Neuroimaging standards for research into small vessel disease and its contribution to ageing and neurodegeneration: A united approach

Item does not contain fulltextCerebral small vessel disease (SVD) is a common accompaniment of ageing. Features seen on neuroimaging include recent small subcortical infarcts, lacunes, white matter hyperintensities, perivascular spaces, microbleeds, and brain atrophy. SVD can present as a stroke or cognitive decline, or can have few or no symptoms. SVD frequently coexists with neurodegenerative disease, and can exacerbate cognitive deficits, physical disabilities, and other symptoms of neurodegeneration. Terminology and definitions for imaging the features of SVD vary widely, which is also true for protocols for image acquisition and image analysis. This lack of consistency hampers progress in identifying the contribution of SVD to the pathophysiology and clinical features of common neurodegenerative diseases. We are an international working group from the Centres of Excellence in Neurodegeneration. We completed a structured process to develop definitions and imaging standards for markers and consequences of SVD. We aimed to achieve the following: first, to provide a common advisory about terms and definitions for features visible on MRI; second, to suggest minimum standards for image acquisition and analysis; third, to agree on standards for scientific reporting of changes related to SVD on neuroimaging; and fourth, to review emerging imaging methods for detection and quantification of preclinical manifestations of SVD. Our findings and recommendations apply to research studies, and can be used in the clinical setting to standardise image interpretation, acquisition, and reporting. This Position Paper summarises the main outcomes of this international effort to provide the STandards for ReportIng Vascular changes on nEuroimaging (STRIVE)

The Venular Side of Cerebral Amyloid Angiopathy: Proof of Concept of a Neglected Issue.

Small vessel diseases (SVD) is an umbrella term including several entities affecting small arteries, arterioles, capillaries, and venules in the brain. One of the most relevant and prevalent SVDs is cerebral amyloid angiopathy (CAA), whose pathological hallmark is the deposition of amyloid fragments in the walls of small cortical and leptomeningeal vessels. CAA frequently coexists with Alzheimer's Disease (AD), and both are associated with cerebrovascular events, cognitive impairment, and dementia. CAA and AD share pathophysiological, histopathological and neuroimaging issues. The venular involvement in both diseases has been neglected, although both animal models and human histopathological studies found a deposition of amyloid beta in cortical venules. This review aimed to summarize the available information about venular involvement in CAA, starting from the biological level with the putative pathomechanisms of cerebral damage, passing through the definition of the peculiar angioarchitecture of the human cortex with the functional organization and consequences of cortical arteriolar and venular occlusion, and ending to the hypothesized links between cortical venular involvement and the main neuroimaging markers of the disease

Perivascular spaces in the brain:anatomy, physiology and pathology

Perivascular spaces include a variety of passageways around arterioles, capillaries and venules in the brain, along which a range of substances can move. Although perivascular spaces were first identified over 150 years ago, they have come to prominence recently owing to advances in knowledge of their roles in clearance of interstitial fluid and waste from the brain, particularly during sleep, and in the pathogenesis of small vessel disease, Alzheimer disease and other neurodegenerative and inflammatory disorders. Experimental advances have facilitated in vivo studies of perivascular space function in intact rodent models during wakefulness and sleep, and MRI in humans has enabled perivascular space morphology to be related to cognitive function, vascular risk factors, vascular and neurodegenerative brain lesions, sleep patterns and cerebral haemodynamics. Many questions about perivascular spaces remain, but what is now clear is that normal perivascular space function is important for maintaining brain health. Here, we review perivascular space anatomy, physiology and pathology, particularly as seen with MRI in humans, and consider translation from models to humans to highlight knowns, unknowns, controversies and clinical relevance

The etiology and evolution of magnetic resonance imaging-visible perivascular spaces: Systematic review and meta-analysis

