Cross-sectional imaging of the pancreas in diabetes.

Diabetes mellitus presents a global health challenge characterized by dysregulated glucose metabolism and insulin resistance. Pancreas dysfunction contributes to the development and progression of diabetes. Cross-sectional imaging modalities have provided new insight into the structural and functional alterations of the pancreas in individuals with diabetes. This review summarizes MRI and CT studies that characterize pancreas alterations in both type 1 and type 2 diabetes and discusses future applications of these techniques.

A review of deep learning and radiomics approaches for pancreatic cancer diagnosis from medical imaging.

PURPOSE OF REVIEW: Early and accurate diagnosis of pancreatic cancer is crucial for improving patient outcomes, and artificial intelligence (AI) algorithms have the potential to play a vital role in computer-aided diagnosis of pancreatic cancer. In this review, we aim to provide the latest and relevant advances in AI, specifically deep learning (DL) and radiomics approaches, for pancreatic cancer diagnosis using cross-sectional imaging examinations such as computed tomography (CT) and magnetic resonance imaging (MRI). RECENT FINDINGS: This review highlights the recent developments in DL techniques applied to medical imaging, including convolutional neural networks (CNNs), transformer-based models, and novel deep learning architectures that focus on multitype pancreatic lesions, multiorgan and multitumor segmentation, as well as incorporating auxiliary information. We also discuss advancements in radiomics, such as improved imaging feature extraction, optimized machine learning classifiers and integration with clinical data. Furthermore, we explore implementing AI-based clinical decision support systems for pancreatic cancer diagnosis using medical imaging in practical settings. SUMMARY: Deep learning and radiomics with medical imaging have demonstrated strong potential to improve diagnostic accuracy of pancreatic cancer, facilitate personalized treatment planning, and identify prognostic and predictive biomarkers. However, challenges remain in translating research findings into clinical practice. More studies are required focusing on refining these methods, addressing significant limitations, and developing integrative approaches for data analysis to further advance the field of pancreatic cancer diagnosis.

Diagnosis of chronic pancreatitis using semi-quantitative MRI features of the pancreatic parenchyma: results from the multi-institutional MINIMAP study.

PURPOSE: To determine the diagnostic performance of parenchymal MRI features differentiating CP from controls. METHODS: This prospective study performed abdominal MRI scans at seven institutions, using 1.5 T Siemens and GE scanners, in 50 control and 51 definite CP participants, from February 2019 to May 2021. MRI parameters included the T1-weighted signal intensity ratio of the pancreas (T1 score), arterial-to-venous enhancement ratio (AVR) during venous and delayed phases, pancreas volume, and diameter. We evaluated the diagnostic performance of these parameters individually and two semi-quantitative MRI scores derived using logistic regression: SQ-MRI Model A (T1 score, AVR venous, and tail diameter) and Model B (T1 score, AVR venous, and volume). RESULTS: When compared to controls, CP participants showed a significantly lower mean T1 score (1.11 vs. 1.29), AVR venous (0.86 vs. 1.45), AVR delayed (1.07 vs. 1.57), volume (54.97 vs. 80.00 ml), and diameter of the head (2.05 vs. 2.39 cm), body (2.25 vs. 2.58 cm), and tail (1.98 vs. 2.51 cm) (p < 0.05 for all). AUCs for these individual MR parameters ranged from 0.66 to 0.79, while AUCs for the SQ-MRI scores were 0.82 and 0.81 for Model A (T1 score, AVR venous, and tail diameter) and Model B (T1 score, AVR venous, and volume), respectively. After propensity-matching adjustments for covariates, AUCs for Models A and B of the SQ-MRI scores increased to 0.92 and 0.93, respectively. CONCLUSION: Semi-quantitative parameters of the pancreatic parenchyma, including T1 score, enhancement ratio, pancreas volume, diameter and multi-parametric models combining these parameters are helpful in diagnosis of CP. Longitudinal analyses including more extensive population are warranted to develop new diagnostic criteria for CP.

Integrated Physiology of the Exocrine and Endocrine Compartments in Pancreatic Diseases: Workshop Proceedings.

