Title:
Neuroimaging standards for research into small vessel disease and
its contribution to ageing and neurodegeneration: A united approach
STandards for ReportIng Vascular Changes on NEuroimaging
(STRIVE) v1
Authors:
*Joanna M Wardlaw MDa,b, Neuroimaging Sciences, Centre for Clinical Brain Sciences
and Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh,
Bramwell Dott Building, Western General Hospital, Crewe Road, Edinburgh EH4 2XU,
UK
*Eric E Smith MDc, Departments of Clinical Neurosciences and Radiology, Hotchkiss
Brain Institute, University of Calgary and Seaman Family MR Research Centre, Foothills
Medical Centre, Alberta Health Services, 1403 29th Street NW, Calgary, Alberta, T2N
2T9, Canada
Geert J Biessels MDd, Department of Neurology, G03.232, Rudolf Magnus Institute of
Neuroscience, UMC Utrecht, PO Box 85500, 3508 GA Utrecht, The Netherlands
Charlotte Cordonnier MDe, Univ Lille Nord de France, EA1046, Department of Neurology,
Lille University Hospital. Lille, France
1
Franz Fazekas MDf, Department of Neurology, Medical University of Graz,
Auenbruggerplatz 22, A-8036 Graz, Austria
Richard Frayne PhDg, Departments of Radiology, and Clinical Neurosciences, Hotchkiss
Brain Institute, University of Calgary and Seaman Family MR Research Centre, Foothills
Medical Centre, Alberta Health Services, 1403 29th Street NW, Calgary, Alberta, T2N
2T9, Canada
Richard I. Lindley MDh, University of Sydney and George Institute for Global Health,
Level 2 Clinical Sciences, Westmead Hospital C24, University of Sydney, Sydney, NSW
2006, Australia
John T O'Brien DMi, Department of Psychiatry, University of Cambridge, Box 189,
Addenbrooke's Hospital, Cambridge CB2 0QQ, UK
Frederik Barkhof MDj, Department of Radiology & Nuclear Medicine, VU University
Medical Centre, PO Box 7057 1007 MB Amsterdam The Netherlands
Oscar R Benavente MDk, Department of Medicine, Division of Neurology, Brain
Research Centre, University of British Columbia, 2211 Wesbrook Mall, Vancouver, BC
V6T 2B5, Canada
Sandra Black MDl, Sunnybrook Health Sciences Centre, 2075 Bayview Avenue, Room
A 421, Toronto, Ontario M4N 3M5, Canada
2
Carol Brayne PhDm, Cambridge Institute of Public Health, School of Clinical Medicine,
Forvie Site, Robinson Way, Cambridge CB2 0SR, UK
Monique Breteler MDn, German Center for Neurodegenerative diseases (DZNE),
Holbeinstrasse 13-15, 53175 Bonn, Germany
Hugues Chabriat MDo, Service de Neurologie, Hopital Lariboisiere, APHP; INSERM
U740; Université Denis Diderot Paris 7, France
Charles DeCarli MDp, University of California at Davis, Department of Neurology, 4860 Y
Street, Suite 3700, Sacramento, CA 95817, USA
Frank-Erik de Leeuw MDq, Radboud University Nijmegen Medical Center Donders
Institute for Brain Cognition & Behaviour, Center for Neuroscience Department of
Neurology PO Box 9101 6500HB Nijmegen, The Netherlands
Fergus Doubal PhDr, Brain Research Imaging Centre, University of Edinburgh, Bramwell
Dott Building, Western General Hospital, Crewe Road, Edinburgh EH4 2XU, UK
Marco Duering MDs , Institute for Stroke and Dementia Research, Klinikum der
Universität München, Marchioninistr. 15, 81377 München, Germany
3
Nick C Fox MDt, Department of Neurodegeneration, Institute of Neurology, University
College London, Dementia Research Centre, Box 16, Queen Square, London, WC1N
3BG, UK
Steven Greenberg MDu, Neurology, Massachusetts General Hospital, MGH Stroke
Research Center, 175 Cambridge Street, Suite 300, Boston, MA, USA
Vladimir Hachinski MDv, Department of Clinical Neurological Sciences, Western
University, 339 Windermere Road, London, Ontario N6A 5A5, Canada
Ingo Kilimann MDw, DZNE Rostock/Greifswald, Gehlsheimer Straße 20, 18147 Rostock,
Germany
Vincent Mok MDx, Division of Neurology, Department of Medicine and Therapeutics,
Prince of Wales Hospital, The Chinese University of Hong Kong
Robert van Oostenbrugge MDy, Department of Neurology, School of Mental Health and
Neuroscience and the Cardiovascular Research Institute Maastricht, Maastricht
University Medical Center, PO Box 5800, 6202 AZ, Maastricht, The Netherlands
Leonardo Pantoni MDz, Azienda Universitario Ospedaliera Careggi and NeuroFarBa
Department, University of Florence, Piazza di San Marco, 4 50121 Florence, Italy
4
Oliver Speck PhDaa, Department of Biomedical Magnetic Resonance, Faculty for Natural
Sciences, Institute for Experimental Physics, Otto-von-Guericke University Magdeburg,
Leipziger Str. 44, Haus 65, 39120 Magdeburg, Germany
