Asymmetric Hearing Loss Prompting MRI Referral in a Military Population: Redefining Audiometric Criteria.

Objective To reevaluate asymmetric sensorineural hearing loss (ASNHL) criteria used to justify magnetic resonance imaging (MRI) in the evaluation of retrocochlear tumors in a military population. Study Design Retrospective case-control study. Setting Tertiary care military medical center. Subjects and Methods Patients with military service and a history of ASNHL prompting referral for MRI, with or without retrocochlear tumors, were compared between 2005 and 2016. Predictor variables included pure tone ASNHL, speech audiometry, and a history of noise exposure. Logistic regression models for hearing asymmetries were performed, and receiver operator curves were used to calculate sensitivity and specificity. Results Thirty-eight retrocochlear tumors were identified. The MRI diagnosis rate for patients with ASHNL was 0.85%. Patients with tumors were slightly older (42 vs 37 years, P = .021) and had less noise exposure (47% vs 85%, P < .001). A sensitivity of 0.83 and a specificity of 0.58 were calculated for asymmetries ≥10 dB at 2000 Hz without adjusting for noise exposure. Instituting this imaging threshold would have reduced the number of MRI scans by half while missing 16% of tumors. Conclusion The tumor diagnosis rate among those undergoing MRI for ASNHL is low in the military population, likely because service-related noise exposure commonly causes ASNHL. Optimal MRI referral criteria should conserve resources while balancing the risks of over- and underdiagnosis. For those with a history of military service, an asymmetry ≥10 dB at 2000 Hz among patients meeting current ANSHL referral criteria is most predictive of a retrocochlear tumor.

Magnetic resonance perfusion image features uncover an angiogenic subgroup of glioblastoma patients with poor survival and better response to antiangiogenic treatment.

BACKGROUND: In previous clinical trials, antiangiogenic therapies such as bevacizumab did not show efficacy in patients with newly diagnosed glioblastoma (GBM). This may be a result of the heterogeneity of GBM, which has a variety of imaging-based phenotypes and gene expression patterns. In this study, we sought to identify a phenotypic subtype of GBM patients who have distinct tumor-image features and molecular activities and who may benefit from antiangiogenic therapies. METHODS: Quantitative image features characterizing subregions of tumors and the whole tumor were extracted from preoperative and pretherapy perfusion magnetic resonance (MR) images of 117 GBM patients in 2 independent cohorts. Unsupervised consensus clustering was performed to identify robust clusters of GBM in each cohort. Cox survival and gene set enrichment analyses were conducted to characterize the clinical significance and molecular pathway activities of the clusters. The differential treatment efficacy of antiangiogenic therapy between the clusters was evaluated. RESULTS: A subgroup of patients with elevated perfusion features was identified and was significantly associated with poor patient survival after accounting for other clinical covariates (P values <.01; hazard ratios > 3) consistently found in both cohorts. Angiogenesis and hypoxia pathways were enriched in this subgroup of patients, suggesting the potential efficacy of antiangiogenic therapy. Patients of the angiogenic subgroups pooled from both cohorts, who had chemotherapy information available, had significantly longer survival when treated with antiangiogenic therapy (log-rank P=.022). CONCLUSIONS: Our findings suggest that an angiogenic subtype of GBM patients may benefit from antiangiogenic therapy with improved overall survival.

Magnetic resonance image features identify glioblastoma phenotypic subtypes with distinct molecular pathway activities.

Glioblastoma (GBM) is the most common and highly lethal primary malignant brain tumor in adults. There is a dire need for easily accessible, noninvasive biomarkers that can delineate underlying molecular activities and predict response to therapy. To this end, we sought to identify subtypes of GBM, differentiated solely by quantitative magnetic resonance (MR) imaging features, that could be used for better management of GBM patients. Quantitative image features capturing the shape, texture, and edge sharpness of each lesion were extracted from MR images of 121 single-institution patients with de novo, solitary, unilateral GBM. Three distinct phenotypic "clusters" emerged in the development cohort using consensus clustering with 10,000 iterations on these image features. These three clusters--pre-multifocal, spherical, and rim-enhancing, names reflecting their image features--were validated in an independent cohort consisting of 144 multi-institution patients with similar tumor characteristics from The Cancer Genome Atlas (TCGA). Each cluster mapped to a unique set of molecular signaling pathways using pathway activity estimates derived from the analysis of TCGA tumor copy number and gene expression data with the PARADIGM (Pathway Recognition Algorithm Using Data Integration on Genomic Models) algorithm. Distinct pathways, such as c-Kit and FOXA, were enriched in each cluster, indicating differential molecular activities as determined by the image features. Each cluster also demonstrated differential probabilities of survival, indicating prognostic importance. Our imaging method offers a noninvasive approach to stratify GBM patients and also provides unique sets of molecular signatures to inform targeted therapy and personalized treatment of GBM.