The Integrated Physiology of the Exocrine and Endocrine Compartments in Pancreatic Diseases workshop was a 1.5-day scientific conference at the National Institutes of Health (Bethesda, MD) that engaged clinical and basic science investigators interested in diseases of the pancreas. This report provides a summary of the proceedings from the workshop. The goals of the workshop were to forge connections and identify gaps in knowledge that could guide future research directions. Presentations were segregated into six major theme areas, including 1) pancreas anatomy and physiology, 2) diabetes in the setting of exocrine disease, 3) metabolic influences on the exocrine pancreas, 4) genetic drivers of pancreatic diseases, 5) tools for integrated pancreatic analysis, and 6) implications of exocrine-endocrine cross talk. For each theme, multiple presentations were followed by panel discussions on specific topics relevant to each area of research; these are summarized here. Significantly, the discussions resulted in the identification of research gaps and opportunities for the field to address. In general, it was concluded that as a pancreas research community, we must more thoughtfully integrate our current knowledge of normal physiology as well as the disease mechanisms that underlie endocrine and exocrine disorders so that there is a better understanding of the interplay between these compartments.

Radiomics Boosts Deep Learning Model for IPMN Classification.

Intraductal Papillary Mucinous Neoplasm (IPMN) cysts are pre-malignant pancreas lesions, and they can progress into pancreatic cancer. Therefore, detecting and stratifying their risk level is of ultimate importance for effective treatment planning and disease control. However, this is a highly challenging task because of the diverse and irregular shape, texture, and size of the IPMN cysts as well as the pancreas. In this study, we propose a novel computer-aided diagnosis pipeline for IPMN risk classification from multi-contrast MRI scans. Our proposed analysis framework includes an efficient volumetric self-adapting segmentation strategy for pancreas delineation, followed by a newly designed deep learning-based classification scheme with a radiomics-based predictive approach. We test our proposed decision-fusion model in multi-center data sets of 246 multi-contrast MRI scans and obtain superior performance to the state of the art (SOTA) in this field. Our ablation studies demonstrate the significance of both radiomics and deep learning modules for achieving the new SOTA performance compared to international guidelines and published studies (81.9% vs 61.3% in accuracy). Our findings have important implications for clinical decision-making. In a series of rigorous experiments on multi-center data sets (246 MRI scans from five centers), we achieved unprecedented performance (81.9% accuracy). The code is available upon publication.

Rationale and Design for the Diabetes RElated to Acute Pancreatitis and Its Mechanisms Study: A Prospective Cohort Study From the Type 1 Diabetes in Acute Pancreatitis Consortium.

ABSTRACT: Acute pancreatitis (AP) is a disease characterized by an acute inflammatory phase followed by a convalescent phase. Diabetes mellitus (DM) was historically felt to be a transient phenomenon related to acute inflammation; however, it is increasingly recognized as an important late and chronic complication. There are several challenges that have prevented precisely determining the incidence rate of DM after AP and understanding the underlying mechanisms. The DREAM (Diabetes RElated to Acute Pancreatitis and its Mechanisms) Study is a prospective cohort study designed to address these and other knowledge gaps to provide the evidence needed to screen for, prevent, and treat DM after AP. In the following article, we summarize literature regarding the epidemiology of DM after AP and provide the rationale and an overview of the DREAM study.

Design and Rationale for the Use of Magnetic Resonance Imaging Biomarkers to Predict Diabetes After Acute Pancreatitis in the Diabetes RElated to Acute Pancreatitis and Its Mechanisms Study: From the Type 1 Diabetes in Acute Pancreatitis Consortium.

ABSTRACT: This core component of the Diabetes RElated to Acute pancreatitis and its Mechanisms (DREAM) study will examine the hypothesis that advanced magnetic resonance imaging (MRI) techniques can reflect underlying pathophysiologic changes and provide imaging biomarkers that predict diabetes mellitus (DM) after acute pancreatitis (AP). A subset of participants in the DREAM study will enroll and undergo serial MRI examinations using a specific research protocol. The aim of the study is to differentiate at-risk individuals from those who remain euglycemic by identifying parenchymal features after AP. Performing longitudinal MRI will enable us to observe and understand the natural history of post-AP DM. We will compare MRI parameters obtained by interrogating tissue properties in euglycemic, prediabetic, and incident diabetes subjects and correlate them with metabolic, genetic, and immunological phenotypes. Differentiating imaging parameters will be combined to develop a quantitative composite risk score. This composite risk score will potentially have the ability to monitor the risk of DM in clinical practice or trials. We will use artificial intelligence, specifically deep learning, algorithms to optimize the predictive ability of MRI. In addition to the research MRI, the DREAM study will also correlate clinical computed tomography and MRI scans with DM development.

