On the Prognosis of Multifocal Glioblastoma: An Evaluation Incorporating Volumetric MRI.
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ABSTRACT:
SUBMITTER: Kasper J
PROVIDER: S-EPMC8167648 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:IntroductionMR imaging can noninvasively visualize tumor phenotype characteristics at the macroscopic level. Here, we investigated whether somatic mutations are associated with and can be predicted by MRI-derived tumor imaging features of glioblastoma (GBM).MethodsSeventy-six GBM patients were identified from The Cancer Imaging Archive for whom preoperative T1-contrast (T1C) and T2-FLAIR MR images were available. For each tumor, a set of volumetric imaging features and their ratios were measured, including necrosis, contrast enhancing, and edema volumes. Imaging genomics analysis assessed the association of these features with mutation status of nine genes frequently altered in adult GBM. Finally, area under the curve (AUC) analysis was conducted to evaluate the predictive performance of imaging features for mutational status.ResultsOur results demonstrate that MR imaging features are strongly associated with mutation status. For example, TP53-mutated tumors had significantly smaller contrast enhancing and necrosis volumes (p = 0.012 and 0.017, respectively) and RB1-mutated tumors had significantly smaller edema volumes (p = 0.015) compared to wild-type tumors. MRI volumetric features were also found to significantly predict mutational status. For example, AUC analysis results indicated that TP53, RB1, NF1, EGFR, and PDGFRA mutations could each be significantly predicted by at least one imaging feature.ConclusionMRI-derived volumetric features are significantly associated with and predictive of several cancer-relevant, drug-targetable DNA mutations in glioblastoma. These results may shed insight into unique growth characteristics of individual tumors at the macroscopic level resulting from molecular events as well as increase the use of noninvasive imaging in personalized medicine.
| S-EPMC4648958 | biostudies-literature
Project description:Simultaneous, high-resolution imaging across a large number of synaptic and dendritic sites is critical for understanding how neurons receive and integrate signals. Yet, functional imaging that targets a large number of submicrometer-sized synaptic and dendritic locations poses significant technical challenges. We demonstrate a new parallelized approach to address such questions, increasing the signal-to-noise ratio by an order of magnitude compared to previous approaches. This selective access multifocal multiphoton microscopy uses a spatial light modulator to generate multifocal excitation in three dimensions (3D) and a Gaussian-Laguerre phase plate to simultaneously detect fluorescence from these spots throughout the volume. We test the performance of this system by simultaneously recording Ca2+ dynamics from cultured neurons at 98-118 locations distributed throughout a 3D volume. This is the first demonstration of 3D imaging in a "single shot" and permits synchronized monitoring of signal propagation across multiple different dendrites.
| S-EPMC6980307 | biostudies-literature
Project description:Publicly available Glioblastoma (GBM) datasets predominantly include pre-operative Magnetic Resonance Imaging (MRI) or contain few follow-up images for each patient. Access to fully longitudinal datasets is critical to advance the refinement of treatment response assessment. We release a single-center longitudinal GBM MRI dataset with expert ratings of selected follow-up studies according to the response assessment in neuro-oncology criteria (RANO). The expert rating includes details about the rationale of the ratings. For a subset of patients, we provide pathology information regarding methylation of the O6-methylguanine-DNA methyltransferase (MGMT) promoter status and isocitrate dehydrogenase 1 (IDH1), as well as the overall survival time. The data includes T1-weighted pre- and post-contrast, T2-weighted, and fluid-attenuated inversion recovery (FLAIR) MRI. Segmentations from state-of-the-art automated segmentation tools, as well as radiomic features, complement the data. Possible applications of this dataset are radiomics research, the development and validation of automated segmentation methods, and studies on response assessment. This collection includes MRI data of 91 GBM patients with a total of 638 study dates and 2487 images.
| S-EPMC9755255 | biostudies-literature
Project description:ObjectiveTo develop a radiomics risk score based on dynamic contrast-enhanced (DCE) MRI for prognosis prediction in patients with glioblastoma.Materials and methodsOne hundred and fifty patients (92 male [61.3%]; mean age ± standard deviation, 60.5 ± 13.5 years) with glioblastoma who underwent preoperative MRI were enrolled in the study. Six hundred and forty-two radiomic features were extracted from volume transfer constant (Ktrans), fractional volume of vascular plasma space (Vp), and fractional volume of extravascular extracellular space (Ve) maps of DCE MRI, wherein the regions of interest were based on both T1-weighted contrast-enhancing areas and non-enhancing T2 hyperintense areas. Using feature selection algorithms, salient radiomic features were selected from the 642 features. Next, a radiomics risk score was developed using a weighted combination of the selected features in the discovery set (n = 105); the risk score was validated in the validation set (n = 45) by investigating the difference in prognosis between the "radiomics risk score" groups. Finally, multivariable Cox regression analysis for progression-free survival was performed using the radiomics risk score and clinical variables as covariates.Results16 radiomic features obtained from non-enhancing T2 hyperintense areas were selected among the 642 features identified. The radiomics risk score was used to stratify high- and low-risk groups in both the discovery and validation sets (both p < 0.001 by the log-rank test). The radiomics risk score and presence of isocitrate dehydrogenase (IDH) mutation showed independent associations with progression-free survival in opposite directions (hazard ratio, 3.56; p = 0.004 and hazard ratio, 0.34; p = 0.022, respectively).ConclusionWe developed and validated the "radiomics risk score" from the features of DCE MRI based on non-enhancing T2 hyperintense areas for risk stratification of patients with glioblastoma. It was associated with progression-free survival independently of IDH mutation status.
