The value of adding DWI and FLAIR signal changes in the resection cavity on the diagnostic performance of BT-RADS category 3 for tumor progression prediction in post-treated glioma patients: a prospective pilot study

Author:

Metwally Maha IbrahimORCID,Hafez Faten Fawzy Mohammad,Ibrahim Sara Abdulrhman,Morsy Ahmed Ali,Zeed Nesma Adel

Abstract

Abstract Background BT-RADS is a structured reporting system of post-treatment glioma. BT-RADS category 3 carries a probability of recurrent malignancy versus treatment-related changes. The aim of this study is to evaluate the additive value of DWI and resection cavity FLAIR signal changes to BT-RADS category 3 in the prediction of tumor progression. We prospectively evaluated follow-up contrast-enhanced MR imaging where 27 post-treated glioma patients were assigned BT-RADS category 3. In all images, FLAIR signal, enhancement component, mass effect, and ADCmean were assessed. We used imaging follow-up from the second stage of the study as the gold standard for comparing the diagnostic performance of BT-RADS category 3 for predicting tumor recurrence before and after the addition of DWI and resection cavity FLAIR signal changes. ROC curves analyses were assessed and compared using the Delong test. Results 48.1% of patients had tumor recurrence and 51.9% of patients had treatment-related changes. There was significant difference between ADCmean in recurrent and non-recurrent groups measuring 0.9 and 1.15 × 10−3mm2/s, respectively (p value < 0.001). BT-RADS, BT-RADS added DWI, and BT-RADS added DWI and resection cavity FLAIR signal had a specificity of 64.3, 71.4, and 71.4%, sensitivity of 76.9, 84.6, and 92.3%, and accuracy of 70.5, 77.8, and 81.5%, with improved AUC from 0.706 (95% CI of 0.50–0.86) to 0.78 (95% CI of 0.58–0.92) to 0.819 (95% CI of 0.64–0.94), respectively. Conclusions Adding DWI and resection cavity FLAIR signal alteration improves the diagnostic performance of BT-RADS category 3.

Publisher

Springer Science and Business Media LLC

Subject

Radiology, Nuclear Medicine and imaging

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