Dataset Information

White matter hyperintensities associated with progression of cerebral small vessel disease: a 7-year Chinese urban community study.

ABSTRACT: We aimed to explore the role of white matter hyperintensities (WMH) in progression of cerebral small vessel disease (CSVD) in an urban community in China over a period of 7 years, and to investigate associations between WMH volume (baseline and progression) and cognitive impairment. CSVD markers and neuropsychological tests at baseline and follow-up of 191 participants of the Shanghai Aging Study (SAS) were assessed. WMH volume were assessed by automatic segmentation based on U-net model. Lacunes, cerebral microbleeds (CMBs) and enlarged perivascular spaces (ePVS) were rated manually. Small vessel disease (SVD) score was rated as the total burden of CSVD markers. Global cognitive function and 5 main cognitive domains (memory, language, spatial construction, attention and executive function) were evaluated by neuropsychological tests. We performed multivariable linear regression and binominal logistic regression. Participants with higher baseline WMH volume developed more progression of WMH volume, increased risk of incident lacunes, incident CMBs, and ePVS progression. WMH (baseline and progression) were associated with decline of executive function. WMH were associated with progression of cerebral small vessel disease and decline of executive function in a Chinese urban community study over a period of 7 years.

SUBMITTER: Xia Y

PROVIDER: S-EPMC7244059 | biostudies-literature | 2020 May

REPOSITORIES: biostudies-literature

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White matter hyperintensities associated with progression of cerebral small vessel disease: a 7-year Chinese urban community study.

Xia Yiwei Y Shen Yi Y Wang Yi Y Yang Lumeng L Wang Yiqing Y Li Yu Y Liang Xiaoniu X Zhao Qianhua Q Wu Jianjun J Chu Shuguang S Liang Zonghui Z Wang Xiaoxiao X Qiu Bensheng B Ding Hansheng H Ding Ding D Cheng Xin X Dong Qiang Q

Aging 20200510 9

We aimed to explore the role of white matter hyperintensities (WMH) in progression of cerebral small vessel disease (CSVD) in an urban community in China over a period of 7 years, and to investigate associations between WMH volume (baseline and progression) and cognitive impairment. CSVD markers and neuropsychological tests at baseline and follow-up of 191 participants of the Shanghai Aging Study (SAS) were assessed. WMH volume were assessed by automatic segmentation based on U-net model. Lacune ...[more]

PMID: 32388497

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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:Cerebral white matter hyperintensities (WMHs) are central MRI markers of the brain aging process, but the mechanisms for its progression remain unclear. In this study, we aimed to determine whether the baseline serum cystatin C level represented one mechanism underlying WMH progression, and whether it was associated with the long-term progression of cerebral WMH volume in MRI. 166 consecutive individuals who were ≥50 years of age and who underwent initial/follow-up MRI evaluations within an interval of 34-45 months were included. Serum cystatin C level, glomerular-filtration rate (GFR), and other laboratory parameters were measured at their initial evaluation and at the end of follow-up. Cerebrovascular risk factors, medications, and blood-pressure parameters were also reviewed. WMH progression rate was measured by subtracting WMH volume at baseline from that at the follow-up using volumetric analysis, divided by the MRI intervals. At baseline, WMH volume was 9.61±13.17 mL, mean GFR was 77.3±22.8 mL/min, and mean cystatin C level was 0.92±0.52 mg/L. After 37.9±3.4 months, the change in WMH volume was 3.64±6.85 mL, the progression rate of WMH volume was 1.18±2.28 mL/year, the mean ΔGFR was 2.4±7.9 mL/min, and the mean Δcystatin C was 0.03±0.34 mg/L. The progression rate of WMH volume was linearly associated with cystatin C level (B coefficient = 0.856; 95% confidence interval [CI] 0.174-1.538; P = 0.014), along with the baseline WMH volume (B = 0.039; 95% CI 0.019-0.059; P<0.001), after adjusting for the conventional vascular risk factors, laboratory parameters, medication profiles, and GFR. Especially, patients with a baseline level of cystatin C ≥1.00 mg/L exhibited a much higher progression rate of WMH as compared with those with a baseline level of cystatin C <1.00 mg/L (1.60±1.91 mL/year vs. 0.82±1.63 mL/year, P = 0.010). We concluded that serum cystatin C level is independently associated with the long-term progression rate of the cerebral WMH volume. Therefore, serum cystatin C level might predict the progression of cerebral WMH.

Project description:Importance:White matter hyperintense lesions (WMHs) are highly prevalent in patients with reversible cerebral vasoconstriction syndrome (RCVS); however, their characteristics and underlying pathophysiology are unclear. Objective:To investigate the spatiotemporal distribution and pathomechanisms of WMHs in patients with RCVS. Design, Setting, and Participants:We prospectively recruited patients with RCVS over a 3-year period from January 2010 through December 2012 from the headache center or emergency department of Taipei Veterans General Hospital, Taipei, Taiwan, a 2947-bed national medical center. In total, 85 patients with RCVS were approached, of whom 4 declined to participate, 5 declined follow-up scans, 6 were lost to follow-up, and 5 had suboptimal images. Patients received serial isotropic 3-dimension fluid-attenuated inversion recovery sequence imaging (1-mm slice thickness) with a 3-T magnetic resonance imaging machine as well as transcranial and extracranial color-coded sonography on registration and during follow-ups (at 1 and 2 months, with variations adapting to clinical condition). Data were analyzed from January 2015 to May 2017. Main Outcomes and Measures:The fluid-attenuated inversion recovery lesion segmentation toolbox was used to segment WMHs automatically. The WMHs were classified as periventricular or deep and were segmented into 13 anatomical locations. The neuroimaging scientists who executed the program were blinded to clinical information. Vascular parameters, including the Lindegaard index (vasoconstriction severity), pulsatility index, and resistance index of the internal carotid artery, were independently collected for comparison. Results:Sixty-five patients with RCVS completed the study and underwent a total of 162 magnetic resonance imaging examinations. Of the 65 included patients, 58 (89%) were women, and the mean (SD) age was 50.1 (8.9) years. The total mean (SD) WMH load peaked at 3.2 (4.4) cm3 in the third week postonset and fell to 0.8 (0.6) cm3 in the fourth week. White matter hyperintensities were predominantly frontal and periventricular. White matter hyperintensity load correlated strongly with Lindegaard index during the second week of the disease course (r?=?0.908; P?<?.001) and also correlated with the pulsatility index and resistance index of the internal carotid artery. Conclusions and Relevance:White matter hyperintensities in patients with RCVS have a dynamic temporal evolution that parallels disease severity. The finding of partially reversible WMHs deserves attention and should be known by clinicians taking care of patients with RCVS. White matter hyperintensities in RCVS may be attributed, at least partially, to regional hypoperfusion and impaired dampening capacity to central pulsatile flow.

Dataset Information

White matter hyperintensities associated with progression of cerebral small vessel disease: a 7-year Chinese urban community study.

Publications

White matter hyperintensities associated with progression of cerebral small vessel disease: a 7-year Chinese urban community study.

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