Spatial Distribution Of Lesions Research Articles

Developing an Online Interactive Volumetric Surface Viewer for Visualizing Spatial Distribution of Intracranial Lesions.

The exact location of intracranial neoplasms and metastatic lesions within the cortex may provide key insights into predicting treatment effectiveness and toxicities. Modern neuroimaging approaches have enabled precise, rapid diffeomorphic alignment from individual brains to an atlas, allowing the registration of contours and dose distributions onto a common template. However, there is a paucity of intuitive tools to perform such functions. Here, we developed an online interactive volumetric surface viewer that displays distribution of brain lesions of specific clinical features within the context of prior radiation treatment in populations of patients on a common atlas. Data from 647 patients treated at our institution with radiotherapy for intracranial lesions were analyzed with FreeSurfer to perform intensity normalization, skull-stripping, and affine registration to Talairach coordinates. A custom-built VoxelMorph model was trained to register T1 MRIs to a common atlas. Radiation dose maps and contours on underlying CT simulation scans were rigidly aligned to the T1 MRIs. The diffeomorphic warps were then applied to the radiation dose maps and contours, including the gross tumor volumes. Surface rendering of the template atlas was performed using FreeSurfer and visualized using PyCortex. Clinical information including primary sites for brain metastases, lesion size, survival, recurrence, use of anti-epileptic medications, radiation necrosis, and neuro-cognitive toxicity was embedded into the PyCortex viewer. The custom-trained VoxelMorph model enabled rapid normalization of the T1MRIs to the atlas brain. PyCortex allows for interactive visualization of the spatial distribution of lesions on the cortical surface across a rich array of clinical parameters. Initial maps have qualitatively revealed a predilection for metastases in the right hemisphere. This WebGL viewer allows intuitive clinical interrogation on a visual surface enabling population inferences. For example, one can visualize the distribution of brain metastases of a large patient cohort based on their primary tumor sites, propensity for seizure and risk for radionecrosis. We successfully built an online interactive viewer to visualize the spatial distribution of intracranial lesions on a common reference. Our approach extends prior work allowing visual interaction of lesions and real-time generation of inference maps by combining a front-end viewer and back-end database of clinical data. This viewer may represent a critical step towards uncovering the location-dependent breakdown of the blood-brain-barrier, differentiating the propensity of primary lesions metastasizing to brain regions, and allowing the discovery of associations of previously understudied spatial neighborhoods. We plan to release a publicly available web-based viewer to further explore, interrogate, and inform future radiation treatments.

Spatial distribution of multiple sclerosis iron rim lesions and their impact on disability

BackgroundIn multiple sclerosis (MS), iron rim lesions (IRLs) on magnetic resonance imaging (MRI) have been suggested as an imaging marker of disease progression. However, the exact mechanisms how they contribute to disability are yet not completely known. Strategic lesion location may be an important factor concerning the impact of focal lesions on clinical disability. Therefore, the aim of this study was to investigate the spatial distribution of IRLs compared to non-IRLs and their impact on disability. MethodsWe retrospectively identified 67 patients with at least one IRL on MRI and 67 age- and sex-matched patients without IRLs. We compared the spatial distribution of lesions between both groups and between IRLs and non-IRLs in patients with IRLs. Furthermore, we assessed the relationship between lesion localisation and disability on a voxel-by-voxel basis and investigated the impact on structural network disruptions. ResultsPatients with IRLs had higher disability scores (median Expanded Disability Status Scale score (range): 3.0 (0 – 8.5) versus 1.5 (0 – 6.5); p = 0.001; median pyramidal functional system score (range): 1.0 (0 – 5) versus 0 (0 – 4); p = 0.003), significantly lower brain volumes (mean normal-appearing grey matter volume: 749.66 ± 60.58 versus 785.83 ± 53.71 mL; mean normal-appearing white matter volume: 723.58 ± 60.13 versus 753.25 ± 69.61 mL; mean deep grey matter volume: 33.21 ± 4.19 versus 35.85 ± 4.89 mL; p < 0.05 for all comparisons) and a significantly higher total T2 lesion volume (mean: 9.96 ± 11.6 versus 4.31 ± 8.9 mL; p < 0.001). We found no neuroanatomical regions that were more often affected by IRLs. Furthermore, comparing the overall network disruption in the IRL group, IRLs caused less network disruption/mL lesion size compared to non-IRLs (1.54% / mL versus 2.0% / mL; p < 0.05). ConclusionIRLs are associated with higher disability scores. However, our results suggest that a higher disability is not explained by the sheer topography of IRLs or their network disruption.