Quantitative MRI of chronic pancreatitis: results from a multi-institutional prospective study, magnetic resonance imaging as a non-invasive method for assessment of pancreatic fibrosis (MINIMAP).

PURPOSE: To determine if quantitative MRI techniques can be helpful to evaluate chronic pancreatitis (CP) in a setting of multi-institutional study. METHODS: This study included a subgroup of participants (n = 101) enrolled in the Prospective Evaluation of Chronic Pancreatitis for Epidemiologic and Translational Studies (PROCEED) study (NCT03099850) from February 2019 to May 2021. MRI was performed on 1.5 T using Siemens and GE scanners at seven clinical centers across the USA. Quantitative MRI parameters of the pancreas included T1 relaxation time, extracellular volume (ECV) fraction, apparent diffusion coefficient (ADC), and fat signal fraction. We report the diagnostic performance and mean values within the control (n = 50) and CP (n = 51) groups. The T1, ECV and fat signal fraction were combined to generate the quantitative MRI score (Q-MRI). RESULTS: There was significantly higher T1 relaxation time; mean 669 ms (± 171) vs. 593 ms (± 82) (p = 0.006), ECV fraction; 40.2% (± 14.7) vs. 30.3% (± 11.9) (p < 0.001), and pancreatic fat signal fraction; 12.2% (± 5.5) vs. 8.2% (± 4.4) (p < 0.001) in the CP group compared to controls. The ADC was similar between groups (p = 0.45). The AUCs for the T1, ECV, and pancreatic fat signal fraction were 0.62, 0.72, and 0.73, respectively. The composite Q-MRI score improved the diagnostic performance (cross-validated AUC: 0.76). CONCLUSION: Quantitative MR parameters evaluating the pancreatic parenchyma (T1, ECV fraction, and fat signal fraction) are helpful in the diagnosis of CP. A Q-MRI score that combines these three MR parameters improves diagnostic performance. Further studies are warranted with larger study populations including patients with acute and recurrent acute pancreatitis and longitudinal follow-ups.

T1 signal intensity ratio of the pancreas as an imaging biomarker for the staging of chronic pancreatitis.

PURPOSE: Our purpose was to validate the T1 SIR (T1 score) as an imaging biomarker for the staging of CP in a large, multi-institutional, prospective study. METHODS: The prospective study population included 820 participants enrolled in the PROCEED study from nine clinical centers between June 2017 and December 2021. A radiologist at each institution used a standardized method to measure the T1 signal intensity of the pancreas and the reference organs (spleen, paraspinal muscle, liver), which was used to derive respective T1 scores. Participants were stratified according to the seven mechanistic stages of chronic pancreatitis (MSCP 0-6) based on their clinical history, MRCP, and CT findings. RESULTS: The mean pancreas-to-spleen T1 score was 1.30 in participants with chronic abdominal pain, 1.22 in those with acute or recurrent acute pancreatitis, and 1.03 in definite CP. After adjusting for covariates, we observed a linear, progressive decline in the pancreas-to-spleen T1 score with increasing MSCP from 0 to 6. The mean pancreas-to-spleen T1 scores were 1.34 (MSCP 0), 1.27 (MSCP 1), 1.21 (MSCP 2), 1.16 (MSCP 3), 1.18 (MSCP 4), 1.12 (MSCP 5), and 1.05 (MSCP 6) (p < 0.0001). The pancreas-to-liver and pancreas-to-muscle T1 scores showed less linear trends and wider confidence intervals. CONCLUSION: The T1 score calculated by SIR of the pancreas-to-spleen shows a negative linear correlation with the progression of chronic pancreatitis. It holds promise as a practical imaging biomarker in evaluating disease severity in clinical research and practice.

Histopathologic correlation of pancreatic fibrosis with pancreatic magnetic resonance imaging quantitative metrics and Cambridge classification.