| S-EPMC8390822 | biostudies-literature
Project description:BackgroundPseudoprogression is a diagnostic challenge in early posttreatment glioblastoma. We therefore developed and validated a radiomics model using multiparametric MRI to differentiate pseudoprogression from early tumor progression in patients with glioblastoma.MethodsThe model was developed from the enlarging contrast-enhancing portions of 61 glioblastomas within 3 months after standard treatment with 6472 radiomic features being obtained from contrast-enhanced T1-weighted imaging, fluid-attenuated inversion recovery imaging, and apparent diffusion coefficient (ADC) and cerebral blood volume (CBV) maps. Imaging features were selected using a LASSO (least absolute shrinkage and selection operator) logistic regression model with 10-fold cross-validation. Diagnostic performance for pseudoprogression was compared with that for single parameters (mean and minimum ADC and mean and maximum CBV) and single imaging radiomics models using the area under the receiver operating characteristics curve (AUC). The model was validated with an external cohort (n = 34) imaged on a different scanner and internal prospective registry data (n = 23).ResultsTwelve significant radiomic features (3 from conventional, 2 from diffusion, and 7 from perfusion MRI) were selected for model construction. The multiparametric radiomics model (AUC, 0.90) showed significantly better performance than any single ADC or CBV parameter (AUC, 0.57-0.79, P < 0.05), and better than a single radiomics model using conventional MRI (AUC, 0.76, P = 0.012), ADC (AUC, 0.78, P = 0.014), or CBV (AUC, 0.80, P = 0.43). The multiparametric radiomics showed higher performance in the external validation (AUC, 0.85) and internal validation (AUC, 0.96) than any single approach, thus demonstrating robustness.ConclusionsIncorporating diffusion- and perfusion-weighted MRI into a radiomics model improved diagnostic performance for identifying pseudoprogression and showed robustness in a multicenter setting.
| S-EPMC6380413 | biostudies-literature
Project description:Malignant gliomas are aggressive malignancies which inevitably recur despite multimodality treatment. In a subset of patients who are longer term survivors of this disease, progressive radiologic worsening can also occur from late effects of radiation rather than recurrent tumor, a differential diagnosis that is commonly considered in this setting. However, other causes for radiologic progression are not as well recognized and could potentially confound management leading to incorrect treatment decisions. Progressive multifocal leukoencephalopathy (PML) is a rare infectious demyelinating disease of the central nervous system seen primarily in immunocompromised patients, the early diagnosis and treatment of which remains a challenge. Here, we report a case of a long term survivor with glioblastoma whose diagnostic and therapeutic management was confounded by the development of PML. We review the radiological features and clinical course of this patient to highlight the dramatic neurological course in the setting of a highly malignant tumor, and emphasize the unusual changes in diffusion weighted images, and the need for clinical suspicion for early diagnosis of PML.
| S-EPMC5546753 | biostudies-other
Project description:BackgroundAlthough mutations in the promoter region of the telomerase reverse transcriptase (TERTp) gene are the most common alterations in glioblastoma (GBM), their clinical significance remains unclear. Therefore, we investigated the impact of TERTp status on patient outcome and clinicopathological features in patients with GBM over a long period of follow-up.MethodsWe retrospectively analyzed 153 cases of GBM. Six patients with isocitrate dehydrogenase 1 (IDH1) or H3F3A gene mutations were excluded from this study. Among the 147 cases of IDH wild-type GBM, 92 (62.6%) had the TERTp mutation. Clinical, immunohistochemical, and genetic factors (BRAF, TP53 gene mutation, CD133, ATRX expression, O 6-methylguanine-DNA methyltransferase [MGMT] promoter methylation) and copy number alterations (CNAs) were investigated.ResultsGBM patients with the TERTp mutation were older at first diagnosis versus those with TERTp wild type (66.0 vs. 60.0 years, respectively, P = .034), and had shorter progression-free survival (7 vs. 10 months, respectively, P = .015) and overall survival (16 vs. 24 months, respectively, P = .017). Notably, magnetic resonance imaging performed showed that TERTp-mutant GBM was strongly associated with multifocal/distant lesions (P = .004). According to the CNA analysis, TERTp mutations were positively correlated with EGFR amp/gain, CDKN2A deletion, and PTEN deletion; however, these mutations were negatively correlated with PDGFR amp/gain, CDK4 gain, and TP53 deletion.ConclusionsTERTp mutations were strongly correlated with multifocal/distant lesions and poor prognosis in patients with IDH wild-type GBM. Less aggressive GBM with TERTp wild type may be a distinct clinical and molecular subtype of IDH wild-type GBM.
