T1-weighted Brain Research Articles

Abstract B152: MR-based assessment and quantification of cerebral edema in an orthotopic mouse glioma model.

Abstract Introduction: Brain edema is a prominent feature of brain cancer and contributes to neurologic dysfunction and impaired quality of life. While corticosteroids are the standard of care, improved treatments that are more efficacious and reduce side effects are sought after. In discovery of novel therapies for edema, animal brain tumor models that show relevant, reproducible and high incidence of tumor and cerebral edema are needed. Additionally, quantitative, non-invasive methods for detecting and measuring brain tumor associated edema are needed to facilitate therapeutic discovery efforts. In this work, an intracranial U251-luc human glioma model was characterized for edema incidence and progression. MRI-based relaxivity and contrast-enhancement protocols for edema detection and delineation from tumor tissue, were tested and characterized in the model. Methods: Female nude mice were implanted intracranially with 1×10∧6 U251-luc (Luc-mCherry) glioma cells. Tumor volume assessment was performed by manual segmentation of T1-weighted, gadolinium-enhanced anatomical brain images based on the assumption of tumor enhancement due to leaky vessels or compromised blood-brain barrier. Edema assessment was performed by manual segmentation of T2-weighted anatomical brain images based on the assumption that enhancing regions include tumor tissue in addition to regions of brain edema. The difference in T2-weighted and T1-weighted volumes was assumed to be edema. T2 maps were also generated over the whole brain to measure T2 values over the respective regions of interest, and confirm the differentiation between tumor tissue and edema. Results: Edema volume was successfully distinguished from contrast enhancing tumor tissue and quantified in orthotopically implanted U251-luc (Luc-mCherry) glioma. Incidence was 100%. Edema progression occurred with increasing tumor volume over time. Regions of edema exhibited greater T2 values compared to tumor tissue regions (that also had greater T2 than normal tissue). This is consistent with edematous tissue water content, compared with tumor tissue and normal brain. These results support the use of intracranial U251-luc (Luc-mCherry) as a reliable model for studying the effects of therapies targeting tumor-related cerebral edema, and the application of MR imaging for quantifying those effects real-time in vivo. Citation Information: Mol Cancer Ther 2013;12(11 Suppl):B152. Citation Format: Deanne R. Lister, Deepa Balagurunathan, Meridith Baugher, Erin Trachet, Patrick McConville, Scott Wise, W.R. Leopold. MR-based assessment and quantification of cerebral edema in an orthotopic mouse glioma model. [abstract]. In: Proceedings of the AACR-NCI-EORTC International Conference: Molecular Targets and Cancer Therapeutics; 2013 Oct 19-23; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Ther 2013;12(11 Suppl):Abstract nr B152.

MAP–Based Framework for Segmentation of MR Brain Images Based on Visual Appearance and Prior Shape

We propose a new MAP-based technique for the unsupervised segmentation of different brain structures (white matter, gray matter, etc.) from T1-weighted MR brain images. In this paper, we follow a procedure like most conventional approaches, in which T1-weighted MR brain images and desired maps of regions (white matter, gray matter, etc.) are modeled by a joint Markov-Gibbs Random Field model (MGRF) of independent image signals and interdependent region labels. However, we specifically focus on the most accurate model identification that can be achieved. The proposed joint MGRF model accounts for the following three descriptors: i) a 1st-order visual appearance descriptor(empirical distribution of signal intensity), ii) a 3D probabilistic shape prior, and iii) a 3D spatially invariant 2nd-order homogeneity descriptor. To better specify the 1st-order visual appearance descriptor, each empirical distribution of signals is precisely approximated by a Linear Combination of Discrete Gaussians (LCDG) having both positive and negative components. The 3D probabilistic shape prior is learned using a subset of 3D co-aligned training T1-weighted MR brain images. The 2nd-order homogeneity descriptor is modeled by a 2nd-order translation and rotation invariant MGRF of 3D T1-weighted MR brain region labels with analytically estimated potentials. The initial segmentation, based on a 1st-order visual appearance and 3D probabilistic shape, is then iteratively refined using a 3D MGRF model with analytically estimated potentials. Experiments on twelve 3D T1-weighted MR brain images confirm the high accuracy of the proposed approach.