PURPOSE: To determine the correlation of the T1-weighted signal intensity ratio (T1 SIR, or T1 Score) and arterial-to-delayed venous enhancement ratio (ADV ratio) of the pancreas with pancreatic fibrosis on histopathology. METHODS: Sixty consecutive adult CP patients who had an MRI/MRCP study prior to pancreatic surgery were analyzed. Three blinded observers measured T1 SIR of pancreas to spleen (T1 SIR p/s), pancreas-to-paraspinal muscle (T1 SIR p/m), ADV ratio, and Cambridge grade. Histopathologic grades were given by a gastrointestinal pathologist using Ammann's fibrosis score. Statistical analysis included Spearman's correlation coefficient of the T1 SIR, ADV ratio, Cambridge grade with the fibrosis score, and weighted kappa for interobserver agreement. RESULTS: The study population included 31 female and 29 male patients, with an average age of 52.1 (26-78 years). Correlations between fibrosis score and T1 SIR p/s, T1 SIR p/m, and ADV ratio were ρ = - 0.54 (p = 0.0001), ρ = - 0.19 (p = 0.19), and ρ = - 0.39 (p = 0.003), respectively. The correlation of Cambridge grade with fibrosis score was ρ = 0.26 (p = 0.07). There was substantial interobserver agreement (weighted kappa) for T1 SIR p/s (0.78), T1 SIR p/m (0.71), and ADV ratio (0.64). T1 SIR p/s of ≤ 1.20 provided a sensitivity of 74% and specificity of 50% (AUC: 0.74), while ADV ratio of ≤ 1.10 provided a sensitivity of 75% and specificity of 55% (AUC: 0.68) to detect a fibrosis score of ≥ 6. CONCLUSION: There is a moderate negative correlation between the T1 Score (SIR p/s) and ADV ratio with pancreatic fibrosis and a substantial interobserver agreement. These parenchymal metrics show a higher correlation than the Cambridge grade.

Integrated Physiology of the Exocrine and Endocrine Compartments in Pancreatic Diseases: Workshop Proceedings.

ABSTRACT: The "Integrated Physiology of the Exocrine and Endocrine Compartments in Pancreatic Diseases" Workshop was a 1.5-day scientific conference at the National Institutes of Health (Bethesda, MD) that engaged clinical and basic science investigators interested in diseases of the pancreas. This report summarizes the workshop proceedings. The goal of the workshop was to forge connections and identify gaps in knowledge that could guide future research directions. Presentations were segregated into 6 major themes, including (a) Pancreas Anatomy and Physiology; (b) Diabetes in the Setting of Exocrine Disease; (c) Metabolic Influences on the Exocrine Pancreas; (d) Genetic Drivers of Pancreatic Diseases; (e) Tools for Integrated Pancreatic Analysis; and (f) Implications of Exocrine-Endocrine Crosstalk. For each theme, there were multiple presentations followed by panel discussions on specific topics relevant to each area of research; these are summarized herein. Significantly, the discussions resulted in the identification of research gaps and opportunities for the field to address. In general, it was concluded that as a pancreas research community, we must more thoughtfully integrate our current knowledge of the normal physiology as well as the disease mechanisms that underlie endocrine and exocrine disorders so that there is a better understanding of the interplay between these compartments.

Renal Replacement Lipomatosis Presenting in the Setting of Ureteral Stricture with Absence of Renal Calculus Disease.

Renal replacement lipomatosis of the kidney is a rare, benign entity in which extensive fibrofatty proliferation of the renal sinus is associated with marked atrophy of the renal parenchyma. It is often associated with calculi or long-standing inflammation. This entity may be confused with a fatty neoplasm of the kidney. A 51-year-old woman with a past medical history of pancreas transplant for type 1 diabetes subsequently developed ureteral stricture. This was initially managed by a nephrostomy tube and nephroureterostomy stenting with periodic exchanges to help restore urine flow; however, the renal function of the kidney progressively declined with recurrent and complicated urinary tract infections. She presented for kidney transplant with right native nephrectomy. Gross examination of the right kidney revealed a 12.8 cm renal sinus lipomatous mass replacing much of the kidney. Microscopically, the mass consisted of mature adipose tissue with fibrous septae and occasional thick-walled vessels with prominent smooth muscle bundles. A rare atypical stromal cell was present, otherwise no significant cytologic atypia or lipoblasts were identified. After excluding fat-predominant angiomyolipoma and well-differentiated liposarcoma, a diagnosis of renal replacement lipomatosis was made. Renal replacement lipomatosis is a benign condition typically associated with a nonfunctioning or poorly functioning kidney often linked to renal calculus disease or chronic renal infection. The presentation in our case was atypical given an absence of associated renal calculus disease. This case is intended to increase awareness of this less commonly encountered entity as it may be confused with a fatty neoplasm of the kidney, some with malignant potential.

