Louis Lassalle, Nor-Eddine Regnard, Jeanne Ventre, Vincent Marty, Lauryane Clovis, Zekun Zhang, Nicolas Nitche, Ali Guermazi, Jean-Denis Laredo
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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.</p><p><strong>Results: </strong>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.</p><p><strong>Conclusion: </strong>AI demonstrated potential for accurate and automated measurements on weight-bearing forefoot and lateral foot radiographs.</p>","PeriodicalId":21783,"journal":{"name":"Skeletal Radiology","volume":" ","pages":"229-241"},"PeriodicalIF":1.9000,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"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\",\"doi\":\"10.1007/s00256-024-04726-z\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Objective: </strong>To assess the accuracy of an artificial intelligence (AI) software (BoneMetrics, Gleamer) in performing automated measurements on weight-bearing forefoot and lateral foot radiographs.</p><p><strong>Methods: </strong>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.</p><p><strong>Results: </strong>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. 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引用次数: 0
摘要
目的评估人工智能（AI）软件（BoneMetrics，Gleamer）对负重前足和足外侧X光片进行自动测量的准确性：从三家影像机构回顾性地收集了连续的前足和足外侧X光片。两名资深肌肉骨骼放射科医生独立标注关键点，测量前足X光片上的拇指外翻、第一-第二跖骨和第一-第五跖骨角度，以及足外侧X光片上的距骨-第一跖骨、内侧足弓和小方块倾斜角度。地面真实值定义为其测量值的平均值。统计分析包括平均绝对误差 (MAE)、地面实况与人工智能预测之间的偏差评估（Bland-Altman 分析）以及人工评级之间的类内系数 (ICC)：结果：共纳入了 80 张前足X光片（53 ± 17 岁，50 位女性），排除了 26 张。纳入了 97 张足部外侧 X 光片（51 ± 20 岁，46 名女性），排除了 21 张。前足X光片上的外翻角、第一-第二跖骨角和第一-第五跖骨角的 MAE 分别为 1.2° (95% CI [1; 1.4]，偏差 = - 0.04°，ICC = 0.98）、0.7°（95% CI [0.6；0.9]，偏差 = - 0.19°，ICC = 0.91）和 0.9°（95% CI [0.7；1.1]，偏差 = 0.44°，ICC = 0.96）。足外侧X光片上距骨第一角、内侧足弓角和小关节倾斜角的 MAE 分别为 3.9° (95% CI [3.4; 4.5]，偏差 = 0.61° ICC = 0.88)、1.5° (95% CI [1.2; 1.8]，偏差 = - 0.18°，ICC = 0.95) 和 1° (95% CI [0.8; 1.2]，偏差 = 0.74°，ICC = 0.99)。在所有测量中，地面实况与人工智能预测之间的偏差和 MAE 都很低。除距骨-第一跖骨角外，两种人工评级之间的 ICC 非常好：人工智能展示了对负重前足和足外侧X光片进行准确自动测量的潜力。
Automated weight-bearing foot measurements using an artificial intelligence-based software.
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.
期刊介绍：
Skeletal Radiology provides a forum for the dissemination of current knowledge and information dealing with disorders of the musculoskeletal system including the spine. While emphasizing the radiological aspects of the many varied skeletal abnormalities, the journal also adopts an interdisciplinary approach, reflecting the membership of the International Skeletal Society. Thus, the anatomical, pathological, physiological, clinical, metabolic and epidemiological aspects of the many entities affecting the skeleton receive appropriate consideration.
This is the Journal of the International Skeletal Society and the Official Journal of the Society of Skeletal Radiology and the Australasian Musculoskelelal Imaging Group.
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