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17-06-2024 | Artificial Intelligence | Scientific Article

Automated weight-bearing foot measurements using an artificial intelligence–based software

Authors: Louis Lassalle, Nor-eddine Regnard, Jeanne Ventre, Vincent Marty, Lauryane Clovis, Zekun Zhang, Nicolas Nitche, Ali Guermazi, Jean-Denis Laredo

Published in: Skeletal Radiology

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Abstract

Objective

To assess the accuracy of an artificial intelligence (AI) software (BoneMetrics, Gleamer) in performing automated measurements on weight-bearing forefoot and lateral foot radiographs.

Methods

Consecutive forefoot and lateral foot radiographs were retrospectively collected from three imaging institutions. Two senior musculoskeletal radiologists independently annotated key points to measure the hallux valgus, first–second metatarsal, and first–fifth metatarsal angles on forefoot radiographs and the talus–first metatarsal, medial arch, and calcaneus inclination angles on lateral foot radiographs. The ground truth was defined as the mean of their measurements. Statistical analysis included mean absolute error (MAE), bias assessed with Bland–Altman analysis between the ground truth and AI prediction, and intraclass coefficient (ICC) between the manual ratings.

Results

Eighty forefoot radiographs were included (53 ± 17 years, 50 women), and 26 were excluded. Ninety-seven lateral foot radiographs were included (51 ± 20 years, 46 women), and 21 were excluded. MAE for the hallux valgus, first–second metatarsal, and first–fifth metatarsal angles on forefoot radiographs were respectively 1.2° (95% CI [1; 1.4], bias =  − 0.04°, ICC = 0.98), 0.7° (95% CI [0.6; 0.9], bias =  − 0.19°, ICC = 0.91) and 0.9° (95% CI [0.7; 1.1], bias = 0.44°, ICC = 0.96). MAE for the talus–first, medial arch, and calcaneal inclination angles on the lateral foot radiographs were respectively 3.9° (95% CI [3.4; 4.5], bias = 0.61° ICC = 0.88), 1.5° (95% CI [1.2; 1.8], bias =  − 0.18°, ICC = 0.95) and 1° (95% CI [0.8; 1.2], bias = 0.74°, ICC = 0.99). Bias and MAE between the ground truth and the AI prediction were low across all measurements. ICC between the two manual ratings was excellent, except for the talus–first metatarsal angle.

Conclusion

AI demonstrated potential for accurate and automated measurements on weight-bearing forefoot and lateral foot radiographs.
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Metadata
Title
Automated weight-bearing foot measurements using an artificial intelligence–based software
Authors
Louis Lassalle
Nor-eddine Regnard
Jeanne Ventre
Vincent Marty
Lauryane Clovis
Zekun Zhang
Nicolas Nitche
Ali Guermazi
Jean-Denis Laredo
Publication date
17-06-2024
Publisher
Springer Berlin Heidelberg
Published in
Skeletal Radiology
Print ISSN: 0364-2348
Electronic ISSN: 1432-2161
DOI
https://doi.org/10.1007/s00256-024-04726-z