Blossom CM Stephan PhDbb, Newcastle University, The Baddiley-Clark Building,
Richardson Road, Newcastle upon Tyne NE2 4AX, UK
Stefan Teipel MDcc, Department of Psychosomatic Medicine, University Medicine
Rostock, and DZNE Rostock, Gehlsheimer Str. 20, 18471 Rostock, Germany
Anand Viswanathan MDu, Massachusetts General Hospital Stroke Research Center,
Harvard Medical School, 175 Cambridge Street, Suite 300, Boston, MA 02114, USA
David Werring PhDdd, Stroke Research Group, Dept Brain Repair and Rehabilitation,
UCL Institute of Neurology, Queen Square, London WC1N 3BG, UK
Christopher Chen BM BChee, Yong Loo Lin School of Medicine, National University of
Singapore
Colin Smith MDff, Centre for Clinical Brain Sciences, University of Edinburgh,
Chancellor's Building, Edinburgh, EH16 4SB, UK
Mark van Buchem MDgg, Department of Radiology, Leiden University Medical Center,
PO Box 9600, 2300RC Leiden, The Netherlands
5
Bo Norrving MDhh, Department of Clinical Sciences, Section of Neurology Skåne
University Hospital, S-221 85 Lund, Sweden
Philp B Gorelick MDii, Saint Mary's Health Care, Hauenstein Neuroscience Center, 220
Cherry Street SE, Room H 3037, Grand Rapids, MI 49503, USA
*Martin Dichgans MDs, 1. Institute for Stroke and Dementia Research, Klinikum der
Universität München, Ludwig-Maximilians-University, Marchioninistr. 15, 81377
München, Germany; 2. German Center for Neurodegenerative Diseases (DZNE,
Munich), Schillerstraße 44, 80336 Munich, Germany; 3. Munich Cluster for Systems
Neurology (SyNergy), Munich, Germany
Correspondence: JM Wardlaw, Division of Neuroimaging Sciences, Western General
Hospital, Crewe Rd, Edinburgh, EH4 2XU, UK, tel +44 131 537 2943, fax +44 131 332
5150, email Joanna.wardlaw@ed.ac.uk
6
Abstract:
Cerebral small vessel disease (SVD) is a common accompaniment of ageing, whose
visible neuroimaging features include recent small subcortical infarcts, lacunes, white
matter hyperintensities, perivascular spaces, microbleeds and brain atrophy. SVD may
present as a stroke or cognitive decline, or may be asymptomatic or minimally
symptomatic, and frequently coexists with neurodegenerative disease where it may
exacerbate cognitive deficits, physical disabilities, and other symptoms arising from
neurodegeneration. The terminology and definitions used to describe imaging features
of SVD vary widely as do protocols for image acquisition and image analysis. This lack
of consistency obstructs progress in determining the contribution that SVD makes to the
pathophysiology and clinical expression of common neurodegenerative diseases.
Against this background, an International working group of the Centres of Excellence in
Neurodegeneration completed a structured process to develop definitions and imaging
standards for specific markers and consequences of SVD. The group was charged with
the following tasks: to i) provide a common advisory terminology and definitions for
imaging features of SVD visible on magnetic resonance (MR) imaging (MRI), ii) suggest
minimum standards for their image acquisition and analysis, iii) agree on standards for
scientific reporting of small-vessel-related changes on neuroimaging, iv) review
emerging imaging methods for detecting and quantifying preclinical manifestations of
SVD. Our findings apply to research studies and in addition can be used in the clinical
setting to standardise image interpretation, acquisition, and reporting.
This manuscript summarises the main outcomes of this international effort to provide the
STandards for ReportIng Vascular Changes on NEuroimaging (STRIVE).
7
Funding: Centres of Excellence in Neurodegeneration (COEN) concordat (United
Kingdom Medical Research Council, the German Center for Neurodegenerative Disease
[Deutsches Zentrum für Neurodegenerative Erkrankungen, DZNE], Germany) and the
Canadian Institutes of Health Research [CIHR, Canada]) reference COEN017; Royal
Society of Edinburgh; Scottish Imaging Network, a Platform for Scientific Excellence
(SINAPSE) Collaboration; UK Cross-Council Centre for Cognitive Ageing and Cognitive
Epidemiology, Edinburgh; Carl Friedrich von Siemens Foundation; Vascular Dementia
Research Foundation; NIHR Biomedical Research Unit in Dementia awarded to
Cambridge University Hospitals NHS Trust and the University of Cambridge; NIHR
Biomedical Research Unit in Dementia awarded to UCL Hospitals NHS Trust and UCL;
FP6 ERA-NET NEURON grant (01 EW1207); and Canadian Stroke Network.
