Background: Artificial intelligence (AI), including machine learning (ML) and deep learning (DL), is increasingly being integrated into total knee arthroplasty (TKA) to improve accuracy, efficiency, and personalized care. These technologies enable the analysis of large, complex datasets to support evidence-based clinical decision-making across all phases of the surgical process. Main body: AI has demonstrated utility in multiple stages of TKA. In patient selection, ML algorithms can predict postoperative complications such as transfusion needs with high accuracy (AUC up to 0.842). For preoperative planning, DL techniques facilitate 3D anatomical reconstruction and implant size prediction, with some models achieving over 90% accuracy for exact component sizing, significantly outperforming traditional 2D templating. Intraoperatively, AI-assisted robotic systems and sensor technologies offer real-time feedback on alignment and soft tissue balancing. Postoperatively, AI-integrated wearable devices and mobile applications enable continuous monitoring and tailored rehabilitation; in some randomized trials, these tools have been associated with a statistically significant reduction in hospital readmission rates. Despite these advances, significant challenges remain, including algorithmic bias, a lack of model generalizability and explainability, and unresolved ethical and regulatory hurdles that present formidable barriers to widespread clinical implementation. Conclusions: AI has the potential to significantly reshape TKA by enabling more precise, data-driven, and patient-centered care. However, its promise is contingent on overcoming critical limitations. Broader implementation requires robust multicenter validation to ensure model reliability, the development of explainable algorithms to build clinical trust, and a commitment to responsible innovation. With continued progress, AI can serve as a powerful complementary tool to augment surgical expertise and enhance patient outcomes in orthopedic surgery.

Shin WC, et al. Clin Orthop Surg. 2023 Jan;15:e2. https://doi.org/10.4055/cios22103

This article determines the accuracy and reliability of dual-energy computed tomography (DECT) with metal artifact reduction (MAR) in the evaluation of femoral component rotation after total knee arthroplasty (TKA), in comparison with conventional CT images. A total of 49 patients (mean age, 69 years; 42 women) who underwent TKA between January 2019 and March 2020 were retrospectively enrolled. Femoral component rotation, including the anatomic and surgical transepicondylar axes, was evaluated with preoperative conventional CT and postoperative conventional CT and DECT with MAR. Surgical femoral component rotation was also assessed as a reference standard. Accuracy was assessed using paired t-test, and inter- and intraobserver reliability using intraclass correlation coefficients (ICCs) based on postoperative conventional CT and DECT with MAR. Clinical outcomes were evaluated using the Knee Society objective and functional scores. Accuracy of femoral component rotation was not significantly different from that of surgical rotation with both conventional CT and DECT with MAR. However, inter- and intraobserver reliability were better for DECT with MAR (ICC: 0.953–0.966) than for conventional CT (ICC: 0.641–0.749). The Knee Society objective and functional scores improved 1 year postoperatively. Conclusion DECT with MAR showed accurate and more reliable results than did conventional CT in the evaluation of femoral component rotation after TKA.

Rationale: Excessive distal clavicle resection can result in severe bone loss and disruption of the coracoclavicular (CC) ligament attachment, leading to significant vertical instability of the acromioclavicular joint. The optimal surgical approach in such cases remains controversial due to the technical challenges associated with achieving anatomical fixation. Patient concerns: A 40-year-old male construction worker presented with persistent shoulder pain, limited range of motion, and visible clavicular prominence 1 year and 7months after undergoing distal clavicle resection at an outside hospital following a traumatic fracture. Diagnoses: Radiography and physical examination revealed substantial bone loss in the distal clavicle and vertical instability, with a CC distance of 15.16 mm, confirming CC ligament insufficiency. Interventions: The patient underwent a single-tunnel arthroscopically assisted CC ligament reconstruction with allograft augmentation using the TightRope system and a peroneus brevis tendon allograft. Outcomes: At the 60-month follow-up, radiographs demonstrated maintained joint stability. The CC distance was reduced to 6.01 mm immediately postoperatively and was 9.30 mm at the final follow-up. Clinical scores significantly improved (Visual Analog Scale: 6→1, American Shoulder and Elbow Surgeons: 13→95, and University of California at Los Angeles: 9→35), and the patient returned to heavy manual labor 6 months postoperatively, maintaining full function. Lessons: In patients with severe distal clavicle bone loss, single-tunnel arthroscopically assisted CC ligament reconstruction with allograft augmentation can yield excellent long-term clinical and radiological outcomes, serving as a viable and effective treatment option.