Brain tissue pulsates with each cardiac cycle, however the effect of disease on this natural motion is still unclear. Current literature mainly focuses on healthy brain tissue, with only limited studies looking at disease states such as Chiari malformation and acute ischemic stroke. This case report advances on recent literature by describing the case of a patient with an acute intracerebral hemorrhage and demonstrating an amplified MRI cine of the brain's motion. A clearer understanding of the effects of disease on brain motion may guide clinical application of pulsation measurement.

BACKGROUND:Reliable measurements of cervical cord atrophy progression may be useful for monitoring neurodegeneration in multiple sclerosis (MS). PURPOSE:To compare a new, registration-based (Reg) method with two existing methods (active surface [AS] and propagation segmentation [PropSeg]) to measure cord atrophy changes over time in MS. STUDY TYPE:Retrospective. SUBJECTS:Cohort I: Eight healthy controls (HC) and 28 MS patients enrolled at a single institution, and cohort II: 25 HC and 63 MS patients enrolled at three European sites. FIELD STRENGTH/SEQUENCE:3D T1-weighted gradient echo sequence, acquired at 1.5 T (cohort I) and 3.0 T (cohort II). ASSESSMENT:Percentage cord area changes (PCACs) between baseline and follow-up (cohort I: 2.34 years [interquartile range = 2.00-2.55 years], cohort II: 1.05 years [interquartile range = 1.01-1.18 years]) were evaluated for all subjects using Reg, AS, and PropSeg. Reg included an accurate registration of baseline and follow-up straightened cord images, followed by AS-based optimized cord segmentation. A subset of studies was analyzed twice by two observers. STATISTICAL TESTS:Linear regression models were used to estimate annualized PCAC, and effect sizes expressed as the ratio between the estimated differences and HC error term (P < 0.05). Reproducibility was assessed by linear mixed-effect models. Annualized PCACs were used for sample size calculations (significance: α = 0.05, power: 1 - β = 0.80). RESULTS:Annualized PCACs and related standard errors (SEs) were lower with Reg than with other methods: PCAC in MS patients at 1.5 T was -1.12% (SE = 0.22) with Reg, -1.32% (SE = 0.30) with AS, and -1.40% (SE = 0.33) with PropSeg, while at 3.0 T PCAC was -0.83% (SE = 0.25) with Reg, -0.92% (SE = 0.32) with AS, and -1.18 (SE = 0.53) with PropSeg. This was reflected in larger effect sizes and lower sample sizes. Intra- and inter-observer agreement range was 0.72-0.91 with AS, and it was >0.96 with Reg. DATA CONCLUSION:The results support the use of the registration method to measure cervical cord atrophy progression in future MS clinical studies. LEVEL OF EVIDENCE:3 TECHNICAL EFFICACY STAGE: 2.

It is well known that the brain pulses with each cardiac cycle, but interest in measuring cardiac-induced brain tissue pulsations (BTPs) is relatively recent. This study was aimed at generating BTP reference data from healthy patients for future clinical comparisons and modelling. BTPs were measured through the forehead and temporal positions as a function of age, sex, heart rate, mean arterial pressure and pulse pressure. A multivariate regression model was developed based on transcranial tissue Doppler BTP measurements from 107 healthy adults (56 male) aged from 20–81 y. A subset of 5 participants (aged 20–49 y) underwent a brain magnetic resonance imaging scan to relate the position of the ultrasound beam to anatomy. BTP amplitudes were found to vary widely between patients (from ∼4 to ∼150 µm) and were strongly associated with pulse pressure. Comparison with magnetic resonance images confirmed regional variations in BTP with depth and probe position.

Objectives: This study draws on advances in Doppler ultrasound bubble sizing to investigate whether high volumes of macro-bubbles entering the brain during cardiac surgery increase the risk of new cerebral microbleeds (CMBs), ischemic MR lesions, or post-operative cognitive decline (POCD). Methods: Transcranial Doppler (TCD) ultrasound recordings were analysed to estimate numbers of emboli and macrobubbles (>100 mu m) entering the brain during cardiac surgery. Logistic regression was used to explore the hypothesis that emboli characteristics affect the incidence of new brain injuries identified through preand postoperative MRI and neuropsychological testing. Results: TCD, MRI, and neuropsychological test data were compared between 28 valve and 18 CABG patients. Although valve patients received over twice as many emboli per procedure [median: 1995 vs. 859, p = .004], and seven times as many macro-bubbles [median: 218 vs. 28, p = .001], high volumes of macrobubbles were not found to be significantly associated with new CMBs, new ischaemic lesions, or POCD. The odds of acquiring new CMBs increased by approximately 5% [95% CI: 1 to 10%] for every embolus detected in the first minute after the release of the aortic cross-clamp (AxC). Logistic regression models also confirmed previous findings that cardiopulmonary bypass time and valve surgery were significant predictors for new CMBs (both p = .03). Logistic regression analysis estimated an increase in the odds of acquiring new CMBs of 6% [95% CI: 1 to 12%] for every minute of bypass time over 91 mins. Conclusions: This small study provides new information about the properties and numbers of bubbles entering the brain during surgery, but found no evidence to substantiate a direct link between large numbers of macrobubbles and adverse cognitive or MR outcome.