8
Introduction
Neurodegenerative diseases such as Alzheimer’s disease (AD) commonly co-exist with
cerebrovascular disease in older people. Cerebral small vessel disease (SVD) is the
commonest vascular cause of dementia, the major contributor to mixed dementia, and is
the cause of at least a fifth of all strokes.1,2 AD and SVD share risk factors,3,4 both lead
to cognitive decline and dementia,5-7 and the clinical differentiation of AD from “vascular
cognitive impairment” or “vascular dementia” is recognised increasingly to be blurred.8
Visible manifestations of SVD on conventional MR imaging (MRI) include recent small
subcortical infarcts, white matter MR hyperintensities (WMH), lacunes, prominent
perivascular spaces (PVS), cerebral microbleeds (CMB) and atrophy.2 However, the
terms and definitions of these lesions have varied hugely across studies. 9,10 For
example, our systematic review of terms for WMH identified 1,144 instances of 50
different terms used to describe WMH among 940 publications; in some cases two
different terms were used within the same publication (table 1 and appendix). This
degree of variation in terms inhibits cross-study comparisons, and is a barrier to
research on the risk factors, pathophysiology, pathological correlations and clinical
consequences of these lesions. Indeed, the same lesions may be classified differently
across studies—for example, small cavities have been variably classified as either
perivascular spaces or lacunes by different definitions.9 Variable fates of acute SVDrelated lesions and convergence of aetiologically different lesions into similar
appearances on MRI (figure 1) adds to the difficulties in interpreting data from many
research reports. More standard terminology, definitions, image acquisition and analysis
methods across research centres would remove a major barrier to progress in the field.
9
Furthermore, such standardization could be adopted in clinical practice to improve our
ability to diagnose and understanding the cause of cognitive impairment in the elderly
Neuroimaging consensus standards for SVD classification were first proposed by the
U.S. National Institute of Neurological Disorders and Stroke (NINDS) and Canadian
Stroke Network (CSN) as part of standards for vascular cognitive impairment (VCI)
research.11 Subsequently, a scientific statement from the American Heart Association
incorporated neuroimaging evidence of SVD or stroke as part of “probable” criteria for
vascular mild cognitive impairment and dementia, and included a class II
recommendation for neuroimaging as part of the work-up for vascular cognitive
impairment.12
However,
neither
of
these
guidelines
provide
comprehensive
recommendations for the many neuroimaging manifestations of SVD, and neither reflect
recent advances in understanding the pathophysiology and measurement of SVD, a
rapidly changing field.
This international effort builds on prior initiatives to provide clear, scientifically rigorous,
evidence based, easy to apply definitions and terminologies for structural neuroimaging
features of SVD that avoid presuming mechanisms of pathogenesis, with examples to
facilitate improved standard use; minimum advisory standards for image acquisition;
standards for analysis of neuroimaging SVD and related features; and scientific
reporting standards to improve clarity of publications on SVD. The present standard
focuses on SVD. However other vascular lesions, including non-SVD-related ischemic
or haemorrhagic stroke, subarachnoid haemorrhage, subdural hematoma and vascular
10
malformations, can also contribute to cognitive impairment and dementia, especially
after stroke. These, and neuroimaging recommendations, are discussed in the appendix.
This manuscript summarises the resulting STandards for ReportIng Vascular Changes
on NEuroimaging (STRIVE). Our primary aim is to recommend standards for research
using MRI; however, many of the principles also apply to research using CT, and the
standards may also facilitate a more consistent approach to identifying neuroimaging
manifestations of SVD in clinical practice.
Methods
In 2011, the United Kingdom Medical Research Council, the German Center for
Neurodegenerative Disease (DZNE, Germany) and the Canadian Institutes of Health
Research (CIHR, Canada) issued a call for proposals under a funding concordat the
Centres of Excellence in Neurodegeneration (COEN) which aimed to accelerate
progress in understanding the pathogenesis of neurodegeneration (www.coen.org).13
This provided funding for a working group of experts to establish standards for
neuroimaging in SVD.
The core group of experts was convened in Edinburgh in March 2012. These experts
were identified by three study co-chairs (JW, MD and EES) based on location in a
COEN-affiliated Centre, supplemented by representatives from active research groups
in SVD neuroimaging in non-COEN participant countries. The group included experts in
neurology, neuroradiology, neuroepidemiology, psychiatry, geriatrics, stroke, medical
imaging physics and neuropathology. The working method was based on the Delphi
11
principle, with workshops at the beginning and end of the project and interim work
packages (details in appendix). A template focused the discussion on achieving a
consensus in key areas: terminology, definitions, image acquisition, image analysis, and
reporting standards. The group endorsed a key principle that terms and definitions
should reflect imaging characteristics as descriptively as possible, avoiding unfounded
presumptions of mechanism or pathological correlation not well supported by the
scientific literature, so as not to inhibit future studies of the pathophysiology of SVD.
Subsequently, working groups were assigned to develop standards for each of six key
lesion types, following established principles for guideline development published by the
equator
network
(http://www.equator-network.org/).
Systematic
searches
were
conducted to identify relevant literature (appendix). The entire group reconvened in
Munich in November 2012 to present draft standards from each working group for
discussion and revision, with additional review and comment from six external advisors
newly invited to the process. This consensus document was drafted and revised with
input from all workshop members. The final manuscript document was reviewed and
endorsed by all participants.
