ArticleJournal of robotic surgery2026
Robotic-referenced automated measurement of acetabular cup orientation on postoperative CT: development and internal validation.
Article in Journal of robotic surgery, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Accurate measurement of acetabular cup orientation after total hip arthroplasty is essential, but postoperative CT relies on subjective, error-prone manual measurement. Robot-assisted surgery provides intraoperative cup-orientation measurements but is costly and not widely available. We aimed to develop and evaluate a deep-learning model measuring cup orientation on postoperative CT, using robotic navigation values as reference standard. This secondary analysis of a randomized trial (ChiCTR2200060115) analyzed 94 hips with robotic intraoperative angle measurements and postoperative CT (May 2023 to May 2024). A VGG16-based U-Net segmented key anatomical structures into three-dimensional point clouds. Three measurement pathways were compared: manual annotation, machine learning, and deep learning. The optimal model was integrated into a graphical user interface. Ninety-four hips (mean age, 57.0 years ± 9.5 [standard deviation]; 62 men) were evaluated using 27,821 CT images. The best model (PointNet++) achieved mean absolute errors of 4.48° (anteversion) and 3.89° (inclination), compared with 4.08°/ 5.52° for machine learning and 8.91°/ 8.70° for manual measurement, significantly outperforming manual measurement (both p < 0.05). Exploratory full-cohort Lewinnek classification was correct in 81/94 hips versus 57/94 with manual measurement; in internal validation, 71% and 81% of predictions were within 5° of the robotic reference. A deep-learning model developed using robotic navigation values showed promising internal-validation performance for automated cup-orientation measurement on postoperative CT; independent external validation is required before broader clinical application.Trial registration ChiCTR2200060115, 19 May 2022.
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