Background: Multiple sclerosis (MS) is characterized by focal white matter damage, and when the brain is modeled as a network, lesions can be treated as disconnection events. Objective: To evaluate whether modeling disconnection caused by lesions helps explain motor and cognitive impairment in MS. Methods: Pathways connecting 116 cortical regions were reconstructed with magnetic resonance imaging (MRI) tractography from diffusion tensors averaged across healthy controls (HCs); maps of pathways were applied to 227 relapse-onset MS patients and 50 HCs to derive structural connectivity. Then, the likelihood of individual connections passing through lesions was used to model disconnection. Patients were grouped according to clinical phenotype (113 relapsing-remitting multiple sclerosis (RRMS), 69 secondary progressive multiple sclerosis (SPMS), 45 benign MS), and then network metrics were compared between groups (analysis of variance (ANOVA)) and correlated with motor and cognitive scores (linear regression). Results: Global metrics differentiated RRMS from SPMS and benign MS patients, but not benign from SPMS patients. Nodal connectivity strength replicated global results. After disconnection, few nodes were significantly different between benign MS and RRMS patients. Correlations revealed nodes pertinent to motor and cognitive dysfunctions; these became slightly stronger after disconnection. Conclusion: Connectivity did not change greatly after modeled disconnection, suggesting that the brain network is robust against damage caused by MS lesions.

Background and Purpose— Cerebral microbleeds (CMBs) have been observed using magnetic resonance imaging in patients with cardiovascular risk factors, cognitive deterioration, small vessel disease, and dementia. They are a well-known consequence of cerebral amyloid angiopathy, chronic hypertension, and diffuse axonal injury, among other causes. However, the frequency and location of new CMBs postadult cardiac surgery, in association with cognition and perioperative risk factors, have yet to be studied. Methods— Pre- and postsurgery magnetic resonance susceptibility-weighted images and neuropsychological tests were analyzed from a total of 75 patients undergoing cardiac surgery (70 men; mean age, 63±10 years). CMBs were identified by a neuroradiologist blinded to clinical details who independently assessed the presence and location of CMBs using standardized criteria. Results— New CMBs were identified in 76% of patients after cardiac surgery. The majority of new CMBs were located in the frontal lobe (46%) followed by the parietal lobe (15%), cerebellum (13%), occipital lobe (12%), and temporal lobe (8%). Patients with new CMBs typically began with a higher prevalence of preexisting CMBs ( P =0.02). New CMBs were associated with longer cardiopulmonary bypass times ( P =0.003), and there was a borderline association with lower percentage hematocrit ( P =0.04). Logistic regression analysis suggested a ≈2% increase in the odds of acquiring new CMBs during cardiac surgery for every minute of bypass time (odds ratio, 1.02; 95% CI, 1.00–1.05; P =0.04). Postoperative neuropsychological decline was observed in 44% of patients and seemed to be unrelated to new CMBs. Conclusions— New CMBs identified using susceptibility-weighted images were found in 76% of patients who underwent cardiac surgery. CMBs were globally distributed with the highest numbers in the frontal and parietal lobes. Our regression analysis indicated that length of cardiopulmonary bypass time and lowered hematocrit may be significant predictors for new CMBs after cardiac surgery. Clinical Trial Registration— URL: http://www.isrctn.com . Unique identifier: 66022965.

To compare aortic size and stiffness parameters on MRI between bicuspid aortic valve (BAV) and tricuspid aortic valve (TAV) patients with aortic stenosis (AS).