RATS: Rapid Automatic Tissue Segmentation in rodent brain MRI

BackgroundHigh-field MRI is a popular technique for the study of rodent brains. These datasets, while similar to human brain MRI in many aspects, present unique image processing challenges. We address a very common preprocessing step, skull-stripping, which refers to the segmentation of the brain tissue from the image for further processing. While several methods exist for addressing this problem, they are computationally expensive and often require interactive post-processing by an expert to clean up poorly segmented areas. This further increases total processing time per subject. New methodWe propose a novel algorithm, based on grayscale mathematical morphology and LOGISMOS-based graph segmentation, which is rapid, robust and highly accurate. ResultsComparative results obtained on two challenging in vivo datasets, consisting of 22 T1-weighted rat brain images and 10 T2-weighted mouse brain images illustrate the robustness and excellent performance of the proposed algorithm, in a fraction of the computational time needed by existing algorithms. Comparison with existing methodsIn comparison to current state-of-the-art methods, our approach achieved average Dice similarity coefficient of 0.92±0.02 and average Hausdorff distance of 13.6±5.2 voxels (vs. 0.85±0.20, p<0.05 and 42.6±22.9, p≪0.001) for the rat dataset, and 0.96±0.01 and average Hausdorff distance of 21.6±12.7 voxels (vs. 0.93±0.01, p≪0.001 and 33.7±3.5, p≪0.001) for the mouse dataset. The proposed algorithm took approximately 90s per subject, compared to 10–20min for the neural-network based method and 30–90min for the atlas-based method. ConclusionsRATS is a robust and computationally efficient method for accurate rodent brain skull-stripping even in challenging data.

Test–retest reliability of structural brain networks from diffusion MRI

Structural brain networks constructed from diffusion MRI (dMRI) and tractography have been demonstrated in healthy volunteers and more recently in various disorders affecting brain connectivity. However, few studies have addressed the reproducibility of the resulting networks. We measured the test–retest properties of such networks by varying several factors affecting network construction using ten healthy volunteers who underwent a dMRI protocol at 1.5T on two separate occasions.Each T1-weighted brain was parcellated into 84 regions-of-interest and network connections were identified using dMRI and two alternative tractography algorithms, two alternative seeding strategies, a white matter waypoint constraint and three alternative network weightings. In each case, four common graph-theoretic measures were obtained. Network properties were assessed both node-wise and per network in terms of the intraclass correlation coefficient (ICC) and by comparing within- and between-subject differences.Our findings suggest that test–retest performance was improved when: 1) seeding from white matter, rather than grey; and 2) using probabilistic tractography with a two-fibre model and sufficient streamlines, rather than deterministic tensor tractography. In terms of network weighting, a measure of streamline density produced better test–retest performance than tract-averaged diffusion anisotropy, although it remains unclear which is a more accurate representation of the underlying connectivity. For the best performing configuration, the global within-subject differences were between 3.2% and 11.9% with ICCs between 0.62 and 0.76. The mean nodal within-subject differences were between 5.2% and 24.2% with mean ICCs between 0.46 and 0.62. For 83.3% (70/84) of nodes, the within-subject differences were smaller than between-subject differences. Overall, these findings suggest that whilst current techniques produce networks capable of characterising the genuine between-subject differences in connectivity, future work must be undertaken to improve network reliability.

Why size matters: Differences in brain volume account for apparent sex differences in callosal anatomy: The sexual dimorphism of the corpus callosum

Numerous studies have demonstrated a sexual dimorphism of the human corpus callosum. However, the question remains if sex differences in brain size, which typically is larger in men than in women, or biological sex per se account for the apparent sex differences in callosal morphology. Comparing callosal dimensions between men and women matched for overall brain size may clarify the true contribution of biological sex, as any observed group difference should indicate pure sex effects. We thus examined callosal morphology in 24 male and 24 female brains carefully matched for overall size. In addition, we selected 24 extremely large male brains and 24 extremely small female brains to explore if observed sex effects might vary depending on the degree to which male and female groups differed in brain size. Using the individual T1-weighted brain images (n=96), we delineated the corpus callosum at midline and applied a well-validated surface-based mesh-modeling approach to compare callosal thickness at 100 equidistant points between groups determined by brain size and sex. The corpus callosum was always thicker in men than in women. However, this callosal sex difference was strongly determined by the cerebral sex difference overall. That is, the larger the discrepancy in brain size between men and women, the more pronounced the sex difference in callosal thickness, with hardly any callosal differences remaining between brain-size matched men and women. Altogether, these findings suggest that individual differences in brain size account for apparent sex differences in the anatomy of the corpus callosum.

