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Purpose: While the T2-FLAIR mismatch sign is highly specific for isocitrate dehydrogenase (IDH)-mutant, 1p/19q-noncodeleted astrocytomas among lower-grade gliomas, its utility in WHO grade 4 gliomas is not well-studied. We derived the partial T2-FLAIR mismatch sign as an imaging biomarker for IDH mutation in WHO grade 4 gliomas., Methods: Preoperative MRI scans of adult WHO grade 4 glioma patients (n = 2165) from the multi-institutional ReSPOND (Radiomics Signatures for PrecisiON Diagnostics) consortium were analyzed. Diagnostic performance of the partial T2-FLAIR mismatch sign was evaluated. Subset analyses were performed to assess associations of imaging markers with overall survival (OS)., Results: One hundred twenty-one (5.6%) of 2165 grade 4 gliomas were IDH-mutant. Partial T2-FLAIR mismatch was present in 40 (1.8%) cases, 32 of which were IDH-mutant, yielding 26.4% sensitivity, 99.6% specificity, 80.0% positive predictive value, and 95.8% negative predictive value. Multivariate logistic regression demonstrated IDH mutation was significantly associated with partial T2-FLAIR mismatch (odds ratio [OR] 5.715, 95% CI [1.896, 17.221], p = 0.002), younger age (OR 0.911 [0.895, 0.927], p < 0.001), tumor centered in frontal lobe (OR 3.842, [2.361, 6.251], p < 0.001), absence of multicentricity (OR 0.173, [0.049, 0.612], p = 0.007), and presence of cystic (OR 6.596, [3.023, 14.391], p < 0.001) or non-enhancing solid components (OR 6.069, [3.371, 10.928], p < 0.001). Multivariate Cox analysis demonstrated cystic components (p = 0.024) and non-enhancing solid components (p = 0.003) were associated with longer OS, while older age (p < 0.001), frontal lobe center (p = 0.008), multifocality (p < 0.001), and multicentricity (p < 0.001) were associated with shorter OS., Conclusion: Partial T2-FLAIR mismatch sign is highly specific for IDH mutation in WHO grade 4 gliomas., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Background: Imaging of glioblastoma patients after maximal safe resection and chemoradiation commonly demonstrates new enhancements that raise concerns about tumor progression. However, in 30% to 50% of patients, these enhancements primarily represent the effects of treatment, or pseudo-progression (PsP). We hypothesize that quantitative machine learning analysis of clinically acquired multiparametric magnetic resonance imaging (mpMRI) can identify subvisual imaging characteristics to provide robust, noninvasive imaging signatures that can distinguish true progression (TP) from PsP., Methods: We evaluated independent discovery (n = 40) and replication (n = 23) cohorts of glioblastoma patients who underwent second resection due to progressive radiographic changes suspicious for recurrence. Deep learning and conventional feature extraction methods were used to extract quantitative characteristics from the mpMRI scans. Multivariate analysis of these features revealed radiophenotypic signatures distinguishing among TP, PsP, and mixed response that compared with similar categories blindly defined by board-certified neuropathologists. Additionally, interinstitutional validation was performed on 20 new patients., Results: Patients who demonstrate TP on neuropathology are significantly different (P < .0001) from those with PsP, showing imaging features reflecting higher angiogenesis, higher cellularity, and lower water concentration. The accuracy of the proposed signature in leave-one-out cross-validation was 87% for predicting PsP (area under the curve [AUC], 0.92) and 84% for predicting TP (AUC, 0.83), whereas in the discovery/replication cohort, the accuracy was 87% for predicting PsP (AUC, 0.84) and 78% for TP (AUC, 0.80). The accuracy in the interinstitutional cohort was 75% (AUC, 0.80)., Conclusion: Quantitative mpMRI analysis via machine learning reveals distinctive noninvasive signatures of TP versus PsP after treatment of glioblastoma. Integration of the proposed method into clinical studies can be performed using the freely available Cancer Imaging Phenomics Toolkit., (© 2020 American Cancer Society.)