Purpose To compare available methods for whole-brain and gray matter (GM) atrophy estimation in multiple sclerosis (MS) in terms of repeatability (same magnetic resonance [MR] imaging unit) and reproducibility (different system/field strength) for their potential clinical applications. Materials and Methods The softwares ANTs-v1.9, CIVET-v2.1, FSL-SIENAX/SIENA-5.0.1, Icometrix-MSmetrix-1.7, and SPM-v12 were compared. This retrospective study, performed between March 2015 and March 2017, collected data from (a) eight simulated MR images and longitudinal data (2 weeks) from 10 healthy control subjects to assess the cross-sectional and longitudinal accuracy of atrophy measures, (b) test-retest MR images in 29 patients with MS acquired within the same day at different imaging unit field strengths/manufacturers to evaluate precision, and (c) longitudinal data (1 year) in 24 patients with MS for the agreement between methods. Tissue segmentation, image registration, and white matter (WM) lesion filling were also evaluated. Multiple paired t tests were used for comparisons. Results High values of accuracy (0.87-0.97) for whole-brain and GM volumes were found, with the lowest values for MSmetrix. ANTs showed the lowest mean error (0.02%) for whole-brain atrophy in healthy control subjects, with a coefficient of variation of 0.5%. SPM showed the smallest mean error (0.07%) and coefficient of variation (0.08%) for GM atrophy. Globally, good repeatability (P > .05) but poor reproducibility (P < .05) were found for all methods. WM lesion filling technique mainly affected ANTs, MSmetrix, and SPM results (P < .05). Conclusion From this comparison, it would be possible to select a software for atrophy measurement, depending on the requirements of the application (research center, clinical trial) and its goal (accuracy and repeatability or reproducibility). An improved reproducibility is required for clinical application. © RSNA, 2018 Online supplemental material is available for this article.

April 22, 2018April 10, 2018Free AccessComparison of Methods for Whole-Brain and Grey Matter Atrophy Assessment in Multiple Sclerosis (S6.006)Loredana Storelli, Maria A. Rocca, Elisabetta Pagani, Wim Van Hecke, Mark A. Horsfield, Nicola De Stefano, Alex Rovira, Jaume Sastre-Garriga, Jacqueline Palace, Diana Sima, Dirk Smeets, and Massimo FilippiAuthors Info & AffiliationsApril 10, 2018 issue90 (15_supplement)https://doi.org/10.1212/WNL.90.15_supplement.S6.006 Letters to the Editor

ObjectiveThe aim of this study was to examine cross-sectional associations between objectively measured sedentary time and magnetic resonance imaging (MRI)-assessed adiposity in a population at high risk for type 2 diabetes (T2DM) and to determine whether associations are modified by the recommended levels of moderate-to-vigorous physical activity (MVPA). MethodsSedentary time and MVPA were measured objectively by using accelerometers. Linear regression models examined the association of sedentary time with liver, visceral, subcutaneous, and total abdominal fat (quantified by using MRI). Interaction terms determined whether results were consistent across activity categories (active [>150 min/wk of MVPA] vs. inactive [<150 min/wk of MVPA]). ResultsOne hundred and twenty-four participants (age=64.07.1 years; male=65.3%; BMI=31.8 +/- 5.6 kg/m(2)) were included. Following adjustment, each 60 minutes of sedentary time was associated with 1.74 L higher total abdominal fat, 0.62 L higher visceral fat, 1.14 L higher subcutaneous fat, and 1.86% higher liver fat. When results were stratified by MVPA (active vs. inactive), sedentary time was associated with greater liver, visceral, and total abdominal fat in the inactive group only. ConclusionsThese findings suggest that sedentary time is associated with higher levels of inter- and intraorgan fat, but associations with liver, visceral, and total abdominal fat were stronger in those who do not reach the current exercise recommendations for health.

Because of the unique characteristics of polymer gel dosimeters, it appears that these gels might offer a reliable method for measuring absorbed radiation dose from various radiotherapy techniques, such as BNCT. In this study, the ability of NIPAM polymer gel to record the dose distribution from the BNCT treatment modality was evaluated by simulating the clinical conditions for treatment of shallow tumors. In this regards, two polymethyl methacrylate (PMMA) cylinder phantoms, measuring 8 cm in diameter and 6 cm in height with a wall thickness of 5 mm, were used for irradiating the gel in front of the BNCT beam of the Tehran Research Reactor (TRR). One of the phantoms was filled by only NIPAM gel prepared by standard formulation and the other one containing about 20 cc NIPAM gel with 30 ppm of B-10 which was embedded inside the standard gel, with no separating layer, at a depth of 1 cm from the phantom wall. From the results, 18% increased dose was recorded in the area that was loaded the 10B doped gel in comparison with the pure NIPAM gel. It can be concluded that NIPAM gel has the potential to be used in verification of BNCT treatment planning. (C) 2017 Elsevier Ltd. All rights reserved.

Patients with the main clinical phenotypes of multiple sclerosis (MS) manifest varying degrees of brain atrophy beyond that of normal aging. Assessment of atrophy helps to distinguish clinically and cognitively deteriorating patients and predicts those who will have a less-favorable clinical outcome over the long term. Atrophy can be measured from brain MRI scans, and many technological improvements have been made over the last few years. Several software tools, with differing requirements on technical ability and levels of operator intervention, are currently available and have already been applied in research or clinical trial settings. Despite this, the measurement of atrophy in routine clinical practice remains an unmet need. After a short summary of the pathologic substrates of brain atrophy in MS, this review attempts to guide the clinician towards a better understanding of the methods currently used for quantifying brain atrophy in this condition. Important physiologic factors that affect brain volume measures are also considered. Finally, the most recent research on brain atrophy in MS is summarized, including whole brain and various compartments thereof (i.e., white matter, gray matter, selected CNS structures). Current methods provide sufficient precision for cohort studies, but are not adequate for confidently assessing changes in individual patients over the scale of months or a few years.