ObjectivesPerivascular spaces have been involved in neuroinflammatory and neurodegenerative diseases. Upon a certain size, these spaces can become visible on magnetic resonance imaging (MRI), referred to as enlarged perivascular spaces (EPVS) or MRI-visible perivascular spaces (MVPVS). However, the lack of systematic evidence on etiology and temporal dynamics of MVPVS hampers their diagnostic utility as MRI biomarker. Thus, the goal of this systematic review was to summarize potential etiologies and evolution of MVPVS.MethodsIn a comprehensive literature search, out of 1,488 unique publications, 140 records assessing etiopathogenesis and dynamics of MVPVS were eligible for a qualitative summary. 6 records were included in a meta-analysis to assess the association between MVPVS and brain atrophy.ResultsFour overarching and partly overlapping etiologies of MVPVS have been proposed: (1) Impairment of interstitial fluid circulation, (2) Spiral elongation of arteries, (3) Brain atrophy and/or perivascular myelin loss, and (4) Immune cell accumulation in the perivascular space. The meta-analysis in patients with neuroinflammatory diseases did not support an association between MVPVS and brain volume measures [R: −0.15 (95%-CI −0.40–0.11)]. Based on few and mostly small studies in tumefactive MVPVS and in vascular and neuroinflammatory diseases, temporal evolution of MVPVS is slow.ConclusionCollectively, this study provides high-grade evidence for MVPVS etiopathogenesis and temporal dynamics. Although several potential etiologies for MVPVS emergence have been proposed, they are only partially supported by data. Advanced MRI methods should be employed to further dissect etiopathogenesis and evolution of MVPVS. This can benefit their implementation as an imaging biomarker.Systematic review registrationhttps://www.crd.york.ac.uk/prospero/display_record.php?RecordID=346564, identifier CRD42022346564

Segmentation of perivascular spaces in 7 T MR image using auto-context model with orientation-normalized features

Quantitative study of perivascular spaces (PVSs) in brain magnetic resonance (MR) images is important for understanding the brain lymphatic system and its relationship with neurological diseases. One of major challenges is the accurate extraction of PVSs that have very thin tubular structures with various directions in three-dimensional (3D) MR images. In this paper, we propose a learning-based PVS segmentation method to address this challenge. Specifically, we first determine a region of interest (ROI) by using the anatomical brain structure and the vesselness information derived from eigenvalues of image derivatives. Then, in the ROI, we extract a number of randomized Haar features which are normalized with respect to the principal directions of the underlying image derivatives. The classifier is trained by the random forest model that can effectively learn both discriminative features and classifier parameters to maximize the information gain. Finally, a sequential learning strategy is used to further enforce various contextual patterns around the thin tubular structures into the classifier. For evaluation, we apply our proposed method to the 7T brain MR images scanned from 17 healthy subjects aged from 25 to 37. The performance is measured by voxel-wise segmentation accuracy, cluster- wise classification accuracy, and similarity of geometric properties, such as volume, length, and diameter distributions between the predicted and the true PVSs. Moreover, the accuracies are also evaluated on the simulation images with motion artifacts and lacunes to demonstrate the potential of our method in segmenting PVSs from elderly and patient populations. The experimental results show that our proposed method outperforms all existing PVS segmentation methods

Applied Clinical Neuroimaging in Cerebral Amyloid Angiopathy and Spontaneous Intracerebral Haemorrhage

Sporadic cerebral amyloid angiopathy is a common small vessel disease that preferentially involves small cortical and leptomeningeal arteries due to progressive amyloid-β deposition in their walls. Cerebral amyloid angiopathy occurs frequently in elderly people, and is a common and important cause of symptomatic lobar intracerebral haemorrhage and cognitive impairment. There is currently a growing interest in cerebral amyloid angiopathy, at least partly thanks neuroimaging, which now allows an unprecedented ability to investigate the disease dynamics in vivo using MRI to reveal complex patterns of cerebral bleeding and ischaemia. The detection of CAA during life is becoming an increasingly important challenge, since approaches of prevention or treatment (disease-modification) are now emerging as realistic possibilities. Determining the most promising treatments requires development of reliable biomarkers, the goal of my research. The main objective of this PhD thesis is to provide new insights into potential clinical and applied clinical neuroimaging biomarkers in patients with cerebral amyloid angiopathy. This is accomplished by a portfolio of research studies investigating: (a) the clinical and radiological spectrum of transient focal neurological episodes as a potential clinical clue for cerebral amyloid angiopathy; (b) cortical superficial siderosis, a distinct pattern on bleeding in the brain, as both a diagnostic and a prognostic marker of cerebral amyloid angiopathy; (c) MRI-visible perivascular spaces topography, as a new marker of small vessel disease and cerebral amyloid angiopathy; (d) potential pathological, neuroimaging and genetic differences in patients with pathology-proven CAA with and without intracerebral haemorrhage and presents evidence for different disease phenotypes; (e) the evidence whether the presence and burden of cerebral microbleeds on MRI scans is associated with an increased risk of recurrent spontaneous ICH, and if this risk is different according to MRI-defined microangiopathy subtype, in a meta-analysis

