RESUMO
PURPOSE: According to the World Health Organization classification for tumors of the central nervous system, mutation status of the isocitrate dehydrogenase (IDH) genes has become a major diagnostic discriminator for gliomas. Therefore, imaging-based prediction of IDH mutation status is of high interest for individual patient management. We compared and evaluated the diagnostic value of radiomics derived from dual positron emission tomography (PET) and magnetic resonance imaging (MRI) data to predict the IDH mutation status non-invasively. METHODS: Eighty-seven glioma patients at initial diagnosis who underwent PET targeting the translocator protein (TSPO) using [18F]GE-180, dynamic amino acid PET using [18F]FET, and T1-/T2-weighted MRI scans were examined. In addition to calculating tumor-to-background ratio (TBR) images for all modalities, parametric images quantifying dynamic [18F]FET PET information were generated. Radiomic features were extracted from TBR and parametric images. The area under the receiver operating characteristic curve (AUC) was employed to assess the performance of logistic regression (LR) classifiers. To report robust estimates, nested cross-validation with five folds and 50 repeats was applied. RESULTS: TBRGE-180 features extracted from TSPO-positive volumes had the highest predictive power among TBR images (AUC 0.88, with age as co-factor 0.94). Dynamic [18F]FET PET reached a similarly high performance (0.94, with age 0.96). The highest LR coefficients in multimodal analyses included TBRGE-180 features, parameters from kinetic and early static [18F]FET PET images, age, and the features from TBRT2 images such as the kurtosis (0.97). CONCLUSION: The findings suggest that incorporating TBRGE-180 features along with kinetic information from dynamic [18F]FET PET, kurtosis from TBRT2, and age can yield very high predictability of IDH mutation status, thus potentially improving early patient management.
RESUMO
Extracranial metastases of intracranial meningiomas are rare. Little is known about the mutational pattern of these tumors and their metastatic seeding. Here, we retrospectively explored the molecular alterations of these metastatic lesions and their respective intracranial tumor manifestations.Histology and genome sequencing were performed in intracranial meningiomas and their extracranial metastatic lesions operated upon between 2002 and 2021. Next-generation DNA/RNA sequencing (NGS) and methylome analysis were performed to determine molecular alterations.We analyzed the tumors of five patients with clinically suspected metastases of a meningioma using methylome analysis and next generation panel sequencing of the primary tumors as well as the metastatic lesions. Metastases were found in the spinal cord and one in the lung. In four of these patients, molecular analyses confirmed metastatic disease, while the fifth patient was found to harbor two molecularly distinct meningiomas. On pathological assessment, the primary lesions ranged from CNS WHO grades 1 to 3 (integrated molecular-morphologic meningioma classification scores 2 to 6). Of the four true metastatic cases, three out of the four metastasizing tumors harbored alterations in the BAP1 gene, comprising a stop-mutation combined with copy-number loss (WHO grade 1), copy number loss (WHO grade 3) and a frameshift mutation (WHO grade 2). Furthermore, the latter was confirmed to harbor a BAP1 tumor predisposition syndrome. The fourth metastasizing tumor had copy-number losses in NF2 and PTEN. Only one of four showed CDKN2A homozygous deletion; none showed TERT promotor mutation.Our results molecularly confirm true metastatic disease in four meningioma patients. BAP1 gene alterations were the most frequent. Larger cohorts, most likely from multicenter studies are necessary to evaluate the role of BAP-1 alterations to further understand the metastatic spread in meningiomas. for metastatic spread and might indicate patients at risk for metastatic spread. Further explorations within larger cohorts are necessary to validate these findings which might influence the clinical management in the future.