P14.30 Voxelwise analysis of spatial distribution of postoperative ischemia in diffuse glioma

Abstract BACKGROUND Surgical treatment of diffuse glioma is performed to reduce tumor mass effect and to pave the way for adjuvant (chemo)radiotherapy. As a complication of surgery, ischemic lesions are often found in the postoperative setting. Not only can these lesion induce neurological deficits, but their volume has also been associated with reduced survival time. Prior studies suggest areas with a singular vascular supply to be more prone to postoperative ischemic lesions, although the precise cause is yet unknown. The aim of this study was to explore the volumetric and spatial distributions of postoperative ischemic lesions and their relation to arterial territories in glioma patients. MATERIAL AND METHODS We accessed a retrospective database of 144 adult cases with WHO grade II-IV supratentorial gliomas, who received surgery and postoperative MRI within 3 days in 2012–2014. We identified 93 patients with postoperative ischemia, defined as new confluent diffusion restriction on DWI. Ischemic lesions were manually delineated and spatially normalized to stereotaxic MNI space. Voxel-based analysis (VBA) was performed to compare presence and absence of postoperative ischemia. False positive results were eliminated by family-wise error correction. Areas of ischemia were labeled using an arterial territory map, the Harvard-Oxford cortical and subcortical atlases and the XTRACT white matter atlas. RESULTS Median volume of confluent ischemia was 3.52cc (IQR 2.15–5.94). 23 cases had only ischemic lesion in the left hemisphere, 46 in the right hemisphere and 24 bilateral. Median volume was 3.08cc (IQR 1.35–5.72) in left-sided lesions and 2.47cc (1.01–4.24) in right-sided lesions. Volume of ischemic lesions was not associated with survival after 1, 2 or 5 years. A cluster of 125.18cc was found to be significantly associated with development of postoperative ischemia. 73% of this cluster was situated in the arterial territory of the right middle cerebral artery (MCA), limited by the border of the posterior cerebral artery (PCA), and the watershed area between the right MCA and the right anterior cerebral artery (ACA). Significant areas were located in the frontal lobes, spanning into the right temporo-occipital region, and predominantly included right and left thalamus, caudate nucleus, putamen, pallidum, as well as right temporal gyri and insular cortex, and parts of the right corticospinal tract, longitudinal fasciculi and superior thalamic radiation. CONCLUSION We found slightly more and larger ischemic lesions in the right than left hemisphere after glioma resection. A statistically significant cluster of voxels of postoperative ischemia was found in the territory of the right MCA and watershed area of the right ACA. Exploration of the spatial distribution of these lesions could help elucidate their etiology and form the basis for predicting clinically relevant postoperative ischemia.

Brain network reorganisation and spatial lesion distribution in systemic lupus erythematosus.

ObjectiveThis work investigates network organisation of brain structural connectivity in systemic lupus erythematosus (SLE) relative to healthy controls and its putative association with lesion distribution and disease indicators.MethodsWhite matter hyperintensity (WMH) segmentation and connectomics were performed in 47 patients with SLE and 47 healthy age-matched controls from structural and diffusion MRI data. Network nodes were divided into hierarchical tiers based on numbers of connections. Results were compared between patients and controls to assess for differences in brain network organisation. Voxel-based analyses of the spatial distribution of WMH in relation to network measures and SLE disease indicators were conducted.ResultsDespite inter-individual differences in brain network organization observed across the study sample, the connectome networks of SLE patients had larger proportion of connections in the peripheral nodes. SLE patients had statistically larger numbers of links in their networks with generally larger fractional anisotropy weights (i.e. a measure of white matter integrity) and less tendency to aggregate than those of healthy controls. The voxels exhibiting connectomic differences were coincident with WMH clusters, particularly the left hemisphere’s intersection between the anterior limb of the internal and external capsules. Moreover, these voxels also associated more strongly with disease indicators.ConclusionOur results indicate network differences reflective of compensatory reorganization of the neural circuits, reflecting adaptive or extended neuroplasticity in SLE.

