Prediction of TERTp-mutation status in IDH-wildtype high-grade gliomas using pre-treatment dynamic 18FFET PET radiomics

Li, Zhicong; Kaiser, Lena; Holzgreve, Adrien; Ruf, Viktoria C.; Suchorska, Bogdana; Wenter, Vera; Quach, Stefanie; Herms, Jochen; Bartenstein, Peter; Tonn, Jörg-Christian; Unterrainer, Marcus und Albert, Nathalie L. (2021): Prediction of TERTp-mutation status in IDH-wildtype high-grade gliomas using pre-treatment dynamic 18FFET PET radiomics. In: European journal of nuclear medicine and molecular imaging, Bd. 48, Nr. 13: S. 4415-4425

Abstract

PURPOSE To evaluate radiomic features extracted from standard static images (20-40~min p.i.), early summation images (5-15~min p.i.), and dynamic 18FFET PET images for the prediction of TERTp-mutation status in patients with IDH-wildtype high-grade glioma. METHODS A total of 159 patients (median age 60.2~years, range 19-82~years) with newly diagnosed IDH-wildtype diffuse astrocytic glioma (WHO grade III or IV) and dynamic 18FFET PET prior to surgical intervention were enrolled and divided into a training (n = 112) and a testing cohort (n = 47) randomly. First-order, shape, and texture radiomic features were extracted from standard static (20-40~min summation images; TBR20-40), early static (5-15~min summation images; TBR5-15), and dynamic (time-to-peak; TTP) images, respectively. Recursive feature elimination was used for feature selection by 10-fold cross-validation in the training cohort after normalization, and logistic regression models were generated using the radiomic features extracted from each image to differentiate TERTp-mutation status. The areas under the ROC curve (AUC), accuracy, sensitivity, specificity, and positive and negative predictive value were calculated to illustrate diagnostic power in both the training and testing cohort. RESULTS The TTP model comprised nine selected features and achieved highest predictability of TERTp-mutation with an AUC of 0.82 (95{\%} confidence interval 0.71-0.92) and sensitivity of 92.1{\%} in the independent testing cohort. Weak predictive capability was obtained in the TBR5-15 model, with an AUC of 0.61 (95{\%} CI 0.42-0.80) in the testing cohort, while no predictive power was observed in the TBR20-40 model. CONCLUSIONS Radiomics based on TTP images extracted from dynamic 18FFET PET can predict the TERTp-mutation status of IDH-wildtype diffuse astrocytic high-grade gliomas with high accuracy preoperatively.

• Dokumententyp: Zeitschriftenartikel
• Fakultät: Medizin
• Themengebiete: 600 Technik, Medizin, angewandte Wissenschaften > 610 Medizin und Gesundheit
• Sprache: Englisch