Prognostic Value of Preoperative MRI Metrics for Diffuse Lower-Grade Glioma Molecular Subtypes.

BACKGROUND AND PURPOSE: Despite the improved prognostic relevance of the 2016 WHO molecular-based classification of lower-grade gliomas, variability in clinical outcome persists within existing molecular subtypes. Our aim was to determine prognostically significant metrics on preoperative MR imaging for lower-grade gliomas within currently defined molecular categories. MATERIALS AND METHODS: We undertook a retrospective analysis of 306 patients with lower-grade gliomas accrued from an institutional data base and The Cancer Genome Atlas. Two neuroradiologists in consensus analyzed preoperative MRIs of each lower-grade glioma to determine the following: tumor size, tumor location, number of involved lobes, corpus callosum involvement, hydrocephalus, midline shift, eloquent cortex involvement, ependymal extension, margins, contrast enhancement, and necrosis. Adjusted hazard ratios determined the association between MR imaging metrics and overall survival per molecular subtype, after adjustment for patient age, patient sex, World Health Organization grade, and surgical resection status. RESULTS: For isocitrate dehydrogenase (IDH) wild-type lower-grade gliomas, tumor size (hazard ratio, 3.82; 95% CI, 1.94-7.75; P < .001), number of involved lobes (hazard ratio, 1.70; 95% CI, 1.28-2.27; P < .001), hydrocephalus (hazard ratio, 4.43; 95% CI, 1.12-17.54; P = .034), midline shift (hazard ratio, 1.16; 95% CI, 1.03-1.30; P = .013), margins (P = .031), and contrast enhancement (hazard ratio, 0.34; 95% CI, 0.13-0.90; P = .030) were associated with overall survival. For IDH-mutant 1p/19q-codeleted lower-grade gliomas, tumor size (hazard ratio, 2.85; 95% CI, 1.06-7.70; P = .039) and ependymal extension (hazard ratio, 6.34; 95% CI, 1.07-37.59; P = .042) were associated with overall survival. CONCLUSIONS: MR imaging metrics offers prognostic information for patients with lower-grade gliomas within molecularly defined classes, with the greatest prognostic value for IDH wild-type lower-grade gliomas.

Urinary and Plasma Metabolomics Identify the Distinct Metabolic Profile of Disease State in Chronic Mouse Model of Multiple Sclerosis.

Identification of non-invasive biomarkers of disease progression in multiple sclerosis (MS) is critically needed for monitoring the disease progression and for effective therapeutic interventions. Urine is an attractive source for non-invasive biomarkers because it is easily obtained in the clinic. In search of a urine metabolite signature of progression in chronic experimental autoimmune encephalomyelitis (EAE), we profiled urine at the chronic stage of the disease (day 45 post immunization) by global untargeted metabolomics. Using a combination of high-throughput liquid-and-gas chromatography with mass spectrometry, we found 105 metabolites (P < 0.05) significantly altered at the chronic stage, indicating a robust alteration in the urine metabolite profile during disease. Assessment of altered metabolites against the Kyoto Encyclopedia of Genes and Genomes revealed distinct non-overlapping metabolic pathways and revealed phenylalanine-tyrosine and associated metabolism being the most impacted. Combined with previously performed plasma profiling, eight common metabolites were significantly altered in both of the biofluids. Metaboanalyst analysis of these common metabolites revealed that phenylalanine metabolism and Valine, leucine, and isoleucine biosynthetic pathways are central metabolic pathways in both bio-fluids and could be analyzed further, either for the discovery of therapeutics or biomarker development. Overall, our study suggests that urine and plasma metabolomics may contribute to the identification of a distinct metabolic fingerprint of EAE disease discriminating from the healthy control which may aid in the development of an objective non-invasive monitoring method for progressive autoimmune diseases like MS. Graphical Abstract Untargeted urinary metabolomics of a chronic mouse model of multiple sclerosis identified Phenylalanine, tyrosine & tryptophan metabolism as the significantly altered metabolic pathway. Eight common metabolites were identified when we combined urinary and plasma metabolic signature, which revealed a perturbation of Phenylalanine metabolism and valine, leucine & isoleucine metabolic pathways, involved in CNS dysfunction during diseases. The identified eight metabolic signature of urine and plasma may be of clinical relevance as potential biomarkers and guide towards the identification of specific metabolic pathways as novel drug targets.

