Citations

Abstract Purpose The purpose of this article is to explore the potential of digital twin technologies in orthopaedics and to evaluate how their integration with artificial intelligence (AI) and deep learning (DL) can improve orthopaedic evaluation and treatment. This review addresses key applications of digital twins, including surgical planning, patient‐specific outcome prediction, augmented reality‐assisted surgery and simulation‐based surgical training. Methods Existing studies on digital twins in various domains, including engineering, biomedical and orthopaedics are reviewed. We also reviewed advancements in AI and DL relevant to digital twins. We focused on identifying key benefits, challenges and future directions for the implementation of digital twins in orthopaedic practice. Results The review highlights that digital twins offer significant potential to revolutionise orthopaedic care by enabling precise surgical planning, real‐time outcome prediction and enhanced training. Digital twins can model patient‐specific anatomy using advanced imaging techniques and dynamically update with real‐time data, providing valuable insights during surgery and postoperative care. However, challenges such as the need for large‐scale data sets, technological limitations and integration issues must be addressed to fully realise these benefits. Conclusion Digital twins represent a promising frontier in orthopaedic research and practice, with the potential to improve patient outcomes and enhance surgical precision. To enable widespread adoption, future research must focus on overcoming current challenges and further refining the integration of digital twins with AI and DL technologies. Level of Evidence Level V.

AbstractPurposeTo systematically review the literature regarding machine learning in leg length discrepancy (LLD) and to provide insight into the most relevant manuscripts on this topic in order to highlight the importance and future clinical implications of machine learning in the diagnosis and treatment of LLD.MethodsA systematic electronic search was conducted using PubMed, OVID/Medline and Cochrane libraries in accordance with Preferred Reporting Items for Systematic Review and Meta‐Analysis guidelines. Two observers independently screened the abstracts and titles of potential articles.ResultsA total of six studies were identified in the search. All measurements were calculated using standardized anterior‐posterior long‐leg radiographs. Five (83.3%) of the studies used measurements of the femoral length, tibial length and leg length to assess LLD, whereas one (16.6%) study used the iliac crest height difference to quantify LLD. The deep learning models showed excellent reliability in predicting all length measurements with intraclass correlation coefficients ranging from 0.98 to 1.0 and mean absolute error (MAE) values ranging from 0.11 to 0.45 cm. Three studies reported measurements of LLD, and the convolutional neural network model showed the lowest MAE of 0.13 cm in predicting LLD.ConclusionsMachine learning models are effective and efficient in determining LLD. Implementation of these models may reduce cost, improve efficiency and lead to better overall patient outcomes.Clinical RelevanceThis review highlights the potential of deep learning (DL) algorithms for accurate and reliable measurement of lower limb length and leg length discrepancy (LLD) on long‐leg radiographs. The reported mean absolute error and intraclass correlation coefficient values indicate that the performance of the DL models was comparable to that of radiologists, suggesting that DL‐based assessments could potentially be used to automate the measurement of lower limb length and LLD in clinical practice.Level of EvidenceLevel IV.

Purpose To evaluate the available literature on the relationship between knee bony morphology and medial meniscus posterior root tears (MMPRTs) to determine which tibiofemoral morphologic risk factors may predispose the development of MMPRTs. Methods Embase, MEDLINE, and PubMed databases were searched to identify all relevant human clinical studies investigating knee morphologic features and MMPRTs. Shape features were compared between control groups and patients with MMPRTs. The methodological index for nonrandomized studies (MINORS) instrument was utilized to assess the methodological quality of included studies. Results Thirteen level III evidence studies and 1 level IV evidence study were included in this review (n = 2,181), with 895 patients in the MMPRT group and 1,286 in the control group. Tibial morphology features associated with an increased risk for MMPRTs included an increased medial tibial slope (6 studies), increased tibial torsion (1 study), increased medial meniscal slope (1 study), and shallower medial tibial plateau concavity (1 study). Varus mechanical alignment was found to increase the risk for MMPRTs (4 studies). Femoral morphology features associated with an increased risk for MMPRTs included an A‐type intercondylar notch (1 study), increased medial femoral condyle (MFC) angle (1 study), narrower intercondylar distance (1 study), narrower intercondylar notch width (1 study), shorter MFC distal offset distance (1 study), increased MFC width (1 study), increased MFC to medial tibial condyle width ratio (1 study), greater distance between the medial tibial eminence and MFC (1 study), and smaller femoral offset ratios of both the medial and lateral condyles (1 study). Conclusions Multiple tibiofemoral shape features, including a steeper slope of the medial tibial plateau, greater varus alignment, and a narrower intercondylar distance and notch width, were found to be predictive factors for MMPRTs. Level of Evidence Level IV, systematic review of Level III and IV studies.

