Visualization of mouse pancreas architecture using MR microscopy

3D Virtual Pancreatography

We present 3D virtual pancreatography (VP), a novel visualization procedure and application for non-invasive diagnosis and classification of pancreatic lesions, the precursors of pancreatic cancer. Currently, non-invasive screening of patients is performed through visual inspection of 2D axis-aligned CT images, though the relevant features are often not clearly visible nor automatically detected. VP is an end-to-end visual diagnosis system that includes: A machine learning based automatic segmentation of the pancreatic gland and the lesions, a semi-automatic approach to extract the primary pancreatic duct, a machine learning based automatic classification of lesions into four prominent types, and specialized 3D and 2D exploratory visualizations of the pancreas, lesions and surrounding anatomy. We combine volume rendering with pancreas- and lesion-centric visualizations and measurements for effective diagnosis. We designed VP through close collaboration and feedback from expert radiologists, and evaluated it on multiple real-world CT datasets with various pancreatic lesions and case studies examined by the expert radiologists.

Abnormalities of the Exocrine Pancreas in Type 1 Diabetes

Type 1 diabetes (T1D) is considered a pancreatic beta cell-specific disease that results in absolute insulin deficiency. Nevertheless, clinical studies from 1940 onwards showed that patients with T1D had an abnormal exocrine pancreas due to the presence of subclinical exocrine insufficiency and acinar atrophy. Exocrine abnormalities are an important, and mostly neglected, characteristic associated with T1D. It is however still unclear whether the exocrine dysfunction in T1D is a primary damage caused by the same pathogenic event that led to beta cell destruction or secondary to beta cell loss. In this review, we collect evidence supporting the hypothesis that T1D is a combined endocrine-exocrine disease in which the loss of functional beta cell mass is most clinically apparent.

A non-invasive method of quantifying pancreatic volume in mice using micro-MRI

In experimental models of pancreatic growth and recovery, changes in pancreatic size are assessed by euthanizing a large cohort of animals at varying time points and measuring organ mass. However, to ascertain this information in clinical practice, patients with pancreatic disorders routinely undergo non-invasive cross-sectional imaging of the pancreas using magnetic resonance imaging (MRI) or computed tomography (CT). The aim of the current study was to develop a thin-sliced, optimized sequence protocol using a high field MRI to accurately calculate pancreatic volumes in the most common experimental animal, the mouse. Using a 7 Telsa Bruker micro-MRI system, we performed abdominal imaging in whole-fixed mice in three standard planes: axial, sagittal, and coronal. The contour of the pancreas was traced using Vitrea software and then transformed into a 3-dimensional (3D) reconstruction, from which volumetric measurements were calculated. Images were optimized using heart perfusion-fixation, T1 sequence analysis, and 0.2 to 0.4 mm thick slices. As proof of principle, increases in pancreatic volume among mice of different ages correlated tightly with increasing body weight. In summary, this is the first study to measure pancreatic volumes in mice, using a high field 7 Tesla micro-MRI and a thin-sliced, optimized sequence protocol. We anticipate that micro-MRI will improve the ability to non-invasively quantify changes in pancreatic size and will dramatically reduce the number of animals required to serially assess pancreatic growth and recovery.