A critical guide to the automated quantification of perivascular spaces in magnetic resonance imaging

The glymphatic system is responsible for waste clearance in the brain. It is comprised of perivascular spaces (PVS) that surround penetrating blood vessels. These spaces are filled with cerebrospinal fluid and interstitial fluid, and can be seen with magnetic resonance imaging. Various algorithms have been developed to automatically label these spaces in MRI. This has enabled volumetric and morphological analyses of PVS in healthy and disease cohorts. However, there remain inconsistencies between PVS measures reported by different methods of automated segmentation. The present review emphasizes that importance of voxel-wise evaluation of model performance, mainly with the Sørensen Dice similarity coefficient. Conventional count correlations for model validation are inadequate if the goal is to assess volumetric or morphological measures of PVS. The downside of voxel-wise evaluation is that it requires manual segmentations that require large amounts of time to produce. One possible solution is to derive these semi-automatically. Additionally, recommendations are made to facilitate rigorous development and validation of automated PVS segmentation models. In the application of automated PVS segmentation tools, publication of image quality metrics, such as the contrast-to-noise ratio, alongside descriptive statistics of PVS volumes and counts will facilitate comparability between studies. Lastly, a head-to-head comparison between two algorithms, applied to two cohorts of astronauts reveals how results can differ substantially between techniques

Neuroimaging at 7 Tesla: a pictorial narrative review

Neuroimaging using the 7-Tesla (7T) human magnetic resonance (MR) system is rapidly gaining popularity after being approved for clinical use in the European Union and the USA. This trend is the same for functional MR imaging (MRI). The primary advantages of 7T over lower magnetic fields are its higher signal-to-noise and contrast-to-noise ratios, which provide high-resolution acquisitions and better contrast, making it easier to detect lesions and structural changes in brain disorders. Another advantage is the capability to measure a greater number of neurochemicals by virtue of the increased spectral resolution. Many structural and functional studies using 7T have been conducted to visualize details in the white matter and layers of the cortex and hippocampus, the subnucleus or regions of the putamen, the globus pallidus, thalamus and substantia nigra, and in small structures, such as the subthalamic nucleus, habenula, perforating arteries, and the perivascular space, that are difficult to observe at lower magnetic field strengths. The target disorders for 7T neuroimaging range from tumoral diseases to vascular, neurodegenerative, and psychiatric disorders, including Alzheimer’s disease, Parkinson’s disease, multiple sclerosis, epilepsy, major depressive disorder, and schizophrenia. MR spectroscopy has also been used for research because of its increased chemical shift that separates overlapping peaks and resolves neurochemicals more effectively at 7T than a lower magnetic field. This paper presents a narrative review of these topics and an illustrative presentation of images obtained at 7T. We expect 7T neuroimaging to provide a new imaging biomarker of various brain disorders

An assessment of small vessel disease in human post-mortem tissue through radiology and histology

