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1.
Neuroimage ; 261: 119528, 2022 11 01.
Article in English | MEDLINE | ID: mdl-35914668

ABSTRACT

Cerebral small vessel disease (CSVD) is a major vascular contributor to cognitive impairment in ageing, including dementias. Imaging remains the most promising method for in vivo studies of CSVD. To replace the subjective and laborious visual rating approaches, emerging studies have applied state-of-the-art artificial intelligence to extract imaging biomarkers of CSVD from MRI scans. We aimed to summarise published computer-aided methods for the examination of three imaging biomarkers of CSVD, namely cerebral microbleeds (CMB), dilated perivascular spaces (PVS), and lacunes of presumed vascular origin. Seventy classical image processing, classical machine learning, and deep learning studies were identified. Transfer learning and weak supervision techniques have been applied to accommodate the limitations in the training data. While good performance metrics were achieved in local datasets, there have not been generalisable pipelines validated in different research and/or clinical cohorts. Future studies could consider pooling data from multiple sources to increase data size and diversity, and evaluating performance using both image processing metrics and associations with clinical measures.


Subject(s)
Artificial Intelligence , Cerebral Small Vessel Diseases , Biomarkers , Cerebral Small Vessel Diseases/complications , Cerebral Small Vessel Diseases/diagnostic imaging , Computers , Humans , Magnetic Resonance Imaging/methods
2.
Front Neurol ; 12: 640498, 2021.
Article in English | MEDLINE | ID: mdl-33746892

ABSTRACT

Lacunar strokes are a common type of ischemic stroke. They are associated with long-term disability, but the factors affecting the dynamic of the infarcted lesion and the brain imaging features associated with them, reflective of small vessel disease (SVD) severity, are still largely unknown. We investigated whether the distribution, volume and 1-year evolution of white matter hyperintensities (WMH), one of these SVD features, relate to the extent and location of these infarcts, accounting for vascular risk factors. We used imaging and clinical data from all patients [n = 118, mean age 64.9 (SD 11.75) years old] who presented to a regional hospital with a lacunar stroke syndrome within the years 2010 and 2013 and consented to participate in a study of stroke mechanisms. All patients had a brain MRI scan at presentation, and 88 had another scan 12 months after. Acute lesions (i.e., recent small subcortical infarcts, RSSI) were identified in 79 patients and lacunes in 77. Number of lacunes was associated with baseline WMH volume (B = 0.370, SE = 0.0939, P = 0.000174). RSSI volume was not associated with baseline WMH volume (B = 3.250, SE = 2.117, P = 0.129), but predicted WMH volume change (B = 2.944, SE = 0.913, P = 0.00184). RSSI location was associated with the spatial distribution of WMH and the pattern of 1-year WMH evolution. Patients with the RSSI in the centrum semiovale (n = 33) had significantly higher baseline volumes of WMH, recent and old infarcts, than patients with the RSSI located elsewhere [median 33.69, IQR (14.37 50.87) ml, 0.001 ≤ P ≤ 0.044]. But patients with the RSSI in the internal/external capsule/lentiform nucleus experienced higher increase of WMH volume after a year [n = 21, median (IQR) from 18 (11.70 31.54) ml to 27.41 (15.84 40.45) ml]. Voxel-wise analyses of WMH distribution in patients grouped per RSSI location revealed group differences increased in the presence of vascular risk factors, especially hypertension and recent or current smoking habit. In our sample of patients presenting to the clinic with lacunar strokes, lacunar strokes extent influenced WMH volume fate; and RSSI location and WMH spatial distribution and dynamics were intertwined, with differential patterns emerging in the presence of vascular risk factors. These results, if confirmed in wider samples, open potential avenues in stroke rehabilitation to be explored further.

3.
J Cereb Blood Flow Metab ; 41(6): 1219-1228, 2021 06.
Article in English | MEDLINE | ID: mdl-33023386

ABSTRACT

The etiology of cerebral small vessel disease (CSVD) is the subject of ongoing research. Although intracranial atherosclerosis (ICAS) has been proposed as a possible cause, studies on their relationship remain sparse. We used 7 T vessel wall magnetic resonance imaging (MRI) to study the association between intracranial vessel wall lesions-a neuroimaging marker of ICAS-and MRI features of CSVD. Within the SMART-MR study, cross-sectional analyses were performed in 130 patients (68 ± 9 years; 88% male). ICAS burden-defined as the number of vessel wall lesions-was determined on 7 T vessel wall MRI. CSVD features were determined on 1.5 T and 7 T MRI. Associations between ICAS burden and CSVD features were estimated with linear or modified Poisson regression, adjusted for age, sex, vascular risk factors, and medication use. In 125 patients, ≥1 vessel wall lesions were found (mean 8.5 ± 5.7 lesions). ICAS burden (per + 1 SD) was associated with presence of large subcortical and/or cortical infarcts (RR = 1.65; 95%CI: 1.12-2.43), lacunes (RR = 1.45; 95% CI: 1.14-1.86), cortical microinfarcts (RR = 1.48; 95%CI: 1.13-1.94), and total white matter hyperintensity volume (b = 0.24; 95%CI: 0.02-0.46). Concluding, patients with a higher ICAS burden had more CSVD features, although no evidence of co-location was observed. Further longitudinal studies are required to determine if ICAS precedes development of CSVD.