Glioblastoma multiforme: exploratory radiogenomic analysis by using quantitative image features.

PURPOSE: To derive quantitative image features from magnetic resonance (MR) images that characterize the radiographic phenotype of glioblastoma multiforme (GBM) lesions and to create radiogenomic maps associating these features with various molecular data. MATERIALS AND METHODS: Clinical, molecular, and MR imaging data for GBMs in 55 patients were obtained from the Cancer Genome Atlas and the Cancer Imaging Archive after local ethics committee and institutional review board approval. Regions of interest (ROIs) corresponding to enhancing necrotic portions of tumor and peritumoral edema were drawn, and quantitative image features were derived from these ROIs. Robust quantitative image features were defined on the basis of an intraclass correlation coefficient of 0.6 for a digital algorithmic modification and a test-retest analysis. The robust features were visualized by using hierarchic clustering and were correlated with survival by using Cox proportional hazards modeling. Next, these robust image features were correlated with manual radiologist annotations from the Visually Accessible Rembrandt Images (VASARI) feature set and GBM molecular subgroups by using nonparametric statistical tests. A bioinformatic algorithm was used to create gene expression modules, defined as a set of coexpressed genes together with a multivariate model of cancer driver genes predictive of the module's expression pattern. Modules were correlated with robust image features by using the Spearman correlation test to create radiogenomic maps and to link robust image features with molecular pathways. RESULTS: Eighteen image features passed the robustness analysis and were further analyzed for the three types of ROIs, for a total of 54 image features. Three enhancement features were significantly correlated with survival, 77 significant correlations were found between robust quantitative features and the VASARI feature set, and seven image features were correlated with molecular subgroups (P < .05 for all). A radiogenomics map was created to link image features with gene expression modules and allowed linkage of 56% (30 of 54) of the image features with biologic processes. CONCLUSION: Radiogenomic approaches in GBM have the potential to predict clinical and molecular characteristics of tumors noninvasively. Online supplemental material is available for this article.

Reversible cerebral vasoconstriction syndrome and bilateral vertebral artery dissection presenting in a patient after cesarean section.

Reversible cerebral vasoconstriction syndrome (RCVS) is characterized by sudden-onset thunderclap headache and focal neurologic deficits. Once thought to be a rare syndrome, more advanced non-invasive imaging has led to an increase in RCVS diagnosis. Unilateral vertebral artery dissection has been described in fewer than 40% of cases of RCVS. Bilateral vertebral artery dissection has rarely been reported. We describe the case of a patient with RCVS and bilateral vertebral artery dissection presenting with an intramedullary infarct treated successfully with medical management and careful close follow-up. This rare coexistence should be recognized as the treatment differs.

CT, MRI, PET, PET/CT, and ultrasound in the evaluation of obstetric and gynecologic patients.

The role of imaging in obstetrics and gynecology has undergone a revolution over the past few decades. Well-established methods such as endovaginal ultrasound have had a central role in the evaluation of nongravid patients with pelvic pain, as well as in the workup for ectopic pregnancy and evaluation of adnexal masses. Additional tools include MRI in the evaluation of appendicitis and other potentially surgical conditions in pregnant patients and MRI and CT in the evaluation of surgical complications. Newer tools in the radiology armamentarium include PET scanning which, alongside MRI and CT, are often helpful in staging gynecologic malignancy. The role of imaging in the obstetric and gynecology patient will continue to change as new modalities and techniques are introduced.