Objective: Machine learning has potential to play a key role across a variety of medical imaging applications. This review seeks to elucidate the ways in which machine learning can aid and enhance diagnosis, treatment, and follow-up in neurooncology., Conclusion: Given the rapid pace of development in machine learning over the past several years, a basic proficiency of the key tenets and use cases in the field is critical to assessing potential opportunities and challenges of this exciting new technology.

Purpose: Lower-grade gliomas (WHO grade II/III) have been classified into clinically relevant molecular subtypes based on IDH and 1p/19q mutation status. The purpose was to investigate whether T2/FLAIR MRI features could distinguish between lower-grade glioma molecular subtypes. Experimental Design: MRI scans from the TCGA/TCIA lower grade glioma database ( n = 125) were evaluated by two independent neuroradiologists to assess (i) presence/absence of homogenous signal on T2WI; (ii) presence/absence of "T2-FLAIR mismatch" sign; (iii) sharp or indistinct lesion margins; and (iv) presence/absence of peritumoral edema. Metrics with moderate-substantial agreement underwent consensus review and were correlated with glioma molecular subtypes. Somatic mutation, DNA copy number, DNA methylation, gene expression, and protein array data from the TCGA lower-grade glioma database were analyzed for molecular-radiographic associations. A separate institutional cohort ( n = 82) was analyzed to validate the T2-FLAIR mismatch sign. Results: Among TCGA/TCIA cases, interreader agreement was calculated for lesion homogeneity [ κ = 0.234 (0.111-0.358)], T2-FLAIR mismatch sign [ κ = 0.728 (0.538-0.918)], lesion margins [ κ = 0.292 (0.135-0.449)], and peritumoral edema [ κ = 0.173 (0.096-0.250)]. All 15 cases that were positive for the T2-FLAIR mismatch sign were IDH -mutant, 1p/19q non-codeleted tumors ( P < 0.0001; PPV = 100%, NPV = 54%). Analysis of the validation cohort demonstrated substantial interreader agreement for the T2-FLAIR mismatch sign [ κ = 0.747 (0.536-0.958)]; all 10 cases positive for the T2-FLAIR mismatch sign were IDH -mutant, 1p/19q non-codeleted tumors ( P < 0.00001; PPV = 100%, NPV = 76%). Conclusions: Among lower-grade gliomas, T2-FLAIR mismatch sign represents a highly specific imaging biomarker for the IDH -mutant, 1p/19q non-codeleted molecular subtype. Clin Cancer Res; 23(20); 6078-85. ©2017 AACR ., (©2017 American Association for Cancer Research.)

Objective: Individual MRI characteristics (e.g., volume) are routinely used to identify survival-associated phenotypes for glioblastoma (GBM). This study investigated whether combinations of MRI features can also stratify survival. Furthermore, the molecular differences between phenotype-induced groups were investigated., Methods: Ninety-two patients with imaging, molecular, and survival data from the TCGA (The Cancer Genome Atlas)-GBM collection were included in this study. For combinatorial phenotype analysis, hierarchical clustering was used. Groups were defined based on a cutpoint obtained via tree-based partitioning. Furthermore, differential expression analysis of microRNA (miRNA) and mRNA expression data was performed using GenePattern Suite. Functional analysis of the resulting genes and miRNAs was performed using Ingenuity Pathway Analysis. Pathway analysis was performed using Gene Set Enrichment Analysis., Results: Clustering analysis reveals that image-based grouping of the patients is driven by 3 features: volume-class, hemorrhage, and T1/FLAIR-envelope ratio. A combination of these features stratifies survival in a statistically significant manner. A cutpoint analysis yields a significant survival difference in the training set (median survival difference: 12 months, p = 0.004) as well as a validation set (p = 0.0001). Specifically, a low value for any of these 3 features indicates favorable survival characteristics. Differential expression analysis between cutpoint-induced groups suggests that several immune-associated (natural killer cell activity, T-cell lymphocyte differentiation) and metabolism-associated (mitochondrial activity, oxidative phosphorylation) pathways underlie the transition of this phenotype. Integrating data for mRNA and miRNA suggests the roles of several genes regulating proliferation and invasion., Conclusions: A 3-way combination of MRI phenotypes may be capable of stratifying survival in GBM. Examination of molecular processes associated with groups created by this combinatorial phenotype suggests the role of biological processes associated with growth and invasion characteristics.