Deep-Learning-Based Segmentation and Localization of White Matter Hyperintensities on Magnetic Resonance Images.

White matter magnetic resonance hyperintensities of presumed vascular origin, which could be widely observed in elderly people, and has significant importance in multiple neurological studies. Quantitative measurement usually relies heavily on manual or semi-automatic delineation and intuitive localization, which is time-consuming and observer-dependent. Current automatic quantification methods focus mainly on the segmentation, but the spatial distribution of lesions plays a vital role in clinical diagnosis. In this study, we implemented four segmentation algorithms and compared the performances quantitatively and qualitatively on two open-access datasets. The location-specific analysis was conducted sequentially on 213 clinical patients with cerebral ischemia and lacune. The experimental results suggest that our deep-learning-based model has the potential to be integrated into the clinical workflow.

Symptoms and probabilistic anatomical mapping of lacunar infarcts

BackgroundThe anatomical distribution of acute lacunar infarcts has mainly been studied for supratentorial lesions. In addition, little is known about the association with distinct stroke symptoms, not summarized as classical lacunar syndromes. We aimed to describe the spatial lesion distribution of acute supra- and infratentorial lacunar infarcts and their association with stroke symptoms in patients eligible for thrombolysis.MethodsAll patients enrolled in the WAKE-UP trial (efficacy and safety of magnetic resonance imaging [MRI]-based thrombolysis in wake-up stroke) were screened for lacunar infarcts on diffusion-weighted imaging (DWI). The relationship between the anatomical distribution of supra- and infratentorial lacunar infarcts, their demographic characteristics and acute stroke symptoms, defined by the National Institutes of Health Stroke Scale (NIHSS) score, were correlated and compared.ResultsMaps of lesion distribution from 224 lacunar infarct patients (76 [33.9%] females, mean age [standard deviation] of 63.4 [11.5] years) were generated using computational image mapping methods. Median infarct volume was 0.73 ml (interquartile range [IQR] 0.37–1.15 ml). Median NIHSS sum score on hospital arrival was 4 (IQR 3–6). 165 (73.7%) patients had lacunar infarcts in the supratentorial deep white or grey matter, while 59 (26.3%) patients had infratentorial lacunar infarcts. Patients with supratentorial lacunar infarcts presented with a significantly lower occurrence of deficits in the NIHSS items gaze (p < 0.001) and dysarthria (p = 0.008), but had more often a paresis of the left arm (p = 0.009) and left leg (p = 0.068) compared to patients with infratentorial infarcts.ConclusionsThe anatomical lesion distribution of lacunar infarcts reveals a distinct pattern and supports an association of localization with different stroke symptoms.Trial registrationNCT01525290.

Hemato-biochemical changes and spatial distribution of lesions on body surface in demodicosis affected dogs.

Hemato-biochemical changes and spatial distribution of lesions on body surface in demodicosis affected dogs.

Occam’s broom and the dirty DSB: cytogenetic perspectives on cellular response to changes in track structure and ionization density

Given equal doses, it is well-known that densely ionizing radiations are more potent in causing a number of biological effects compared to sparsely ionizing radiations, such as x- or gamma rays. According to classical models of radiation action, this results from differences in the spatial distribution of lesions along charged particle tracks. In recent years investigators have been barraged with the alternative narrative that this is instead due to ‘qualitative’ differences in the types of molecular lesions that each type of radiation produces. The present review discusses, mainly from a cytogenetic perspective, the merits and shortcomings of these seemingly contradictory viewpoints. There may be a kernel of truth to the idea that qualitative differences in the types of molecular lesions produced at the nanometer level affect RBE/LET relationships, but to ignore the fact that such differences result from longer-range spatial distributions of lesions produced along charged particle tracks is an unjustifiably narrow stance tantamount to employing Occam’s Broom. Not only are such spatial considerations indispensable in explaining the impact of ionization density upon higher-order biological endpoints, particularly chromosome aberrations, the explanations they provide render arguments based principally on the quality of IR damage largely superfluous.