Magnetic resonance imaging-derived fat fraction predicts risk of malignancy in intraductal papillary mucinous neoplasm.

PURPOSE: Assess the relationship between MRI-derived pancreatic fat fraction and risk of malignancy in intraductal papillary mucinous neoplasm (IPMN). METHODS: MRIs of patients with IPMN who underwent pancreaticoduodenectomy were analyzed. IPMN with low-grade dysplasia (n = 29) were categorized as low-risk while IPMN at high risk of malignancy consisted of those with high-grade dysplasia/invasive carcinoma (n = 33). Pancreatic fat-fraction (FFmean) was measured using the 2-point Dixon-method. Images were evaluated for the high-risk stigmata and worrisome features according to the revised 2017 Fukuoka consensus criteria. Data on serum CA19-9, Diabetes Mellitus (DM) status, body mass index (BMI), and histological chronic pancreatitis were obtained. RESULTS: A significant difference in FFmean was found between the high-risk IPMN (11.45%) and low-risk IPMN (9.95%) groups (p = 0.027). Serum CA19-9 level (p = 0.021), presence of cyst wall enhancement (p = 0.029), and solid mass (p = 0.008) were significantly associated with high-risk IPMN. There was a significant correlation between FFmean and mural nodule size (r = 0.36, p Ë‚ 0.01), type 2 DM (r = 0.34, p Ë‚ 0.01), age (r = 0.31, p Ë‚ 0.05), serum CA 19-9 (r = 0.30, p Ë‚ 0.05), cyst diameter (r = 0.30, p Ë‚ 0.05), and main pancreatic duct diameter (r = 0.26, p Ë‚ 0.05). Regression analysis revealed FFmean (OR 1.103, p = 0.035) as an independent predictive variable of high-risk IPMN. CONCLUSION: FFmean is significantly associated with high-risk IPMN and an independent predictor of IPMN malignant risk. FFmean may have clinical utility as a biomarker to complement the current IPMN treatment algorithm and improve clinical decision making regarding the need for surgical resection or surveillance.

Role of standardized reporting and novel imaging markers in chronic pancreatitis.

PURPOSE OF REVIEW: This article reviews recent efforts about standardized imaging features and reporting of chronic pancreatitis and recently published or ongoing imaging studies, which aim to establish novel imaging biomarkers for detection of parenchymal changes seen in chronic pancreatitis. RECENT FINDINGS: New novel MRI techniques are being developed to increase the diagnostic yield of chronic pancreatitis specifically in the early stage. T1 relaxation time, T1 signal intensity ratio and extracellular volume fraction offer potential advantages over conventional cross-sectional imaging, including simplicity of analysis and more objective interpretation of observations allowing population-based comparisons. In addition, standardized definitions and reporting guidelines for chronic pancreatitis based on available evidence and expert consensus have been proposed. These new imaging biomarkers and reporting guidelines are being validated for prognostic/therapeutic assessment of adult patients participating in longitudinal studies of The Consortium for the Study of Chronic Pancreatitis, Diabetes and Pancreatic Cancer. SUMMARY: New imaging biomarkers derived from novel MRI sequences promise a new chapter for diagnosis and severity assessment of chronic pancreatitis; a cross-sectional imaging-based diagnostic criteria for chronic pancreatitis combining ductal and parenchymal findings. Standardized imaging findings and reporting guidelines of chronic pancreatitis would enhance longitudinal assessment of disease severity in clinical trials and improve communication between radiologists and pancreatologists in clinical practice.

Pancreatic cystic neoplasms and post-inflammatory cysts: interobserver agreement and diagnostic performance of MRI with MRCP.

