2D/3D ultrasound diagnosis of pediatric distal radius fractures by human readers vs artificial intelligence

Jessica Knight; Yuyue Zhou; Christopher Keen; Abhilash Rakkunedeth Hareendranathan; Fatima Alves-Pereira; Siyavesh Ghasseminia; Stephanie Wichuk; Alan Brilz; David Kirschner; Jacob Jaremko

doi:10.1038/s41598-023-41807-w

Scientific Reports (Sep 2023)

2D/3D ultrasound diagnosis of pediatric distal radius fractures by human readers vs artificial intelligence

Jessica Knight,
Yuyue Zhou,
Christopher Keen,
Abhilash Rakkunedeth Hareendranathan,
Fatima Alves-Pereira,
Siyavesh Ghasseminia,
Stephanie Wichuk,
Alan Brilz,
David Kirschner,
Jacob Jaremko

Affiliations

Jessica Knight: Department of Radiology and Diagnostic Imaging, Walter C. Mackenzie Health Sciences Centre, University of Alberta
Yuyue Zhou: Department of Radiology and Diagnostic Imaging, Walter C. Mackenzie Health Sciences Centre, University of Alberta
Christopher Keen: Department of Radiology and Diagnostic Imaging, Walter C. Mackenzie Health Sciences Centre, University of Alberta
Abhilash Rakkunedeth Hareendranathan: Department of Radiology and Diagnostic Imaging, Walter C. Mackenzie Health Sciences Centre, University of Alberta
Fatima Alves-Pereira: Department of Radiology and Diagnostic Imaging, Walter C. Mackenzie Health Sciences Centre, University of Alberta
Siyavesh Ghasseminia: Department of Radiology and Diagnostic Imaging, Walter C. Mackenzie Health Sciences Centre, University of Alberta
Stephanie Wichuk: Department of Radiology and Diagnostic Imaging, Walter C. Mackenzie Health Sciences Centre, University of Alberta
Alan Brilz: Department of Family Medicine, University of Alberta
David Kirschner: Department of Pediatrics, Edmonton Clinic Health Academy, University of Alberta
Jacob Jaremko: Department of Radiology and Diagnostic Imaging, Walter C. Mackenzie Health Sciences Centre, University of Alberta

DOI: https://doi.org/10.1038/s41598-023-41807-w
Journal volume & issue: Vol. 13, no. 1
pp. 1 – 10

Abstract

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Abstract Wrist trauma is common in children and generally requires radiography for exclusion of fractures, subjecting children to radiation and long wait times in the emergency department. Ultrasound (US) has potential to be a safer, faster diagnostic tool. This study aimed to determine how reliably US could detect distal radius fractures in children, to contrast the accuracy of 2DUS to 3DUS, and to assess the utility of artificial intelligence for image interpretation. 127 children were scanned with 2DUS and 3DUS on the affected wrist. US scans were then read by 7 blinded human readers and an AI model. With radiographs used as the gold standard, expert human readers obtained a mean sensitivity of 0.97 and 0.98 for 2DUS and 3DUS respectively. The AI model sensitivity was 0.91 and 1.00 for 2DUS and 3DUS respectively. Study data suggests that 2DUS is comparable to 3DUS and AI diagnosis is comparable to human experts.

Published in Scientific Reports

ISSN: 2045-2322 (Online)
Publisher: Nature Portfolio
Country of publisher: United Kingdom
LCC subjects: Medicine; Science
Website: https://www.nature.com/srep/

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