For each of six key SVD lesion types, we describe the context, terminology and
definitions. Image acquisition, image analysis and reporting standards for SVD-related
lesions are described thereafter. We also comment on haemorrhage as a component of
SVD and other vascular lesions as these may contribute to dementia (appendix). We
discussed size limits for perforating arteries and arterioles to determine the correct term,
but found these to be highly variable in the literature and not well translated to their
appearance on imaging. We therefore decided to use the term ‘arteriole’ to refer to small
12
perforating arteries/arterioles that are affected in SVD. Example images of the key SVD
lesion types are given in figure 2, with further details in the appendix. These standards
are expected to reliably classify most neuroimaging manifestations of SVD; however, we
acknowledge that individual investigator judgment may be required to classify
ambiguous lesions on the borderline between clear cut categories (appendix), and that
clinical judgment may be even more necessary when using these standards in clinical
practice.
Context, terminology and definitions of individual imaging features of SVD
Recent small subcortical infarcts
Context: Clinically evident recent small subcortical infarcts (SSI), frequently referred to
clinically as “lacunar stroke” or “lacunar syndrome”, cause about 25% of all ischaemic
strokes (figure 2). Occasionally, a recent asymptomatic SSI may be identified
serendipitously on imaging,14,15 and referred to as a ‘silent cerebral infarct’. Conversely,
for as yet unexplained reasons, symptomatic lacunar stroke syndromes may not be
accompanied by visible SSI in up to 30% of cases, 16 indicating that MRI is not perfectly
sensitive for recent SSI. Additionally, more recent work demonstrates that SSI may have
variable fates, evolving into either a lacunar cavity, a T2 hyperintensity without apparent
cavitation, or may disappear leaving little visible consequence on conventional MRI
(figure 1). Estimates of the proportion of recent SSI that cavitate range from 28%17 to
94%.18
Limited pathological correlation studies suggest that SSI may be associated with small
artery occlusion, although the aetiopathogenesis of SSI is unclear. SSI occur in the
13
perfusion territory of a small artery or arteriole penetrating into the internal part of the
brain. MRI studies suggest that recent SSI may exceed 15 mm axial diameter (the usual
size limit for lacunes of presumed vascular origin, see below) in the acute phase and
can range up to approximately 20 mm on axial sections. MRI also shows that SSI and
lacunes may exceed 20 mm in length when measured in the coronal or sagittal plane
(appendix).
Terminology: A sampling of 641 abstracts and a prior systematic review9 identified 159
different terms for recent SSI; the commonest terms included lacunar infarcts, lacunar
infarctions and lacunar strokes (appendix). We propose the new consensus term recent
small subcortical infarct (rSSI), dropping the term “lacunar” because of emerging
evidence that not all small subcortical infarcts become lacunes (i.e. cavities).17,18
Definition: We propose that recent small subcortical infarct should refer to neuroimaging
evidence of recent infarction in the territory of a single perforating arteriole with imaging
features or correlating clinical symptoms consistent with a lesion occurring in the last
few weeks (table 2). “Recent” should refer to lesions with symptoms or imaging features
suggesting that they occurred within the last few weeks and is used instead of ‘acute’ to
reflect the first few weeks not just the hyperacute stage. “Small” indicates a lesion that
should generally be less than 20 mm maximum diameter in the axial plane, although it is
acknowledged that some lesions that appear to represent infarction in the territory of a
single vessel could be somewhat larger in the coronal plane (appendix).19 Additional
research is required to determine the upper size limits more precisely. Lesions in the
basal ganglia and internal capsule that are larger and appear to represent infarction in
14
multiple penetrating arteries simultaneously should not be classified as SSI, rather as
the aetiologically distinct subtype of infarction, striatocapsular infarct.20 Similarly, anterior
choroidal artery infarcts are also aetiologically distinct, identifiable by their location (in
the caudate nucleus head) and shape (usually ‘comma’ shaped) so should not be
classified as SSI. There is no lower size limit for SSI, in contrast to lacunes of presumed
vascular origin, because positive diffusion-weighted images (DWI) allow discrimination
of small recent infarcts from perivascular spaces. MR signal characteristics of rSSI are
given in figure 2.
Lacunes of presumed vascular origin
Context: Miller Fisher wrote concerning pathology: “Historically, the original small vessel
disease feature was the ’lacune‘ (hole) which derived from French for a small fluid-filled
cavity that was thought to mark the healed stage of a small deep brain infarct. The term
was adopted into English. By a process of medico-linguistic evolution, the precavitary
phase became the lacunar infarct, the associated clinical entity became the lacunar
stroke and the neurological features became the lacunar syndrome”. 21 Lacunes are
commonly seen on imaging in asymptomatic elderly and are associated with an
increased risk of stroke, gait impairment and dementia.22-25 Most lacunes are presumed
to result from SSI, symptomatic or silent; however, some may represent the sequelae of
small deep haemorrhages (figure 1).26
Terminology: A systematic review identified more than 100 terms that have been used to
describe lacunes of presumed vascular origin (appendix); commonly used terms
included “lacune”, “lacunar stroke” and “silent brain infarct”. We propose the new term
15
lacune of presumed vascular origin, which discriminates small cavitated lesions of
presumed vascular origin from other small brain cavities, and accommodates the fact
that there may be some uncertainty regarding ischemic or hemorrhagic origin of the
lesion when imaging in the acute phase is unavailable, as is commonly the case.