Evidence for Widespread Structural Brain Changes in Glaucoma: A Preliminary Voxel-Based MRI Study

To investigate structural brain changes in patients with glaucoma. High-resolution T1-weighted anatomical brain magnetic resonance images (MRI) were collected in 15 patients with glaucoma of varying severity and in 15 age-, race-, and sex-matched controls. Exclusion criteria included neurological disease, another disorder which could affect the visual field, and a score of less than 25 on the mini-mental status examination. The scans were analyzed with an automatic volumetric MRI technique to measure the volumes of 93 structures in each brain. Analyses of covariance with age as a covariate were carried out to identify structures that differed significantly between the two groups (i.e., glaucoma versus normal control). The volumes of all brain structures in the group of 15 glaucoma patients were also correlated with clinical measures of disease severity. Linear multivariate regression analyses were conducted to determine the significance of these relationships. Five structures differed significantly between the two groups (P < 0.05). These structures included the right and left inferior occipital gyri and the right middle occipital gyrus, right inferior temporal gyrus, and right occipital lobe white matter. Interestingly, all of these structures were larger in the glaucoma group than in the control group. Within the group of glaucoma patients, 38% of all brain structures had independent associations between decreasing volume and more severe disease in multivariate regression analysis. These results suggest that patients with glaucoma undergo widespread and complex changes in cortical brain structure and that the extent of these changes correlates with disease severity.

Simultaneous Multiresolution Strategies for Nonrigid Image Registration

Multiresolution strategies are commonly used in the nonrigid registration to avoid local minima in the optimization space. Generally, a step-by-step hierarchical approach is adopted, in which the registration starts on a level with reduced complexity (downsampled images, global transformations), then continuing to levels with increased complexity, until the finest level is reached. In this paper, we propose two alternative multiresolution strategies for both the data and transformation models, in which different resolution levels are considered simultaneously instead of subsequently. Through combining the different strategies for data and transformation, we systematically define 3 × 3 multiresolution schemes, including both existing and novel methods. Experiments on 10 pairs of computed tomography lung data sets showed that the best performing strategy resulted in a reduction of the upper quartile of the mean target registration error from 2 to 1.5 mm, compared with the conventionally hierarchical multiresolution method, while achieving smoother deformations. Experiments with intersubject registration of 18 3D T1-weighted MRI brain scans confirmed that simultaneous multiresolution strategies produce more accurate registration results (median of mean overlap increased from 0.55 to 0.57) and smoother deformation fields than the traditionally hierarchical method. Evaluation of robustness indicated that the largest differences in accuracy between methods are observed for structures with a relatively large initial misalignment.

A unified framework for cross-modality multi-atlas segmentation of brain MRI

Multi-atlas label fusion is a powerful image segmentation strategy that is becoming increasingly popular in medical imaging. A standard label fusion algorithm relies on independently computed pairwise registrations between individual atlases and the (target) image to be segmented. These registrations are then used to propagate the atlas labels to the target space and fuse them into a single final segmentation. Such label fusion schemes commonly rely on the similarity between intensity values of the atlases and target scan, which is often problematic in medical imaging - in particular, when the atlases and target images are obtained via different sensor types or imaging protocols. In this paper, we present a generative probabilistic model that yields an algorithm for solving the atlas-to-target registrations and label fusion steps simultaneously. The proposed model does not directly rely on the similarity of image intensities. Instead, it exploits the consistency of voxel intensities within the target scan to drive the registration and label fusion, hence the atlases and target image can be of different modalities. Furthermore, the framework models the joint warp of all the atlases, introducing interdependence between the registrations. We use variational expectation maximization and the Demons registration framework in order to efficiently identify the most probable segmentation and registrations. We use two sets of experiments to illustrate the approach, where proton density (PD) MRI atlases are used to segment T1-weighted brain scans and vice versa. Our results clearly demonstrate the accuracy gain due to exploiting within-target intensity consistency and integrating registration into label fusion.

