White matter in different regions evolves differently during progression to dementia.
TL;DR: The results show a significantly greater increase of all regional WMH volumes in the MCI population that converts to dementia, and changes differ according to the WM region, suggesting that different mechanisms affect the juxtacortical area in comparison to deep and periventricular regions in the process of conversion to dementia.
About: This article is published in Neurobiology of Aging.The article was published on 2019-04-01. It has received 45 citations till now. The article focuses on the topics: Hyperintensity & Dementia.
Citations
More filters
TL;DR: Both grey and white matter damage contribute to motor and cognitive deficits in PD and the relationships between MRI measurements and clinical symptoms in PD are assessed.
35 citations
TL;DR: The presence of cerebral small‐vessel disease, measured by T2‐weighted magnetic resonance imaging white matter hyperintensity (WMH) burden, is also observed in patients with PD with faster cognitive decline.
Abstract: Background Patients with Parkinson's disease (PD) present with a broad spectrum of nonmotor features including autonomic disorders. More severe autonomic dysfunction in PD is associated with increased cognitive deficits. The presence of cerebral small-vessel disease, measured by T2-weighted magnetic resonance imaging white matter hyperintensity (WMH) burden, is also observed in patients with PD with faster cognitive decline. Objective To investigate whether baseline orthostatic hypotension and autonomic dysfunction in early-stage PD affect later cognitive decline via mediation through cerebral small-vessel disease. Methods De novo PD patients (N = 365) and age-matched controls (N = 174) with baseline T2-weighted/ fluid-attenuated inversion recovery scans were selected from the Parkinson's Progression Markers Initiative. WMHs were automatically segmented. Mediation analysis was used to assess whether WMH load mediates the effect of orthostatic hypotension and autonomic dysfunction (measured by Scales for Outcomes in Parkinson's Disease-Autonomic) on future cognitive decline (measured by Montreal Cognitive Assessment) in an average of 4 years of follow-up. Results Mediation analysis supported the existence of a full mediation of WMHs on the effect of diastolic orthostatic hypotension in patients with PD and future cognitive decline (average causal mediation effect: ab = -0.032, 95% confidence interval = -0.064 to -0.01, P = 0.01). There was also a partial mediation for overall autonomic dysfunction (ab = -0.027, 95% confidence interval = -0.054 to 0.00, P = 0.02). Conclusions WMHs fully mediate the effect of diastolic orthostatic hypotension and partially mediate the effect of autonomic dysregulation on future cognitive decline in patients with PD. Our findings support the hypothesis that autonomic dysfunction in early clinical stages predisposes the brain to WMHs through dysregulation of the blood flow in the small vessels. This in turn increases the risk of future cognitive impairment in early PD.
30 citations
Cites background from "White matter in different regions e..."
...otherwise healthy elderly individuals as well as patients with mild cognitive impairment and dementia.(12,13) The presence of...
[...]
TL;DR: Baseline WMHs lead to greater future GM atrophy and cognitive decline, suggesting that WM damage precedes neurodegeneration and cognitive drop, and a potential role of amyloid in WM damage.
29 citations
15 May 2020
TL;DR: Deformation-based morphometry provides a sensitive indicator of atrophy in Amyotrophic lateral sclerosis and has potential as a biomarker of disease burden, in both grey matter and white matter.
Abstract: Amyotrophic lateral sclerosis is a neurodegenerative disease characterized by a preferential involvement of both upper and lower motor neurons. Evidence from neuroimaging and post-mortem studies confirms additional involvement of brain regions extending beyond the motor cortex. The aim of this study was to assess the extent of cerebral disease in amyotrophic lateral sclerosis cross-sectionally and longitudinally and to compare the findings with a recently proposed disease-staging model of amyotrophic lateral sclerosis pathology. Deformation-based morphometry was used to identify the patterns of brain atrophy associated with amyotrophic lateral sclerosis and to assess their relationship with clinical symptoms. Longitudinal T1-weighted MRI data and clinical measures were acquired at baseline, 4 months and 8 months, from 66 patients and 43 age-matched controls who participated in the Canadian Amyotrophic Lateral Sclerosis Neuroimaging Consortium study. Whole brain voxel-wise mixed-effects modelling analysis showed extensive atrophy patterns differentiating patients from the normal controls. Cerebral atrophy was present in the motor cortex and corticospinal tract, involving both grey matter and white matter, and to a lesser extent in non-motor regions. More specifically, the results showed significant bilateral atrophy in the motor cortex and corticospinal tract (including the internal capsule and brainstem) and ventricular enlargement, along with significant longitudinal atrophy in precentral gyrus, frontal and parietal white matter, accompanied by ventricular and sulcal enlargement. Atrophy in the precentral gyrus was significantly associated with greater disability as quantified with the Amyotrophic Lateral Sclerosis Functional Rating Scale-Revised (P < 0.0001). The pattern of atrophy observed using deformation-based morphometry was consistent with the Brettschneider's four-stage pathological model of the disease. Deformation-based morphometry provides a sensitive indicator of atrophy in Amyotrophic lateral sclerosis and has potential as a biomarker of disease burden, in both grey matter and white matter.