Definitions: We define a lacune of presumed vascular origin as a round or ovoid,
subcortical, fluid filled (similar signal to CSF) cavity between 3 and about 15 mm in
diameter, compatible with a previous acute small deep brain infarct or haemorrhage in
the territory of a single perforating arteriole (table 2). MRI signal characteristics are given
in figure 2. On fluid-attenuated inversion recovery (FLAIR) images, lacunes of presumed
vascular origin usually have central CSF-like hypointensity with a surrounding rim of
hyperintensity although the rim is not universal and a hyperintense rim may also
surround PVS when passing through a WMH. In some cases the central cavity fluid may
not be suppressed on FLAIR, such that the lesion appears entirely hyperintense on
FLAIR despite clearly showing CSF-like intensity on other sequences such as T1weighted (T1-w) and T2-weighted (T2-w).18 Lacunes of presumed vascular origin should
be distinguished from perivascular spaces (PVS). Although pathological studies show
that there is no absolute size cut-off, lesions <3 mm in diameter are more likely to be
PVS than lacunes (appendix) and therefore we recommend the continued use of this
size criterion to discriminate the two lesion types, consistent with prior studies. 27,28 The
maximum size of 15 mm was chosen to reflect the generally smaller size of old versus
recent infarcts due to tissue loss and ex-vacuo effect in the former and swelling in the
latter, but we recognise that there is little objective data to support this size boundary
and that more research is required.
16
White matter hyperintensities of presumed vascular origin
Context: White matter lesions marked by usually
bilateral and largely symmetrical
hyperintensities on T2-w images are common in older subjects. They are strongly
associated with cerebrovascular disease and vascular risk factors,29 although their
pathogenesis is poorly understood and may be multifactorial. 30 WMH are associated
with covert neurological and cognitive symptoms and physical difficulties such as gait
disturbance.31-35 Hyperintensities may be present in subcortical gray matter structures,
such as the basal ganglia as well, and have sometimes been analyzed together with
WMH. They may also be present in the brainstem. Some studies have distinguished
between perivascular and deep WMH (appendix) in analysis, with the suggestion, as yet
the subject of debate, that they may have different pathogenesis, risk factors and clinical
consequences. Many studies analyze total WMH.
Terminology: A systematic review of 940 abstracts identified 50 different terms for WMH;
the commonest terms were leukoaraiosis, white matter lesions, white matter
hyperintensities, leukoencephalopathy (usually in the context of CADASIL) and white
matter disease (table 1; appendix). Leukoaraiosis is a descriptive term for reduced x-ray
attenuation seen on CT,36 subsequently adopted to denote hyperintensity on T2-w and
FLAIR, sometimes also hypointensity on T1-w MR images (appendix), reflecting a
situation in which radiological preceded pathological description. We propose the term
white matter hyperintensity of presumed vascular origin (WMH) to exclude white
matter lesions from other diseases such as multiple sclerosis or leukodystrophies.
17
Definitions: MRI signal characteristics of white matter hyperintensities of presumed
vascular origin (WMH) are provided in figure 2. On T1-w sequences WMH may appear
iso- or hypointense depending on the sequence (and severity of pathology), although
the hypointensity should not approach that of CSF (table 2; appendix). Opinion was
divided regarding whether gray matter hyperintensities or brainstem hyperintensities
should be classified routinely as “WMH”, as some studies have done. The consensus
opinion was that lesions in the subcortical gray matter or brainstem are not included into
the WMH category unless explicitly stated; the use of the term “subcortical
hyperintensities” was endorsed as an acceptable alternative collective term to refer to
any non-cortical hyperintensities including those in white matter, deep gray matter and
brainstem. In the context of CT scanning, the term ‘white matter hypoattenuation’ or
‘white matter hypodensities’ can be substituted, reflecting their appearance on CT
Perivascular spaces
Context: Perivascular spaces (PVS) constitute an extension of the extracerebral fluid
spaces around arteries, arterioles, veins and venules as they course from the brain
surface into and through the brain parenchyma and are variably followed by sheets of
leptomeninges (figure 2).37 PVS are most often microscopic and thus not visible by
conventional neuroimaging, but larger ones tend to become increasingly apparent with
increasing age especially at the base of the brain.38 A more general enlargement of PVS
has been associated with other morphologic features of small vessel disease such as
white matter hyperintensities39 and lacunes,40 but not atrophy.41 The clinical significance
of having numerous visible PVS is still controversial and they should therefore not be
18
termed “lesions”; however, emerging evidence associates more prominent PVS with
worse cognitive function.42
Terminology: Synonymous terms for PVS include “Virchow-Robin Space” (VRS),40 “type
3 lacune”,43 or (when predominantly in the basal ganglia) état crible.38 Numerous terms
such as large’, ‘dilated’, ‘large dilated’ or ‘enlarged’ ‘VRS’ or ‘PVS' have also been used
to describe visible PVS.38,41,42,44-48 These were not considered appropriate because the
relationship between PVS size and clinical consequences is not well understood, and
because the visibility of PVS depends on MR sequence characteristics which vary
across studies, therefore visibility alone cannot be a uniform criterion for pathologically
enlarged PVS. We therefore recommend the consensus term perivascular space
(PVS).
