A research paper by scientists at Capital Medical University proposed a diffusion tensor imaging (DTI)-based DenseNet to identify SVCI from subcortical ischemic vascular disease (SIVD) and to profile multidomain cognitive risks.

The research paper, published on May 13, 2026 in the journal Cyborg and Bionic Systems.

An investigator at the Icahn School of Medicine at Mount Sinai has received international recognition for innovative imaging research that may help physicians identify patients at increased risk of chronic kidney disease (CKD) before they undergo surgery for kidney tumors. Mira Liu, PhD, a postdoctoral fellow at the Mount Sinai BioMedical Engineering and Imaging Institute, received the prestigious W.S. Moore Award for Original Clinical Research at the 2026 International Society for Magnetic Resonance in Medicine & International Society for MR Radiographers & Technologists Annual Meeting & Exhibition.

A new study from the Keck School of Medicine of USC reveals subtle but widespread differences in the brain's communication networks in people with bipolar disorder — and how those differences relate to illness severity and treatment. In the largest diffusion MRI network analysis of bipolar disorder to date, researchers analyzed brain scans from 449 people with bipolar disorder and 510 healthy controls across 16 international research sites through the ENIGMA Bipolar Disorder Working Group. Using a network-based approach, they found that people with bipolar disorder had less densely connected brain networks, lower communication efficiency, and longer routes for information exchange compared to healthy controls. The most pronounced differences appeared in circuits involved in emotion regulation, reward processing, and self-reflection. The study also found that longer illness duration, history of psychosis, and number of manic episodes were each linked to distinct patterns of network disruption. Published in Biological Psychiatry, the findings provide a framework for understanding bipolar disorder at the level of brain systems rather than isolated regions — an essential step toward more personalized, biologically informed approaches to care.