AI Model Can Diagnose Fatty Liver Disease Using Chest X-Ray: Study

Researchers from Osaka Metropolitan University have created an AI-based model capable of identifying the condition using routine chest X-rays. The study, published in the journal Radiology Cardiothoracic Imaging, demonstrates that the new method offers a cost-effective and widely accessible alternative to current diagnostic tools that rely on specialized imaging equipment.

Fatty liver disease affects about one in four people worldwide and can lead to cirrhosis or liver cancer if untreated. While standard diagnostic tools like ultrasounds, CT scans, and MRIs are costly and require specialized equipment, chest X-rays are cheaper, widely used, and expose patients to minimal radiation. Though chest X-rays capture part of the liver, their potential for detecting fatty liver disease has been largely unexplored.

Recognizing this gap, Associate Professor Sawako Uchida-Kobayashi and Associate Professor Daiju Ueda from the Graduate School of Medicine at Osaka Metropolitan University led a study to develop an artificial intelligence model capable of detecting fatty liver disease from chest X-ray images. Using a retrospective dataset of 6,599 chest X-rays from 4,414 patients, the team trained the AI model with controlled attenuation parameter (CAP) scores, a recognized metric for liver fat content.