Subject(s)
Cerebral Small Vessel Diseases/complications , Cerebral Small Vessel Diseases/diagnostic imaging , Intracranial Arteriosclerosis/complications , Intracranial Arteriosclerosis/diagnostic imaging , Aged , Cross-Sectional Studies , Female , Humans , Magnetic Resonance Imaging/methods , Male , Middle Aged , Neuroimaging/methods
4.
Neurobiol Aging ; 84: 33-40, 2019 12.
Article in English | MEDLINE | ID: mdl-31479862

ABSTRACT

We estimated associations of subjective cognitive decline (SCD) with neuroimaging markers of dementia and cognitive functioning in patients with a history of vascular disease without objective cognitive impairment. Within the Second Manifestations of ARTerial disease-Memory, depression and aging study, 599 patients (62 ± 9 years) had 1.5 T brain magnetic resonance imaging and cognitive testing at the baseline and after 8 years of follow-up. Using multiple regression analyses, we estimated cross-sectional and longitudinal associations of SCD according to research criteria with volumes of total brain, hippocampus, white matter hyperintensities, and presence of lacunes and with memory, executive functioning, information processing speed, and working memory. SCD was associated with increased risk of lacunes at the baseline (relative risk = 1.48, 95% confidence interval: 1.03; 2.12) but not during follow-up. No significant associations with volumes of white matter hyperintensities, total brain, or hippocampus were observed. SCD was cross-sectionally associated with poorer executive functioning and speed but not during follow-up. More prospective studies are needed to further elucidate the relationship between SCD, brain imaging markers, and cognitive decline and the role of SCD in the preclinical stage of Alzheimer's disease.


Subject(s)
Brain/diagnostic imaging , Cognitive Dysfunction/physiopathology , Aged, 80 and over , Cognition , Cognitive Dysfunction/diagnostic imaging , Cognitive Dysfunction/etiology , Female , Humans , Male , Middle Aged , Vascular Diseases/complications
5.
Brain ; 142(4): 1009-1023, 2019 04 01.
Article in English | MEDLINE | ID: mdl-30859180

ABSTRACT

We report a composite extreme phenotype design using distribution of white matter hyperintensities and brain infarcts in a population-based cohort of older persons for gene-mapping of cerebral small vessel disease. We demonstrate its application in the 3C-Dijon whole exome sequencing (WES) study (n = 1924, nWESextremes = 512), with both single variant and gene-based association tests. We used other population-based cohort studies participating in the CHARGE consortium for replication, using whole exome sequencing (nWES = 2,868, nWESextremes = 956) and genome-wide genotypes (nGW = 9924, nGWextremes = 3308). We restricted our study to candidate genes known to harbour mutations for Mendelian small vessel disease: NOTCH3, HTRA1, COL4A1, COL4A2 and TREX1. We identified significant associations of a common intronic variant in HTRA1, rs2293871 using single variant association testing (Pdiscovery = 8.21 × 10-5, Preplication = 5.25 × 10-3, Pcombined = 4.72 × 10-5) and of NOTCH3 using gene-based tests (Pdiscovery = 1.61 × 10-2, Preplication = 3.99 × 10-2, Pcombined = 5.31 × 10-3). Follow-up analysis identified significant association of rs2293871 with small vessel ischaemic stroke, and two blood expression quantitative trait loci of HTRA1 in linkage disequilibrium. Additionally, we identified two participants in the 3C-Dijon cohort (0.4%) carrying heterozygote genotypes at known pathogenic variants for familial small vessel disease within NOTCH3 and HTRA1. In conclusion, our proof-of-concept study provides strong evidence that using a novel composite MRI-derived phenotype for extremes of small vessel disease can facilitate the identification of genetic variants underlying small vessel disease, both common variants and those with rare and low frequency. The findings demonstrate shared mechanisms and a continuum between genes underlying Mendelian small vessel disease and those contributing to the common, multifactorial form of the disease.


Subject(s)
Cerebral Small Vessel Diseases/genetics , High-Temperature Requirement A Serine Peptidase 1/genetics , Receptor, Notch3/genetics , Aged , Aged, 80 and over , Brain Ischemia/genetics , Cerebral Small Vessel Diseases/diagnostic imaging , Cerebral Small Vessel Diseases/metabolism , Cohort Studies , Female , Heterozygote , High-Temperature Requirement A Serine Peptidase 1/metabolism , Humans , Magnetic Resonance Imaging , Male , Middle Aged , Mutation , Polymorphism, Single Nucleotide , Receptor, Notch3/metabolism , Receptor, Notch3/physiology , Stroke/genetics , White Matter/diagnostic imaging , White Matter/metabolism , Exome Sequencing/methods
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