Is there a skeletal age index that can predict accurate curve progression in adolescent idiopathic scoliosis? A systematic review.

BACKGROUND

The diagnosis of adolescent idiopathic scoliosis requires clinical and radiographic evaluation; the management options vary depending on the severity of the curve and potential for progression. Identifying predictors of scoliosis progression is crucial to avoid incorrect management; clinical and radiographic factors have been studied as potential predictors. The present study aims to review the literature on radiological indexes for the peak height velocity or curve acceleration phase to help clinicians manage treatment of patients with adolescent idiopathic scoliosis.

METHODS

This systematic review was carried out in accordance with Preferential Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) guidelines. The search was carried out including only peer-reviewed articles written in English that described the radiological indexes assessing skeletal maturity in patients with adolescent idiopathic scoliosis and evaluated their correlation with curve progression, expressed as peak height velocity and/or curve acceleartion phase.

RESULTS

Thirteen studies were included and showed promising results in terms of reliable radiological indexes. Risser staging gives a general measure of skeletal maturity, but it cannot be used as a primary index for driving the treatment of patients with adolescent idiopathic scoliosis since more reliable indexes are available.

CONCLUSION

Skeletal maturity quantification for adolescent idiopathic scoliosis has the potential to significantly modify disease management. However, idiopathic scoliosis is a complex and multifactorial disease: therefore, it is unlikely that a single index will ever be sufficient to predict its evolution. Therefore, as more adolescent idiopathic scoliosis progression-associated indexes are identified, a collective scientific effort should be made to develop a therapeutic strategy based on reliable and reproducible algorithms.