It is difficult to identify normal peritoneal folds and ligaments at imaging. However, infectious, inflammatory, neoplastic, and traumatic processes frequently involve the peritoneal cavity and its reflections; thus, it is important to identify the affected peritoneal ligaments and spaces. Knowledge of these structures is important for accurate reporting and helps elucidate the sites of involvement to the surgeon. The potential peritoneal spaces; the peritoneal reflections that form the peritoneal ligaments, mesenteries, and omenta; and the natural flow of peritoneal fluid determine the route of spread of intraperitoneal fluid and disease processes within the abdominal cavity. The peritoneal ligaments, mesenteries, and omenta also serve as boundaries for disease processes and as conduits for the spread of disease.

New cross-sectional imaging feature definitions and standardized reporting recommendations for chronic pancreatitis will allow a more standardized approach to diagnosis and assessment of disease severity for clinical trials. Chronic pancreatitis is an inflammatory condition of the pancreas with clinical manifestations ranging from abdominal pain, acute pancreatitis, exocrine and/or endocrine dysfunction, and pancreatic cancer. There is a need for longitudinal studies in well-phenotyped patients to ascertain the utility of cross-sectional imaging findings of chronic pancreatitis for diagnosis and assessment of disease severity. CT and MR cholangiopancreatography are the most common cross-sectional imaging studies performed for the evaluation of chronic pancreatitis. Currently, there are no universal reporting standards for chronic pancreatitis. Several features of chronic pancreatitis are applied clinically, such as calcifications, parenchymal T1 signal changes, focal or diffuse gland atrophy, or irregular contour of the gland. Such findings have not been incorporated into standardized diagnostic criteria. There is also lack of consensus on quantification of disease severity in chronic pancreatitis, other than by using ductal ...

Automated volumetric segmentation of the pancreas on cross-sectional imaging is needed for diagnosis and follow-up of pancreatic diseases. While CT-based pancreatic segmentation is more established, MRI-based segmentation methods are understudied, largely due to a lack of publicly available datasets, benchmarking research efforts, and domain-specific deep learning methods. In this retrospective study, we collected a large dataset (767 scans from 499 participants) of T1-weighted (T1 W) and T2-weighted (T2 W) abdominal MRI series from five centers between March 2004 and November 2022. We also collected CT scans of 1,350 patients from publicly available sources for benchmarking purposes. We introduced a new pancreas segmentation method, called PanSegNet, combining the strengths of nnUNet and a Transformer network with a new linear attention module enabling volumetric computation. We tested PanSegNet's accuracy in cross-modality (a total of 2,117 scans) and cross-center settings with Dice and Hausdorff distance (HD95) evaluation metrics. We used Cohen's kappa statistics for intra and inter-rater agreement evaluation and paired t-tests for volume and Dice comparisons, respectively. For segmentation accuracy, we achieved Dice coefficients of 88.3% (±7.2%, at case level) with CT, 85.0% (±7.9%) with T1 W MRI, and 86.3% (±6.4%) with T2 W MRI. There was a high correlation for pancreas volume prediction with R² of 0.91, 0.84, and 0.85 for CT, T1 W, and T2 W, respectively. We found moderate inter-observer (0.624 and 0.638 for T1 W and T2 W MRI, respectively) and high intra-observer agreement scores. All MRI data is made available at https://osf.io/kysnj/. Our source code is available at https://github.com/NUBagciLab/PaNSegNet.

OBJECTIVE. The purpose of this study was to determine if extracellular volume fraction and T1 mapping can be used to diagnose chronic pancreatitis (CP). MATERIALS AND METHODS. This HIPAA-compliant study analyzed 143 consecutive patients with and without CP who underwent MR imaging between May 2016 and February 2017. Patients were selected for the study according to inclusion and exclusion criteria that considered history and clinical and laboratory findings. Eligible patients (n = 119) were grouped as normal (n = 60) or with mild (n = 22), moderate (n = 27), or severe (n = 10) CP on the basis of MRCP findings using the Cambridge classification as the reference standard. T1 maps were acquired in unenhanced and late contrast-enhanced phases using a 3D dual flip-angle gradient-echo sequence. All patients were imaged on the same 3-T scanner using the same imaging parameters, contrast agent, and dosage. RESULTS. Mean extracellular volume fractions and T1 relaxation times were significantly different within the...