Definitions: Perivascular spaces (PVS) are defined as fluid-filled spaces, which follow
the typical course of a vessel penetrating/traversing the brain through gray or white
matter; with signal intensity similar to CSF on all sequences (figure 2); because they
follow the course of penetrating vessels, they will appear linear when imaged parallel to
the course of the vessel and round or sometimes ovoid shape with a diameter
commonly not exceeding 2 mm when imaged perpendicular to the course of the vessel
(table 2; appendix). At high resolution, a central vessel may occasionally be seen
coursing through the centre of the PVS, possibly differentiating them from lacunes. PVS
tend to be most prominent in the inferior basal ganglia, may also be seen coursing
centripetally through the hemispheric white matter and in the midbrain, but are rarely if
19
ever seen in the cerebellum. They may exhibit focal enlargement, and can be
particularly enlarged (up to 10-20 mm even with mass effect) in the inferior basal ganglia.
PVS must be discriminated from small lacunes of presumed vascular origin (appendix).
In contrast to lacunes, PVS usually do not exceed a diameter of 2 mm as confirmed
pathologically,49,50 and do not have a T2 hyperintense rim around the fluid filled space
on T2w or FLAIR imaging, unless they happen to be coursing through an area of
WMH.51
Cerebral Microbleeds
Context: Microbleeds are small hypointense lesions on paramagnetic sensitive MR
sequences such as T2*-weighted gradient-recalled echo (GRE) or susceptibilityweighted sequences, and are most frequently located in the cortico-subcortical junction,
deep grey or white matter in the cerebral hemispheres, brainstem and cerebellum (figure
2). Pathologically, the few correlative studies30,52,53 suggest that the MR-visible lesions
correspond to haemosiderin-laden macrophages in perivascular tissue consistent with
vascular leakage of blood cells.52,54-56 Cerebral microbleeds are associated with SVD
and Alzheimer’s disease.57,58 The presence or absence of strictly lobar microbleeds has
been incorporated into research criteria for cerebral amyloid angiopathy (CAA). 59
Originally thought to be asymptomatic markers of SVD, emerging studies demonstrate
associations with cognitive impairment although the mechanisms of the association,
including whether microbleeds directly damage the brain and cause dysfunction, are not
well understood. Recommendations for microbleed imaging and reporting have been
recently published, and we endorse the use of these standards.60 When microbleeds
occur in the context of AD or beta-amyloid immunotherapies they have been termed
20
amyloid-related imaging abnormalities-haemorrhage (ARIA-H). A consensus group
convened by the Alzheimer’s Association has recently published standards for
assessing microbleeds in this specific clinical context,61 and we endorse the use of
these guidelines as well.
Terminology: A literature search revealed 387 instances of 20 different terms for
microbleeds in 370 abstracts (appendix). Microbleed was by far the commonest term,
followed by ‘cerebral microbleed’ and then ‘brain microbleed’. We propose the
consensus term cerebral microbleed.
Definitions: Cerebral microbleeds (CMB) are visualised as small (usually 2-5 mm or
sometimes 10 mm in diameter) areas of signal void with associated “blooming” on T2* or
other MR sequences sensitive to susceptibility effects,57,60 (table 2) that are generally
not visualised on CT or on FLAIR, T1-w- or T2-w MR sequences. On T2*-weighted (T2*w) gradient-recalled echo (GRE) images, they are well defined, of homogeneous low
signal, either round or oval, in shape (figure 2). Because the blooming artifact, and
therefore the visualized size, depends on MR field strength and sequence we do not
recommend an absolute criteria for size. On 1.5 and 3T GRE, CMB are usually 2-5 mm,
but can range up to 10 mm in diameter. Hypointensities less than 2 mm, which could
represent signal loss over only a single voxel, should be regarded as questionable on
MRI at 1.5T because such small hypointensities could be artifactual. Susceptibilityweighted imaging (SWI) may also be used to assess CMBs. Emerging quantitative
based methodologies (i.e., quantitative susceptibility mapping, QSM) require more
evaluation, but may provide improved methods for CMB assessment. Several lesions or
21
structures may mimic cerebral microbleeds and should be considered, including
calcification, normal vessels seen in cross-section, iron deposits from other causes,
haemorrhagic metastases (e.g. melanoma), and diffuse axonal injury (e.g. after head
trauma).60 CMB may be differentiated from old small deep spontaneous intracerebral
haemorrhage because, in general, the latter may be larger, irregular with a cystic cavity
(figure 1), and will be usually be visualised on T1-w, and T2-w or FLAIR imaging.
Other haemorrhagic lesions
The consensus group discussed two other haemorrhagic manifestations of SVD worthy
of mention: intracerebral haemorrhage and superficial cortical siderosis (appendix).