Gray matter abnormalities in schizophrenia patients with tardive dyskinesia: a magnetic resonance imaging voxel-based morphometry study.

ObjectiveThe pathophysiological mechanism of TD remains unknown. All previous studies, using the region-of-interest method, focused on basal ganglion areas, were with inconsistent results. This whole-brain voxel-based morphometry (VBM) study investigate the grey matter abnormality of TD and its correlates with clinical ratings.MethodHigh resolution T1-weighted brain volumetric MRI from 25 schizophrenia patients with TD (TD group), 25 age-, gender-, and handedness-matched schizophrenia patients without TD (non-TD group), and 25 matched healthy subjects (NC group) were analyzed using a VBM approach. Clinical ratings included the Positive and Negative Symptom Scale (PANSS), Abnormal Involuntary Movement Scale (AIMS), and the Simpson-Angus Scale (SAS).ResultsThe TD group had significantly smaller total gray matter volumes than the NC group (p = 0.05). Compared to the non-TD group, the TD group had significantly higher PANSS negative (p<0.001), SAS (p<0.001), and AIMS (p<0.001) scores; and smaller bilateral inferior frontal gyrus, which correlated negatively with the PANSS negative scores (r = −0.366, p<0.05); and smaller right superior frontal gyrus, which correlated negatively with AIMS scores (r = −0.399, p<0.001), and PANSS general score (r = −0.338, p<0.05).LimitationsThe cross-section design can’t separate the gray matter change to TD from the context of the illness of schizophrenia, although TD with more severe clinical psychopathology could be a phenotype.ConclusionsThe schizophrenia patients with TD had significantly reduced gray matter, mostly at the bilateral inferior frontal gyrus and the right superior frontal gyrus, which correlated with severity of clinical symptoms and involuntary movement, respectively.

Seropositivity for CMV and IL-6 levels are associated with grip strength and muscle size in the elderly

BackgroundSarcopenia is an important cause of morbidity and mortality in older adults, with immunosenescence and inflammation being possible underlying mechanisms. We investigated the relationship between latent cytomegalovirus (CMV) infection, Interleukin 6 (IL-6) levels, muscle size and strength in a group of healthy older community-dwelling people.MethodsParticipants were healthy volunteers from the Lothian Birth Cohort 1936 study. Participants had IL-6 level and CMV antibody titre measured at age 70 years and grip strength and a volumetric T1-weighted MRI brain scan (allowing measurement of neck muscle cross-sectional area (CSA)) at age 73. Markers of childhood deprivation were adjusted for in the analysis due to correlations between childhood deprivation and latent CMV infection.Results866 participants were studied; 448 men (mean age 72.48 years, sd 0.70) and 418 women (mean age 72.51 years, sd 0.72). In men, CMV seropositivity was associated with smaller neck muscle CSA (p = 0.03, partial eta squared = 0.01), even after adjustment for IL-6 levels. Neck muscle CSA was not associated with CMV seropositivity in women, or CMV antibody titre or IL-6 level in either sex. Grip strength associated negatively with IL-6 level (right grip strength p<0.00001, partial eta squared 0.032 and left grip strength p<0.00001, partial eta squared 0.027) with or without adjustment for CMV serostatus or antibody titre. CMV status and antibody titre were not significantly associated with grip strength in either hand.ConclusionThese findings support the hypothesis that there is a relationship between markers of immunosenescence (i.e. CMV serostatus and IL6 level) and low muscle mass and strength and longitudinal studies in older cohorts are now required to investigate these relationships further.

Phase III Randomized Trial Comparing the Efficacy of Cediranib As Monotherapy, and in Combination With Lomustine, Versus Lomustine Alone in Patients With Recurrent Glioblastoma

