I read with great interest a recent article published by Kim et al. [1] in the Asian Spine Journal titled “Current issues in the treatment of adolescent idiopathic scoliosis.” The authors discussed an extensive analysis of existing treatments, exploring both traditional methods and emergent innovations, and providing extensive resource for clinicians and researchers to improve outcomes for adolescent idiopathic scoliosis (AIS).

Remarkably, the review highlights the necessity of a tailored approach to treatment, emphasizing how variations in progression of curve, patient’s age, and skeletal maturity influence decision-making. The most captivating aspects of the review are the investigation of novel surgical techniques, minimally invasive surgical options and the role of artificial intelligence in surgical management.

Even though the review covers many essential aspects, there is evidence supporting the effectiveness of physiotherapeutic interventions and the role of artificial intelligence (AI)-driven predictive tools in customizing treatment protocols for AIS. These considerations could pave the way for a more holistic and comprehensive, individually tailored approach.

Physiotherapy, including exercise therapy, has been shown to affect the Cobb angle, angle of trunk rotation, and health-related quality of life in patients with AIS [2]. Scoliosis-specific exercises are individualized exercises aimed at decreasing the deformity. These exercises work by altering the soft tissue that affects the spine and improving control of spinal movement, with no known side effects [3]. The Schroth method has been proven to significantly reduce the angle of trunk rotation, while both the Scientific Exercise Approach to Scoliosis and the Schroth method have demonstrated positive effects on health-related quality of life [4].

Cardiopulmonary dysfunction after surgery of AIS can develop owing to the decreased flexibility of the spine and mobility of the ribs and may not recover even 2 years after surgery [5]. After fusion surgeries, patients may have compromised postural control. The loss of mobility in the spine–thorax may also cause restrictive pulmonary disease owing to the loss of chest wall compliance; however, respiratory exercise can improve outcomes. Intensive postoperative rehabilitation has proven better results to early mobilization for improving pain, thorax mobility, balance, walk distance, and health-related quality of life in patients with scoliosis surgery [6].

The applications of AI in AIS care, notably including automatic radiographic analysis, classification of curve type, prediction of curve progression, and AIS diagnosis could be utilized for better health outcomes [7].

Physiotherapy scoliosis-specific exercises have displayed favorable outcomes in managing AIS by improving postural control and flexibility. AI is evolving in its ability to predict the progression of curves through factors like age and Cobb angle, which helps to tailor management. By linking to these approaches, clinicians and surgeons can build more custom-made and possibly more effective interventions for AIS management, improving long-term health outcomes. Customized treatment plans including comprehensive approaches to prevention, rehabilitation, and surgery along with AI-driven predictions could significantly improve patient outcomes.

Once again, I commend the authors on their in-depth review, which will confidently aid as a reference for upcoming developments in AIS management.