Anterolateral Oblique Distal Femoral Osteotomy for the Removal of Well Fixed Cemented Femoral TKA Components

In the setting of periprosthetic joint infection, the complete removal of implants and cement can be challenging with well-fixed, cemented implants about the knee. This can get especially complex in the setting of long cemented femoral component stems. Osteotomies are well described in the proximal femur and tibia for removal of implants and cement. There is little information available on distal femoral osteotomies. We describe an anterolateral oblique distal femoral osteotomy for the removal of well-fixed, cemented components in resection knee arthroplasty that preserves vascularity to the osteotomized segment

Hitting the target: Natural history of the hip based on achieving an acetabular safe zone following periacetabular osteotomy

BACKGROUND: Periacetabular osteotomy (PAO) remains the gold-standard treatment for acetabular dysplasia in skeletally mature patients with preserved cartilage. The purpose of this multicenter cohort study was to delineate the long-term radiographic natural history of the dysplastic hip following PAO based on the final position of the acetabular fragment. METHODS: We evaluated patients who underwent PAO performed by 4 hip preservation surgeons to treat acetabular dysplasia with or without concomitant retroversion from 1996 to 2012 at 3 academic institutions. There were 288 patients with a mean clinical and radiographic follow-up of 9 years (range, 5 to 21 years). Postoperative radiographs made at the first clinical visit were used to determine if the acetabular fragment fell into a safe zone according to the absence of retroversion, a lateral center-edge angle (LCEA) of 25° to 40°, an anterior center-edge angle (ACEA) of 25° to 40°, and a Tönnis angle of 0° to 10°. Every available subsequent radiograph was assessed for degenerative changes by the Tönnis classification (grades 0 to 3). The time to progression was analyzed using Cox proportional hazards regression and multistate modeling. RESULTS: Only the absence of retroversion was independently associated with a decreased risk of progressing at least 1 Tönnis grade during follow-up: hazard ratio (HR), 0.60 (95% confidence interval [CI], 0.38 to 0.94; p = 0.025). Achieving the ACEA safe zone yielded the greatest time increase for remaining in Tönnis grade 0 or 1 (43 years for having an ACEA in the safe zone compared with 28 years for not having an ACEA in the safe zone), followed by the absence of retroversion (34 years for the absence of retroversion compared with 24 years for the presence of retroversion). However, attaining the Tönnis angle or LCEA safe zones did not delay progression. The achievement of additional safe zones generally increased the length of time that patients spent in Tönnis grade 0 or 1: 25 years for 0 safe zones, 36 years for 1 safe zone, 29 years for 2 safe zones, 37 years for 3 safe zones, and 44 years for 4 safe zones. CONCLUSIONS: This study demonstrates the importance of achieving appropriate acetabular reorientation to enhance the longevity of the native hip following PAO. Although the LCEA and the Tönnis angle are the most common metrics used to assess appropriate acetabular correction, this study shows that adequately addressing retroversion and the ACEA has a greater impact on improving the natural history. LEVEL OF EVIDENCE: Therapeutic Level IV. See Instructions for Authors for a complete description of levels of evidence

Laceration of the Sciatic Nerve After Closed Reduction of a Dislocated Total Hip Arthroplasty

Sciatic nerve injury after closed reduction of a dislocated total hip arthroplasty (THA) is an exceedingly rare but tremendously devastating complication. Closed reduction is the standard of care and is typically associated with a low complication rate. There have only been seven sciatic nerve injuries after closed reduction of a dislocated THA reported in the literature, and none were secondary to nerve laceration. We report a case of sciatic nerve laceration after attempted closed reduction of a dislocated THA. This resulted in complete loss of sensory and motor sciatic nerve function. This case highlights the importance of a detailed neurologic examination before and after closed reduction of a dislocated total hip, the importance of using careful reduction maneuvers, and transitioning to open reduction when necessary

The use of deep learning in medical imaging to improve spine care: A scoping review of current literature and clinical applications

Background: Artificial intelligence is a revolutionary technology that promises to assist clinicians in improving patient care. In radiology, deep learning (DL) is widely used in clinical decision aids due to its ability to analyze complex patterns and images. It allows for rapid, enhanced data, and imaging analysis, from diagnosis to outcome prediction. The purpose of this study was to evaluate the current literature and clinical utilization of DL in spine imaging. Methods: This study is a scoping review and utilized the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology to review the scientific literature from 2012 to 2021. A search in PubMed, Web of Science, Embased, and IEEE Xplore databases with syntax specific for DL and medical imaging in spine care applications was conducted to collect all original publications on the subject. Specific data was extracted from the available literature, including algorithm application, algorithms tested, database type and size, algorithm training method, and outcome of interest. Results: A total of 365 studies (total sample of 232,394 patients) were included and grouped into 4 general applications: diagnostic tools, clinical decision support tools, automated clinical/instrumentation assessment, and clinical outcome prediction. Notable disparities exist in the selected algorithms and the training across multiple disparate databases. The most frequently used algorithms were U-Net and ResNet. A DL model was developed and validated in 92% of included studies, while a pre-existing DL model was investigated in 8%. Of all developed models, only 15% of them have been externally validated. Conclusions: Based on this scoping review, DL in spine imaging is used in a broad range of clinical applications, particularly for diagnosing spinal conditions. There is a wide variety of DL algorithms, database characteristics, and training methods. Future studies should focus on external validation of existing models before bringing them into clinical use