Artificial intelligence vs. radiologist: accuracy of wrist fracture detection on radiographs.

Autor: Cohen, Mathieu, Puntonet, Julien, Sanchez, Julien, Kierszbaum, Elliott, Crema, Michel, Soyer, Philippe, Dion, Elisabeth
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Zdroj: European Radiology; Jun2023, Vol. 33 Issue 6, p3974-3983, 10p, 4 Black and White Photographs, 1 Diagram, 5 Charts, 1 Graph
Abstrakt: Objective: To compare the performances of artificial intelligence (AI) to those of radiologists in wrist fracture detection on radiographs. Methods: This retrospective study included 637 patients (1917 radiographs) with wrist trauma between January 2017 and December 2019. The AI software used was a deep neuronal network algorithm. Ground truth was established by three senior musculoskeletal radiologists who compared the initial radiology reports (IRR) made by non-specialized radiologists, the results of AI, and the combination of AI and IRR (IR+AI) Results: A total of 318 fractures were reported by the senior radiologists in 247 patients. Sensitivity of AI (83%; 95% CI: 78–87%) was significantly greater than that of IRR (76%; 95% CI: 70–81%) (p < 0.001). Specificities were similar for AI (96%; 95% CI: 93–97%) and for IRR (96%; 95% CI: 94–98%) (p = 0.80). The combination of AI+IRR had a significantly greater sensitivity (88%; 95% CI: 84–92%) compared to AI and IRR (p < 0.001) and a lower specificity (92%; 95% CI: 89–95%) (p < 0.001). The sensitivity for scaphoid fracture detection was acceptable for AI (84%) and IRR (80%) but poor for the detection of other carpal bones fracture (41% for AI and 26% for IRR). Conclusions: Performance of AI in wrist fracture detection on radiographs is better than that of non-specialized radiologists. The combination of AI and radiologist's analysis yields best performances. Key Points: • Artificial intelligence has better performances for wrist fracture detection compared to non-expert radiologists in daily practice. • Performance of artificial intelligence greatly differs depending on the anatomical area. • Sensitivity of artificial intelligence for the detection of carpal bones fractures is 56%. [ABSTRACT FROM AUTHOR]
Databáze: Complementary Index
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