Radiological response assessment after stereotactic body radiotherapy for spine metastases using magnetic resonance imaging: a systematic review.

Background And Purpose Magnetic resonance imaging (MRI) plays a central role in evaluating treatment response after stereotactic body radiotherapy (SBRT) for spinal metastases. However, current guidelines focus mainly on conventional MRI sequences and lack standardized, comprehensive criteria for post-treatment assessment. This systematic review aimed to summarize available evidence on MRI-based response assessment following spine SBRT, emphasizing the potential of advanced MRI techniques and computational tools to improve clinical decision-making.Materials And Methods We systematically searched PubMed, Scopus, Web of Science, and Embase from their inception to August 1, 2024. Two reviewers independently screened studies on MRI-based response assessment after SBRT for spinal metastases, evaluated eligibility, and extracted data on MRI techniques, response criteria, imaging biomarkers, and clinical outcomes.Results Thirteen studies met the inclusion criteria. Tumor volume changes assessed by sagittal T1-weighted MRI, with a minimum detectable difference of approximately 11 %, were essential for evaluating local control. T2 signal alterations and reductions in dynamic contrast-enhanced (DCE) MRI perfusion parameters, such as Ktrans and Vp, correlated with improved outcomes, including pain relief and local control. Pseudo-progression and intralesional fatty content were identified as key imaging features that may mimic progression. Diffusion-weighted imaging (DWI) and apparent diffusion coefficient (ADC) mapping showed promise as response biomarkers, but lack clinical validation. Radiomics and machine learning models improved predictive accuracy for treatment outcomes and individual follow-up strategies.Conclusions MRI provides essential morphological and functional biomarkers for response assessment after spine SBRT. Standardized, multi-parametric MRI protocols and computational tools are needed to optimize patient care.