Spatial distribution of damage affects the healing, growth, and morphology of coral.

Many predators and herbivores do not kill their prey, but rather remove or damage tissue. Prey are often able to heal or regenerate this lost tissue. If the prey are modular organisms (e.g., some plants and cnidarians), regeneration is frequently influenced by other modules interconnected to damaged ones. For example, many coral predators remove tissue from colonies consisting of many polyps, and these polyps often share resources with their neighbors. Thus, the distribution of tissue loss on a coral colony could affect the coral's response. I hypothesized that spatially aggregated damage might be slow to heal due to competing demands on nearby polyps. To explore the spatial patterns of corallivory and their implications, I conducted: (1) field surveys documenting the spatial distribution of lesions on corals; (2) field experiments testing the effect of the distance between lesions on coral tissue healing, skeletal growth, and morphology; and (3) field surveys relating corallivore presence to coral growth and morphology. In the field surveys, lesions were aggregated at multiple spatial scales, and most lesions had other lesions within 2cm. When lesions were near one another, coral tissue regeneration was depressed, although there was no effect on whole colony growth. After a year, however, linear extension was lower in the neighborhood of the lesions. Additionally, gastropod corallivores (Coralliophila violacea) with low movement decreased coral growth and increased coral topographical complexity. These results suggest that corallivores that create clusters of coral damage have a greater effect on coral growth and recovery from damage than corallivores that spread damage throughout the colony.

Modelling the distribution of white matter hyperintensities due to ageing on MRI images using Bayesian inference

White matter hyperintensities (WMH), also known as white matter lesions, are localised white matter areas that appear hyperintense on MRI scans. WMH commonly occur in the ageing population, and are often associated with several factors such as cognitive disorders, cardiovascular risk factors, cerebrovascular and neurodegenerative diseases. Despite the fact that some links between lesion location and parametric factors such as age have already been established, the relationship between voxel-wise spatial distribution of lesions and these factors is not yet well understood. Hence, it would be of clinical importance to model the distribution of lesions at the population-level and quantitatively analyse the effect of various factors on the lesion distribution model.In this work we compare various methods, including our proposed method, to generate voxel-wise distributions of WMH within a population with respect to various factors. Our proposed Bayesian spline method models the spatio-temporal distribution of WMH with respect to a parametric factor of interest, in this case age, within a population. Our probabilistic model takes as input the lesion segmentation binary maps of subjects belonging to various age groups and provides a population-level parametric lesion probability map as output. We used a spline representation to ensure a degree of smoothness in space and the dimension associated with the parameter, and formulated our model using a Bayesian framework.We tested our algorithm output on simulated data and compared our results with those obtained using various existing methods with different levels of algorithmic and computational complexity. We then compared the better performing methods on a real dataset, consisting of 1000 subjects of the UK Biobank, divided in two groups based on hypertension diagnosis. Finally, we applied our method on a clinical dataset of patients with vascular disease.On simulated dataset, the results from our algorithm showed a mean square error (MSE) value of 7.27×10−5, which was lower than the MSE value reported in the literature, with the advantage of being robust and computationally efficient. In the UK Biobank data, we found that the lesion probabilities are higher for the hypertension group compared to the non-hypertension group and further verified this finding using a statistical t-test. Finally, when applying our method on patients with vascular disease, we observed that the overall probability of lesions is significantly higher in later age groups, which is in line with the current literature.

Institutional experience with SRS VMAT planning for multiple cranial metastases.

