Presence of cerebral microbleeds is associated with worse executive function in pediatric brain tumor survivors.

BackgroundA specific form of small-vessel vasculopathy-cerebral microbleeds (CMBs)-has been linked to various types of dementia in adults. We assessed the incidence of CMBs and their association with neurocognitive function in pediatric brain tumor survivors.MethodsIn a multi-institutional cohort of 149 pediatric brain tumor patients who received cranial radiation therapy (CRT) between 1987 and 2014 at age <21 years and 16 patients who did not receive CRT, we determined the presence of CMBs on brain MRIs. Neurocognitive function was assessed using a computerized testing program (CogState). We used survival analysis to determine cumulative incidence of CMBs and Poisson regression to examine risk factors for CMBs. Linear regression models were used to assess effect of CMBs on neurocognitive function.ResultsThe cumulative incidence of CMBs was 48.8% (95% CI: 38.3-60.5) at 5 years. Children who had whole brain irradiation developed CMBs at a rate 4 times greater than those treated with focal irradiation (P < .001). In multivariable analysis, children with CMBs performed worse on the Groton Maze Learning test (GML) compared with those without CMBs (Z-score -1.9; 95% CI: -2.7, -1.1; P < .001), indicating worse executive function when CMBs are present. CMBs in the frontal lobe were associated with worse performance on the GML (Z-score -2.4; 95% CI: -2.9, -1.8; P < .001). Presence of CMBs in the temporal lobes affected verbal memory (Z-score -2.0; 95% CI: -3.3, -0.7; P = .005).ConclusionCMBs are common and associated with neurocognitive dysfunction in pediatric brain tumor survivors treated with radiation

Apparent diffusion coefficient and pituitary macroadenomas: pre-operative assessment of tumor atypia.

Rationale and objectivesPituitary macroadenomas are predominantly benign intracranial neoplasms that can be locally aggressive with invasion of adjacent structures. Biomarkers of aggressive behavior have been identified in the pathology literature, including the proliferative marker MIB-1. In the radiology literature, diffusion weighted imaging and low ADC values provide similar markers of aggressive behavior in brain tumors. The purpose of this study was to determine if there is a correlation between ADC and MIB-1 in pituitary macroadenomas.Materials and methodsA retrospective review of diffusion imaging and immunohistochemical characteristics of pituitary macroadenomas was performed. The ADC ratio and specimen Ki-67 (MIB-1) indices were measured. Linear regression analysis of normalized ADC values and MIB-1 indices was used to compare these parameters.ResultsThere were 17 patients with available ADC maps and MIB-1 indices. Local invasion was confirmed by imaging and intraoperative visualization in 11 patients. The mean ADC ratio for the invasive group was 0.68, with a mean MIB-1 index of 2.21 %. In the noninvasive group, the mean ADC ratio was 1.05, with a mean MIB-1 index of 0.9 %. Linear regression analysis of normalized ADC values versus MIB-1 demonstrates a negative correlation, with a linear slope significantly different from zero (p = 0.003, correlation coefficient of 0.77, and r squared = 0.59).ConclusionWe determine a strong correlation of low ADC values and MIB-1, demonstrating the potential of diffusion imaging as a possible biomarker for atypical, proliferative adenomas, which may ultimately affect the surgical approach and postoperative management