Predicting Genotype and Survival in Glioma Using Standard Clinical MR Imaging Apparent Diffusion Coefficient Images: A Pilot Study from The Cancer Genome Atlas.

BACKGROUND AND PURPOSE: 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: Presurgical MRIs and ADC maps of 131 patients with diffuse gliomas and available molecular and survival data from The Cancer Genome Atlas were reviewed. MR imaging features, ADC (obtained by ROIs within the lowest ADC area), and mean relative ADC values were evaluated to predict isocitrate dehydrogenase (IDH) mutation, 1p/19q codeletion status, MGMT promoter methylation, and overall survival. RESULTS: IDH wild-type gliomas tended to exhibit enhancement, necrosis, and edema; >50% enhancing area (P < .001); absence of a cystic area (P = .013); and lower mean relative ADC (median, 1.1 versus 1.6; P < .001) than IDH-mutant gliomas. By means of a cutoff value of 1.08 for mean relative ADC, IDH-mutant and IDH wild-type gliomas with lower mean relative ADC (<1.08) had poorer survival than those with higher mean relative ADC (median survival time, 24.2 months; 95% CI, 0.0-54.9 months versus 62.0 months; P = .003; and median survival time, 10.4 months; 95% CI, 4.4-16.4 months versus 17.7 months; 95% CI, 11.6-23.7 months; P = .041, respectively), regardless of World Health Organization grade. Median survival of those with IDH-mutant glioma with low mean relative ADC was not significantly different from that in those with IDH wild-type glioma. Other MR imaging features were not statistically significant predictors of survival. CONCLUSIONS: IDH wild-type glioma showed lower ADC values, which also correlated with poor survival in both IDH-mutant and IDH wild-type gliomas, irrespective of histologic grade. A subgroup with IDH-mutant gliomas with lower ADC had dismal survival similar to that of those with IDH wild-type gliomas.

Deep-Learning Convolutional Neural Networks Accurately Classify Genetic Mutations in Gliomas.

BACKGROUND AND PURPOSE: The World Health Organization has recently placed new emphasis on the integration of genetic information for gliomas. While tissue sampling remains the criterion standard, noninvasive imaging techniques may provide complimentary insight into clinically relevant genetic mutations. Our aim was to train a convolutional neural network to independently predict underlying molecular genetic mutation status in gliomas with high accuracy and identify the most predictive imaging features for each mutation. MATERIALS AND METHODS: MR imaging data and molecular information were retrospectively obtained from The Cancer Imaging Archives for 259 patients with either low- or high-grade gliomas. A convolutional neural network was trained to classify isocitrate dehydrogenase 1 (IDH1) mutation status, 1p/19q codeletion, and O6-methylguanine-DNA methyltransferase (MGMT) promotor methylation status. Principal component analysis of the final convolutional neural network layer was used to extract the key imaging features critical for successful classification. RESULTS: Classification had high accuracy: IDH1 mutation status, 94%; 1p/19q codeletion, 92%; and MGMT promotor methylation status, 83%. Each genetic category was also associated with distinctive imaging features such as definition of tumor margins, T1 and FLAIR suppression, extent of edema, extent of necrosis, and textural features. CONCLUSIONS: Our results indicate that for The Cancer Imaging Archives dataset, machine-learning approaches allow classification of individual genetic mutations of both low- and high-grade gliomas. We show that relevant MR imaging features acquired from an added dimensionality-reduction technique demonstrate that neural networks are capable of learning key imaging components without prior feature selection or human-directed training.

CSF Pressure Change in Relation to Opening Pressure and CSF Volume Removed.

