCLUSION The developed EUS-CNN model accurately differentiated AIP from PDAC and benign pancreatic conditions, thereby offering the capability of earlier and more accurate diagnosis. Use of this model offers the potential for more timely and appropriate patient care and improved outcome.
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Affiliation(s)
- Neil B Marya
- Gastroenterology and Hepatology, Mayo Clinic, Rochester, Minnesota, USA
| | | | - Suresh T Chari
- Gastroenterology, Hepatology and Nutrition, University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Ferga C Gleeson
- Gastroenterology and Hepatology, Mayo Clinic, Rochester, Minnesota, USA
| | - Cadman L Leggett
- Gastroenterology and Hepatology, Mayo Clinic, Rochester, Minnesota, USA
| | | | | | - Prasad G Iyer
- Gastroenterology and Hepatology, Mayo Clinic, Rochester, Minnesota, USA
| | - Shounak Majumder
- Gastroenterology and Hepatology, Mayo Clinic, Rochester, Minnesota, USA
| | - Randall K Pearson
- Gastroenterology and Hepatology, Mayo Clinic, Rochester, Minnesota, USA
| | - Bret T Petersen
- Gastroenterology and Hepatology, Mayo Clinic, Rochester, Minnesota, USA
| | - Elizabeth Rajan
- Gastroenterology and Hepatology, Mayo Clinic, Rochester, Minnesota, USA
| | - Tarek Sawas
- Gastroenterology and Hepatology, Mayo Clinic, Rochester, Minnesota, USA
| | - Andrew C Storm
- Gastroenterology and Hepatology, Mayo Clinic, Rochester, Minnesota, USA
| | - Santhi S Vege
- Gastroenterology and Hepatology, Mayo Clinic, Rochester, Minnesota, USA
| | - Shigao Chen
- Diagnostic Radiology, Mayo Clinic, Rochester, Minnesota, USA
| | - Zaiyang Long
- Diagnostic Radiology, Mayo Clinic, Rochester, Minnesota, USA
| | - David M Hough
- Diagnostic Radiology, Mayo Clinic, Rochester, Minnesota, USA
| | - Kristin Mara
- Biomedical Statistics and Informatics, Mayo Clinic Rochester, Rochester, Minnesota, USA
| | - Michael J Levy
- Gastroenterology and Hepatology, Mayo Clinic, Rochester, Minnesota, USA
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11
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[Chronic pancreatitis : Characterization and differentiation from pancreatic cancer]. Radiologe 2021; 61:563-571. [PMID: 34002282 PMCID: PMC8187200 DOI: 10.1007/s00117-021-00857-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 04/19/2021] [Indexed: 12/02/2022]
Abstract
Klinisches/methodisches Problem Bei der chronischen Pankreatitis (CP) handelt es sich um eine langanhaltende Entzündung der Bauchspeicheldrüse, welche die normale Struktur und Funktion des Organs schädigt. Das breite Spektrum an entzündlichen Pankreaserkrankungen umfasst einzelne Entitäten, wie die fokale Pankreatitis (FP) oder den Pseudotumor („mass-forming pancreatitis“), welche radiomorphologisch ein Adenokarzinom der Bauchspeicheldrüse (PDAC) nachahmen können. In weiterer Folge kann eine Fehldiagnose zu einem vermeidbaren und unnötigen operativen Eingriff oder zu einer Therapieverzögerung führen. Radiologische Standardverfahren Der Ultraschall (US) ist das primäre bildgebende Verfahren zur Abklärung von Pankreaserkrankungen, gefolgt von kontrastmittelverstärkter Computertomographie (KM-CT), die als meistverwendete Methode bei der diagnostischen Abklärung von Bauchspeicheldrüsenerkrankungen gilt. Die Magnetresonanztomographie (MRT) und/oder die MR-Cholangiopankreatographie (MRCP) können als Problemlöser eingesetzt werden, um zwischen soliden und zystischen Läsionen zu unterscheiden sowie auch Anomalien der Pankreasgänge auszuschließen, welche bei rezidivierender akuter Pankreatitis (AP) vorhanden sein können, oder um frühe Anzeichen einer CP zu visualisieren. Die MRCP hat dabei die diagnostische endoskopische retrograde Cholangiopankreatographie (ERCP) in der Abklärung von therapeutischen Interventionen im Wesentlichen ersetzt. Empfehlung für die Praxis Folgender Übersichtsartikel fasst die relevanten Merkmale in der Computertomographie (CT) und MRT zusammen, um eine akkurate, frühzeitige Diagnose einer CP zu stellen und eine Differenzierung zwischen FP und Pankreaskarzinom zu ermöglichen, um somit – auch in schwierigen Fällen – ein adäquates Therapiemanagement zu gewährleisten.
