Applications of artificial intelligence for adolescent idiopathic scoliosis: mapping the evidence.

PURPOSE: Adolescent idiopathic scoliosis (AIS) is a common spinal deformity with varying progression, complicating treatment decisions. Artificial intelligence (AI) and machine learning (ML) are increasingly prominent in orthopedic care, aiding in diagnosis, risk-stratification, and treatment guidance. This scoping review outlines AI applications in AIS. METHODS: This study followed PRISMA-ScR guidelines and included articles that reported the development, use, or validation of AI models for treating, diagnosing, or predicting clinical outcomes in AIS. RESULTS: 40 full-text articles were included, with most studies published in the last 5 years (77.5%). Common ML techniques were convolutional neural networks (55%), decision trees and random forests (15%), and artificial neural networks (15%). Most AI applications in AIS were for imaging analysis (25/40; 62.5%), focusing on automatic measurement of Cobb angle, and axial vertebral rotation (13/25; 52%) and curve classification/severity (13/25; 52%). Prediction was the second most common application (15/40; 37.5%), with studies predicting curve progression (9/15; 60%), and Cobb angles (9/15; 60%). Only 15 studies (37.5%) reported clinical implementation guidelines for AI in AIS management. 52.5% of studies reported model accuracy, with an average of 85.4%. CONCLUSION: This review highlights the applications of AI in AIS care, notably including automatic radiographic analysis, curve type classification, prediction of curve progression, and AIS diagnosis. However, the current lack of clear clinical implementation guidelines, model transparency, and external validation of studied models limits clinician trust and the generalizability and applicability of AI in AIS management.

Early Onset Scoliosis and Adolescent Idiopathic Scoliosis: A Review of the Literature and Correlations With Pulmonary Dysfunction.

In the management of early onset scoliosis (EOS) and adolescent idiopathic scoliosis (AIS), orthopedic surgeons are tasked with considering the effects that curves and their treatment can have on the respiratory system, possibly the most relevant being pulmonary dysfunction due to thoracic cage changes. The pulmonary impairment that occurs as a result of scoliosis varies widely and requires a multimodal response, including physiologic testing, such as pulmonary function tests (PFTs) and consistent psychosocial monitoring of the patient. This forces healthcare providers to consider all factors affecting the patient's quality of life (QOL) and not just the primary pathology they are treating. One method that could be utilized to ensure a more holistic approach to treatment is the use of patient-reported outcome measures (PROMs) to assess the QOL domains. Thus, this review serves to highlight the importance of addressing and correcting pulmonary dysfunction in the care of children with EOS and AIS in a holistic manner.