A new MRI tag-based method to non-invasively visualize cerebrospinal fluid flow

PURPOSE: Abnormal cerebrospinal fluid (CSF) dynamics can produce a number of significant clinical problems to include hydrocephalus, loculated areas within the ventricles or subarachnoid spaces as well as impairment of normal CSF movement between the cranial and spinal compartments that can result in a cerebellar ectopia and hydrosyringomyelia. Thus, assessing the patency of fluid flow between adjacent CSF compartments non-invasively by magnetic resonance imaging (MRI) has definite clinical value. Our objective was to demonstrate that a novel tag-based CSF imaging methodology offers improved contrast when compared with a commercially available application. METHODS: In a prospective study, ten normal healthy adult subjects were examined on 3T magnets with time-spatial labeling inversion pulse (Time-SLIP) and a new tag-based flow technique-time static tagging and mono-contrast preservation (Time-STAMP). The image contrast was calculated for dark-untagged CSF and bright-flowing CSF. We tested the results with the D\u27Agostino and Pearson normality test and Friedman\u27s test with Dunn\u27s multiple comparison correction for significance. Separately 96 pediatric patients were evaluated using the Time-STAMP method. RESULTS: In healthy adults, contrasts were consistently higher with Time-STAMP than Time-SLIP (p \u3c 0.0001, in all ROI comparisons). The contrast between untagged CSF and flowing tagged CSF improved by 15 to 34%. In both healthy adults and pediatric patients, CSF flow between adjacent fluid compartments was demonstrated. CONCLUSIONS: Time-STAMP provided images with higher contrast than Time-SLIP, without diminishing the ability to visualize qualitative CSF movement and between adjacent fluid compartments

Quantitative Nuclear Histomorphometry Predicts Molecular Subtype and Clinical Outcome in Medulloblastomas: Preliminary Findings

Molecular subtypes of medulloblastoma [Sonic Hedgehog (SHH), Wingless/INT (WNT), Group 3, and Group 4] are defined by common patterns of gene expression. These differential gene expression patterns appear to result in different histomorphology and prognosis. Quantitative histomorphometry is a well-known method of computer-aided pathology image analysis. The hypotheses we sought to examine in this preliminary proof of concept study were whether computer extracted nuclear morphological features of medulloblastomas from digitized tissue slide images could independently: (1) distinguish between molecularly determined subgroups and (2) identify patterns within these subgroups that correspond with clinical outcome. Our dataset was composed of 46 medulloblastoma patients: 16 SHH (5 dead, 11 survived), 3 WNT (0 dead, 3 survived), 12 Group 3 (4 dead, 8 survived), and 15 were Group 4 (5 dead, 10 survived). A watershed-based thresholding scheme was used to automatically identify individual nuclei within digitized whole slide hematoxylin and eosin tissue images. Quantitative histomorphometric features corresponding to the texture (variation in pixel intensity), shape (variations in size, roundness), and architectural rearrangement (distances between, and number of connected neighbors) of nuclei were subsequently extracted. These features were ranked using feature selection schemes and these top-ranked features were then used to train machine-learning classifiers via threefold cross-validation to separate patients based on: (1) molecular subtype and (2) disease-specific outcomes within the individual molecular subtype groups. SHH and WNT tumors were separated from Groups 3 and 4 tumors with a maximum area under the receiver operating characteristic curve (AUC) of 0.7, survival within Group 3 tumors was predicted with an AUC of 0.92, and Group 3 and 4 patients were separated into high- and low-risk groups with p = 0.002. Model prediction was quantitatively compared with age, stage, and histological subtype using univariate and multivariate Cox hazard ratio models. Age was the most statistically significant variable for predicting survival in Group 3 and 4 tumors, but model predictions had the highest hazard ratio value. Quantitative nuclear histomorphometry can be used to study medulloblastoma genetic expression phenotypes as it may distinguish meaningful features of disease pathology

Quantitative Susceptibility Mapping: Translating an Investigative Research Tool into High Volume Clinical Diagnostic Imaging

Quantitative susceptibility mapping (QSM) is an MRI-based technique for iron quantification of targeted tissue. QSM provides information relevant to clinicians in a broad range of diagnostic contexts, including sickle cell disease, inflammatory/demyelinating processes, and neoplasms. However, major MRI vendors do not offer QSM post-processing in a form ready for general use. This work describes a vendor-agnostic approach for scaling QSM analysis from a research technique to a routine diagnostic test. We provide the details needed to seamlessly integrate hardware, software, and clinical systems to provide QSM processing for a busy clinical radiology workflow. This approach can be generalized to other advanced MRI acquisitions and analyses with proven diagnostic utility, yet without crucial MR vendor support