Refinement of response assessment in neuro-oncology (RANO) using non-enhancing lesion type and contrast enhancement evolution pattern in IDH wild-type glioblastomas

Abstract

BackgroundUpdated response assessment in neuro-oncology (RANO) does not consider peritumoral non-enhancing lesion (NEL) and baseline (residual) contrast enhancement (CE) volume. The objective of this study is to explore helpful imaging characteristics to refine RANO for assessing early treatment response (pseudoprogression and time-to-progression [TTP]) in patients with IDH wild-type glioblastoma.MethodsThis retrospective study enrolled 86 patients with IDH wild-type glioblastoma who underwent consecutive MRI examinations before and after concurrent chemoradiotherapy (CCRT). NEL was classified as edema- or tumor-dominant type on pre-CCRT MRI. CE evolution was categorized into 4 patterns based on post-operative residual CE (measurable vs. non-measurable) and CE volume change (same criteria with RANO) during CCRT. Multivariable logistic regression, including clinical parameters, NEL type, and CE evolution pattern, was used to analyze pseudoprogression rate. TTP and OS according to NEL type and CE evolution pattern was analyzed by the Kaplan-Meier method.ResultsPseudoprogression rate was significantly lower (chi-square test, P=.047) and TTP was significantly shorter (hazard ratio [HR]=2.03, P=.005) for tumor-dominant type than edema-dominant type of NEL. NEL type was the only predictive marker of pseudoprogression on multivariate analysis (odds ratio=0.26, P=.046). Among CE evolution patterns, TTP and OS was shortest in patients with residual CE compared with those exhibiting new CE (HR=4.33, P<0.001 and HR=3.71, P=.009, respectively). In edema-dominant NEL type, both TTP and OS was stratified by CE evolution pattern (log-rank, P=.001), whereas it was not in tumor-dominant NEL.ConclusionsNEL type improves prediction of pseudoprogression and, together with CE evolution pattern, further stratifies TTP and OS in patients with IDH wild-type glioblastoma and may become a helpful biomarker for refining RANO.