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A recurrent tumor is defined as a re-emerging subclone originating from an ancestorial clone of the primary neoplasm. Hence, it should be distinguished from de novo tumor emerging from other clones. Herein, we describe an exceptional case in which the locally re-emerging glioma did not share genetic alterations of the primary tumor. While the initial tumor harbored mutations in IDH1 and TERT genes as well as 1p/19q codeletion, the re-emerging tumor did not present any of these genetic abnormalities. Variant calling for tumor samples using whole-genome sequencing revealed that 1696 mutations within the primary tumor faded in the re-emerging tumor, and that 4591 mutations were newly detected in the re-emerging tumor. These results suggested that the initial and re-emerging tumors did not share same clonal origins, although the second tumor appeared adjacent to the old surgical cavity 5 years after the initial surgery. We finally speculated that the re-emerging tumor could be a "de novo glioma" or "radiation-induced glioblastoma following treatment of a diffuse glioma." This case highlights the importance of molecular re-evaluation of clinically diagnosed "recurrent" glioma lesions. [ABSTRACT FROM AUTHOR]

Purpose: Arterial spin labeling (ASL) is a non-invasive perfusion technique that may be an alternative to dynamic susceptibility contrast magnetic resonance imaging (DSC-MRI) for assessment of brain tumors. To our knowledge, there have been no reports on histogram analysis of ASL. The purpose of this study was to determine whether ASL is comparable with DSC-MRI in terms of differentiating high-grade and low-grade gliomas by evaluating the histogram analysis of cerebral blood flow (CBF) in the entire tumor.Methods: Thirty-four patients with pathologically proven glioma underwent ASL and DSC-MRI. High-signal areas on contrast-enhanced T1-weighted images or high-intensity areas on fluid-attenuated inversion recovery images were designated as the volumes of interest (VOIs). ASL-CBF, DSC-CBF, and DSC-cerebral blood volume maps were constructed and co-registered to the VOI. Perfusion histogram analyses of the whole VOI and statistical analyses were performed to compare the ASL and DSC images.Results: There was no significant difference in the mean values for any of the histogram metrics in both of the low-grade gliomas (n = 15) and the high-grade gliomas (n = 19). Strong correlations were seen in the 75th percentile, mean, median, and standard deviation values between the ASL and DSC images. The area under the curve values tended to be greater for the DSC images than for the ASL images.Conclusions: DSC-MRI is superior to ASL for distinguishing high-grade from low-grade glioma. ASL could be an alternative evaluation method when DSC-MRI cannot be used, e.g., in patients with renal failure, those in whom repeated examination is required, and in children. [ABSTRACT FROM AUTHOR]

Enchondromatosis is a rare skeletal disorder characterized by the development of multiple enchondromas, which can also manifest non-cartilage tumors including gliomas. Here, we describe a genetic analysis of a low-grade glioma that developed in an enchondromatosis case. A 32-year-old man with a long history of enchondromatosis developed a left frontal tumor. The histopathological findings of his surgical specimen revealed characteristics of a low-grade glioma with an IDH1 c.395G>A (R132H) mutation and 1p/19q codeletion, which led to a definitive diagnosis of oligodendroglioma. A common point mutation in IDH1 (R132H) was detected in the patient's enchondroma and glioma-matched pair specimens. To the best of our knowledge, this is the first case of molecularly confirmed oligodendroglioma associated with enchondromatosis. Furthermore, identification of a common IDH1 mutation in enchondroma and oligodendroglioma-matched pair specimens supports the hypothesis that IDH1/ 2 mosaicism initiates tumorigenesis. [ABSTRACT FROM AUTHOR]

Purpose: This study aimed to compare the tumor volume definition using conventional magnetic resonance (MR) and 11C-methionine positron emission tomography (MET/PET) images in the differentiation of the pre-operative glioma grade by using whole-tumor histogram analysis of normalized cerebral blood volume (nCBV) maps.Materials and Methods: Thirty-four patients with histopathologically proven primary brain low-grade gliomas (n = 15) and high-grade gliomas (n = 19) underwent pre-operative or pre-biopsy MET/PET, fluid-attenuated inversion recovery, dynamic susceptibility contrast perfusion-weighted magnetic resonance imaging, and contrast-enhanced T1-weighted at 3.0 T. The histogram distribution derived from the nCBV maps was obtained by co-registering the whole tumor volume delineated on conventional MR or MET/PET images, and eight histogram parameters were assessed.Results: The mean nCBV value had the highest AUC value (0.906) based on MET/PET images. Diagnostic accuracy significantly improved when the tumor volume was measured from MET/PET images compared with conventional MR images for the parameters of mean, 50th, and 75th percentile nCBV value (p = 0.0246, 0.0223, and 0.0150, respectively).Conclusion: Whole-tumor histogram analysis of CBV map provides more valuable histogram parameters and increases diagnostic accuracy in the differentiation of pre-operative cerebral gliomas when the tumor volume is derived from MET/PET images. [ABSTRACT FROM AUTHOR]

Molecular biological characterization of tumors has become a pivotal procedure for glioma patient care. The aim of this study is to build conventional MRI-based radiomics model to predict genetic alterations within grade II/III gliomas attempting to implement lesion location information in the model to improve diagnostic accuracy. One-hundred and ninety-nine grade II/III gliomas patients were enrolled. Three molecular subtypes were identified: IDH1/2-mutant, IDH1/2-mutant with TERT promoter mutation, and IDH-wild type. A total of 109 radiomics features from 169 MRI datasets and location information from 199 datasets were extracted. Prediction modeling for genetic alteration was trained via LASSO regression for 111 datasets and validated by the remaining 58 datasets. IDH mutation was detected with an accuracy of 0.82 for the training set and 0.83 for the validation set without lesion location information. Diagnostic accuracy improved to 0.85 for the training set and 0.87 for the validation set when lesion location information was implemented. Diagnostic accuracy for predicting 3 molecular subtypes of grade II/III gliomas was 0.74 for the training set and 0.56 for the validation set with lesion location information implemented. Conventional MRI-based radiomics is one of the most promising strategies that may lead to a non-invasive diagnostic technique for molecular characterization of grade II/III gliomas. [ABSTRACT FROM AUTHOR]