Precise implant positioning, tailored to individual spinopelvic biomechanics and phenotype, is paramount for stability in total hip arthroplasty (THA). Despite a few studies on instability prediction, there is a notable gap in research utilizing artificial intelligence (AI). The objective of our pilot study was to evaluate the feasibility of developing an AI algorithm tailored to individual spinopelvic mechanics and patient phenotype for predicting impingement. This international, multicentre prospective cohort study across two centres encompassed 157 adults undergoing primary robotic arm-assisted THA. Impingement during specific flexion and extension stances was identified using the virtual range of motion (ROM) tool of the robotic software. The primary AI model, the Light Gradient-Boosting Machine (LGBM), used tabular data to predict impingement presence, direction (flexion or extension), and type. A secondary model integrating tabular data with plain anteroposterior pelvis radiographs was evaluated to assess for any potential enhancement in prediction accuracy.Aims
Methods
Computer-assisted 3D preoperative planning software has the potential to improve postoperative stability in total hip arthroplasty (THA). Commonly, preoperative protocols simulate two functional positions (standing and relaxed sitting) but do not consider other common positions that may increase postoperative impingement and possible dislocation. This study investigates the feasibility of simulating commonly encountered positions, and positions with an increased risk of impingement, to lower postoperative impingement risk in a CT-based 3D model. A robotic arm-assisted arthroplasty planning platform was used to investigate 11 patient positions. Data from 43 primary THAs were used for simulation. Sacral slope was retrieved from patient preoperative imaging, while angles of hip flexion/extension, hip external/internal rotation, and hip abduction/adduction for tested positions were derived from literature or estimated with a biomechanical model. The hip was placed in the described positions, and if impingement was detected by the software, inspection of the impingement type was performed.Aims
Methods
Implant waste during total hip arthroplasty (THA) represents a significant cost to the USA healthcare system. While studies have explored methods to improve THA cost-effectiveness, the literature comparing the proportions of implant waste by intraoperative technology used during THA is limited. The aims of this study were to: 1) examine whether the use of enabling technologies during THA results in a smaller proportion of wasted implants compared to navigation-guided and conventional manual THA; 2) determine the proportion of wasted implants by implant type; and 3) examine the effects of surgeon experience on rates of implant waste by technology used. We identified 104,420 implants either implanted or wasted during 18,329 primary THAs performed on 16,724 patients between January 2018 and June 2022 at our institution. THAs were separated by technology used: robotic-assisted (n = 4,171), imageless navigation (n = 6,887), and manual (n = 7,721). The primary outcome of interest was the rate of implant waste during primary THA.Aims
Methods
Traditionally, acetabular component insertion during total hip arthroplasty (THA) is visually assisted in the posterior approach and fluoroscopically assisted in the anterior approach. The present study examined the accuracy of a new surgeon during anterior (NSA) and posterior (NSP) THA using robotic arm-assisted technology compared to two experienced surgeons using traditional methods. Prospectively collected data was reviewed for 120 patients at two institutions. Data were collected on the first 30 anterior approach and the first 30 posterior approach surgeries performed by a newly graduated arthroplasty surgeon (all using robotic arm-assisted technology) and was compared to standard THA by an experienced anterior (SSA) and posterior surgeon (SSP). Acetabular component inclination, version, and leg length were calculated postoperatively and differences calculated based on postoperative film measurement.Aims
Methods
This study aimed to evaluate the accuracy of implant placement with robotic-arm assisted total hip arthroplasty (THA) in patients with developmental dysplasia of the hip (DDH). The study analyzed a consecutive series of 69 patients who underwent robotic-arm assisted THA between September 2018 and December 2019. Of these, 30 patients had DDH and were classified according to the Crowe type. Acetabular component alignment and 3D positions were measured using pre- and postoperative CT data. The absolute differences of cup alignment and 3D position were compared between DDH and non-DDH patients. Moreover, these differences were analyzed in relation to the severity of DDH. The discrepancy of leg length and combined offset compared with contralateral hip were measured.Aims
Methods
