Predictive Value of Early DCE and DSC Perfusion MRI Parameters for Midterm Clinical Outcomes in Lung Cancer Brain Metastases Treated with Stereotactic Radiosurgery

Purpose: Stereotactic Radiosurgery (SRS) is an effective way of controlling the brain metastasis (BM) of lung carcinoma. This study evaluates the performance of dynamic contrast-enhanced MRI (DCE-MRI), and dynamic susceptibility contrast MRI (DSC-MRI) parameters to distinguish responders from non-responders at midterm follow-up in lung carcinoma BMs. Methods: Twenty-six patients (mean age 62 ± 10 years) with 54 lung carcinoma BMs (NSCLC 67%, SCLC 33%) underwent SRS. The DCE-MRI and DSC-MRI were performed at baseline and repeated 4–8 weeks post-SRS to predict treatment responses at the midterm follow-up (6–12 months). Midterm outcomes were classified according to RANO-BM criteria as responders (complete response, partial response, or stable disease) or non-responders (progressive disease). Receiver operating characteristic (ROC) analyses evaluated the diagnostic accuracy of individual perfusion parameters and their combinations. Results: Forty lesions (74%) were responders, while 14 (26%) were non-responders. Progressive lesions showed a mean volume increase of 5.5-fold, whereas responders demonstrated a 60% mean volume reduction. Responders showed significantly lower absolute post-SRS Ktrans (median 0.015 vs. 0.035 min⁻¹; p=0.005), a higher proportional decrease in Ktrans from baseline (−27% vs. +13%; p=0.017), and lower post-SRS Ve (p=0.009) compared to non-responders. Absolute post-SRS K-trans had the highest individual predictive accuracy (AUC=0.75, accuracy=78%, sensitivity=86%, specificity=55%). Neither the dynamic change nor post-SRS nCBV alone predicted midterm response; however, combining post-SRS nCBV with Ktrans slightly improved predictive performance (AUC=0.76, accuracy=79%). Conclusion: Early post-SRS absolute Ktrans is the best perfusion parameter for predicting midterm response in lung carcinoma BMs. DSC-MRI parameters alone offer limited predictive value.