Artificial intelligence-assisted three-dimensional preoperative planning with patient-specific cutting guides versus conventional planning and instrumentation in total knee arthroplasty: a prospective exploratory cohort study.
5 affiliations
- 1Third Clinical Medical College of Ningxia Medical University, People's Hospital of Ningxia Hui Autonomous Region, Yinchuan, 750004, People's Republic of China.
- 2Department of Orthopedics, People's Hospital of Ningxia Hui Autonomous Region, Ningxia Medical University, Yinchuan, 750002, People's Republic of China.
- 3Department of Anesthesiology, People's Hospital of Ningxia Hui Autonomous Region, Ningxia Medical University, Yinchuan, 750002, People's Republic of China.
- 4Department of Pain Management, The 2nd Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, 330006, Jiangxi, People's Republic of China. [email protected].
- 5Department of Orthopedics, People's Hospital of Ningxia Hui Autonomous Region, Ningxia Medical University, Yinchuan, 750002, People's Republic of China. [email protected].
Abstract
Background
Total knee arthroplasty (TKA) outcomes may be influenced by preoperative planning and accurate execution. This study compared an AI-assisted three-dimensional preoperative planning and patient-specific instrumentation (PSI) workflow with conventional planning and instrumentation for primary unilateral TKA. The AI-assisted workflow was a CT-based preoperative software platform for repeated virtual osteotomy, implant selection, component-position review, and virtual postoperative joint motion-state visualization; it was not robotic execution or a validated predictor of postoperative range of motion.Methods
In this single-center prospective exploratory cohort, 22 patients with knee osteoarthritis undergoing primary unilateral TKA were non-randomly allocated to an AI-assisted planning/PSI group (n = 11) or a Conventional group (n = 11). Outcomes were assessed preoperatively and at 2 and 6 months postoperatively. Clinical, perioperative, radiographic, and gait outcomes were compared using standard between-group and repeated-measures analyses. P values were interpreted as nominal because of the small sample size and multiple comparisons.Results
At 6 months, WOMAC scores were lower in the AI-assisted planning/PSI group than in the Conventional group [15.00 (14.00, 17.00) vs. 17.00 (15.00, 18.00); nominal P = 0.02]. KSS function scores were higher in the AI-assisted planning/PSI group at 2 and 6 months [80.00 (70.00, 90.00) vs. 55.00 (55.00, 60.00), and 80.00 (80.00, 90.00) vs. 70.00 (70.00, 70.00); both nominal P < 0.001]. Pain-related outcomes, HALP, drainage volume, and gait parameters showed directional between-group differences that were interpreted as exploratory and descriptive. Postoperative HKA deviation and HKA outlier rates were comparable, while coronal tibial component error was smaller in the AI-assisted planning/PSI group [0.4 (0.2, 0.7) vs. 0.9 (0.6, 1.1) degrees; nominal P = 0.018].Conclusions
In this exploratory cohort, AI-assisted planning with PSI was associated with selected short-term functional, perioperative, gait, and radiographic component-positioning differences, but not superior overall HKA alignment. Findings are preliminary and require confirmation in larger randomized or well-matched studies.
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BibTeX
@article{liu2026artificial,
title = {{Artificial intelligence-assisted three-dimensional preoperative planning with patient-specific cutting guides versus conventional planning and instrumentation in total knee arthroplasty: a prospective exploratory cohort study.}},
author = {Xueqi Liu and Hui Sun and Tianxiang Yang and Tao Ma and Yinbin Wang and Jun Li and Yi Wang and He Shang and Jian Wen and Desheng Chen},
journal = {Journal of orthopaedic surgery and research},
year = {2026},
month = aug,
doi = {10.1186/s13018-026-07132-4},
url = {https://europepmc.org/article/MED/43010001},
note = {CC BY},
}
RIS
TY - JOUR
TI - Artificial intelligence-assisted three-dimensional preoperative planning with patient-specific cutting guides versus conventional planning and instrumentation in total knee arthroplasty: a prospective exploratory cohort study.
AU - Xueqi Liu
AU - Hui Sun
AU - Tianxiang Yang
AU - Tao Ma
AU - Yinbin Wang
AU - Jun Li
AU - Yi Wang
AU - He Shang
AU - Jian Wen
AU - Desheng Chen
PY - 2026
DA - 2026/08/14
JO - Journal of orthopaedic surgery and research
DO - 10.1186/s13018-026-07132-4
UR - https://europepmc.org/article/MED/43010001
AB - Background Total knee arthroplasty (TKA) outcomes may be influenced by preoperative planning and accurate execution. This study compared an AI-assisted three-dimensional preoperative planning and patient-specific instrumentation (PSI) workflow with conventional planning and instrumentation for primary unilateral TKA. The AI-assisted workflow was a CT-based preoperative software platform for repeated virtual osteotomy, implant selection, component-position review, and virtual postoperative joint motion-state visualization; it was not robotic execution or a validated predictor of postoperative range of motion.Methods In this single-center prospective exploratory cohort, 22 patients with knee osteoarthritis undergoing primary unilateral TKA were non-randomly allocated to an AI-assisted planning/PSI group (n = 11) or a Conventional group (n = 11). Outcomes were assessed preoperatively and at 2 and 6 months postoperatively. Clinical, perioperative, radiographic, and gait outcomes were compared using standard between-group and repeated-measures analyses. P values were interpreted as nominal because of the small sample size and multiple comparisons.Results At 6 months, WOMAC scores were lower in the AI-assisted planning/PSI group than in the Conventional group [15.00 (14.00, 17.00) vs. 17.00 (15.00, 18.00); nominal P = 0.02]. KSS function scores were higher in the AI-assisted planning/PSI group at 2 and 6 months [80.00 (70.00, 90.00) vs. 55.00 (55.00, 60.00), and 80.00 (80.00, 90.00) vs. 70.00 (70.00, 70.00); both nominal P < 0.001]. Pain-related outcomes, HALP, drainage volume, and gait parameters showed directional between-group differences that were interpreted as exploratory and descriptive. Postoperative HKA deviation and HKA outlier rates were comparable, while coronal tibial component error was smaller in the AI-assisted planning/PSI group [0.4 (0.2, 0.7) vs. 0.9 (0.6, 1.1) degrees; nominal P = 0.018].Conclusions In this exploratory cohort, AI-assisted planning with PSI was associated with selected short-term functional, perioperative, gait, and radiographic component-positioning differences, but not superior overall HKA alignment. Findings are preliminary and require confirmation in larger randomized or well-matched studies.
SN - 1749-799X
ER -