Magnetic Resonance Imaging-Based Assessment of Pancreatic Fat Strongly Correlates With Histology-Based Assessment of Pancreas Composition.

OBJECTIVE: The aim of the study is to assess the relationship between magnetic resonance imaging (MRI)-based estimation of pancreatic fat and histology-based measurement of pancreatic composition. MATERIALS AND METHODS: In this retrospective study, MRI was used to noninvasively estimate pancreatic fat content in preoperative images from high-risk individuals and disease controls having normal pancreata. A deep learning algorithm was used to label 11 tissue components at micron resolution in subsequent pancreatectomy histology. A linear model was used to determine correlation between histologic tissue composition and MRI fat estimation. RESULTS: Twenty-seven patients (mean age 64.0 ± 12.0 years [standard deviation], 15 women) were evaluated. The fat content measured by MRI ranged from 0% to 36.9%. Intrapancreatic histologic tissue fat content ranged from 0.8% to 38.3%. MRI pancreatic fat estimation positively correlated with microanatomical composition of fat (r = 0.90, 0.83 to 0.95], P < 0.001); as well as with pancreatic cancer precursor ( r = 0.65, P < 0.001); and collagen ( r = 0.46, P < 0.001) content, and negatively correlated with pancreatic acinar ( r = -0.85, P < 0.001) content. CONCLUSIONS: Pancreatic fat content, measurable by MRI, correlates to acinar content, stromal content (fibrosis), and presence of neoplastic precursors of cancer.

A novel approach to high accuracy of video-based microrheology.

Video-based particle tracking monitors the microscopic movement of labeled biomolecules and fluorescent probes within a complex cellular environment. Information gained from this technique enables us to extract the dynamic behavior of biomolecules and the local mechanical properties inside the cell from a tracked particle's mean-square displacement (MSD). However, MSD measurements are highly susceptible to static error introduced by noise in the image acquisition process that leads to an incorrect positioning of the particle. Static error can mask the subtle effects from the local microenvironment on the MSD and potentially generate misleading conclusions about the biophysical properties of cells. An approach that greatly increases the accuracy of MSD measurements is presented herein by combining experimental data with Monte Carlo simulations to eliminate the inherent static error. This practical method of static error correction greatly advances particle-tracking techniques.

Aspiration and compromise effect.

Consumers' choice is often influenced by numerous reference points, such as the consumers' aspiration for product quality. In this study, the effect of such aspiration in compromise was investigated. Two experiments with 722 participants (309 men and 413 women) indicated that, when the quality of a product was below participants' aspiration level, the compromise effect decreased.