PURPOSE: We aimed to answer several clinically relevant questions; (1) the interobserver agreement, (2) diagnostic performance of MRI with MRCP for (a) branch duct intraductal papillary mucinous neoplasms (BD-IPMN), mucinous cystic neoplasms (MCN) and serous cystic neoplasms (SCN), (b) distinguishing mucinous (BD-IPMN and MCN) from non-mucinous cysts, and (c) distinguishing three pancreatic cystic neoplasms (PCN) from post-inflammatory cysts (PIC). METHODS: A retrospective analysis was performed at a tertiary referral center for pancreatic diseases on 71 patients including 44 PCNs and 27 PICs. All PCNs were confirmed by surgical pathology to be 17 BD-IPMNs, 13 MCNs, and 14 SCNs. Main duct and mixed type IPMNs were excluded. Two experienced abdominal radiologists blindly reviewed all the images. RESULTS: Sensitivity of two radiologists for BD-IPMN, MCN and SCN was 88-94%, 62-69% and 57-64%, specificity of 67-78%, 67-78% and 67-78%, and accuracy of 77-82%, 65-75% and 63-73%, respectively. There was 80% sensitivity, 63-73% specificity, 70-76% accuracy for distinguishing mucinous from non-mucinous neoplasms, and 73-75% sensitivity, 67-78% specificity, 70-76% accuracy for distinguishing all PCNs from PICs. There was moderate-to-substantial interobserver agreement (Cohen's kappa: 0.65). CONCLUSION: Two experienced abdominal radiologists had moderate-to-high sensitivity, specificity, and accuracy for BD-IPMN, MCN, and SCN. The interobserver agreement was moderate-to-substantial. MRI with MRCP can help workup of incidental pancreatic cysts by distinguishing PCNs from PICs, and premalignant mucinous neoplasms from cysts with no malignant potential.

T1 mapping for the diagnosis of early chronic pancreatitis: correlation with Cambridge classification system.

OBJECTIVE: This study aims to determine if T1 relaxation time of the pancreas can detect parenchymal changes in early chronic pancreatitis (CP). METHODS: This study retrospectively analyzed 42 patients grouped as no CP (Cambridge 0; n = 21), equivocal (Cambridge 1; n = 12) or mild CP (Cambridge 2; n = 9) based on magnetic resonance cholangiopancreatography findings using the Cambridge classification as the reference standard. Unenhanced T1 maps were acquired using a three-dimensional dual flip-angle gradient-echo technique on the same 1.5 T scanner with the same imaging parameters. RESULTS: There was no significant difference between the T1 relaxation times of Cambridge 0 and 1 group (p = 0.58). There was a significant difference (p = 0.0003) in the mean T1 relaxation times of the pancreas between the combined Cambridge 0 and 1 (mean = 639 msec, 95% CI: 617, 660) and Cambridge 2 groups (mean = 726 msec, 95% CI: 692, 759). There was significant difference (p = 0.0009) in the mean T1 relaxation times of the pancreas between the Cambridge 0 (mean = 636 msec, 95% CI: 606, 666) and Cambridge 2 groups (mean = 726 msec, 95% CI: 692,759) as well as between Cambridge 1 (mean = 643 msec, 95% CI: 608, 679) and Cambridge 2 groups (mean = 726 msec, 95% CI: 692,759) (p = 0.0017). Bland-Altman analysis showed measurements of one reader to be marginally higher than the other by 15.7 msec (2.4%, p = 0.04). CONCLUSION: T1 mapping is a practical method capable of quantitatively reflecting morphologic changes even in the early stages of chronic pancreatitis, and demonstrates promise for future implementation in routine clinical imaging protocols. ADVANCES IN KNOWLEDGE: T1 mapping can distinguish subtle parenchymal changes seen in early stage CP, and demonstrates promise for implementation in routine imaging protocols for the diagnosis of CP.

Secretin-Enhanced MRCP: How and Why-AJR Expert Panel Narrative Review.

Secretin-enhanced MRCP (S-MRCP) has advantages over standard MRCP for imaging of the pancreaticobiliary tree. Through the use of secretin to induce fluid production from the pancreas and leveraging of fluid-sensitive MRCP sequences, S-MRCP facilitates visualization of ductal anatomy, and the findings provide insight into pancreatic function, allowing radiologists to provide additional insight into a range of pancreatic conditions. This narrative review provides detailed information on the practical implementation of S-MRCP, including patient preparation, logistics of secretin administration, and dynamic secretin-enhanced MRCP acquisition. Also discussed are radiologists' interpretation and reporting of S-MRCP examinations, including assessments of dynamic compliance of the main pancreatic duct and of duodenal fluid volume. Established indications for S-MRCP include pancreas divisum, anomalous pancreaticobiliary junction, Santorinicele, Wirsungocele, chronic pancreatitis, main pancreatic duct stenosis, and assessment of complex postoperative anatomy. Equivocal or controversial indications are also described along with an approach to such indications. These indications include acute and recurrent acute pancreatitis, pancreatic exocrine function, sphincter of Oddi dysfunction, and pancreatic neoplasms.