Intracerebral haemorrhage (ICH) may be a manifestation of SVD62 or may be secondary
to other causes such as vascular malformations. The consensus term spontaneous
ICH presumed due to SVD was suggested, as opposed to secondary ICH from other
causes or traumatic ICH. Comprehensive guidelines for the diagnosis and management
of ICH have been published previously. In the context of studying SVD, we promote
research to disentangle the contribution of different vascular diseases to ICH; in the
meantime, we recommend that lobar ICHs, which may be caused by CAA, should be
distinguished from non-lobar ICHs, which are thought generally not to be caused by
CAA and are mostly attributed to perforating arteriolar vasculopathy.63,64 A small study
suggested good, but not perfect, inter-rater agreement on the site of origin of ICH.65 The
Boston criteria for CAA should be considered for use in assigning the likelihood of
underlying CAA in patients with lobar ICH.59
22
We propose the consensus term superficial cortical siderosis to refer to neuroimaging
evidence of chronic blood products in the superficial cortex just below the pia.
Superficial cortical siderosis may be a chronic consequence of subarachnoid bleeding or
may result from other causes of very superficial cortical bleeding, including vascular
malformations, CAA,66 spinal dural defects, or may be idiopathic.66,67 It is visible as
linear hypointensity overlying the cortex on T2* GRE or other blood-sensitive sequences.
It may be mimicked by petechial cortical haemorrhagic transformation of an infarct.
Revised research criteria for CAA incorporate the presence of superficial cortical
siderosis as another haemorrhagic manifestation of CAA, equivalent to a lobar ICH. 66
The location of the siderosis (the number of sulci involved 66 and in which lobes) should
be described.
Brain Atrophy
Context: Brain atrophy can be generalized or focal (affecting only particular lobes or
specific brain regions, e.g. the hippocampus), symmetrical or asymmetrical or tissue
selective (affecting a certain tissue class, e.g. white matter) and occurs in many
conditions. The pathological changes that underlie atrophy are heterogeneous and do
not necessarily reflect neuronal loss.68-70 Brain atrophy accompanies normal ageing to a
varying extent. In the context of vascular disease and dementia, the neuropathological
substrate of atrophy includes neuronal loss,71 cortical thinning, subcortical vascular
pathology with white matter rarefaction and shrinkage, arteriolosclerosis, venous
collagenosis and secondary neurodegenerative changes.72,73 Many imaging studies
have observed an association between presence and severity of SVD and brain atrophy,
including global atrophy as well as atrophy of the corpus callosum, central atrophy (with
23
increased ventricular size and atrophy of the basal ganglia), mesencephalic atrophy,
hippocampal atrophy, and focal cortical thinning in brain regions connected to
subcortical infarcts (figure 3).74,75 Vascular lesions should therefore be considered in
studies that focus on atrophy and conversely, atrophy is an important measure in
imaging studies that assess the burden of vascular damage in the brain and mediates at
least partially the effects of vascular lesions on cognition.76-78
Terminology: A systematic review of literature on SVD and atrophy revealed use of
multiple synonymous terms including “atrophy”, “brain volume”, “volume loss” and others.
We propose the consensus term brain atrophy. We also propose that studies should
use unambiguous terms regarding whether the atrophy assessment was cross-sectional
or longitudinal, and avoid the use of terms such as “accelerated atrophy” or “brain
volume loss” in cross-sectional studies, in favour of “more atrophy” or “lower brain
volume”. When discussing atrophy, investigators should be clear regarding which brain
volumes have been measured and should consider including the brain subregion in their
description- e.g. hippocampal atrophy.
Definitions (table 2): We define ‘brain atrophy’ in the context of SVD, operationalised
through imaging, as lower brain volume, not related to a specific macroscopic focal
injury such as trauma or infarction. Tissue loss is often inferred from enlargement of
peripheral (sulcal) and central (ventricular) cerebrospinal fluid (CSF) spaces in relation
to the intracranial volume and other measures (figure 3). However, in the strict sense
such assumption would require longitudinal observation. Tissue loss resulting from
discrete focal lesions, such as cortical infarcts, is more easy to substantiate cross24
sectionally and should not be confused with generalised global or regional brain atrophy
likely secondary to a diffuse process.
Other vascular lesions
These consensus standards are focused on SVD. However, there are other vascular
lesions that may be seen particularly in the elderly subjects and in subjects with
cognitive impairment. They include non-SVD-related ischemic stroke, ICH from non-SVD
causes, subarachnoid haemorrhage, subdural hematoma, vascular malformations and
larger arterial ischaemic disease. These are described in detail in the online appendix.
Advisory minimum standards for imaging of SVD
Image acquisition standards and parameters (table 3)
For both routine clinical and research uses, if there are no contraindications then MR is
preferred to CT as MR has higher sensitivity and specificity for detecting most
manifestations of SVD. Field strength of 3T may be preferred, but modern 1.5T is often
of as high definition,79 is acceptable and may be more widely available, an important
consideration for multicenter studies. Regardless, imaging sequences should be
optimized for field strength and scanner configuration. If CT is used in SVD, then a thin
section volume sequence without contrast covering the whole brain on a brain
parenchymal algorithm and axial 5 mm reconstructions should be obtained. However, in
general, CT is no longer recommended except possibly in large scale epidemiological
studies or where MR imaging is not available or too expensive.