A randomized, phase III, placebo-controlled, partially blinded clinical trial (REGAL [Recent in in Glioblastoma Alone and With Lomustine]) was conducted to determine the efficacy of cediranib, an oral pan-vascular endothelial growth factor (VEGF) receptor tyrosine kinase inhibitor, either as monotherapy or in combination with lomustine versus lomustine in patients with recurrent glioblastoma. Patients (N = 325) with recurrent glioblastoma who previously received radiation and temozolomide were randomly assigned 2:2:1 to receive (1) cediranib (30 mg) monotherapy; (2) cediranib (20 mg) plus lomustine (110 mg/m(2)); (3) lomustine (110 mg/m(2)) plus a placebo. The primary end point was progression-free survival based on blinded, independent radiographic assessment of postcontrast T1-weighted and noncontrast T2-weighted magnetic resonance imaging (MRI) brain scans. The primary end point of progression-free survival (PFS) was not significantly different for either cediranib alone (hazard ratio [HR] = 1.05; 95% CI, 0.74 to 1.50; two-sided P = .90) or cediranib in combination with lomustine (HR = 0.76; 95% CI, 0.53 to 1.08; two-sided P = .16) versus lomustine based on independent or local review of postcontrast T1-weighted MRI. This study did not meet its primary end point of PFS prolongation with cediranib either as monotherapy or in combination with lomustine versus lomustine in patients with recurrent glioblastoma, although cediranib showed evidence of clinical activity on some secondary end points including time to deterioration in neurologic status and corticosteroid-sparing effects.

Local Feature Extraction and Information Bottleneck-Based Segmentation of Brain Magnetic Resonance (MR) Images

Automated tissue segmentation of brain magnetic resonance (MR) images has attracted extensive research attention. Many segmentation algorithms have been proposed for this issue. However, due to the existence of noise and intensity inhomogeneity in brain MR images, the accuracy of the segmentation results is usually unsatisfactory. In this paper, a high-accuracy brain MR image segmentation algorithm based on the information bottleneck (IB) method is presented. In this approach, the MR image is first mapped into a “local-feature space”, then the IB method segments the brain MR image through an information theoretic formulation in this local-feature space. It automatically segments the image into several clusters of voxels, by taking the intensity information and spatial information of voxels into account. Then, after the IB-based clustering, each cluster of voxels is classified into one type of brain tissue by threshold methods. The performance of the algorithm is studied based on both simulated and real T1-weighted 3D brain MR images. Our results show that, compared with other well-known brain image segmentation algorithms, the proposed algorithm can improve the accuracy of the segmentation results substantially.

Delayed hemichorea syndrome associated with nonketotic hyperglycemia

A 69-year-old woman was admitted for investigation of an acute-onset right hemichorea1. T1-weighted brain magnetic resonance imaging (MRI) showed hyperintensity in the left basal ganglia (Figs 1A and B). Although diabetic, she had no hyperglycemia. Interestingly, two weeks earlier, the patient was admitted due to nonketotic hyperglycemia. Brain computed tomography, previously reported as normal (Fig 1C), showed subtle hyperdensity in the left basal ganglia. However, there were no movement disorders. Choreic movements have been reported in patients with nonketotic hyperglycemia. Usually, dyskinesia [...]

Deformable templates guided discriminative models for robust 3D brain MRI segmentation.

Automatically segmenting anatomical structures from 3D brain MRI images is an important task in neuroimaging. One major challenge is to design and learn effective image models accounting for the large variability in anatomy and data acquisition protocols. A deformable template is a type of generative model that attempts to explicitly match an input image with a template (atlas), and thus, they are robust against global intensity changes. On the other hand, discriminative models combine local image features to capture complex image patterns. In this paper, we propose a robust brain image segmentation algorithm that fuses together deformable templates and informative features. It takes advantage of the adaptation capability of the generative model and the classification power of the discriminative models. The proposed algorithm achieves both robustness and efficiency, and can be used to segment brain MRI images with large anatomical variations. We perform an extensive experimental study on four datasets of T1-weighted brain MRI data from different sources (1,082 MRI scans in total) and observe consistent improvement over the state-of-the-art systems.

