Tumor response evaluation by combined modalities of chest magnetic resonance imaging and computed tomography in locally advanced non-small cell lung cancer after concurrent chemoradiotherapy

This study aimed to explore the role of a modified criteria for assessing tumor response to concurrent chemoradiotherapy (CCRT) in locally advanced non-small cell lung cancer (LA-NSCLC), using the combined modalities of anatomical and functional MRI and CT.One hundred and fifty-three patients with LA-NSCLC who underwent CCRT with continuous chest MRI and CT follow-up were analyzed. The tumor response to CCRT was evaluated two months after the completion of CCRT. The RECIST criteria (CT imaging) and modified criteria (combined chest MRI and CT imaging) were compared and validated on follow-up imaging. The chest MRI scan analysis included T1C, T2fs, DWI imaging and the apparent diffusion coefficient values. Progression free survival (PFS) ≥ 18 months was used as a surrogate endpoint of complete response to analyze the accuracy of tumor response assessment.Eight (5.2%) patients were considered to have complete response (CR) by the RECIST criteria while fifty-five (35.9%) were considered to have CR (CT + MRI) by the modified criteria. Using PFS ≥ 18 months as a surrogate for CR, the sensitivity and specificity of the modified criteria were 71.2% and 90.8% (AUC = 0.810, 95%CI 0.735-0.885), but were 9.1% and 97.7%, respectively, for the RECIST criteria (AUC = 0.534, 95%CI 0.441-0.627). The median PFS was 58.4 months for patients with CR (CT + MRI) and 9.7 months for those with non-CR (P < 0.001). Multivariate analysis showed that the tumor response evaluated by the modified criteria [CR (CT + MRI) vs. non-CR] was an independent factor for both PFS (HR 0.182, 95%CI 0.088-0.373, P < 0.001) and overall survival (HR 0.134, 95%CI 0.044-0.410, P < 0.001).Combined multi-parameter MRI and CT imaging could improve the accuracy of tumor response assessment in LA-NSCLC patients after definitive CCRT, therefore contributed to the risk stratification and survival prediction for clinical practice.