The JACR Focus Issue on Impact of AI on Workflow Optimization offers a collection of invited research and reviews that explore the ways in which AI technology is being regularly utilized across radiology practice types.

A machine-learning model developed by Weill Cornell Medicine investigators may provide clinicians with an early warning of a complication that can occur late in pregnancy.

Resection of tumors in the caudate lobe (a deep, hard-to-reach part of the liver) is recognized as one of the most technically challenging procedures in hepatic surgery

due to its unique anatomical position and complex vascular relationships.

 

Researchers at Boston University Chobanian & Avedisian School of Medicine now show that it is possible to remove the caudate lobe safely using a surgical robot, even in an older patient, and still remove the cancer completely. The clinical case they describe in the journal Annals of Surgical Oncology, combines two “guidance” tools (1) a hanging/traction technique using the Arantius ligament and (2) Indocyanine green (ICG) “negative staining” to clearly mark the caudate lobe boundaries and guide a margin-focused cancer operation in a very difficult area.