Background and PurposeThis study summarizes the cranial stereotactic radiosurgery (SRS) volumetric modulated arc therapy (VMAT) procedure at our institution.Materials and MethodsVolumetric modulated arc therapy plans were generated for 40 patients with 188 lesions (range 2–8, median 5) in Eclipse and treated on a TrueBeam STx. Limitations of the custom beam model outside the central 2.5 mm leaves necessitated more than one isocenter pending the spatial distribution of lesions. Two to nine arcs were used per isocenter. Conformity index (CI), gradient index (GI) and target dose heterogeneity index (HI) were determined for each lesion. Dose to critical structures and treatment times are reported.ResultsLesion size ranged 0.05–17.74 cm3 (median 0.77 cm3), and total tumor volume per case ranged 1.09–26.95 cm3 (median 7.11 cm3). For each lesion, HI ranged 1.2–1.5 (median 1.3), CI ranged 1.0–2.9 (median 1.2), and GI ranged 2.5–8.4 (median 4.4). By correlating GI to PTV volume a predicted GI = 4/PTV0.2 was determined and implemented in a script in Eclipse and used for plan evaluation. Brain volume receiving 7 Gy (V 7 Gy) ranged 10–136 cm3 (median 42 cm3). Total treatment time ranged 24–138 min (median 61 min).ConclusionsVolumetric modulated arc therapy provide plans with steep dose gradients around the targets and low dose to critical structures, and VMAT treatment is delivered in a shorter time than conventional methods using one isocenter per lesion. To further improve VMAT planning for multiple cranial metastases, better tools to shorten planning time are needed. The most significant improvement would come from better dose modeling in Eclipse, possibly by allowing for customizing the dynamic leaf gap (DLG) for a special SRS model and not limit to one DLG per energy per treatment machine and thereby remove the limitation on the Y‐jaw and allow planning with a single isocenter.

Spatial statistical modelling of capillary non-perfusion in the retina

Manual grading of lesions in retinal images is relevant to clinical management and clinical trials, but it is time-consuming and expensive. Furthermore, it collects only limited information - such as lesion size or frequency. The spatial distribution of lesions is ignored, even though it may contribute to the overall clinical assessment of disease severity, and correspond to microvascular and physiological topography. Capillary non-perfusion (CNP) lesions are central to the pathogenesis of major causes of vision loss. Here we propose a novel method to analyse CNP using spatial statistical modelling. This quantifies the percentage of CNP-pixels in each of 48 sectors and then characterises the spatial distribution with goniometric functions. We applied our spatial approach to a set of images from patients with malarial retinopathy, and found it compares favourably with the raw percentage of CNP-pixels and also with manual grading. Furthermore, we were able to quantify a biological characteristic of macular CNP in malaria that had previously only been described subjectively: clustering at the temporal raphe. Microvascular location is likely to be biologically relevant to many diseases, and so our spatial approach may be applicable to a diverse range of pathological features in the retina and other organs.

Sequential MR imaging (with diffusion-weighted imaging) changes in metronidazole-induced encephalopathy.

Metronidazole-induced neuro-toxicity, though rare, is known. A characteristic spatial distribution of lesions in cerebellar dentate nuclei and dorsal pons is known. However, temporal progression of lesions on magnetic resonance imaging (MRI) has not been described previously. We describe two such cases which presented initially with splenial hyperintesity and showed progression to characterstic lesions. Both cases improved with stoppage of metronidazole.

Multiple Sclerosis Lesion Segmentation Using Joint Label Fusion.

This paper adapts the joint label fusion (JLF) multi-atlas image segmentation algorithm to the problem of multiple sclerosis (MS) lesion segmentation in multi-modal MRI. Conventionally, JLF requires a set of atlas images to be co-registered to the target image using deformable registration. However, given the variable spatial distribution of lesions in the brain, whole-brain deformable registration is unlikely to line up lesions between atlases and the target image. As a solution, we propose to first pre-segment the target image using an intensity regression based technique, yielding a set of "candidate" lesions. Each "candidate" lesion is then matched to a set of similar lesions in the atlas based on location and size; and deformable registration and JLF are applied at the level of the "candidate" lesion. The approach is evaluated on a dataset of 74 subjects with MS and shown to improve Dice similarity coefficient with reference manual segmentation by 12% over intensity regression technique.