16 citations
Additional excerpts
...developed and extensively validated for use in multicentre studies involving different MRI systems and have been used in numerous such studies (Zeighami et al., 2015; Dadar et al., 2018b; Misquitta et al., 2018; Dadar et al., 2019; Manera et al., 2019; Sanford et al., 2019)....
[...]
TL;DR: This paper investigated the impact of the presence of white matter hyperintensities (WMHs) on FreeSurfer gray matter (GM) structure volumes and its possible bias on functional relationships.
Abstract: Volumetric estimates of subcortical and cortical structures, extracted from T1-weighted MRIs, are widely used in many clinical and research applications Here, we investigate the impact of the presence of white matter hyperintensities (WMHs) on FreeSurfer gray matter (GM) structure volumes and its possible bias on functional relationships T1-weighted images from 1,077 participants (4,321 timepoints) from the Alzheimer's Disease Neuroimaging Initiative were processed with FreeSurfer version 600 WMHs were segmented using a previously validated algorithm on either T2-weighted or Fluid-attenuated inversion recovery images Mixed-effects models were used to assess the relationships between overlapping WMHs and GM structure volumes and overall WMH burden, as well as to investigate whether such overlaps impact associations with age, diagnosis, and cognitive performance Participants with higher WMH volumes had higher overlaps with GM volumes of bilateral caudate, cerebral cortex, putamen, thalamus, pallidum, and accumbens areas (p < 0001) When not corrected for WMHs, caudate volumes increased with age (p < 0001) and were not different between cognitively healthy individuals and age-matched probable Alzheimer's disease patients After correcting for WMHs, caudate volumes decreased with age (p < 0001), and Alzheimer's disease patients had lower caudate volumes than cognitively healthy individuals (p < 01) Uncorrected caudate volume was not associated with ADAS13 scores, whereas corrected lower caudate volumes were significantly associated with poorer cognitive performance (p < 0001) Presence of WMHs leads to systematic inaccuracies in GM segmentations, particularly for the caudate, which can also change clinical associations While specifically measured for the Freesurfer toolkit, this problem likely affects other algorithms
16 citations
References
More filters
TL;DR: A novel approach to correcting for intensity nonuniformity in magnetic resonance (MR) data is described that achieves high performance without requiring a model of the tissue classes present, and is applied at an early stage in an automated data analysis, before a tissue model is available.
Abstract: A novel approach to correcting for intensity nonuniformity in magnetic resonance (MR) data is described that achieves high performance without requiring a model of the tissue classes present. The method has the advantage that it can be applied at an early stage in an automated data analysis, before a tissue model is available. Described as nonparametric nonuniform intensity normalization (N3), the method is independent of pulse sequence and insensitive to pathological data that might otherwise violate model assumptions. To eliminate the dependence of the field estimate on anatomy, an iterative approach is employed to estimate both the multiplicative bias field and the distribution of the true tissue intensities. The performance of this method is evaluated using both real and simulated MR data.
4,613 citations
TL;DR: A fully automatic registration method to map volumetric data into stereotaxic space that yields results comparable with those of manually based techniques and therefore does not suffer the drawbacks involved in user intervention.
Abstract: Objective In both diagnostic and research applications, the interpretation of MR images of the human brain is facilitated when different data sets can be compared by visual inspection of equivalent anatomical planes. Quantitative analysis with predefined atlas templates often requires the initial alignment of atlas and image planes. Unfortunately, the axial planes acquired during separate scanning sessions are often different in their relative position and orientation, and these slices are not coplanar with those in the atlas. We have developed a completely automatic method to register a given volumetric data set with Talairach stereotaxic coordinate system. Materials and methods The registration method is based on multi-scale, three-dimensional (3D) cross-correlation with an average (n > 300) MR brain image volume aligned with the Talariach stereotaxic space. Once the data set is re-sampled by the transformation recovered by the algorithm, atlas slices can be directly superimposed on the corresponding slices of the re-sampled volume. the use of such a standardized space also allows the direct comparison, voxel to voxel, of two or more data sets brought into stereotaxic space. Results With use of a two-tailed Student t test for paired samples, there was no significant difference in the transformation parameters recovered by the automatic algorithm when compared with two manual landmark-based methods (p > 0.1 for all parameters except y-scale, where p > 0.05). Using root-mean-square difference between normalized voxel intensities as an unbiased measure of registration, we show that when estimated and averaged over 60 volumetric MR images in standard space, this measure was 30% lower for the automatic technique than the manual method, indicating better registrations. Likewise, the automatic method showed a 57% reduction in standard deviation, implying a more stable technique. The algorithm is able to recover the transformation even when data are missing from the top or bottom of the volume. Conclusion We present a fully automatic registration method to map volumetric data into stereotaxic space that yields results comparable with those of manually based techniques. The method requires no manual identification of points or contours and therefore does not suffer the drawbacks involved in user intervention such as reproducibility and interobserver variability.