Three-dimensional magnetization-prepared imaging using a concentric cylinders trajectory

To develop new magnetization-prepared imaging schemes based on a three-dimensional (3D) concentric cylinders trajectory. The 3D concentric cylinders trajectory, which is robust to off-resonance effects and timing delays while requiring fewer excitations than a comparable 3D Cartesian (3DFT) sequence, is used as the readout for magnetization-prepared sequences exploiting its inherently centric-ordered structure. Two applications: (i) T1 -weighted brain imaging with an inversion-recovery-prepared radiofrequency-spoiled gradient-echo (IR-SPGR) sequence, (ii) non-contrast-enhanced (NCE) peripheral angiography with a magnetization-prepared balanced steady-state free precession (bSSFP) sequence are presented to demonstrate the effectiveness of the proposed method. For peripheral angiography, the scan efficiency is further improved by interleaving different preparations at different rates and by carefully designing the sampling geometry for an efficient parallel imaging method. In vivo brain scans with an IR-SPGR sequence and lower extremity scans with a magnetization-prepared bSSFP sequence for NCE peripheral angiography both demonstrate that the proposed sequences with concentric cylinders effectively capture the transient magnetization-prepared contrast with faster scan times than a corresponding 3DFT sequence. The application of peripheral angiography also shows the feasibility of the proposed interleaving schemes and parallel imaging method. The 3D concentric cylinders trajectory is a robust and efficient readout that is well-suited for magnetization-prepared imaging.

Striatal shape in Parkinson's disease

Parkinson's disease (PD) is marked pathologically by nigrostriatal dopaminergic terminal loss. Histopathological and in vivo labeling studies demonstrate that this loss occurs most extensively in the caudal putamen and caudate head. Previous structural studies have suggested reduced striatal volume and atrophy of the caudate head in PD subjects. The spatial distribution of atrophy in the putamen, however, has not been characterized. We aimed to delineate the specific locations of atrophy in both of these striatal structures. T1- and T2-weighted brain MR (3T) images were obtained from 40 PD and 40 control subjects having no dementia and similar age and gender distributions. Shape analysis was performed using doubly segmented regions of interest. Compared to controls, PD subjects had lower putamen (p = 0.0003) and caudate (p = 0.0003) volumes. Surface contraction magnitudes were greatest on the caudal putamen (p ≤ 0.005) and head and dorsal body of the caudate (p ≤ 0.005). This spatial distribution of striatal atrophy is consistent with the known pattern of dopamine depletion in PD and may reflect global consequences of known cellular remodeling phenomena.

Two Cases of Hemichorea Associated with Nonketotic Hyperglycemia in Type 2 Diabetes Mellitus Patient

Hemichorea-hemiballism is a rare complication of nonketotic hyperglycemia in type 2 diabetes mellitus (T2DM). It can be complicated in long-standing type 1 diabetes mellitus or T2DM, and has been described as a presenting symptom of new-onset diabetes. Rapid correction of diabetic ketoacidosis may also cause the delayed hemichorea. Although hyperglycemic hemiballism rarely causes generalized chorea due to bilateral basal ganglia involvement, patients typically present with hemichorea developing over days to months in the setting of elevated serum glucose. On T1-weighted brain magnetic resonance imaging and computed tomography scan a high signal intensity lesion at the basal ganglia is characteristic. After the correction of hyperglycemia, the movements generally disappear within hours, but atypical cases with delayed onset after the resolution of hyperglycemia, unremitting severe movements, and late recurrence are also reported. We report two cases of female T2DM patients who presented with hemichorea. One patient presented with hemichorea in nonketotic hyperglycemia, and the other with delayed onset hemichorea after the resolution of hyperglycemia.

Image quality improvement in three-dimensional time-of-flight magnetic resonance angiography using the subtraction method for brain and temporal bone diseases

BackgroundTime-of-flight (TOF) magnetic resonance (MR) angiography is based on flow-related enhancement using the T1-weighted spoiled gradient echo, or the fast low-angle shot gradient echo sequence. However, materials with short T1 relaxation times may show hyperintensity signals and contaminate the TOF images. The objective of our study was to determine whether subtraction three-dimensional (3D) TOF MR angiography improves image quality in brain and temporal bone diseases with unwanted contaminations with short T1 relaxation times. MethodsDuring the 12-month study period, patients who had masses with short T1 relaxation times noted on precontrast T1-weighted brain MR images and 24 healthy volunteers were scanned using conventional and subtraction 3D TOF MR angiography. The qualitative evaluation of each MR angiogram was based on signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR) and scores in three categories, namely, (1) presence of misregistration artifacts, (2) ability to display arterial anatomy selectively (without contamination by materials with short T1 relaxation times), and (3) arterial flow-related enhancement. ResultsWe included 12 patients with intracranial hematomas, brain tumors, or middle-ear cholesterol granulomas. Subtraction 3D TOF MR angiography yielded higher CNRs between the area of the basilar artery (BA) and normal-appearing parenchyma of the brain and lower SNRs in the area of the BA compared with the conventional technique (147.7 ± 77.6 vs. 130.6 ± 54.2, p < 0.003 and 162.5 ± 79.9 vs. 194.3 ± 62.3, p < 0.001, respectively) in all 36 cases. The 3D subtraction angiography did not deteriorate image quality with misregistration artifacts and showed a better selective display of arteries (p < 0.0001) and arterial flow-related enhancement (p < 0.044) than the conventional method. ConclusionSubtraction 3D TOF MR angiography is more appropriate than the conventional method in improving the image quality in brain and temporal bone diseases with unwanted contaminations with short T1 relaxation times.