Stroke : Highlights of Selected Articles

<i>Stroke</i> : Highlights of Selected Articles

SU-F-T-613: Multi-Lesion Cranial SRS VMAT Plan Quality

Purpose: Cranial SRS VMAT plans must have steep dose gradient around each target to reduce dose to normal brain. This study reports on the correlation between gradient index (GI=V50%/V100%), target size and target dose heterogeneity index (HI=PTV Dmax/prescription dose) for multi-lesion cranial SRS VMAT plans. Methods: VMAT plans for 10 cranial cases with 3 to 6 lesions (total 39 lesions) generated in Varian Eclipse V11.0.47 with a fine-tuned AAA beam model and 0.125 cm dose grid were analyzed. One or two iso centers were used depending on the spatial distribution of lesions. Two to nine coplanar and non-coplanar arcs were used per isocenter. Conformity index (CI= V100%/VPTV), HI, and GI were determined for each lesion. Dose to critical structures were recorded. Results: Lesion size ranged from 0.05–11.00 cm3. HI ranged from 1.2–1.4, CI ranged from 1.0–2.8 and GI from 3.1–8.4. Maximum dose to brainstem, chiasm, lenses, optic nerves and eyes ranged from 120–1946 cGy, 47–463 cGy, 9–121 cGy, 14–512 cGy, and 17–294 cGy, respectively. Brain minus PTV (Brain-PTV) V7Gy was in the range 1.1–6.5%, and Brain-PTV Dmean was in the range 94–324 cGy. Conclusion: This work shows that a GI 0.4cc. For smaller lesions, GI increases rapidly. GI is lower when HI is increased. Based on this study, recommend HI is 1.4, and recommended GI is for volumes 1.0cc GI<4. CI is < 1.3 for all lesions except for targets < 0.1cc. Cranial SRS VMAT plans must be optimized to lower the GI to reduce the dose to normal brain tissue.

White Matter MS-Lesion Segmentation Using a Geometric Brain Model.

Brain magnetic resonance imaging (MRI) in patients with Multiple Sclerosis (MS) shows regions of signal abnormalities, named plaques or lesions. The spatial lesion distribution plays a major role for MS diagnosis. In this paper we present a 3D MS-lesion segmentation method based on an adaptive geometric brain model. We model the topological properties of the lesions and brain tissues in order to constrain the lesion segmentation to the white matter. As a result, the method is independent of an MRI atlas. We tested our method on the MICCAI MS grand challenge proposed in 2008 and achieved competitive results. In addition, we used an in-house dataset of 15 MS patients, for which we achieved best results in most distances in comparison to atlas based methods. Besides classical segmentation distances, we motivate and formulate a new distance to evaluate the quality of the lesion segmentation, while being robust with respect to minor inconsistencies at the boundary level of the ground truth annotation.

Rethinking voxel-wise lesion-deficit analysis: A new challenge for computational neuropsychology