3,357 citations
French Institute of Health and Medical Research1, Pierre-and-Marie-Curie University2, University of British Columbia3, UBC Hospital4, Beta5, Sahlgrenska University Hospital6, University of Virginia7, McGill University8, Brigham and Women's Hospital9, Washington University in St. Louis10, Vita-Salute San Raffaele University11, University College London12, University of Antwerp13, University of Geneva14, University of California, San Diego15, University of Kentucky16, Karolinska University Hospital17, university of lille18, University of California, San Francisco19, University of Nice Sophia Antipolis20, Brown University21, University of Paris22, Universidade Federal de Minas Gerais23, Maastricht University Medical Centre24, University of Southern California25, NewYork–Presbyterian Hospital26, VU University Amsterdam27, Lou Ruvo Brain Institute28
TL;DR: It is proposed that downstream topographical biomarkers of the disease, such as volumetric MRI and fluorodeoxyglucose PET, might better serve in the measurement and monitoring of the course of disease.
Abstract: In the past 8 years, both the International Working Group (IWG) and the US National Institute on Aging-Alzheimer's Association have contributed criteria for the diagnosis of Alzheimer's disease (AD) that better define clinical phenotypes and integrate biomarkers into the diagnostic process, covering the full staging of the disease. This Position Paper considers the strengths and limitations of the IWG research diagnostic criteria and proposes advances to improve the diagnostic framework. On the basis of these refinements, the diagnosis of AD can be simplified, requiring the presence of an appropriate clinical AD phenotype (typical or atypical) and a pathophysiological biomarker consistent with the presence of Alzheimer's pathology. We propose that downstream topographical biomarkers of the disease, such as volumetric MRI and fluorodeoxyglucose PET, might better serve in the measurement and monitoring of the course of disease. This paper also elaborates on the specific diagnostic criteria for atypical forms of AD, for mixed AD, and for the preclinical states of AD.
2,581 citations
TL;DR: White matter hyperintensities indicate an increased risk of cerebrovascular events when identified as part of diagnostic investigations, and support their use as an intermediate marker in a research setting.
Abstract: Objectives To review the evidence for an association of white matter hyperintensities with risk of stroke, cognitive decline, dementia, and death.
Design Systematic review and meta-analysis.
Data sources PubMed from 1966 to 23 November 2009.
Study selection Prospective longitudinal studies that used magnetic resonance imaging and assessed the impact of white matter hyperintensities on risk of incident stroke, cognitive decline, dementia, and death, and, for the meta-analysis, studies that provided risk estimates for a categorical measure of white matter hyperintensities, assessing the impact of these lesions on risk of stroke, dementia, and death.
Data extraction Population studied, duration of follow-up, method used to measure white matter hyperintensities, definition of the outcome, and measure of the association of white matter hyperintensities with the outcome.
Data synthesis 46 longitudinal studies evaluated the association of white matter hyperintensities with risk of stroke (n=12), cognitive decline (n=19), dementia (n=17), and death (n=10). 22 studies could be included in a meta-analysis (nine of stroke, nine of dementia, eight of death). White matter hyperintensities were associated with an increased risk of stroke (hazard ratio 3.3, 95% confidence interval 2.6 to 4.4), dementia (1.9, 1.3 to 2.8), and death (2.0, 1.6 to 2.7). An association of white matter hyperintensities with a faster decline in global cognitive performance, executive function, and processing speed was also suggested.
Conclusion White matter hyperintensities predict an increased risk of stroke, dementia, and death. Therefore white matter hyperintensities indicate an increased risk of cerebrovascular events when identified as part of diagnostic investigations, and support their use as an intermediate marker in a research setting. Their discovery should prompt detailed screening for risk factors of stroke and dementia.
1,842 citations
TL;DR: The histopathologic changes associated with incidental white matter signal hyperintensities on MRIs from 11 elderly patients are related to a descriptive classification for such abnormalities, and this classification appears to reflect both the different etiologies and severities of incidental MRI signal abnormalities, if it is modified to treat irregular periventricular and confluent deep white matter hyperintENSities together.
Abstract: We related the histopathologic changes associated with incidental white matter signal hyperintensities on MRIs from 11 elderly patients (age range, 52 to 82 years) to a descriptive classification for such abnormalities. Punctate, early confluent, and confluent white matter hyperintensities corresponded to increasing severity of ischemic tissue damage, ranging from mild perivascular alterations to large areas with variable loss of fibers, multiple small cavitations, and marked arteriolosclerosis. Microcystic infarcts and patchy rarefaction of myelin were also characteristic for irregular periventricular high signal intensity. Hyperintense periventricular caps and a smooth halo, however, were of nonischemic origin and constituted areas of demyelination associated with subependymal gliosis and discontinuity of the ependymal lining. Based on these findings, our classification appears to reflect both the different etiologies and severities of incidental MRI signal abnormalities, if it is modified to treat irregular periventricular and confluent deep white matter hyperintensities together.
1,441 citations