| S-EPMC7586143 | biostudies-literature
Project description:Ten to twenty percent of newly diagnosed glioblastoma (GBM) patients initially present with multiple lesions, termed multifocal or multicentric GBM (M-GBM). The prognosis of these patients is poorer than that of solitary GBM (S-GBM) patients. However, it is unknown whether multifocality has a genetic, epigenetic, or molecular basis. Here, we identified the genetic and epigenetic characteristics of M-GBM by performing a comprehensive analysis of multidimensional data, including imaging, genetic, epigenetic, and gene expression profiles, from 30 M-GBM cases in The Cancer Genome Atlas database and comparing the results with those of 173 S-GBM cases. We found that M-GBMs had no IDH1, ATRX, or PDGFRA mutations and were significantly associated with the mesenchymal subtype. We also identified the CYB5R2 gene to be hypo-methylated and overexpressed in M-GBMs. The expression level of CYB5R2 was significantly associated with patient survival in two major independent GBM cohorts, totaling 758 cases. The IDH1 mutation was markedly associated with CYB5R2 promoter methylation, but the survival influence of CYB5R2 was independent of IDH1 mutation status. CYB5R2 expression was significantly associated with collagen maturation and the catabolic process and immunoregulation pathways. These results reveal that M-GBMs have some underlying genetic and epigenetic characteristics that are associated with poor prognosis and that CYB5R2 is a new epigenetic marker for GBM prognosis.
| S-EPMC4776337 | biostudies-literature
Project description:Although there have been a plethora of radiogenomics studies related to glioblastoma (GBM), most of them only used genomic information from tumor cells. In this study, we used radiogenomics profiling to identify MRI-associated immune cell markers in GBM, which was also correlated with prognosis. Expression levels of immune cell markers were correlated with quantitative MRI parameters in a total of 60 GBM patients. Fourteen immune cell markers (i.e., CD11b, CD68, CSF1R, CD163, CD33, CD123, CD83, CD63, CD49d and CD117 for myeloid cells, and CD4, CD3e, CD25 and CD8 for lymphoid cells) were selected for RNA-level analysis using quantitative RT-PCR. For MRI analysis, quantitative MRI parameters from FLAIR, contrast-enhanced (CE) T1WI, dynamic susceptibility contrast perfusion MRI and diffusion-weighted images were used. In addition, PFS associated with interesting mRNA data was performed by Kaplan-Meier survival analysis. CD163, which marks tumor associated microglia/macrophages (TAMs), showed the highest expression level in GBM patients. CD68 (TAMs), CSF1R (TAMs), CD33 (myeloid-derived suppressor cell) and CD4 (helper T cell, regulatory T cell) levels were highly positively correlated with nCBV values, while CD3e (helper T cell, cytotoxic T cell) and CD49d showed a significantly negative correlation with apparent diffusion coefficient (ADC) values. Moreover, regardless of any other molecular characteristics, CD49d was revealed as one independent factor for PFS of GBM patients by Cox proportional-hazards regression analysis (P = 0.0002). CD49d expression level CD49d correlated with ADC can be considered as a candidate biomarker to predict progression of GBM patients.
| S-EPMC6207678 | biostudies-literature
Project description:PurposeMagnetic resonance (MR) imaging and computed tomography (CT) are used almost exclusively in radiation therapy planning of glioblastoma multiforme (GBM), despite their well-recognized limitations. MR spectroscopic imaging (MRSI) can identify biochemical patterns associated with normal brain and tumor, predominantly by observation of choline (Cho) and N-acetylaspartate (NAA) distributions. In this study, volumetric 3-dimensional MRSI was used to map these compounds over a wide region of the brain and to evaluate metabolite-defined treatment targets (metabolic tumor volumes [MTV]).Methods and materialsVolumetric MRSI with effective voxel size of ∼1.0 mL and standard clinical MR images were obtained from 19 GBM patients. Gross tumor volumes and edema were manually outlined, and clinical target volumes (CTVs) receiving 46 and 60 Gy were defined (CTV46 and CTV60, respectively). MTVCho and MTVNAA were constructed based on volumes with high Cho and low NAA relative to values estimated from normal-appearing tissue.ResultsThe MRSI coverage of the brain was between 70% and 76%. The MTVNAA were almost entirely contained within the edema, and the correlation between the 2 volumes was significant (r=0.68, P=.001). In contrast, a considerable fraction of MTVCho was outside of the edema (median, 33%) and for some patients it was also outside of the CTV46 and CTV60. These untreated volumes were greater than 10% for 7 patients (37%) in the study, and on average more than one-third (34.3%) of the MTVCho for these patients were outside of CTV60.ConclusionsThis study demonstrates the potential usefulness of whole-brain MRSI for radiation therapy planning of GBM and revealed that areas of metabolically active tumor are not covered by standard RT volumes. The described integration of MTV into the RT system will pave the way to future clinical trials investigating outcomes in patients treated based on metabolic information.
| S-EPMC4346247 | biostudies-literature