Athwal George S, Nelson Andrew, Antuna Samuel, Ponce Brent, Mighell Mark, St Pierre Patrick, Sanchez-Sotelo Joaquin
Roth | McFarlane Hand & Upper Limb Center, St Joseph's Health Care London, London, ON, Canada.
Stryker Orthopedics, New York, NY, USA.
J Shoulder Elbow Surg. 2025 Aug;34(8):2022-2030. doi: 10.1016/j.jse.2024.12.007. Epub 2025 Jan 23.
Precise and accurate glenoid preparation is important for the success of shoulder arthroplasty. Despite advancements in preoperative planning software and enabling technologies, most surgeons execute the procedure manually. Patient-specific instrumentation (PSI) facilitates accurate glenoid guide pin placement for cannulated reaming; however, few commercially available systems offer depth of reaming control. Robotic arm-assisted bone preparation has gained popularity in knee and hip arthroplasty, but at the present time there is limited information available on the use of robotics for shoulder arthroplasty. The purpose of this study was to compare glenoid preparation and final implant position using 3 techniques: manual, manual assisted with PSI, and robotic arm-assisted bone preparation.
Six shoulder surgeons participated in this study using 3 preparation techniques: (1) manual reaming, (2) manual reaming over a pin inserted using PSI, and (3) preparation using a robotic arm assist with an end-effector burr and haptic boundaries. Each surgeon randomly conducted each technique on 2 separate Bone Matrix glenoid models, for a total of 36 glenoid models tested. To compare the techniques, the final prepared Bone Matrix models underwent a computed tomographic scan with 3D virtual model generation. The prepared 3D virtual glenoid models were then compared to the preoperatively planned models. Parameters compared included deviations in version, inclination, anterior-posterior (AP) translation, superior-inferior (SI) translation, and depth of reaming.
Regarding glenoid version with values reported as mean deviations from the preoperative plan, the robotic-assisted technique (1°) was significantly better than manual (9°, P < .001) and PSI (4°, P < .001) techniques at executing the preoperative plan. Regarding inclination, the robotic-assisted technique (2°) was significantly better than manual (9°, P = .003) but not significantly different than PSI (3°, P = .211). The robotic arm technique, with AP translation, resulted in significantly lower mean displacements (0.3 mm) than the manual technique (2 mm, P = .001) and the PSI technique (2 mm, P = .002). With SI translation, the robotic arm-assisted technique (0.7 mm) resulted in significantly lower mean displacements as compared to the manual (2 mm, P = .007) and PSI (1 mm, P = .011). The robotic arm-assisted technique (0.4 mm) did not result in significantly lower mean depth of reaming displacements compared to the manual technique (0.8 mm, P = .051) but did when compared to PSI (0.8 mm, P = .036).
Glenoid preparation using a robotic arm with an end-effector burr and haptic boundaries was significantly better in its ability to execute a preoperatively planned implant position than manual preparation in 4 of the 5 glenoid metrics examined and was significantly better than PSI in 4 of the 5 glenoid metrics.
精确的肩胛盂准备对于肩关节置换术的成功至关重要。尽管术前规划软件和辅助技术取得了进展,但大多数外科医生仍采用手动操作。定制化器械(PSI)有助于在空心扩孔时精确放置肩胛盂导针;然而,市面上很少有系统能提供扩孔深度控制。机器人手臂辅助骨准备在膝关节和髋关节置换术中已得到广泛应用,但目前关于机器人技术在肩关节置换术中应用的信息有限。本研究的目的是比较三种技术:手动、使用PSI辅助的手动操作以及机器人手臂辅助骨准备,在肩胛盂准备和最终植入物位置方面的差异。
六位肩关节外科医生参与了本研究,采用三种准备技术:(1)手动扩孔,(2)在使用PSI插入的导针上进行手动扩孔,(3)使用带有末端执行器磨头和触觉边界的机器人手臂辅助进行准备。每位外科医生在两个独立的骨基质肩胛盂模型上随机进行每种技术的操作,总共测试36个肩胛盂模型。为了比较这些技术,对最终准备好的骨基质模型进行计算机断层扫描并生成三维虚拟模型。然后将准备好的三维虚拟肩胛盂模型与术前规划模型进行比较。比较的参数包括版本偏差、倾斜度、前后(AP)平移、上下(SI)平移和扩孔深度。
关于肩胛盂版本,以与术前计划的平均偏差值报告,机器人辅助技术(1°)在执行术前计划方面明显优于手动技术(9°,P <.001)和PSI技术(4°,P <.001)。关于倾斜度,机器人辅助技术(2°)明显优于手动技术(9°,P =.003),但与PSI技术(3°,P =.211)无显著差异。机器人手臂技术在AP平移方面,平均位移(0.3毫米)明显低于手动技术(2毫米,P =.001)和PSI技术(2毫米,P =.002)。在SI平移方面,机器人手臂辅助技术(0.7毫米)与手动技术(2毫米,P =.007)和PSI技术(1毫米,P =.011)相比,平均位移明显更低。与手动技术(0.8毫米,P =.051)相比,机器人手臂辅助技术(0.4毫米)在扩孔深度平均位移方面没有显著降低,但与PSI技术(0.8毫米,P =.036)相比有显著降低。
在检查的5个肩胛盂指标中的4个方面,使用带有末端执行器磨头和触觉边界的机器人手臂进行肩胛盂准备,在执行术前计划植入位置的能力上明显优于手动准备,并且在5个肩胛盂指标中的4个方面明显优于PSI。