BACKGROUND AND PURPOSE:The detection of new subtle brain pathology on MR imaging is a time-consuming and error-prone task for the radiologist. This article introduces and evaluates an image-registration and subtraction method for highlighting small changes in the brain with a view to minimizing the risk of missed pathology and reducing fatigue. MATERIALS AND METHODS:We present a fully automated algorithm for highlighting subtle changes between multiple serially acquired brain MR images with a novel approach to registration and MR imaging bias field correction. The method was evaluated for the detection of new lesions in 77 patients undergoing cardiac surgery, by using pairs of fluid-attenuated inversion recovery MR images acquired 1-2 weeks before the operation and 6-8 weeks postoperatively. Three radiologists reviewed the images. RESULTS:On the basis of qualitative comparison of pre- and postsurgery FLAIR images, radiologists identified 37 new ischemic lesions in 22 patients. When these images were accompanied by a subtraction image, 46 new ischemic lesions were identified in 26 patients. After we accounted for interpatient and interradiologist variability using a multilevel statistical model, the likelihood of detecting a lesion was 2.59 (95% CI, 1.18-5.67) times greater when aided by the subtraction algorithm (P = .017). Radiologists also reviewed the images significantly faster (P < .001) by using the subtraction image (mean, 42 seconds; 95% CI, 29-60 seconds) than through qualitative assessment alone (mean, 66 seconds; 95% CI, 46-96 seconds). CONCLUSIONS:Use of this new subtraction algorithm would result in considerable savings in the time required to review images and in improved sensitivity to subtle focal pathology.

Patients with the main clinical phenotypes of multiple sclerosis (MS) manifest varying degrees of brain atrophy beyond that of normal aging. Assessment of atrophy helps to distinguish clinically and cognitively deteriorating patients and predicts those who will have a less-favorable clinical outcome over the long term. Atrophy can be measured from brain MRI scans, and many technological improvements have been made over the last few years. Several software tools, with differing requirements on technical ability and levels of operator intervention, are currently available and have already been applied in research or clinical trial settings. Despite this, the measurement of atrophy in routine clinical practice remains an unmet need. After a short summary of the pathologic substrates of brain atrophy in MS, this review attempts to guide the clinician towards a better understanding of the methods currently used for quantifying brain atrophy in this condition. Important physiologic factors that affect brain volume measures are also considered. Finally, the most recent research on brain atrophy in MS is summarized, including whole brain and various compartments thereof (i. e., white matter, graymatter, selected CNS structures). Current methods provide sufficient precision for cohort studies, but are not adequate for confidently assessing changes in individual patients over the scale of months or a few years.

Novel MRI-based dynamic cerebral autoregulation (dCA) assessment enables the estimation of both global and spatially discriminated autoregulation index values. Before exploring this technique for the evaluation of focal dCA in acute ischaemic stroke (AIS) patients, it is necessary to compare global dCA estimates made using both TCD and MRI. Both techniques were used to study 11 AIS patients within 48 h of symptom onset, and nine healthy controls. dCA was assessed by the rate of return of CBFV (Rturn) following a sudden drop induced by the thigh cuff manoeuvre. No significant between-hemisphere differences were seen in controls using either the TCD or MRI technique. Inter-hemisphere averaged Rturn values were not different between TCD (1.89 ± 0.67%/s) and MRI (2.07 ± 0.60%/s) either. In patients, there were no differences between the affected and unaffected hemispheres whether assessed by TCD (Rturn 0.67 ± 0.72 vs. 0.98 ± 1.09%/s) or MRI (0.55 ± 1.51 vs. 1.63 ± 0.63%/s). Rturn for both TCD and MRI was impaired in AIS patients compared to controls in both unaffected and affected hemispheres (ANOVA, p = 0.00005). These findings pave the way for wider use of MRI for dCA assessment in health and disease.

The identification and segmentation of focal hyperintense lesions on magnetic resonance images (MRI) are essential steps in the assessment of disease burden in multiple sclerosis (MS) patients. Manual lesion segmentation is considered to be the gold standard, although it is time-consuming and has poor intra- and inter-operator reproducibility. Here, we present a segmentation method based on dual-echo MR images initialized by manual identification of lesions and a priori information. The classification technique is based on a region growing approach with a final segmentation refinement step. The results have revealed high similarity between the segmentation performed with this method and that performed manually by an expert operator, as well as a low misclassification of lesions. Moreover, the time required for segmentation is drastically reduced.