Scholarlink

Objective <p>Leg length discrepancy (LLD) and malalignment of the lower extremity can lead to pain and increased risk of osteoarthritis. Radiographic measurements on anteroposterior (AP) full-length radiographs can be used to assess LLD and lower extremity alignment. The primary aim of this study was to evaluate the accuracy of AI software in performing lower extremity radiographic measurements in patients with implants. The secondary aim was to compare its efficiency to that of radiologists.</p> Materials and Methods <p>This study used the following eight angles and five lengths: hip-knee-angle (HKA), anatomical-tibiofemoral angle (aTFA), anatomical-mechanical-axis angle (AMA), joint-line-convergence angle (JLCA), mechanical-lateral-proximal-femur-angle (mLPFA), mechanical-lateral-distal-femur-angle (mLDFA), mechanical-medial-proximal-tibia-angle (mMPTA), mechanical-lateral-distal-tibia- angle (mLDTA), femur length, tibia length, full leg length, leg-length-discrepancy (LLD), and mechanical-axis-deviation (MAD). Two radiologists and AI software independently performed these measurements on 156 legs. The statistical methods used to assess AI performance were intraclass correlation coefficient (ICC) and Bland–Altman analysis.</p> Results <p>The AI generated output for 129/156 legs. 11/13 of the variables showed excellent agreement (ICC ≥ 0.75) between AI and the readers. Bland Altman performance targets were met for 5/13 variables. The mean (standard deviation) reading time for the AI and two readers, respectively, was 38 (6) seconds, 181 (41) seconds, and 214 (77) seconds.</p> Conclusion <p>In a cohort with lower extremity metal implants, AI-based leg length measurements were fast and accurate although most angular measurements were not.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Are artificial intelligence generated lower extremity radiographic measurements accurate in a cohort with implants?

  • 期刊论文

  • 发表日期：

    2025年4月28日

查看全文
  • Holden Archer,
  • Shuda Xia,
  • Seth Reine,
  • Louis Camilo Vazquez,
  • Oganes Ashikyan,
  • Parham Pezeshk,
  • Ajay Kohli,
  • Yin Xi,
  • Joel E. Wells,
  • Allan Hummer,
  • Matthew Difranco,
  • Avneesh Chhabra

摘要

Objective

Leg length discrepancy (LLD) and malalignment of the lower extremity can lead to pain and increased risk of osteoarthritis. Radiographic measurements on anteroposterior (AP) full-length radiographs can be used to assess LLD and lower extremity alignment. The primary aim of this study was to evaluate the accuracy of AI software in performing lower extremity radiographic measurements in patients with implants. The secondary aim was to compare its efficiency to that of radiologists.

Materials and Methods

This study used the following eight angles and five lengths: hip-knee-angle (HKA), anatomical-tibiofemoral angle (aTFA), anatomical-mechanical-axis angle (AMA), joint-line-convergence angle (JLCA), mechanical-lateral-proximal-femur-angle (mLPFA), mechanical-lateral-distal-femur-angle (mLDFA), mechanical-medial-proximal-tibia-angle (mMPTA), mechanical-lateral-distal-tibia- angle (mLDTA), femur length, tibia length, full leg length, leg-length-discrepancy (LLD), and mechanical-axis-deviation (MAD). Two radiologists and AI software independently performed these measurements on 156 legs. The statistical methods used to assess AI performance were intraclass correlation coefficient (ICC) and Bland–Altman analysis.

Results

The AI generated output for 129/156 legs. 11/13 of the variables showed excellent agreement (ICC ≥ 0.75) between AI and the readers. Bland Altman performance targets were met for 5/13 variables. The mean (standard deviation) reading time for the AI and two readers, respectively, was 38 (6) seconds, 181 (41) seconds, and 214 (77) seconds.

Conclusion

In a cohort with lower extremity metal implants, AI-based leg length measurements were fast and accurate although most angular measurements were not.