Background: Value-based decision-making regarding nonoperative management versus early surgical stabilization for first-time anterior shoulder instability (ASI) events remains understudied. Purpose: To perform (1) a systematic review of the current literature and (2) a Markov model–based cost-effectiveness analysis comparing an initial trial of nonoperative management to arthroscopic Bankart repair (ABR) for first-time ASI. Study Design: Economic and decision analysis; Level of evidence, 3. Methods: A Markov chain Monte Carlo probabilistic model was developed to evaluate the outcomes and costs of 1000 simulated patients (mean age, 20 years; range, 12-26 years) with first-time ASI undergoing nonoperative management versus ABR. Utility values, recurrence rates, and transition probabilities were derived from the published literature. Costs were determined based on the typical patient undergoing each treatment strategy at the authors’ institution. Outcome measures included costs, quality-adjusted life-years (QALYs), and the incremental cost-effectiveness ratio (ICER). Results: The Markov model with Monte Carlo microsimulation demonstrated mean (± standard deviation) 10-year costs for nonoperative management and ABR of $38,649 ± $10,521 and $43,052 ± $9352, respectively. Total QALYs acquired over the 10-year time horizon were 7.67 ± 0.43 and 8.44 ± 0.46 for nonoperative management and ABR, respectively. The ICER comparing ABR with nonoperative management was found to be just $5725/QALY, which falls substantially below the $50,000 willingness-to-pay (WTP) threshold. The mean numbers of recurrences were 2.55 ± 0.31 and 1.17 ± 0.18 for patients initially assigned to the nonoperative and ABR treatment groups, respectively. Of 1000 samples run over 1000 trials, ABR was the optimal strategy in 98.7% of cases, with nonoperative management the optimal strategy in 1.3% of cases. Conclusion: ABR reduces the risk for recurrent dislocations and is more cost-effective despite higher upfront costs when compared with nonoperative management for first-time ASI in the young patient. While all these factors are important to consider in surgical decision-making, ultimate treatment decisions should be made on an individual basis and occur through a shared decision-making process.

Background There is a paucity of literature analyzing data for return to sport (RTS) and return to work (RTW) in the setting of direct anterior approach (DAA) total hip arthroplasty (THA). Objective The aims of this systematic review are to identify existing literature and to aggregate rates of RTS/RTW following DAA THA in a meta-analysis. Methods A query of major databases yielded 1819 initial studies. A random-effects model approach was implemented for meta-analysis. Moderator effects were assessed with respect to patient demographics and functional outcomes. Results Five studies reporting RTS after DAA THA were identified, representing a total of 204 patients with a mean age of 60.2±7.5 years and mean follow up of 31.8±9.5 months. Pooled rate of RTS was 76%(95% confidence interval [CI], 63%-86%;range 58%-100%). Pooled rate of return to the same sport was 77%(95%CI, 64%-86%;range of 62%-100%). Pooled rate of RTS to the same intensity was 58%(95%CI, 48%-68%;range of 41%-68%). Meta-regression demonstrated no significant correlations between independent variables and RTS characteristics. Three studies reported RTW rates. Rates of RTW within 3-months were 30%, 45%, and 60%. One study reported rate of RTW of 79% at 6-months and 87% at 12-months. One study demonstrated a mean time to RTW of 38±24.8 days. Conclusion Pooled rate of RTS is satisfactory following DAA THA and are comparable to rates of RTS aggregated without delineating surgical approach. Data supporting RTW rates following DAA THA limited, and thus more primary studies are needed to establish if this approach confers an advantage of faster RTS/RTW.

