Introducing an AI tool for accurate diagnosis of cholelithiasis on abdominal CT scans

▴ artificial intelligence
It focuses on the integration of artificial intelligence in medicine, advancement of radiology, management of medical departments, research, and education of healthcare professionals.

A new artificial intelligence service for the detection of gallstone disease on CT scans has been launched in Moscow for the first time. This advanced neural network automates the identification of gallstones in the gallbladder, accurately measuring their size and accelerating the diagnostic process. Such technological innovation is expected to enhance the likelihood of successful treatment and patient recovery. Anastasia Rakova, Deputy Mayor of Moscow for Social Development, commented on the significance of this development.

Anastasia Rakova, Deputy Mayor of Moscow for Social Development, commented on the initiative, stating, “The capital is actively integrating artificial intelligence into its healthcare system. For the first time, we are deploying an algorithm specifically designed to detect gallstone disease on CT scans of abdominal organs. This condition is prevalent, affecting one-in-five adult patients on average, and often remains asymptomatic for extended periods, posing challenges for timely diagnosis. As a result, computed tomography (CT) has become a highly regarded diagnostic tool, particularly when initial assessments are unclear or require confirmation. The application of computer vision technology functions as an essential support mechanism for radiologists, drawing their attention to the presence of gallstones and providing automatic size measurements, ultimately enhancing diagnostic efficiency,” Rakova elaborated.

Prior to implementation in real patient cases, this AI service underwent rigorous testing to ensure its efficacy in identifying gallstones without mistakenly interpreting other conditions as anomalies. The integration of computer vision technology in medical practice aims to reduce diagnostic time and enhance accuracy.

“In developing artificial intelligence capabilities within our healthcare sector, our goal is to automate processes, thereby freeing radiologists from repetitive measurements. Furthermore, these algorithms serve as tools for validating clinical assessments, thereby enabling physicians to cross-verify their evaluations. We are pleased to announce that the capital's innovations will soon be accessible to regions across our country; at the beginning of 2024, we launched the Moscow artificial intelligence platform ‘MosMedAI’ for healthcare professionals. Currently, the platform offers 17 AI services designed to assist radiologists in detecting various conditions, including osteoporosis, breast cancer, pneumonia, and other diseases,” shared Yuri Vasiliev, Chief Consultant for Radiology and CEO of the Centre for Diagnostics and Telemedicine of the Moscow Healthcare Department.

To date, radiologists in Moscow have access to over 50 different AI services that support the interpretation of imaging studies.  Of these, nine integrated solutions are actively operational in the healthcare sector, with the neural network designed to detect multiple diseases on a single medical image. This development aligns with Moscow's healthcare strategy, which outlines initiatives extending through 2030.

Since 2020, artificially intelligent algorithms have been operational as part of a broader initiative to employ computer vision technologies in healthcare. The neural networks, integrated into the unified radiological information system, UMIAS, assist in medical imaging by identifying potential pathological areas through color-coded markings and providing clinically relevant measurements that facilitate the preparation of diagnostic reports.

The Center for Diagnostics and Telemedicine of the Moscow Healthcare Department is a leading scientific organization within the Social Development Complex of the Moscow Mayor's Office. It focuses on the integration of artificial intelligence in medicine, advancement of radiology, management of medical departments, research, and education of healthcare professionals.


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