Augmented Reality-Guided Individualized Total Knee Arthroplasty: Initial Clinical Implementation and Results.

IF 1.5 Q2 ORTHOPEDICS
H Gene Dossett, Michael Stickels, Rini Desai, Alexander Kozak, Brooke Shanahan, Sailesh Tummala
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引用次数: 0

Abstract

Background: Contemporary total knee arthroplasty (TKA) practice has evolved from uniform mechanical alignment to individualized alignment planning in response to growing evidence that a single alignment strategy does not optimize outcomes for all patients. However, precise execution of patient-specific alignment strategies remains challenging with manual instrumentation. Augmented reality (AR) technology addresses this limitation by providing real-time intraoperative visualization of anatomic landmarks and planned resection parameters. In this study, individualized alignment was applied within predefined safety envelopes, including femoral valgus relative to the mechanical axis of 0° to 3°, tibial varus of 0° to 3°, and hip-knee-ankle alignment within 0° to 3° of neutral. All procedures were performed using the Pixee Knee + AR system (Pixee Medical, Besançon, France). Despite growing interest in AR-assisted surgery, clinical data regarding the accuracy, precision, and early outcomes of AR-guided individualized TKA remain limited, providing the rationale for this study.

Methods: This retrospective consecutive case series evaluated 50 patients with end-stage knee osteoarthritis who underwent primary TKA using the Pixee Knee + AR system between April and August 2024. All procedures used individualized alignment strategies with patient-specific planning parameters. Radiographic accuracy was assessed using postoperative CT imaging, and validated patient-reported outcome measures were collected at minimum 6-month follow-up.

Results: The cohort comprised 45 men and 5 women with mean age 71.4 ± 7.6 years, American Society of Anesthesiologists score 3.0 ± 0.2, and body mass index 31.0 ± 4.1 kg/m2. Alignment accuracy was excellent, with 96% of coronal measurements within 3° of planned values and 53.3% within 1°. Component-specific accuracy rates within 1° were as follows: tibial component 72%, femoral implant 62%, and overall hip-knee-ankle alignment 46%. Four percent of measurements exceeded 3° deviation from planned alignment. No revision surgeries, infections, or mechanical complications occurred during follow-up. Patient-reported outcomes demonstrated notable improvements from preoperative scores: modified single assessment numeric evaluation scores improved 4.7 ± 3.1 points (P < 0.001) and KOOS Jr. normalized scores improved 21.6 ± 23.2 points (P < 0.001).

Conclusion: AR-guided individualized TKA demonstrated high accuracy in executing patient-specific alignment plans with favorable early clinical outcomes and no complications at 6 months. These initial results suggest that AR technology may provide a viable alternative for precise implementation of individualized alignment strategies, although larger studies with longer follow-up are needed to establish long-term efficacy and safety.

增强现实引导个体化全膝关节置换术:初步临床实施和结果。
背景:当代全膝关节置换术(TKA)实践已经从统一的机械对齐发展到个性化的对齐计划,因为越来越多的证据表明单一的对齐策略并不能优化所有患者的结果。然而,精确执行患者特定的对齐策略仍然具有手动仪器的挑战性。增强现实(AR)技术通过提供术中解剖标志和计划切除参数的实时可视化来解决这一限制。在本研究中,在预定义的安全包膜内进行个体化对齐,包括相对于机械轴0°至3°的股骨外翻,0°至3°的胫骨内翻,以及中性0°至3°的髋关节-膝关节-踝关节对齐。所有手术均采用Pixee膝关节+ AR系统(Pixee Medical, besanon, France)。尽管人们对ar辅助手术越来越感兴趣,但关于ar引导的个体化TKA的准确性、精确性和早期结果的临床数据仍然有限,这为本研究提供了基本原理。方法:本回顾性连续病例系列评估了2024年4月至8月期间使用Pixee膝关节+ AR系统进行原发性TKA的50例终末期膝关节骨性关节炎患者。所有手术均采用个性化对齐策略和患者特定的计划参数。通过术后CT成像评估放射成像的准确性,并在至少6个月的随访中收集经过验证的患者报告的结果测量。结果:男性45例,女性5例,平均年龄71.4±7.6岁,美国麻醉医师学会评分3.0±0.2分,体重指数31.0±4.1 kg/m2。对准精度非常好,96%的日冕测量值在计划值的3°范围内,53.3%在计划值的1°范围内。1°范围内的部件特异性准确率如下:胫骨假体72%,股骨假体62%,髋关节-膝关节-踝关节整体对齐46%。百分之四的测量值与计划对准的偏差超过3°。随访期间未发生翻修手术、感染或机械并发症。患者报告的结果与术前评分相比有显著改善:改进的单一评估数值评估评分提高4.7±3.1分(P < 0.001), kos Jr.标准化评分提高21.6±23.2分(P < 0.001)。结论:ar引导的个体化TKA在执行患者特异性对齐计划方面具有很高的准确性,具有良好的早期临床结果,6个月时无并发症。这些初步结果表明,AR技术可能为精确实施个性化对齐策略提供了可行的替代方案,尽管需要更大规模的研究和更长的随访时间来确定长期疗效和安全性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
2.60
自引率
6.70%
发文量
282
审稿时长
8 weeks
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