Purpose: The purpose of our study was to assess whether a model combining clinical factors, MR imaging features, and genomics would better predict overall survival of patients with glioblastoma (GBM) than either individual data type., Methods: The study was conducted leveraging The Cancer Genome Atlas (TCGA) effort supported by the National Institutes of Health. Six neuroradiologists reviewed MRI images from The Cancer Imaging Archive (http://cancerimagingarchive.net) of 102 GBM patients using the VASARI scoring system. The patients' clinical and genetic data were obtained from the TCGA website (http://www.cancergenome.nih.gov/). Patient outcome was measured in terms of overall survival time. The association between different categories of biomarkers and survival was evaluated using Cox analysis., Results: The features that were significantly associated with survival were: (1) clinical factors: chemotherapy; (2) imaging: proportion of tumor contrast enhancement on MRI; and (3) genomics: HRAS copy number variation. The combination of these three biomarkers resulted in an incremental increase in the strength of prediction of survival, with the model that included clinical, imaging, and genetic variables having the highest predictive accuracy (area under the curve 0.679±0.068, Akaike's information criterion 566.7, P<0.001)., Conclusion: A combination of clinical factors, imaging features, and HRAS copy number variation best predicts survival of patients with GBM., (Copyright © 2014 Elsevier Masson SAS. All rights reserved.)

Purpose: To study whether anaplastic astrocytomas that are nonenhancing and/or well-circumscribed (expansive) are associated with a better prognosis., Materials and Methods: We retrospectively identified 59 patients with pathologically confirmed World Health Organizaiton (WHO) grade III anaplastic astrocytoma who underwent craniotomy at our institution from 1995 through 2006. We assessed prognostic variables including age, enhancement (EAA-34 patients) vs. nonenhancement (NEAA-25 patients), MR growth patterns (expansive [28 patients] vs. mixed/infiltrative [31 patients]), recursive partitioning analysis (RPA) class, resection extent, and addition of chemotherapy. Primary outcome measure was survival., Results: Kaplan-Meier curves showed improved survival in NEAA, expansive tumors, and RPA 1 class patients. Within RPA class I patients, expansive growth pattern remained a significant advantage in survival time. Examining extent of resection also showed that patients with gross total resections (GTR) had a better prognosis. A multivariate (Cox proportional hazards) analysis showed that patient age and expansive tumor phenotype affected outcome, whereas RPA class, enhancement, and GTR did not., Conclusion: Circumscribed growth in histologically proven anaplastic astrocytoma, which has not been emphasized in past studies, has a considerable survival advantage., ((c) 2008 Wiley-Liss, Inc.)

