Radiomics of Pediatric Low-Grade Gliomas: Toward a Pretherapeutic Differentiation of BRAF-Mutated and BRAF-Fused Tumors
| Autor: | Wagner, M W, Hainc, N, Khalvati, F, Namdar, K, Figueiredo, L, Sheng, M, Laughlin, S, Shroff, M M, Bouffet, E, Tabori, U, Hawkins, C, Yeom, K W, Ertl-Wagner, B B |
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| Přispěvatelé: | University of Zurich |
| Rok vydání: | 2021 |
| Předmět: |
Oncology
medicine.medical_specialty medicine.diagnostic_test Receiver operating characteristic business.industry Area under the curve 610 Medicine & health Retrospective cohort study Fluid-attenuated inversion recovery Confidence interval 030218 nuclear medicine & medical imaging 03 medical and health sciences 0302 clinical medicine Text mining 10043 Clinic for Neuroradiology Internal medicine Cohort Biopsy medicine Radiology Nuclear Medicine and imaging Neurology (clinical) business 030217 neurology & neurosurgery |
| Zdroj: | American Journal of Neuroradiology. 42:759-765 |
| ISSN: | 1936-959X 0195-6108 |
| Popis: | BACKGROUND AND PURPOSE B-Raf proto-oncogene, serine/threonine kinase (BRAF) status has important implications for prognosis and therapy of pediatric low-grade gliomas. Currently, BRAF status classification relies on biopsy. Our aim was to train and validate a radiomics approach to predict BRAF fusion and BRAF V600E mutation. MATERIALS AND METHODS In this bi-institutional retrospective study, FLAIR MR imaging datasets of 115 pediatric patients with low-grade gliomas from 2 children's hospitals acquired between January 2009 and January 2016 were included and analyzed. Radiomics features were extracted from tumor segmentations, and the predictive model was tested using independent training and testing datasets, with all available tumor types. The model was selected on the basis of a grid search on the number of trees, opting for the best split for a random forest. We used the area under the receiver operating characteristic curve to evaluate model performance. RESULTS The training cohort consisted of 94 pediatric patients with low-grade gliomas (mean age, 9.4 years; 45 boys), and the external validation cohort comprised 21 pediatric patients with low-grade gliomas (mean age, 8.37 years; 12 boys). A 4-fold cross-validation scheme predicted BRAF status with an area under the curve of 0.75 (SD, 0.12) (95% confidence interval, 0.62-0.89) on the internal validation cohort. By means of the optimal hyperparameters determined by 4-fold cross-validation, the area under the curve for the external validation was 0.85. Age and tumor location were significant predictors of BRAF status (P values = .04 and |
| Databáze: | OpenAIRE |
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