RESUMEN
PURPOSE: Predominant or isolated spasticity of the triceps following upper motor neuron injury is rare and often unmasked once the spastic elbow flexors are addressed. The purpose of this study was to delineate the motor branching pattern of the radial nerve to determine the feasibility of hyperselective neurectomies (HSN) for triceps spasticity. METHODS: Dissections of the motor branch to each triceps head were performed on 11 upper-extremity specimens. The numbers of trunks, branching patterns, and muscle entry points were recorded in reference to the acromion to interepicondylar line. Based on anatomic studies, 10 patients underwent a combined fractional lengthening and HSN procedure for triceps spasticity. Patient demographics, time from diagnosis, and complications were recorded. Preoperative and postoperative Modified Ashworth Scale (MAS) and total active elbow arc of motion were compared. RESULTS: The first branch from the radial nerve was consistently a single trunk to the long triceps head. There were many variations in the branching pattern and number of trunks to the lateral and medial heads of the triceps with motor entry points between 31% and 95% of the acromion to interepicondylar line distance. Ten patients (six men and four women; mean age: 48.5 years) underwent the combined procedure. Mean total active elbow arc of motion improved from 78° before surgery to 111° after surgery, with a 17.5° increase in active elbow flexion. Compared with a mean preoperative triceps MAS of 2.75, nine patients had triceps MAS of 0 at a mean of 10.2 months of follow-up. There was no loss of functional elbow extension and no directly related complications. CONCLUSIONS: Given the variable motor entry points, HSN to each triceps head would require extensive dissection. Therefore, a combined approach consisting of fractional lengthening of the long head and lateral head with HSN of the triceps medial head is recommended to address triceps spasticity. TYPE OF STUDY/LEVEL OF EVIDENCE: Therapeutic V.
RESUMEN
PURPOSE: The purpose of this review is to evaluate the current status of research on the application of artificial intelligence (AI)-based three-dimensional (3D) templating in preoperative planning of total joint arthroplasty. METHODS: This scoping review followed the PRISMA, PRISMA-ScR guidelines, and five stage methodological framework for scoping reviews. Studies of patients undergoing primary or revision joint arthroplasty surgery that utilised AI-based 3D templating for surgical planning were included. Outcome measures included dataset and model development characteristics, AI performance metrics, and time performance. After AI-based 3D planning, the accuracy of component size and placement estimation and postoperative outcome data were collected. RESULTS: Nine studies satisfied inclusion criteria including a focus on computed tomography (CT) or magnetic resonance imaging (MRI)-based AI templating for use in hip or knee arthroplasty. AI-based 3D templating systems reduced surgical planning time and improved implant size/position and imaging feature estimation compared to conventional radiographic templating. Several components of data processing and model development and testing were insufficiently covered in the studies included in this scoping review. CONCLUSIONS: AI-based 3D templating systems have the potential to improve preoperative planning for joint arthroplasty surgery. This technology offers more accurate and personalized preoperative planning, which has potential to improve functional outcomes for patients. However, deficiencies in several key areas, including data handling, model development, and testing, can potentially hinder the reproducibility and reliability of the methods proposed. As such, further research is needed to definitively evaluate the efficacy and feasibility of these systems.
