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van den Wittenboer GJ, van der Kolk BYM, Nijholt IM, Langius-Wiffen E, van Dijk RA, van Hasselt BAAM, Podlogar M, van den Brink WA, Bouma GJ, Schep NWL, Maas M, Boomsma MF. Diagnostic accuracy of an artificial intelligence algorithm versus radiologists for fracture detection on cervical spine CT. Eur Radiol 2024:10.1007/s00330-023-10559-6. [PMID: 38206401 DOI: 10.1007/s00330-023-10559-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2023] [Revised: 11/07/2023] [Accepted: 12/08/2023] [Indexed: 01/12/2024]
Abstract
OBJECTIVES To compare diagnostic accuracy of a deep learning artificial intelligence (AI) for cervical spine (C-spine) fracture detection on CT to attending radiologists and assess which undetected fractures were injuries in need of stabilising therapy (IST). METHODS This single-centre, retrospective diagnostic accuracy study included consecutive patients (age ≥18 years; 2007-2014) screened for C-spine fractures with CT. To validate ground truth, one radiologist and three neurosurgeons independently examined scans positive for fracture. Negative scans were followed up until 2022 through patient files and two radiologists reviewed negative scans that were flagged positive by AI. The neurosurgeons determined which fractures were ISTs. Diagnostic accuracy of AI and attending radiologists (index tests) were compared using McNemar. RESULTS Of the 2368 scans (median age, 48, interquartile range 30-65; 1441 men) analysed, 221 (9.3%) scans contained C-spine fractures with 133 IST. AI detected 158/221 scans with fractures (sensitivity 71.5%, 95% CI 65.5-77.4%) and 2118/2147 scans without fractures (specificity 98.6%, 95% CI 98.2-99.1). In comparison, attending radiologists detected 195/221 scans with fractures (sensitivity 88.2%, 95% CI 84.0-92.5%, p < 0.001) and 2130/2147 scans without fracture (specificity 99.2%, 95% CI 98.8-99.6, p = 0.07). Of the fractures undetected by AI 30/63 were ISTs versus 4/26 for radiologists. AI detected 22/26 fractures undetected by the radiologists, including 3/4 undetected ISTs. CONCLUSION Compared to attending radiologists, the artificial intelligence has a lower sensitivity and a higher miss rate of fractures in need of stabilising therapy; however, it detected most fractures undetected by the radiologists, including fractures in need of stabilising therapy. Clinical relevance statement The artificial intelligence algorithm missed more cervical spine fractures on CT than attending radiologists, but detected 84.6% of fractures undetected by radiologists, including fractures in need of stabilising therapy. KEY POINTS The impact of artificial intelligence for cervical spine fracture detection on CT on fracture management is unknown. The algorithm detected less fractures than attending radiologists, but detected most fractures undetected by the radiologists including almost all in need of stabilising therapy. The artificial intelligence algorithm shows potential as a concurrent reader.
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Affiliation(s)
- Gaby J van den Wittenboer
- Department of Radiology and Nuclear Medicine, Isala, Dr. van Heesweg 2, Zwolle, The Netherlands.
- Department of Emergency Medicine, Isala, Dr. van Heesweg 2, Zwolle, The Netherlands.
| | - Brigitta Y M van der Kolk
- Department of Radiology and Nuclear Medicine, Isala, Dr. van Heesweg 2, Zwolle, The Netherlands
- Department of Emergency Medicine, Isala, Dr. van Heesweg 2, Zwolle, The Netherlands
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Centers, location Academic Medical Center, Meibergdreef 9, Amsterdam, The Netherlands
| | - Ingrid M Nijholt
- Department of Radiology and Nuclear Medicine, Isala, Dr. van Heesweg 2, Zwolle, The Netherlands
| | - Eline Langius-Wiffen
- Department of Radiology and Nuclear Medicine, Isala, Dr. van Heesweg 2, Zwolle, The Netherlands
| | - Rogier A van Dijk
- Department of Radiology and Nuclear Medicine, Isala, Dr. van Heesweg 2, Zwolle, The Netherlands
| | | | - Martin Podlogar
- Department of Neurosurgery, Isala, Dr. van Heesweg 2, Zwolle, The Netherlands
| | | | - Gert Joan Bouma
- Department of Neurosurgery, Amsterdam University Medical Centers, Location Academic Medical Center, Meibergdreef 9, Amsterdam, The Netherlands
| | - Niels W L Schep
- Department of Trauma surgery, Maasstad Hospital, Maasstadweg 21, Rotterdam, The Netherlands
| | - Mario Maas
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Centers, location Academic Medical Center, Meibergdreef 9, Amsterdam, The Netherlands
- Amsterdam Movement Sciences, Amsterdam, The Netherlands
| | - Martijn F Boomsma
- Department of Radiology and Nuclear Medicine, Isala, Dr. van Heesweg 2, Zwolle, The Netherlands
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