The clinical and anatomical heterogeneity of environmental dependency phenomena

Following damage to the frontal lobes, the observation of patients presenting with environmental dependency syndrome (EDS), particularly with its two main components--grasping and imitation behavior, provides a unique opportunity to gain new insights into the neural bases of human autonomy and free-will. In the present study, thirty-nine patients with frontal lobe dysfunction [21 with progressive supranuclear palsy (PSP), and 18 with the behavioral variant of frontotemporal dementia, (bvFTD)] were tested for environmental dependency phenomena and underwent neuropsychological evaluation and T1-weighted 3D brain MRI. We correlated scores obtained by assessing grasping, imitation and utilization behaviors with both neuropsychological executive test performance and grey matter density on MRI using Voxel-Based Morphometry (VBM). This study confirms the high frequency of two environmental dependency phenomena- grasping and imitation- in patients with frontal lobe syndrome (34/39 patients) and the rarity of utilization behavior (2/39). The grasping score was significantly and positively correlated with those obtained in all executive tests except the Stroop test, while the imitation score was not. In the VBM study, while the grasping score was correlated with grey matter density in the right superior frontal gyrus and both inferior temporal gyri, the imitation score was correlated with changes in the right insula, left medial frontal gyrus and left precuneus. Environmental dependency is associated with the dysfunction of a frontoparietal network. Within this large network, grasping and imitation behaviors can be dissociated from both neuropsychological and anatomical standpoints, underlining the clinical and anatomical heterogeneity of environmental dependency phenomena.

Enlarged Perivascular Spaces and Cerebral Small Vessel Disease

Background and aimsEnlarged perivascular spaces (also known as Virchow–Robin spaces) on T2-weighted brain magnetic resonance imaging are common, but their etiology, and specificity to small vessel as opposed to general cerebrovascular disease or ageing, is unclear. We tested the association between enlarged perivascular spaces and ischemic stroke subtype, other markers of small vessel disease, and common vascular risk factors.MethodsWe prospectively recruited patients with acute stroke, diagnosed and subtyped by a stroke physician using clinical features and brain magnetic resonance imaging. A neuroradiologist rated basal ganglia and centrum semiovale enlarged perivascular spaces on a five-point scale, white matter lesions, recent and old infarcts, and cerebral atrophy. We assessed associations between basal ganglia-, centrum semiovale- and total (combined basal ganglia and centrum semiovale) enlarged perivascular spaces, stroke subtype, white matter lesions, atrophy, and vascular risk factors.ResultsAmong 298 patients (mean age 68 years), after adjusting for vascular risk factors and white matter lesions, basal ganglia–enlarged perivascular spaces were associated with increasing age (P = 0·001), centrum semiovale–enlarged perivascular spaces (P < 0·001), cerebral atrophy (P = 0·03), and lacunar stroke subtype (P = 0·04). Centrum semiovale–enlarged perivascular spaces were associated mainly with basal ganglia–enlarged perivascular spaces. Total enlarged perivascular spaces were associated with increasing age (P = 0·01), deep white matter lesions (P = 0·005), and previous stroke (P = 0·006).ConclusionsEnlarged perivascular spaces are associated with age, lacunar stroke subtype and white matter lesions and should be considered as another magnetic resonance imaging marker of cerebral small vessel disease. Further evaluation of enlarged perivascular spaces in studies of ageing, stroke, and dementia is needed to determine their pathophysiological importance.