BACKGROUND AND PURPOSE: Idiopathic intracranial hypertension is a complex neurologic disorder resulting from increased intracranial pressure. Our aim was to determine whether a correlation exists between the CSF pressure-volume relationship, specifically the craniospinal elastance and pressure-volume index, in patients with idiopathic intracranial hypertension and whether opening pressure affects this relationship. MATERIALS AND METHODS: Lumbar punctures performed for suspected idiopathic intracranial hypertension from 2006 to 2017 were identified. Opening and closing pressures, CSF volume removed, and clinical diagnosis of idiopathic intracranial hypertension were obtained from the medical records. The craniospinal elastance (pressure change per milliliter of CSF removed) and pressure-volume index were calculated, and the Pearson correlation coefficients between both the craniospinal elastance and pressure-volume index and opening pressure were determined. Linear regression models of craniospinal elastance and the pressure-volume index and interaction terms with opening pressure were assessed for covariate influence on this association. RESULTS: One hundred sixteen patients were included in the final analysis. The mean craniospinal elastance according to opening pressure group was 0.52 ± 0.18 for <20 cm H2O, 0.57 ± 0.20 for 20-29 cm H2O, 0.91 ± 0.28 for 30-39 cm H2O, and 1.20 ± 0.25 for ≥40 cm H2O. There was a positive linear association between opening pressure and craniospinal elastance with a 0.28 cm H2O/mL increase in craniospinal elastance (standard error = 0.03, P < .001) for every 10 cm H2O increase in opening pressure. Of the covariables analyzed, only age older than 50 years and total volume of CSF removed affected this association. CONCLUSIONS: As opening pressure increases, the craniospinal elastance increases in a linear fashion while the pressure-volume index decreases. Further studies are needed to determine whether these changes relate to the underlying pathophysiology of idiopathic intracranial hypertension or simply represent established CSF volume pressure dynamics.

Estimating post-traumatic stress disorder in the community: lifetime perspective and the impact of typical traumatic events.

BACKGROUND: Community surveys have assessed post-traumatic stress disorder (PTSD) in relation to traumatic events designated by respondents as the worst they have ever experienced. An assessment of PTSD in relation to all reported traumas would impose too great a burden on respondents, a considerable proportion of whom report multiple traumas. The 'worst event' method is efficient for identifying persons with PTSD, but may overestimate the conditional probability of PTSD associated with the entire range of PTSD-level traumas. In this report, we evaluate this potential bias. METHOD: The Detroit Area Survey of Trauma (n = 2181) estimated the PTSD risk from two samples of traumas: (1) a representative sample of traumas formed by selecting a random trauma from each respondent's list of traumas; and (2) traumas designated by respondents as the worst (the standard method). RESULTS: Both estimation methods converged on key findings, including identifying trauma types with the highest probability of PTSD and sex differences in the risk of PTSD. Compared to the random events, the 'worst event' method yielded a moderately higher conditional probability for PTSD (0.136 v. 0.092). The bias was due almost entirely to the deviation of the distribution of the worst events from expected values, if all event types had equal prior selection probabilities. Direct adjustment, setting the distribution equal to expected values and applying the observed probabilities of PTSD associated with individual event types brought the estimate close to the unbiased estimate, based on the randomly selected traumas. CONCLUSIONS: Only the 'worst event' method can be used as a short-cut to assessing all traumas. The bias in the estimated risk of PTSD is modest and is attenuated by direct adjustment.

Sarcoidosis and granuloma genes: a family-based study in African-Americans.

The evidence for a genetic component in the aetiology of sarcoidosis includes familial aggregation, associations with genetic polymorphisms, and linkage to the major histocompatibility complex class region on chromosome 6p. Unfortunately, the majority of genetic associations with sarcoidosis have not been consistently replicated. In the present study, using a family-based study design, which controls for population stratification, the authors attempted to replicate previously reported associations between sarcoidosis and three attractive candidate genes studied primarily in case-control samples. In 225 nuclear families, ascertained through African Americans with a history of sarcoidosis, no evidence was found for an association between sarcoidosis susceptibility and polymorphisms in the angiotensin converting enzyme, vitamin D receptor and tumour necrosis factor-alpha genes. Further analyses of chronic and acute disease phenotypes failed to reveal any notable associations. Assuming an underlying inheritance model with an additive allelic effect on disease risk, the current study had approximately 80-90% statistical power to detect a 3-fold increased risk associated with the putative risk allele of the polymorphisms under study. The present authors conclude that in African-Americans, the angiotensin converting enzyme, vitamin D receptor, and tumour necrosis factor-alpha genes are not significant risk factors for sarcoidosis susceptibility.