Cerebral Small Vessel Diseases: From Vessel Alterations to Cortical Parenchymal Injury

Editorial

14 February 2020

Editorial: Cerebral Small Vessel Diseases: From Vessel Alterations to Cortical Parenchymal Injury

Susanne J. van Veluw

Eric Jouvent

and

Andreas Charidimou

2,406 views

2 citations

Editors

Andreas Charidimou

Boston University

Eric Jouvent

Université Sorbonne Paris Cité

Susanne J. Van Veluw

Massachusetts General Hospital, Harvard Medical School

Impact

Forest plots of associations between the cerebral amyloid angiopathy score and specific cognitive domains. CI, confidence interval; CAA, cerebral amyloid angiopathy. Model 1: adjusted for age and sex. Model 2: adjusted for age, sex, hypertension, cholesterol, lipid lowering medication, history of atrial fibrillation, antithrombotic medication and APOE-ε2/ε4 carriership. (A) Executive function, (B) information processing speed, (C) memory, and (D) motor speed.

Original Research

06 December 2019

Application of an Imaging-Based Sum Score for Cerebral Amyloid Angiopathy to the General Population: Risk of Major Neurological Diseases and Mortality

Pinar Yilmaz

, 5 more and

Meike W. Vernooij

5,134 views

13 citations

Patient flow diagram. CNSR, China National Stroke Registry; ICH, intracranial hemorrhage; mRS, modified Ranking Scale.

Original Research

27 November 2019

Risk Profile of Ischemic Stroke Caused by Small-Artery Occlusion vs. Deep Intracerebral Hemorrhage

Zimo Chen

, 8 more and

Yongjun Wang

8,015 views

2 citations

Cerebral microbleeds distribution and markers of CAA in patients with mixed cerebral microbleeds. Prevalence of cortical superficial siderosis (A) and symptomatic lobar intracerebral hemorrhage (B) according to the ratio lobar/total CMB count (categorized by tertile). Increasing cerebral microbleeds ratio is associated with both cortical superficial siderosis (p = 0.03) and lobar intracerebral hemorrhage (p < 0.0001).

Original Research

23 October 2019

Underlying Small Vessel Disease Associated With Mixed Cerebral Microbleeds

Clemence Blanc

, 9 more and

Nicolas Raposo

5,117 views

24 citations

Case Report

23 September 2019

Cerebral Amyloid Angiopathy Related Inflammation With Prominent Meningeal Involvement. A Report of 2 Cases

Agnès Aghetti

, 6 more and

Stéphanie Guey

7,055 views

16 citations

Original Research

14 August 2019

Enlarged Perivascular Spaces and Cerebral Small Vessel Disease in Spontaneous Intracerebral Hemorrhage Patients

Xin Wang

, 3 more and

Xingquan Zhao

5,528 views

16 citations

Original Research

21 August 2019

Enhanced Effective Connectivity From Ipsilesional to Contralesional M1 in Well-Recovered Subcortical Stroke Patients

Yanmin Peng

, 3 more and

Chunshui Yu

4,645 views

16 citations

Original Research

12 August 2019

Correlation Between the Number of Lenticulostriate Arteries and Imaging of Cerebral Small Vessel Disease

Yuan-Chang Chen

, 4 more and

Yue-Hua Li

4,612 views

11 citations

Original Research

27 September 2019

Effects of Dabigatran in Mouse Models of Aging and Cerebral Amyloid Angiopathy

Neethu Michael

, 7 more and

Mark J. Fisher

3,157 views

12 citations

Distribution of mRS score at 90 days in all patients according to burden of small vessel disease. The percentage of participants with the mRS obtained at 90 days is shown in each cell. mRS, modified Rankin Scale; SVD, small vessel disease.

Original Research

06 August 2019

Total Small Vessel Disease Burden Predicts Functional Outcome in Patients With Acute Ischemic Stroke

Ying-chao Huo

, 8 more and

Xin-yue Qin

3,895 views

24 citations

$Top panel shows the water diffusion changes in tract-NAWM with distance to intersecting (tract-WMH) and nearby WMH. Boxplots of (A) fractional anisotropy (FA) and (B) mean diffusivity (MD) measurements averaged for all tracts. WMH measurements were only performed in tract-WMH. In all box plots, the boxes represent the lower and upper quartiles and the median measurement (thick line) for each group. Whiskers indicate the sample minimum and maximum, whereas the represented outliers (dots) differ from the lower and upper quartiles by more than 1.5 times the interquartile range. The bottom panel shows the model predicted water diffusion changes in tract-NAWM with distance from tract-WMH for (C) FA and (D) MD. The distance scale is logarithmic for easier visualization. Open circles show the predicted values for the WMH-tract contours, while red circles show the predicted values for the nearby-WMH contours.$