Objective: To compare diagnostic accuracy of artificial intelligence (AI) for cervical spine (C-spine) fracture detection on CT with attending radiologists.
Design: Retrospective, diagnostic accuracy study.
Methods: AI analyzed 2368 scans from patients screened for C-spine fracture with CT (2007-2014, fracture prevalence 9.3%). With the use of a validated reference standard, which includes information on injuries in need of stabilizing therapy (IST), diagnostic accuracy of AI and radiologists was calculated and subsequently compared.
Results: Median age was 48 years. AI detected 158/221 fractures and radiologists 195/221, with a sensitivity of respectively 71.5% and 88.2% (p<0.001). Specificity of the AI and the radiologists was comparable: 98.6% and 99.2% (p=0.07). Of the fractures undetected by AI, 30/63 were an IST versus 4/26 for radiologists. AI detected 22/26 scans with fractures undetected by radiologists.
Conclusion: Compared to attending radiologists, AI has a lower sensitivity and misses more ISTs; however, it detected most fractures undetected by the radiologists, including ISTs.