AI Gives One-Stop Shopping for Urinary Stone Evaluation

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AuntMinnie.com, 10/3/2017, Erik L. Ridley

An artificial intelligence (AI) algorithm can accurately detect and classify urinary stones based solely on images from noncontrast single-energy CT scans, according to research presented at last week’s Society for Imaging Informatics in Medicine’s Conference on Machine Intelligence in Medical Imaging (C-MIMI) in Baltimore.

In a proof-of-concept study, an algorithm developed by a team from Massachusetts General Hospital (MGH) yielded more than 90% sensitivity and specificity for detecting urinary stones on single-energy CT scans. It was also highly accurate for classifying the stones by type — a task that typically requires dual-energy CT scans.

As a result, the algorithm shows potential as an efficient triage tool in the emergency setting for patients suspected of having urinary stones, according to presenter and doctoral student Hyunkwang Lee.

“It can provide faster prioritization of positive cases for radiologist review, and rapid and accurate diagnosis,” he said.