Abstract
AbstractAdolescent idiopathic scoliosis is a complex three-dimensional deformity of the spine, the moderate forms of which require treatment with an orthopedic brace. Existing brace design approaches rely mainly on empirical manual processes, vary considerably depending on the training and expertise of the orthotist, and do not always guarantee biomechanical effectiveness. To address these issues, we propose a new automated design method for creating bespoke nighttime braces requiring virtually no user input in the process. From standard biplanar radiographs and a surface topography torso scan, a personalized finite element model of the patient is created to simulate bracing and the resulting spine growth over the treatment period. Then, the topography of an automatically generated brace is modified and simulated over hundreds of iterations by a clinically driven optimization algorithm aiming to improve brace immediate and long-term effectiveness while respecting safety thresholds. This method was clinically tested on 17 patients prospectively recruited. The optimized braces showed a highly effective immediate correction of the thoracic and lumbar curves (70% and 90% respectively), with no modifications needed to fit the braces onto the patients. In addition, the simulated lumbar lordosis and thoracic apical rotation were improved by 5° ± 3° and 2° ± 3° respectively. Our approach distinguishes from traditional brace design as it relies solely on biomechanically validated models of the patient’s digital twin and a design strategy that is entirely abstracted from empirical knowledge. It provides clinicians with an efficient way to create effective braces without relying on lengthy manual processes and variable orthotist expertise to ensure a proper correction of scoliosis.
Funder
Gouvernement du Canada | Natural Sciences and Engineering Research Council of Canada
Canada First Research Excellence Fund
Gouvernement du Canada | Canadian Institutes of Health Research
Publisher
Springer Science and Business Media LLC
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