Sporadic human cerebral small vessel disease (SVD) is a significant problem in our aging population. It is the most common cause of haemorrhagic stroke, causes one quarter of all ischaemic strokes, causes vascular dementia and synergistically worsens other dementias. It also causes a range of other psychological and physical problems and is increasingly common with increased age. SVD is well characterised on neuroimaging, with lesions throughout the brain, and particularly in the white matter. The cause(s) and pathophysiological mechanisms underlying the development of SVD, however, remain poorly understood with poor correlations between the abnormalities seen at the cellular level, on neuroimaging, and clinically. There are many theories as to the cause of SVD. However, observational studies and experimental evidence point towards an abnormality in the small vasculature of the brain initiating a cascade of events leading to a variety of vascular and brain parenchymal lesions. What these abnormalities are, and how exactly they result in the pathology seen, is unknown. Different structural components of the vessel wall and parenchymal brain cells appear to be involved, as well as functional abnormalities such as abnormal vascular reactivity. Risk factors also play a role, hypertension being the most significant, but how these interact with the normal vasculature is not fully understood. To provide an overview of our current understanding of SVD in human tissue I first completed a systematic review of the literature comparing the appearances of SVD on post-mortem imaging and histology. This revealed the inconsistency in methods and reporting in these studies and the lack of histopathology agreement on SVD terminology and definitions. I then studied the histological appearances of the lesions identified by post-mortem imaging to provide a reliable precise histological-imaging correlation. I developed a new protocol for ex vivo 7 Tesla magnetic resonance imaging (7T MRI) scanning of human brain tissue on post-mortem material and developed a grading system to assess SVD burden on MRI and histology with histological definitions, to try to encourage standardised, comprehensive and transparent reporting so that results in small studies can be more easily compared. I studied human post-mortem brain tissue to better investigate the disease in the appropriate context. In our cases from individuals with haemorrhagic SVD, normal aging and young controls, the most severe SVD pathology on ex vivo imaging and histology was, as expected, in the haemorrhagic SVD group. The normal aging group also had significant levels of pathology, perhaps representing the increasing burden of disease present but not necessarily detected clinically with increased age. It is possible the underlying pathophysiology in this group might develop by different mechanisms compared to the haemorrhagic group. Directly comparing the imaging and histological lesions confirmed the histological appearances of some lesions on imaging such as enlarged perivascular spaces, lacunes, microinfarcts and microbleeds. However, making direct comparisons is complex. Some lesions, such as small vessel fibrinoid necrosis, presumed to be below the resolution for detection on 7T MRI, were identified on both histology and imaging. Some features seen on histology in association with recognised SVD lesions, such as perivascular inflammation in an area of white matter rarefaction, were present in a variety of different histological contexts with no apparent correlation on imaging. And some lesions, such as white matter rarefaction around enlarged perivascular spaces, were present often on both imaging and histology, but their significance and contribution to SVD is unknown. To try to further understand the mechanisms underlying SVD and the lesions seen on imaging I undertook biochemical studies of protein expression in the deep white matter of the haemorrhagic SVD group, young controls and an Alzheimer’s disease group, who also have white matter pathology on neuroimaging. Increased fibrinogen levels suggested vascular leakage in both disease groups. However, haemorrhagic SVD had more severe white matter hypoxic changes and increased vasoconstrictor levels while in Alzheimer’s disease there was increased amyloid 42 and levels of a pericyte marker, possibly reflecting different pathophysiological mechanisms causing the similar appearing radiological changes. When assessing radiologically defined white matter hyperintensities (WMH) I found hypoxic-induced changes throughout brains with WMH, including in normal appearing areas of white matter. This suggests these brains have abnormalities in areas that appear radiologically normal, as found in in vivo imaging studies. To conclude, this work has confirmed the importance of reaching a consensus in histopathological reporting, terminology and definitions which is a basic requirement before we can better understand the pathophysiology of SVD. This has led to the formation of definitions and a practical grading system that could be used as a basis upon which to build a future agreement. The complexity of the histological lesions underlying radiological SVD changes was apparent, and the frequency with which some other potentially important histological changes were identified suggests these have not, to date, been fully appreciated. Investigating the underlying mechanisms of white matter hyperintensities showed vascular leakage was a shared abnormality in two different diseases with white matter changes on imaging, suggesting it may be a common factor upon which variable pathways converge. Future work is needed to further understand the importance of these less well characterised histological features. Investigating the role of vascular leakage and exploring drugs that maintain or improve vascular integrity could be a potential route for helping to treat SVD. Studies into underlying transcriptomic abnormalities around vascular leakage in human tissue may be informative