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Artificial intelligence accurately detects fractures on X-rays

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Artificial intelligence (AI) can help physicians interpret X-rays after an injury and suspected fracture, a study by the Boston University School of Medicine (BUSM) has found.

Ali Guermazi, chief of radiology at VA Boston Healthcare System and professor of radiology and medicine at BUSM said fracture interpretation errors represent up to 24 per cent of harmful diagnostic errors seen in the emergency department.

He said inconsistencies in the radiographic diagnosis of fractures are more common during the evening and overnight hours (5 p.m. – 3 a.m.), and are likely related to non-expert reading and fatigue.

“Our AI algorithm can quickly and automatically detect X-rays that are positive for fractures and flag those studies in the system so that radiologists can prioritize reading X-rays with positive fractures.

“The system also highlights regions of interest with bounding boxes around areas where fractures are suspected. This can potentially contribute to less waiting time at the time of hospital or clinic visit before patients can get a positive diagnosis of fracture,”

The AI algorithm (AI BoneView), was trained on X-rays from multiple institutions to detect fractures of the limbs, pelvis, torso and lumbar spine and rib cage.

Expert human readers (musculoskeletal radiologists, who are subspecialised radiology doctors after receiving focused training on reading bone X-rays) defined the gold standard in this study and compared the performance of human readers with and without AI assistance.

A variety of readers were used to simulate real-life scenarios, including radiologists, orthopaedic surgeons, emergency physicians and physician assistants, rheumatologists, and family physicians, all of whom read X-rays in real clinical practice to diagnose fractures in their patients.

Each reader’s diagnostic accuracy of fractures, with and without AI assistance, were compared against the gold standard. They also assessed the diagnostic performance of AI alone against the gold standard.

AI assistance helped reduce missed fractures by 29 per cent and increased readers’ sensitivity by 16 per cent, and by 30 per cent for exams with more than one fracture while improving specificity by 5 per cent.

Guermazi said AI can be a powerful tool to help radiologists and other physicians to improve diagnostic performance and increase efficiency, while potentially improving the patient experience at the time of hospital or clinic visit.

“Our study was focused on fracture diagnosis, but a similar concept can be applied to other diseases and disorders.

“Our ongoing research interest is to how best to utilize AI to help human healthcare providers to improve patient care, rather than making AI replace human healthcare providers. Our study showed one such example.”

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