Faculty Bibliography

BACKGROUND AND PURPOSE/OBJECTIVE:-mutant lower grade gliomas based on simple neuroimaging metrics. MATERIALS AND METHODS/METHODS:-mutant lower grade gliomas. RESULTS:= 21); and 2) a logistic regression model based on texture, patient age, T2* susceptibility, primary lobe, and hydrocephalus. Independent validation of the classification algorithm rendered codeletion prediction accuracies of 81.1% and 79.2% in 2 independent readers. The metrics used in the algorithm were associated with moderate-substantial interreader agreement (κ = 0.56-0.79). CONCLUSIONS:-mutant lower grade gliomas.

PURPOSE/OBJECTIVE:Isocitrate dehydrogenase (IDH) mutant gliomas are a distinct glioma molecular subtype for which no effective molecularly-directed therapy exists. Low-grade gliomas, which are 80-90% IDH mutant, have high RNA levels of the cell surface Notch ligand DLL3. We sought to determine DLL3 expression by immunohistochemistry in glioma molecular subtypes and the potential efficacy of an anti-DLL3 antibody drug conjugate (ADC), rovalpituzumab tesirine (Rova-T), in IDH mutant glioma. EXPERIMENTAL DESIGN/METHODS:We evaluated DLL3 expression by RNA using TCGA data and by immunohistochemistry in a discovery set of 63 gliomas and 20 non-tumor brain tissues and a validation set of 62 known IDH wildtype and mutant gliomas using a monoclonal anti-DLL3 antibody. Genotype was determined using a DNA methylation array classifier or by sequencing. The effect of Rova-T on patient-derived endogenous IDH mutant glioma tumorspheres was determined by cell viability assay. RESULTS:Compared to IDH wildtype glioblastoma, IDH mutant gliomas have significantly higher DLL3 RNA (P<1x10-15) and protein by immunohistochemistry (P=0.0014 and P<4.3x10-6 in the discovery and validation set, respectively). DLL3 immunostaining was intense and homogeneous in IDH mutant gliomas, retained in all recurrent tumors, and detected in only 1 of 20 non-tumor brains. Patient-derived IDH mutant glioma tumorspheres overexpressed DLL3 and were potently sensitive to Rova-T in an antigen-dependent manner. CONCLUSIONS:DLL3 is selectively and homogeneously expressed in IDH mutant gliomas and can be targeted with Rova-T in patient-derived IDH mutant glioma tumorspheres. Our findings are potentially immediately translatable and have implications for therapeutic strategies that exploit cell surface tumor-associated antigens.

The T2-FLAIR mismatch sign, in which a low-grade glioma is hyperintense on T2-weighted MR and centrally hypointense on T2-weighted FLAIR MR, has been reported as 100% specific for IDH-mutant astrocytomas in several series. We report several cases of "false positive" T2-FLAIR mismatch sign occurring outside the context of IDH-mutant astrocytomas, predominantly in children or young adults with pediatric-type gliomas. These results suggest caution in the interpretation of the T2-FLAIR mismatch sign in the pediatric glioma population.

A higher degree of angiogenesis is associated with shortened survival in glioblastoma. Feasible morphometric parameters for analyzing vascular networks in brain tumors in clinical practice are lacking. We investigated whether the macrovascular network classified by the number of vessel-like structures (nVS) visible on three-dimensional T1-weighted contrast⁻enhanced (3D-T1CE) magnetic resonance imaging (MRI) could improve survival prediction models for newly diagnosed glioblastoma based on clinical and other imaging features. Ninety-seven consecutive patients (62 men; mean age, 58 ± 15 years) with histologically proven glioblastoma underwent 1.5T-MRI, including anatomical, diffusion-weighted, dynamic susceptibility contrast perfusion, and 3D-T1CE sequences after 0.1 mmol/kg gadobutrol. We assessed nVS related to the tumor on 1-mm isovoxel 3D-T1CE images, and relative cerebral blood volume, relative cerebral flow volume (rCBF), delay mean time, and apparent diffusion coefficient in volumes of interest for contrast-enhancing lesion (CEL), non-CEL, and contralateral normal-appearing white matter. We also assessed Visually Accessible Rembrandt Images scoring system features. We used ROC curves to determine the cutoff for nVS and univariate and multivariate cox proportional hazards regression for overall survival. Prognostic factors were evaluated by Kaplan-Meier survival and ROC analyses. Lesions with nVS > 5 were classified as having highly developed macrovascular network; 58 (60.4%) tumors had highly developed macrovascular network. Patients with highly developed macrovascular network were older, had higher volume_CEL, increased rCBF_CEL, and poor survival; nVS correlated negatively with survival (r = -0.286; p = 0.008). On multivariate analysis, standard treatment, age at diagnosis, and macrovascular network best predicted survival at 1 year (AUC 0.901, 83.3% sensitivity, 93.3% specificity, 96.2% PPV, 73.7% NPV). Contrast-enhanced MRI macrovascular network improves survival prediction in newly diagnosed glioblastoma.

OBJECTIVE:Machine learning has recently gained considerable attention because of promising results for a wide range of radiology applications. Here we review recent work using machine learning in brain tumor imaging, specifically segmentation and MRI radiomics of gliomas. CONCLUSION/CONCLUSIONS:We discuss available resources, state-of-the-art segmentation methods, and machine learning radiomics for glioma. We highlight the challenges of these techniques as well as the future potential in clinical diagnostics, prognostics, and decision making.

PURPOSE/OBJECTIVE:The neuroimaging diagnosis of diffuse gliomas can be challenging owing to their variable clinical and radiologic presentation. The purpose of this study was to identify factors that are associated with imaging errors in the diagnosis of diffuse gliomas. METHODS:A retrospective case-control analysis was undertaken. 18 misdiagnosed diffuse gliomas on initial neuroimaging (cases) and 108 accurately diagnosed diffuse gliomas on initial neuroimaging (controls) were collected. Clinical, pathological, and imaging metrics were tabulated for each patient. The tabulated metrics were compared between cases and controls to determine factors associated with misdiagnosis. RESULTS:Cases of misdiagnosed diffuse glioma (vs controls) were more likely to undergo initial triage as a stroke workup [OR 14.429 (95% CI 4.345, 47.915), p < 0.0001], were less likely to enhance [OR 0.283 (95% CI 0.098, 0.812), p = 0.02], were smaller (mean diameter 4.4 vs 6.0 cm, p = 0.0008), produced less midline shift (median midline shift 0.0 vs 2.0 mm, p = 0.003), were less likely to demonstrate necrosis [OR 0.156 (95% CI 0.034-0.713), p = 0.008], and were less likely to have IV contrast administered on the initial MRI [OR 0.100 (95% CI 0.020, 0.494), p = 0.008]. CONCLUSION/CONCLUSIONS:Several clinical and radiologic metrics are associated with diffuse gliomas that are missed or misdiagnosed on the initial neuroimaging study. Knowledge of these associations may aid in avoiding misinterpretation and accurately diagnosing such cases in clinical practice.

BACKGROUND AND PURPOSE/OBJECTIVE:Few studies have shown MR imaging features and ADC correlating with molecular markers and survival in patients with glioma. Our purpose was to correlate MR imaging features and ADC with molecular subtyping and survival in adult diffuse gliomas. MATERIALS AND METHODS/METHODS:promoter methylation, and overall survival. RESULTS:wild-type glioma. Other MR imaging features were not statistically significant predictors of survival. CONCLUSIONS:wild-type gliomas.