Department of Psychology, Lille Nord de France University (Lille 3), Villeneuve d'Ascq, FranceThiscommentaryreferstotherecentstudypublishedinBrainentitled ‘Human brain lesion-deficit inference re-mapped’,byMah et al.(http://dx.doi.org/10.1093/brain/awu164).Over the two past decades, large-scale neuropsychologicalstudies have permitted to gain considerable insights into theanatomical architecture of complex neurocognitive systems.A partof this advanceinknowledgehasoftenbeen associatedwith the development of sophisticated and powerful lesiondata analysis techniques, such as voxel-based lesion-symp-tom mapping (Bates et al., 2003; Damasio & Frank, 1992). Suchanalyses are becoming increasingly used by neuroscientists(having regard to the tends of published papers using lesion-deficit mapping in journals with a broad audience such asBrain, Cortex,orCerebral Cortex), mainly because they enable inprinciple to minimize or override a number of methodologicalshortcomings inherent to the classical lesion method (e.g.,region-of-interest analysis necessitating prior knowledge orassumptions, low number of patients, inhomogeneous spatialdistribution of lesions). However, one should not lose sight ofthe fact that voxel-wise lesion-deficit analysis suffers from anumber of weaknesses often discussed (see for instanceRorden & Karnath, 2004) but not further addressed. From amethodological standpoint, it is therefore time to tackle theexisting gaps in the technique in order to improve the validityof the resulting brain-behavioural inferences. In this context,the study of (Mah, Husain, Rees, & Nachev, 2014) is timely andconvincingly demonstrates the necessity to refine the way inwhich neuroscientists process lesion data.The fundamental problem in voxelwise lesion-deficit an-alyses is related to the statistical approach used. Schemati-cally, a one-tailed statistical test (parametric or non-parametric) is performed to compare the behavioural perfor-mance of patients having a given voxel damaged versus thebehavioural performance of patients not having that voxeldamaged.Thisprocedureisrepeatedforeachvoxeltakenintoaccount in the analyses, allowing to generate probabilisticmaps of brainebehaviour relationships. The condition ofapplication of this ‘mass-univariate’ approach (each statisti-cal test is performed independently across voxels) should bethat the spatial distribution of lesions is random (i.e., allvoxels have the same probability to be affected by the lesion)and, importantly, that damage to a particular voxel is fullyindependent to damage to other voxels. However, as high-lighted by Mah, Husain, et al. (2014), but also previously byHusain and Nachev (2007) or others (e.g., Bartolomeo, 2011),this is not the case; lesion distributions are anatomicallyconstrained for biological reasons. This is true for ischemicstrokes which typically damage brain structures sculpting thesylvianfissure(brainterritoriesmainlysuppliedbythemiddlecerebral artery which are especially vulnerable to ischemia),but also for other neuropsychological conditions such as, forinstance, diffuse low-grade glioma which preferentiallyinvalidate the posterior medial frontal cortex and the fronto-insular regions (Duffau & Capelle, 2004). As a result, this rai-ses the issue of how consider, from a statistical standpoint, alesioned voxel given that a collection of contiguous voxels

Health effects of lesion localization in multiple sclerosis: spatial registration and confounding adjustment.

Brain lesion localization in multiple sclerosis (MS) is thought to be associated with the type and severity of adverse health effects. However, several factors hinder statistical analyses of such associations using large MRI datasets: 1) spatial registration algorithms developed for healthy individuals may be less effective on diseased brains and lead to different spatial distributions of lesions; 2) interpretation of results requires the careful selection of confounders; and 3) most approaches have focused on voxel-wise regression approaches. In this paper, we evaluated the performance of five registration algorithms and observed that conclusions regarding lesion localization can vary substantially with the choice of registration algorithm. Methods for dealing with confounding factors due to differences in disease duration and local lesion volume are introduced. Voxel-wise regression is then extended by the introduction of a metric that measures the distance between a patient-specific lesion mask and the population prevalence map.

Cerebral white matter hyperintensities in the prediction of cognitive decline and incident dementia

Cerebral white matter hyperintensities (WMH), detected in vivo with magnetic resonance imaging (MRI), are commonly used to assess cerebrovascular burden in cognitive impairment. However, the association between WMH and cognition is not consistent across the literature. The present review examines evidence from published longitudinal studies. We reviewed the PubMed data base from January 1990 to March 2013 and included studies investigating the association of WMH with (1) the risk of dementia in the general population, (2) the risk of conversion to dementia in the mild cognitive impairment (MCI) population, and (3) cognitive decline in the general population. WMH were associated with all types of dementia in the general population, but not in MCI patients. Results are discrepant for global decline. WMH appear to be early predictors of the risk of dementia, but this association appears to be modulated by cognitive reserve, age and the spatial distribution of lesions. There are, however, some limits in the use of WMH as a marker of vascular burden. In addition to their ischaemic origin, WMH may be the result of co-occurring morbidity. Further research is needed to elucidate to what extent WMH actually reflect vascular risk to evaluate the likely efficacy of interventions specifically targeting WMH reduction.