Role of blood brain barrier failure in progression of cerebral small vessel disease: a detailed magnetic resonance imaging study
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Small vessel disease (SVD) is an important cause of stroke, cognitive decline, and age-related disability. The cause of SVD is unknown, increasing evidence from neuropathology and neuroimaging suggests that failure of the blood-brain barrier (BBB) precipitates or worsens cerebral SVD progression and its failure is associated with SVD features such as white matter hyperintensities (WMH), perivascular spaces (PVS) and lacunar infarcts. The BBB change mechanism may also contribute to other common disorders of ageing such as Alzheimer's disease (AD). Magnetic resonance imaging (MRI) has revolutionised our understanding of SVD features. The MRI contributes to better understanding of the SVD pathophysiology and their clinical correlates. The purpose of this project was to better understand the pathogenesis of SVD, which involves improved understanding of BBB structures and pathophysiology and accurate measurement of cerebral SVD imaging characteristics on MRI scans. We aimed to assess (1) structures related to the BBB and factors that affect the BBB; (2) efficient and consistent WMH measurement method; (3) effect of stroke lesions on WMH and cerebral atrophy progression; (4) development and optimisation of computational PVS measurement method; (5) the relationships between PVS and SVD, blood markers, and BBB permeability. Section one describes structures and pathophysiology of the BBB. I reviewed the BBB structural and functional components from the view of neurovascular unit, PVS, and junctional proteins. The PVS part was done in a systematic search. I also reviewed some common stimuli for BBB permeability including inflammation and ischemia. Ischemic triggers for the BBB permeability were summarized systematically. Based on the literatures above, I summarized changes in junctional proteins in ischemia, inflammatory pain and AD models. Section two describes accurate measurement of WMH progression and atrophy. I used data from 100 patients who participated in a stroke study about BBB permeability changes in lacunar versus cortical stroke. To find a most efficient and consistent WMH measurement method, we tested several computational methods and effect of common processing steps including bias field correction and intensity adjustment. To avoid the effect of artefacts, I did a systematic search about artefacts and tested methods of image segmentation to avoid WMH artefacts as much as possible. To investigate the effect of stroke lesions on WMH and atrophy progression, I did the WMH, atrophy segmentation and stroke lesion measurements in a subgroup of 46 patients with follow-up scans, and showed that stroke lesions distorted measurement of WMH and atrophy progression and should be excluded. Section three describes development and optimization of a computational PVS measurement method, which measures the count and volume for PVS based on a threshold method using AnalyzeTM software. We tested the observer variability and validated it by comparison with visual rating scores. We investigated the associations between PVS results with other SVD features (WMH, atrophy), risk factors (hypertension, smoking and diabetes), blood markers, and BBB permeability. In conclusion, MRI is a valuable tool for the investigation of cerebral SVD features and BBB permeability. Exclusions of artefacts and stroke lesions are important in accurate measurement of WMH. PVS are important features of BBB abnormalities, and they correlate and share risk factors with other SVD features, and they should be considered as a marker of SVD and BBB permeability. Further systematic histological and ultrastructural studies of BBB are desirable in understanding the BBB regarding to the different parts of the cerebral vascular tree.