Purpose: To seek to distinguish and visualize the different magnetic resonance imaging (MRI) growth patterns among malignant gliomas utilizing visually enhanced diffusion tensor imaging (DTI)., Materials and Methods: Nineteen consecutive patients undergoing image-guided resection of a newly diagnosed malignant glioma underwent add-on acquisition of DTI data based on an Institutional Review Board (IRB)-approved imaging protocol during preoperative MRI scans for routine intraoperative image guidance. Tumor growth patterns were assigned to expansive or mixed/infiltrative classes as described in the companion article (24). Infiltrating tumors were WHO Grade IV astrocytomas and all expansive tumors were either WHO Grade III astrocytomas or WHO Grade II astrocytomas. DTI-based white matter tractography was conducted and the DTI data were fused with anatomical images using an in-house software package we developed to enhance the visualization of the tumor/fiber interface. In one case additional analysis was performed with 2D multivoxel (1)H-MRSI utilizing a 2D chemical shift imaging (CSI) technique to corroborate the nature of this interface., Results: Out of the 19 tumor patients studied, 11 had infiltrative tumors and the other 8 had expansive tumors. While less clear with 2D axial diffusion color maps, visually enhanced 3D reconstructions of the tumor/fiber interface successfully corroborated distinctive growth patterns. This was particularly evident when viewed in 3D video loops of each tumor/fiber interface., Conclusion: We have successfully developed software that visually enhances the anatomic details of the tumor/fiber interface in patients with anaplastic astrocytomas. These data support the existence of a subgroup of patients within the WHO Grade III classification with expansive tumors and a significantly better prognosis., ((c) 2008 Wiley-Liss, Inc.)

Background: Brain metastases occur in up to 40% of all patients with systemic cancer. We aimed to assess whether stereotactic radiosurgery provided any therapeutic benefit in a randomised multi-institutional trial directed by the Radiation Therapy Oncology Group (RTOG)., Methods: Patients with one to three newly diagnosed brain metastases were randomly allocated either whole brain radiation therapy (WBRT) or WBRT followed by stereotactic radiosurgery boost. Patients were stratified by number of metastases and status of extracranial disease. Primary outcome was survival; secondary outcomes were tumour response and local rates, overall intracranial recurrence rates, cause of death, and performance measurements., Findings: From January, 1996, to June, 2001, we enrolled 333 patients from 55 participating RTOG institutions--167 were assigned WBRT and stereotactic radiosurgery and 164 were allocated WBRT alone. Univariate analysis showed that there was a survival advantage in the WBRT and stereotactic radiosurgery group for patients with a single brain metastasis (median survival time 6.5 vs 4.9 months, p=0.0393). Patients in the stereotactic surgery group were more likely to have a stable or improved Karnofsky Performance Status (KPS) score at 6 months' follow-up than were patients allocated WBRT alone (43% vs 27%, respectively; p=0.03). By multivariate analysis, survival improved in patients with an RPA class 1 (p<0.0001) or a favourable histological status (p=0.0121)., Interpretation: WBRT and stereotactic boost treatment improved functional autonomy (KPS) for all patients and survival for patients with a single unresectable brain metastasis. WBRT and stereotactic radiosurgery should, therefore, be standard treatment for patients with a single unresectable brain metastasis and considered for patients with two or three brain metastases.

Purpose: Preclinical animal experiments support the use of an antisense oligodeoxynucleotide directed against the insulin-like growth factor type I receptor (IGF-IR/AS ODN) as an effective potential antitumor agent. We performed a human pilot safety and feasibility study using an IGF-IR/AS ODN strategy in patients with malignant astrocytoma., Patients and Methods: Autologous glioma cells collected at surgery were treated ex vivo with an IGF-IR/AS ODN, encapsulated in diffusion chambers, reimplanted in the rectus sheath within 24 hours of craniotomy, and retrieved after a 24-hour in situ incubation. Serial posttreatment assessments included clinical examination, laboratory studies, and magnetic resonance imaging scans., Results: Other than deep venous thrombosis noted in some patients, no other treatment-related side effects were observed. IGF-IR/AS ODN-treated cells, when retrieved and assessed, were < or = 2% intact by trypan blue exclusion, and none of the intact cells were viable in culture thereafter. Parallel Western blots disclosed IGF-IR downregulation to < or = 10% after ex vivo antisense treatment. At follow-up, clinical and radiographic improvements were observed in eight of 12 patients, including three cases of distal recurrence with unexpected spontaneous or postsurgical regression at either the primary or the distant intracranial site., Conclusion: Ex vivo IGF-IR/AS ODN treatment of autologous glioma cells induces apoptosis and a host response in vivo without unusual side effects. Subsequent transient and sustained radiographic and clinical improvements warrant further clinical investigations.