scholarly journals Prediction of Lower Grade Insular Glioma Molecular Pathology Using Diffusion Tensor Imaging Metric-Based Histogram Parameters

2021 ◽  
Vol 11 ◽  
Author(s):  
Zhenxing Huang ◽  
Changyu Lu ◽  
Gen Li ◽  
Zhenye Li ◽  
Shengjun Sun ◽  
...  
Keyword(s):  
Diffusion Tensor Imaging ◽  
Molecular Pathology ◽  
Diffusion Tensor ◽  
Lower Grade ◽  
Idh Mutation ◽  
Tert Promoter Mutation ◽  
Mgmt Methylation ◽  
Promoter Mutation ◽  
Tert Promoter ◽  
The Mean

ObjectivesTo explore whether a simplified lesion delineation method and a set of diffusion tensor imaging (DTI) metric-based histogram parameters (mean, 25th percentile, 75th percentile, skewness, and kurtosis) are efficient at predicting the molecular pathology status (MGMT methylation, IDH mutation, TERT promoter mutation, and 1p19q codeletion) of lower grade insular gliomas (grades II and III).Methods40 lower grade insular glioma patients in two medical centers underwent preoperative DTI scanning. For each patient, the entire abnormal area in their b-non (b0) image was defined as region of interest (ROI), and a set of histogram parameters were calculated for two DTI metrics, fractional anisotropy (FA) and mean diffusivity (MD). Then, we compared how these DTI metrics varied according to molecular pathology and glioma grade, with their predictive performance individually and jointly assessed using receiver operating characteristic curves. The reliability of the combined prediction was evaluated by the calibration curve and Hosmer and Lemeshow test.ResultsThe mean, 25th percentile, and 75th percentile of FA were associated with glioma grade, while the mean, 25th percentile, 75th percentile, and skewness of both FA and MD predicted IDH mutation. The mean, 25th percentile, and 75th percentile of FA, and all MD histogram parameters significantly distinguished TERT promoter status. Similarly, all MD histogram parameters were associated with 1p19q status. However, none of the parameters analyzed for either metric successfully predicted MGMT methylation. The 25th percentile of FA yielded the highest prediction efficiency for glioma grade, IDH mutation, and TERT promoter mutation, while the 75th percentile of MD gave the best prediction of 1p19q codeletion. The combined prediction could enhance the discrimination of grading, IDH and TERT mutation, and also with a good fitness.ConclusionsOverall, more invasive gliomas showed higher FA and lower MD values. The simplified ROI delineation method presented here based on the combination of appropriate histogram parameters yielded a more practical and efficient approach to predicting molecular pathology in lower grade insular gliomas. This approach could help clinicians to determine the extent of tumor resection required and reduce complications, enabling more precise treatment of insular gliomas in combination with radiotherapy and chemotherapy.

PATH-19. TERT PROMOTER MUTATION, NOT H3K27M MUTATION IS A PROGNOSTIC FACTOR FOR ADULT THALAMIC GLIOMAS

2021 ◽  
Vol 23 (Supplement_6) ◽  
pp. vi118-vi119
Author(s):  
Masayuki Nitta ◽  
Yoshihiro Muragaki ◽  
Takashi Komori ◽  
kenta Masui ◽  
Taiichi Saito ◽  
...  
Keyword(s):  
Prognostic Factor ◽  
Tumor Resection ◽  
Pathological Diagnosis ◽  
Diffuse Glioma ◽  
Idh Mutation ◽  
Tert Promoter Mutation ◽  
Promoter Mutation ◽  
Who Grade ◽  
Tert Promoter ◽  
H3k27m Mutation

Abstract Purpose Thalamic diffuse glioma is classified as WHO grade 4 as Diffuse midline glioma, H3K27M mutation if H3K27M mutation was found regardless of its histological findings, but the significance of H3K27M mutation is not clear compared with pediatric cases. We aimed to find genetic prognostic factors in adult thalamic diffuse gliomas. METHODS Pathological diagnosis, genetic abnormalities, and clinical course of adult newly diagnosed thalamic gliomas diagnosed and treated at our institution from July 2007 to March 2020 were retrospectively analyzed. RESULTS The number of cases was 41 (24 males, 17 females), median age was 47 years (20-75 years). Tumor localization was 20 cases on the left, 14 cases on the right, and 7 cases on both sides. The pathological diagnosis was GBM 15 cases, DMG 15 cases, AA-IDH WT 7 cases, DA-IDH WT 4 cases, all of which were IDH wild type, and none of them had IDH mutation and 1p/19q co-deletion. H3K27M mutations were found in 15 cases and TERT promoter mutations were found in 12 cases, both of which were completely mutually exclusive. Tumor resection and biopsy was performed in 33 and 8 cases, respectively, and the median removal rate was 95% for those who underwent tumor resection. The median PFS and OS of all cases were 14.3 months and 38 months, respectively, and the median OS by pathological diagnosis was GBM 12.4 months, DMG 47.4 months, AA-IDH WT 37.3 months, DA-IDH WT not reached. The median OS in the H3K27M mutant group (47.4 months) was significantly better (p=0.02) than that in the TERT promoter mutation group (13.5 months). CONCLUSION There was no IDH mutation in adult thalamic gliomas, the H3K27M mutation and the TERT promoter mutation were mutually exclusive. The H3K27M mutation was not a prognostic factor, but the TERT promoter mutation was the strongest prognostic factor.