Objectives: Based in part on the results of randomized controlled trials (RCTs) that suggest a beneficial effect over alternative treatment options, the use of platelet-rich plasma (PRP) for the management of knee osteoarthritis (OA) is widespread and increasing. However, the extent to which these studies are vulnerable to slight variations in the outcomes of patients remains unknown. The purpose of this study is to evaluate the statistical fragility of conclusions from RCTs that reported outcomes of patients with knee OA who were treated with PRP versus alternative nonoperative management strategies. Methods: All RCTs comparing PRP to alternative nonoperative treatment options for knee OA were identified. The fragility index (FI) and reverse fragility index (RFI) were applied to assess the robustness of conclusions regarding the efficacy of PRP for knee OA. Meta-analyses were performed to determine the minimum number of patients from one or more trials included in the meta-analysis for which a modification on the event status would change the statistical significance of the pooled treatment effect. Results: In total, this analysis included outcomes from 1993 patients with a mean (± standard deviation) age of 58.0 ± 3.8 years. The mean number of events required to reverse significance (FI) was 4.57 ± 5.85. This corresponded to a fragility quotient of 0.060 ± 0.075, meaning the significance of the results was contingent on 6 events per 100 participants. For non-significant outcome events, the mean number of events required to reverse statistical nonsignificance (RFI) was 4.41 ± 2.22. This corresponded to a reverse fragility quotient of 0.065 ± 0.056, meaning the non-significance of the results was contingent on 6.5 events per 100 participants (Figure 1). Based on random-effects meta-analyses, PRP demonstrated a significantly higher rate of successful outcomes when compared to hyaluronic acid (p = 0.002, odds ratio 95% CI = 2.19 [1.33-3.62]) (Figure 2) as well as higher rates of patient-reported symptom relief (p = 0.019, odds ratio [95% CI] = 1.55 [1.07-2.24]) (Figure 3), not requiring a reintervention after the initial injection treatment (p = 0.002, odds ratio [95% CI] = 2.17 [1.33-3.53]) (Figure 4), and achieving the minimal clinically important difference (MCID) for pain improvement (p = 0.007, odds ratio [95% CI] = 6.19[1.63-23.42]) when compared to all alternative nonoperative treatments. Overall, the mean number of events per meta-analysis required to change the statistical significance of the pooled treatment effect was 8.67 ± 4.50. Conclusions: Individual RCTs evaluating PRP for knee OA possess slight robustness. Upon meta-analysis, PRP demonstrated a significant advantage over HA as well as improved symptom relief, lower rates of reintervention, and more frequent achievement of the MCID for pain improvement when compared to alternative, nonoperative treatment options. Statistically significant pooled treatment effects evaluating PRP for knee OA are more robust than approximately half of all comparable meta-analyses in medicine and healthcare. Future RCTs and meta-analyses should consider reporting fragility indices and quotients to facilitate interpretation of results in their proper context. In addition, the robustness of these findings suggests that reconsideration of the American Academy of Orthopaedic Surgeons clinical practice guidelines around the use of PRP for knee OA may be warranted.

Background: Understanding interactions between multiple risk factors for shoulder and elbow injuries in Major League Baseball (MLB) pitchers is important to identify potential avenues by which risk can be reduced while minimizing impact on player performance. Purpose: To apply a novel game theory–based approach to develop a machine-learning model predictive of next-season shoulder and elbow injuries in MLB pitchers and use this model to understand interdependencies and interaction effects between the most important risk factors. Study Design: Case-control study; Level of evidence, 3. Methods: Pitcher demographics, workload measures, pitch-tracking metrics, and injury data between 2017 and 2022 were used to construct a database of MLB pitcher-years, where each item in the database corresponded to a pitcher's information and metrics for that year. An extreme gradient boosting machine-learning model was trained to predict next-season shoulder and elbow injuries utilizing Shapley additive explanation values to quantify feature importance as well as interdependencies and interaction effects between predictive variables. Results: A total of 3808 pitcher-years were included in this analysis; 606 (15.9%) of these involved a shoulder or elbow injury resulting in placement on the MLB injured list. Of the >65 candidate features (including workload, demographic, and pitch-tracking metrics), the most important contributors to predicting shoulder/elbow injury were increased: pitch velocity (all pitch types), utilization of sliders (SLs), fastball (FB) spin rate, FB horizontal movement, and player age. The strongest game theory interaction effects were that higher FB velocity did not alter a younger pitcher's predicted risk of shoulder/elbow injury versus older pitchers, risk of shoulder/elbow injury increased with the number of high-velocity pitches thrown (regardless of pitch type and in an additive fashion), and FB velocity <95 mph (<152.9 kph) demonstrated strong negative interaction effects with higher SL percentage, suggesting that the overall predicted risk of injury for pitchers throwing a high number of SLs could be attenuated by lower FB velocity. Conclusion: Pitch-tracking metrics were substantially more predictive of future injury than player demographics and workload metrics. There were many significant game theory interdependencies of injury risk. Notably, the increased risk of injury that was conferred by throwing with a high velocity was even further magnified if the pitchers were also older, threw a high percentage of SLs, and/or threw a greater number of pitches.

