Dataset Information

Free-water diffusion MRI detects structural alterations surrounding white matter hyperintensities in the early stage of cerebral small vessel disease.

ABSTRACT: In cerebral small vessel disease (CSVD), both white matter hyperintensities (WMH) of presumed vascular origin and the normal-appearing white matter (NAWM) contain microstructural brain alterations on diffusion-weighted MRI (DWI). Contamination of DWI-derived metrics by extracellular free-water can be corrected with free-water (FW) imaging. We investigated the alterations in FW and FW-corrected fractional anisotropy (FA-t) in WMH and surrounding tissue and their association with cerebrovascular risk factors. We analysed 1,000 MRI datasets from the Hamburg City Health Study. DWI was used to generate FW and FA-t maps. WMH masks were segmented on FLAIR and T1-weighted MRI and dilated repeatedly to create 8 NAWM masks representing increasing distance from WMH. Linear models were applied to compare FW and FA-t across WMH and NAWM masks and in association with cerebrovascular risk. Median age was 64 ± 14 years. FW and FA-t were altered 8 mm and 12 mm beyond WMH, respectively. Smoking was significantly associated with FW in NAWM (p = 0.008) and FA-t in WMH (p = 0.008) and in NAWM (p = 0.003) while diabetes and hypertension were not. Further research is necessary to examine whether FW and FA-t alterations in NAWM are predictors for developing WMH.

SUBMITTER: Mayer C

PROVIDER: S-EPMC9441727 | biostudies-literature | 2022 Sep

REPOSITORIES: biostudies-literature

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Free-water diffusion MRI detects structural alterations surrounding white matter hyperintensities in the early stage of cerebral small vessel disease.

Mayer Carola C Nägele Felix L FL Petersen Marvin M Frey Benedikt M BM Hanning Uta U Pasternak Ofer O Petersen Elina E Gerloff Christian C Thomalla Götz G Cheng Bastian B

Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism 20220411 9

In cerebral small vessel disease (CSVD), both white matter hyperintensities (WMH) of presumed vascular origin and the normal-appearing white matter (NAWM) contain microstructural brain alterations on diffusion-weighted MRI (DWI). Contamination of DWI-derived metrics by extracellular free-water can be corrected with free-water (FW) imaging. We investigated the alterations in FW and FW-corrected fractional anisotropy (FA-t) in WMH and surrounding tissue and their association with cerebrovascular r ...[more]

PMID: 35410517

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Project description:Cerebral white matter hyperintensities on MRI are markers of cerebral small vessel disease, a major risk factor for dementia and stroke. Despite the successful identification of multiple genetic variants associated with this highly heritable condition, its genetic architecture remains incompletely understood. More specifically, the role of DNA methylation has received little attention. We investigated the association between white matter hyperintensity burden and DNA methylation in blood at ∼450 000 cytosine-phosphate-guanine (CpG) sites in 9732 middle-aged to older adults from 14 community-based studies. Single CpG and region-based association analyses were carried out. Functional annotation and integrative cross-omics analyses were performed to identify novel genes underlying the relationship between DNA methylation and white matter hyperintensities. We identified 12 single CpG and 46 region-based DNA methylation associations with white matter hyperintensity burden. Our top discovery single CpG, cg24202936 (P = 7.6 × 10-8), was associated with F2 expression in blood (P = 6.4 × 10-5) and co-localized with FOLH1 expression in brain (posterior probability = 0.75). Our top differentially methylated regions were in PRMT1 and in CCDC144NL-AS1, which were also represented in single CpG associations (cg17417856 and cg06809326, respectively). Through Mendelian randomization analyses cg06809326 was putatively associated with white matter hyperintensity burden (P = 0.03) and expression of CCDC144NL-AS1 possibly mediated this association. Differentially methylated region analysis, joint epigenetic association analysis and multi-omics co-localization analysis consistently identified a role of DNA methylation near SH3PXD2A, a locus previously identified in genome-wide association studies of white matter hyperintensities. Gene set enrichment analyses revealed functions of the identified DNA methylation loci in the blood-brain barrier and in the immune response. Integrative cross-omics analysis identified 19 key regulatory genes in two networks related to extracellular matrix organization, and lipid and lipoprotein metabolism. A drug-repositioning analysis indicated antihyperlipidaemic agents, more specifically peroxisome proliferator-activated receptor-alpha, as possible target drugs for white matter hyperintensities. Our epigenome-wide association study and integrative cross-omics analyses implicate novel genes influencing white matter hyperintensity burden, which converged on pathways related to the immune response and to a compromised blood-brain barrier possibly due to disrupted cell-cell and cell-extracellular matrix interactions. The results also suggest that antihyperlipidaemic therapy may contribute to lowering risk for white matter hyperintensities possibly through protection against blood-brain barrier disruption.