scholarly journals TB-04 TERT PROMOTER MUTATION AS A SUSCEPTIBLE MOLECULAR MARKER OF BCNU LOCAL THERAPY

2019 ◽  
Vol 1 (Supplement_2) ◽  
pp. ii10-ii11
Author(s):  
Shigeta Miyake ◽  
Kensuke Tateishi ◽  
Joe Sasame ◽  
Yohei Miyake ◽  
Shinichirou Matsuyama ◽  
...  
Keyword(s):  
Molecular Marker ◽  
Methylation Status ◽  
Malignant Gliomas ◽  
Local Therapy ◽  
Tert Promoter Mutation ◽  
Mgmt Methylation ◽  
Promoter Mutation ◽  
Tert Promoter ◽  
Tert Promoter Mutations ◽  
Promoter Mutations

Abstract INTRODUCTION Alkylating agents, including Temozolomide (TMZ) and CCNU (ACNU) have been widely accepted as a standard treatment in malignant gliomas. Several studies also demonstrated that BCNU wafer placement extended survival in glioblastoma patients. However, little study demonstrated gene-specific efficacy of BCNU local therapy in malignant gliomas. Herein, we investigated BCNU sensitivity for patient-derived primary cultured glioma cells. MATERIALS AND METHODS From January 2017 to July 2019, 58 gliomas (grade III, IV) were tested genomic analysis and ATP-based cell viability after BCNU treatment. IDH1/2 mutation and TERT promoter mutation status was determined by Sanger sequencing. MGMT methylation status were evaluated by methylation specific PCR. RESULTS Of 58 cases,10 cases (17.2%) and 32 (55.2%) cases harbored IDH1/2 mutation and TERT mutation (C228T, C250T), respectively. Among them, co-mutation was identified in 5/58 cases (8.6%). MGMT was methylated in 17/58 cases (29.3%). Interestingly, the presence of TERT promoter mutation was positively correlated with BCNU sensitivity, particularly in IDH1/2 wild-type tumors (p<0.05). In contrast, there was no significant relationship between TMZ sensitivity and IDH mutation/MGMT methylation status. CONCLUSION Although sample size is small, our results imply TERT promoter mutations might be a predictive molecular marker for BCNU sensitivity in malignant gliomas. Since TERT mutations are located at two hot spot loci (C228T and C250T), vast majority of TERT promoter mutations can be evaluated during surgery, which may contribute tailored therapeutic strategy in malignant gliomas.

RBIO-03. INITIAL RESULT OF DEVELOP ROBUST DEEP LEARNING MODEL FOR DETECTING GENOMIC STATUS IN GLIOMAS AGAINST IMAGE DIFFERENCES AMONG FACILITIES

2021 ◽  
Vol 23 (Supplement_6) ◽  
pp. vi192-vi192
Author(s):  
Satoshi Takahashi ◽  
Masamichi Takahashi ◽  
Manabu Kinoshita ◽  
Mototaka Miyake ◽  
Jun Sese ◽  
...  
Keyword(s):  
Deep Learning ◽  
Brain Tumor ◽  
Learning Model ◽  
Tumor Segmentation ◽  
Idh Mutation ◽  
Tert Promoter Mutation ◽  
Promoter Mutation ◽  
Test Portion ◽  
Tert Promoter ◽  
Deep Learning Model

Abstract BACKGROUND The importance of detecting the genomic status of gliomas is increasingly recognized and IDH (isocitrate dehydrogenase) mutation and TERT (telomerase reverse transcriptase) promoter mutation have a significant impact on treatment decisions. Noninvasive prediction of these genomic statuses in gliomas is a challenging problem; however, a deep learning model using magnetic resonance imaging (MRI) can be a solution. The image differences among facilities causing performance degradation, called domain shift, have also been reported in other tasks such as brain tumor segmentation. We investigated whether a deep learning model could predict the gene status, and if so, to what extent it would be affected by domain shift. METHOD We used the Multimodal Brain Tumor Segmentation Challenge (BraTS) data and the Japanese cohort (JC) dataset consisted of brain tumor images collected from 544 patients in 10 facilities in Japan. We focused on IDH mutation and TERT promoter mutation. The deep learning models to predict the statuses of these genes were trained by the BraTS dataset or the training portion of the JC dataset, and the test portion of the JC dataset evaluated the accuracy of the models. RESULTS The IDH mutation predicting model trained by the BraTS dataset showed 80.0% accuracy for the validation portion of the BraTS dataset; however, only 67.3% for the test portion of the JC dataset. The TERT promoter mutation predicting model trained by the training portion of the JC dataset showed only 49% accuracy for the test portion of the JC dataset. CONCLUSION IDH mutation can be predicted by deep learning models using MRI, but the performance degeneration by domain shift was significant. On the other hand, TERT promoter mutation could not be predicted accurately enough by current deep learning techniques. In both mutations, further studies are needed.

Diffusion and perfusion MRI may predict EGFR amplification and the TERT promoter mutation status of IDH-wildtype lower-grade gliomas

2020 ◽  
Vol 30 (12) ◽  
pp. 6475-6484
Author(s):  
Yae Won Park ◽  
Sung Soo Ahn ◽  
Chae Jung Park ◽  
Kyunghwa Han ◽  
Eui Hyun Kim ◽  
...  
Keyword(s):  
Perfusion Mri ◽  
Lower Grade ◽  
Tert Promoter Mutation ◽  
Promoter Mutation ◽  
Mutation Status ◽  
Egfr Amplification ◽  
Tert Promoter
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