Objectives: Nonoperative management vs. early reconstruction for partial tears of the medial ulnar collateral ligament (MUCL) remains controversial, with the most common treatment options for partial tears consisting of rest, rehab, platelet rich plasma (PRP), and/or surgical intervention. However, whether the improved outcomes reported for treatments such as MUCL reconstruction (UCLR) or nonoperative management with a series of PRP injections justifies their increased upfront costs remains unknown. Thus, the purpose of this study was to compare the cost-effectiveness of an initial trial of physical therapy alone, an initial trial of physical therapy plus a series of PRP injections, and early UCLR to determine the preferred cost-effective treatment strategy for baseball pitchers with partial tears of the MUCL. Methods: A Markov Chain Monte Carlo probabilistic model was developed to evaluate the outcomes and costs of 1,000 simulated pitchers undergoing nonoperative management with and without PRP vs. early UCLR for partial MUCL tears. Utility values, RTP rates, and transition probabilities were derived from the published literature. Costs were determined based on the typical patient undergoing each treatment strategy at our institution. Outcome measures included costs, acquired playing-years (PYs), and the incremental cost-effectiveness ratio (ICER). Results: Mean total costs resulting from nonoperative management without PRP, nonoperative management with PRP, and early UCLR were $22,520, $24,800, and $43,992, respectively. On average, early UCLR produced an additional 4.0 PYs over the 10-year time horizon relative to nonoperative management, resulting in an ICER of $5,395/PY, which falls well below the $50,000 willingness-to-pay threshold (WTP). Overall, early UCLR was determined the preferred cost-effective strategy in 77.5% of pitchers included in the microsimulation model, with nonoperative management with PRP determined the preferred strategy in 15% of pitchers and nonoperative management alone in 7.5% of pitchers. Conclusions: Based on Monte Carlo microsimulation and probabilistic sensitivity analysis, early UCLR was demonstrated to be more cost-effective than an initial trial of nonoperative management for partial tears of the MUCL for the majority of high-level baseball pitchers. It is important to note that this model does not consider the unique experiences, goals, situations, career trajectory, and pitching horizons of individual patients, and thus a shared decision-making discussion should be conducted regarding optimal initial treatment for partial MUCL tears. This is particularly true as many athletes can successfully be treated non-operatively, which generally results in a quicker return to play when successful compared to surgery.

AbstractPurposeThe present study reviews the available scientific literature on artificial intelligence (AI)‐assisted ultrasound‐guided regional anaesthesia (UGRA) and evaluates the reported intraprocedural parameters and postprocedural outcomes.MethodsA literature search was performed on 19 September 2023, using the Medline, EMBASE, CINAHL, Cochrane Library and Google Scholar databases by experts in electronic searching. All study designs were considered with no restrictions regarding patient characteristics or cohort size. Outcomes assessed included the accuracy of AI‐model tracking, success at the first attempt, differences in outcomes between AI‐assisted and unassisted UGRA, operator feedback and case‐report data.ResultsA joint adaptive median binary pattern (JAMBP) has been applied to improve the tracking procedure, while a particle filter (PF) is involved in feature extraction. JAMBP combined with PF was most accurate on all images for landmark identification, with accuracy scores of 0.83, 0.93 and 0.93 on original, preprocessed and filtered images, respectively. Evaluation of first‐attempt success of spinal needle insertion revealed first‐attempt success in most patients. When comparing AI application versus UGRA alone, a significant statistical difference (p < 0.05) was found for correct block view, correct structure identification and decrease in mean injection time, needle track adjustments and bone encounters in favour of having AI assistance. Assessment of operator feedback revealed that expert and nonexpert operator feedback was overall positive.ConclusionAI appears promising to enhance UGRA as well as to positively influence operator training. AI application of UGRA may improve the identification of anatomical structures and provide guidance for needle placement, reducing the risk of complications and improving patient outcomes.Level of EvidenceLevel IV.