Project description:Objective: Reliable quantification of white matter hyperintensities (WHMs) resulting from cerebral small vessel diseases (CSVD) is essential for understanding their clinical impact. We aim to develop and clinically validate a deep learning system for automatic segmentation of CSVD-WMH from fluid-attenuated inversion recovery (FLAIR) imaging using large multicenter data. Method: A FLAIR imaging dataset of 1,156 patients diagnosed with CSVD associated WMH (median age, 54 years; 653 males) obtained between September 2018 and September 2019 from Beijing Tiantan Hospital was retrospectively analyzed in this study. Locations of CSVD-WMH on the FLAIR scans were manually marked by two experienced neurologists. Using the manually labeled data of 996 patients (development set), a U-shaped novel 2D convolutional neural network (CNN) architecture was trained for automatic segmentation of CSVD-WMH. The segmentation performance of the network was evaluated with per pixel and lesion level dice scores using an independent internal test set (n = 160) and a multi-center external test set (n = 90, three medical centers). The clinical suitability of the segmentation results, classified as acceptable, acceptable with minor revision, acceptable with major revision, and not acceptable, was analyzed by three independent neuroradiologists. The inter-neuroradiologists agreement rate was assessed by the Kendall-W test. Results: On the internal and external test sets, the proposed CNN architecture achieved per pixel and lesion level dice scores of 0.72 (external test set), and they were significantly better than the state-of-the-art deep learning architectures proposed for WMH segmentation. In the clinical evaluation, neuroradiologists observed the segmentation results for 95% of the patients were acceptable or acceptable with a minor revision. Conclusions: A deep learning system can be used for automated, objective, and clinically meaningful segmentation of CSVD-WMH with high accuracy.

Project description:BackgroundThe progression of FLAIR white matter hyperintensities (WMHs) on MRI heralds vascular-mediated cognitive decline. Even before FLAIR WMH progression, adjacent normal appearing white matter (NAWM) already demonstrates microstructural deterioration on diffusion tensor imaging (DTI). We hypothesized that elevated DTI free water (FW) would precede FLAIR WMH progression, implicating interstitial fluid accumulation as a key pathological step in the progression of cerebral small vessel disease.MethodsParticipants at least 3 months after an ischemic stroke or TIA with WMH on MRI underwent serial brain MRIs every 3 months over the subsequent year. For each participant, the WMHs were automatically segmented, serial MRIs were aligned, and a region of WMH penumbra tissue at risk was defined by dilating lesions at any time point and subtracting baseline lesions. Penumbra voxels were classified as either stable or progressing to WMH if they were segmented as new lesions and demonstrated increasing FLAIR intensity over time. Aligned DTI images included FW and FW-corrected fractional anisotropy (FATissue) and mean diffusivity (MDTissue). Logistic regression and area under the receiver-operator characteristic curve (AUC) were used to test whether baseline DTI predicted voxel-wise classification of stable penumbra or progression to WMH while covarying for clinical risk factors.ResultsIn the included participants (n = 26, mean age 71 ± 9 years, 31% female), we detected a median annual voxel-wise WMH growth of 2.9 ± 2.6 ml. Each baseline DTI metric was associated with lesion progression in the penumbra, but FW had the greatest AUC of 0.732 (0.730 - 0.733) for predicting voxel-wise WMH progression pooled across participants.DiscussionBaseline increased interstitial fluid, estimated as FW on DTI, predicted the progression of NAWM to WMH over the following year. These results implicate the presence of FW in the pathogenesis of cerebral small vessel disease progression.

Project description:Background and purposeThis study aimed to explore the correlation and causal relationship between fibrinogen, D-dimer, and the severity of cerebral white matter hyperintensity (MMH).MethodsA retrospective analysis of 120 patients with cerebral small vessel disease (CSVD) confirmed by head MRI attending the Third Affiliated Hospital of Beijing University of Traditional Chinese Medicine from August 2021 to February 2023 was performed. According to the Fazekas scale score, the patients were divided into 42 cases in the mild group, 44 cases in the moderate group, and 34 cases in the severe group. The levels of fibrinogen and D-dimer were compared among the three groups; the correlations between fibrinogen, D-dimer, and WMH severity were further analyzed; and independent risk factors for WMH severity were explored using the multivariate ordered logistic regression analysis. Furthermore, a two-sample Mendelian randomization (MR) analysis was performed to investigate the genetically predicted effect of fibrinogen and D-dimer on WMH.ResultsAs the severity of WMH increased, the levels of D-dimer and fibrinogen also gradually increased, and the results showed a positive correlational association, with significant differences within the groups (all p < 0.05); the multivariate ordered logistic regression model showed that after adjusting for the relevant covariates, D-dimer (OR = 5.998, 95% CI 2.213-16.252, p < 0.001) and fibrinogen (OR = 9.074, 95% CI 4.054-20.311, p < 0.001) remained independent risk factors for the severity of WMH. In the MR study, the random-effect inverse variance weighted (IVW) model showed that increased levels of genetically predicted D-dimer (OR, 1.01; 95% confidence interval 0.95-1.06; p = 0.81) and fibrinogen (OR, 1.91; 95% confidence interval 0.97-3.78; p = 0.06) were not associated with increased risk of WMH. The authors did not obtain strong evidence of a direct causal relationship between D-dimer, fibrinogen, and WMH.ConclusionIn this retrospective-based study, the authors found possible associations between D-dimer, fibrinogen, and WMH, but there was no obvious causal evidence. Further efforts are still needed to investigate the pathophysiology between D-dimer, fibrinogen, and WMH.

Dataset Information

Free-water diffusion MRI detects structural alterations surrounding white matter hyperintensities in the early stage of cerebral small vessel disease.

Publications

Free-water diffusion MRI detects structural alterations surrounding white matter hyperintensities in the early stage of cerebral small vessel disease.

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