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Varvanina G, Lesko K, Bordin D, Dubtsova E, Malykh M, Noskova K, Vinokurova L. Blood biomarkers and computed tomography for differential diagnosis of pancreatic cancer and chronic pancreatitis. DOKAZATEL'NAYA GASTROENTEROLOGIYA 2021; 10:12. [DOI: 10.17116/dokgastro20211004112] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/20/2023]
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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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Ha J, Choi SH, Byun JH, Kim KW, Kim SY, Kim JH, Kim HJ. Meta-analysis of CT and MRI for differentiation of autoimmune pancreatitis from pancreatic adenocarcinoma. Eur Radiol 2020; 31:3427-3438. [PMID: 33146798 DOI: 10.1007/s00330-020-07416-1] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2020] [Revised: 08/28/2020] [Accepted: 10/13/2020] [Indexed: 12/17/2022]
Abstract
OBJECTIVES To systematically determine the diagnostic performance of computed tomography (CT) and magnetic resonance imaging (MRI) for differentiating autoimmune pancreatitis (AIP) from pancreatic ductal adenocarcinoma (PDAC), with a comparison between the two imaging modalities. METHODS Literature search was conducted using PubMed and EMBASE databases to identify original articles published between 2009 and 2019 reporting the diagnostic performance of CT and MRI for differentiating AIP from PDAC. The meta-analytic sensitivity and specificity of CT and MRI were calculated, and compared using a bivariate random effects model. Subgroup analysis for differentiating focal AIP from PDAC was performed. RESULTS Of the 856 articles screened, 11 eligible articles are remained, i.e., five studies for CT, four for MRI, and two for both. The meta-analytic summary sensitivity and specificity of CT were 59% (95% confidence interval [CI], 41-75%) and 99% (95% CI, 88-100%), respectively, while those of MRI were 84% (95% CI, 68-93%) and 97% (95% CI, 87-99%). MRI had a significantly higher meta-analytic summary sensitivity than CT (84% vs. 59%, p = 0.02) but a similar specificity (97% vs. 99%, p = 0.18). In the subgroup analysis for focal AIP, the sensitivity for distinguishing between focal AIP and PDAC was lower than that for the overall analysis. MRI had a higher sensitivity than CT (76% vs. 50%, p = 0.28) but a similar specificity (97% vs. 98%, p = 0.07). CONCLUSION MRI might be clinically more useful to evaluate patients with AIP, particularly for differentiating AIP from PDAC. KEY POINTS • MRI had an overall good diagnostic performance to differentiate AIP from PDAC with a meta-analytic summary estimate of 83% for sensitivity and of 97% for specificity. • CT had a very high specificity (99%), but a suboptimal sensitivity (59%) for differentiating AIP from PDAC. • Compared with CT, MRI had a higher sensitivity, but a similar specificity.
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Affiliation(s)
- Jiyeon Ha
- Department of Radiology and the Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, 88 Olympic-Ro 43-Gil, Songpa-Gu, Seoul, 138-736, South Korea
| | - Sang Hyun Choi
- Department of Radiology and the Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, 88 Olympic-Ro 43-Gil, Songpa-Gu, Seoul, 138-736, South Korea.
| | - Jae Ho Byun
- Department of Radiology and the Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, 88 Olympic-Ro 43-Gil, Songpa-Gu, Seoul, 138-736, South Korea
| | - Kyung Won Kim
- Department of Radiology and the Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, 88 Olympic-Ro 43-Gil, Songpa-Gu, Seoul, 138-736, South Korea
| | - So Yeon Kim
- Department of Radiology and the Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, 88 Olympic-Ro 43-Gil, Songpa-Gu, Seoul, 138-736, South Korea
| | - Jin Hee Kim
- Department of Radiology and the Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, 88 Olympic-Ro 43-Gil, Songpa-Gu, Seoul, 138-736, South Korea
| | - Hyoung Jung Kim
- Department of Radiology and the Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, 88 Olympic-Ro 43-Gil, Songpa-Gu, Seoul, 138-736, South Korea
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