Apparent Diffusion Coefficient Metrics to Differentiate between Treatment-Related Abnormalities and Tumor Progression in Post-Treatment Glioblastoma Patients: A Retrospective Study

SIMPLE SUMMARY: Patients suffering from glioblastoma receive treatment according to the Stupp protocol. After chemoradiotherapy, the glioblastoma either continue to develop, or treatment-related vascular damage comes into play, both causing new, seemingly identical contrast-enhancing lesions in follow-up MRI, where clinicians and radiologists alike can only differentiate between tumor progression (TP) and treatment-related abnormalities (TRA) by seeing the temporal evolution of the lesion and the patients clinical status. We investigate the use of diffusion MRI and the quantitative apparent diffusion coefficient (ADC) in a retrospective patient cohort and we sought to validate a previously reported ADC cutoff value for its distinctive properties between TP and TRA. In the end, ADC values were shown not to be highly discriminative and, compared to the mean ADC values between TP and TRA previously reported in the literature, are more overlapping than expected. ABSTRACT: Distinguishing treatment-related abnormalities (TRA) from tumor progression (TP) in glioblastoma patients is a diagnostic imaging challenge due to the identical morphology of conventional MR imaging sequences. Diffusion-weighted imaging (DWI) and its derived images of the apparent diffusion coefficient (ADC) have been suggested as diagnostic tools for this problem. The aim of this study is to determine the diagnostic accuracy of different cut-off values of the ADC to differentiate between TP and TRA. In total, 76 post-treatment glioblastoma patients with new contrast-enhancing lesions were selected. Lesions were segmented using a T1-weighted, contrast-enhanced scan. The mean ADC values of the segmentations were compared between TRA and TP groups. Diagnostic accuracy was compared by use of the area under the curve (AUC) and the derived sensitivity and specificity values from cutoff points. Although ADC values in TP (mean = 1.32 × 10(−3) mm(2)/s; SD = 0.31 × 10(−3) mm(2)/s) were significantly different compared to TRA (mean = 1.53 × 10(−3) mm(2)/s; SD = 0.28 × 10(−3) mm(2)/s) (p = 0.003), considerable overlap in their distributions exists. The AUC of ADC values to distinguish TP from TRA was 0.71, with a sensitivity and specificity of 65% and 70%, respectively, at an ADC value of 1.47 × 10(−3) mm(2)/s. These findings therefore indicate that ADC maps should not be used in discerning between TP and TRA at a certain timepoint without information on temporal evolution.