25
For MR imaging, the minimum acceptable MR examination should include axial DWI
(and ADC map), FLAIR, T2-w, GRE/T2*-w or SWI, and T1-w images. The DWI
sequence is vital for identifying recent infarcts, e.g. in symptomatic patients. MRI with
DWI should be considered the reference standard for recent SSI, although it may be
negative in some cases.16 Clinical syndrome plus MR without DWI, or clinical syndrome
plus CT, is suboptimal, and clinical syndrome alone is least reliable.80 Acquiring one of
these sequences (T1-w usually) in the coronal or sagittal plane instead of axial facilitates
visualisation of the true lesion dimensions (appendix). Slice thickness should be 5 mm
or less, ideally with no gap; in-plane resolution should be 1 mm by 1 mm or better.
Whole-brain coverage is recommended for all sequences for optimum image analysis. A
3D T1-w thin section isotropic sequence is now commonly available, quick and can be
reformatted on thicker slices for ease of viewing in multiple planes: this sequence also
allows anatomical co-registration and quantification of brain volume. 3D MT T1-w
sequence protocols for the major scanner types at 1.5 and 3T have been validated in
the Alzheimer’s Disease Neuroimaging Initiative (ADNI); sequence protocols are freely
available on the web (www.adni-info.org).
A comprehensive SVD-intensive research MR protocol should consider acquiring the
MR data at higher resolution than the sequences specified above, using volume
acquisitions to allow for volumetric whole brain imaging with near- isotropic resolution.
These 3D acquisitions are now possible on most scanners for T1-w, T2-w, T2* GRE,
SWI and/or FLAIR techniques. Alternative high resolution sequences sensitive to
paramagnetic content such as SWI and equivalents should be considered, although
these also generate more artefacts. Diffusion tensor imaging (DTI) extends DWI and
26
should be used in research protocols. DTI is useful for assessing surrogates of
microarchitectual integrity of normal-appearing and lesional white matter, to determine
structural connectivity of white matter and in tractography. For quantitative volumetric
assessments of atrophy, a high resolution (1 to 1.5 mm isotropic voxels) T1w sequence
with good gray-white matter differentiation is advised. Other MR measurements show
great promise for SVD in research applications including measurements of perfusion,
magnetisation transfer, blood-brain barrier permeability, vascular reactivity, metabolites,
and microatheroma in perforating arterioles (see Future Directions).
Image analysis standards (table 4; appendix)
For all lesion types, qualitative (visual rating) and quantitative (computational analysis)
methods are established or emerging. For at least some lesion types, these two
approaches are highly correlated;81,82 both have advantages and disadvantages that
should be considered in the design of any SVD study. Full details of image processing
are given in the appendix.
For all lesion types, observers should be trained in brain imaging interpretation and
specifically how to recognize SVD lesions. If possible, particularly in trials or large
observational studies, images should be rated centrally by a single or small number of
experienced raters. If more than one rater is used, inter-rater reliability should be
assessed. To measure global and regional atrophy, observers should have good
knowledge of normal neuroanatomy. Observers should train on established training sets
and should aim for high observer agreement before undertaking actual measurements.
27
Regular ‘recalibration’ against standard examples is useful to maintain consistency
when rating large numbers of scans or when rating scans in different sessions.
When using automated computational methods for analysis, we emphasize that the
accuracy of each subject’s output should be visually confirmed by a trained observer.
This validation step is critical for studies of SVD because many automated methods
have not been developed for SVD specifically and there is a high risk of misclassification
of SVD lesions as other lesions or tissue classes, especially when unfamiliar pulsesequences are used or scanners are upgraded. Known examples to avoid include
misclassification of WMH as normal gray matter, of lacunes as ventricle or WMH, or of
SSI as WMH.83 Several of these misclassifications will require manual correction.77,84
For small discrete lesions of limited number, such as rSSI, lacunes, and microbleeds, we
recommend recording the location of each lesion and the total number of lesions. At
minimum, we recommend recording the number of lesions in each of the following brain
subregions, on the right and left side: cerebral cortex (divided by lobe), corona
radiata/centrum semiovale, putamen, globus pallidus, thalamus, internal capsule,
external capsule, brainstem, and cerebellum. Detailed recommendations for analysis of
different lesion types are summarized in table 4 and in the appendix.
Reporting standards for vascular findings on neuroimaging (table 5)
Conduct and reporting of vascular findings on neuroimaging should follow standards
already established for observational, epidemiological, diagnostic test assessment or
randomised clinical trials (www.equator-network.org). In addition to these, we suggest
28
some specific points that will aid progress in and standardize future research using
imaging (table 5). We encourage future reports to use the terms and definitions for SVDrelated imaging findings proposed above. Wherever possible studies using visual rating
scales should employ established broadly used rating scales to secure comparability of
studies and facilitate meta-analyses.
Future Developments and Challenges (table 6)
Advances in imaging technologies as well as novel protocols for image acquisition and
image post-processing have improved options for imaging the various manifestations of
SVD, with the potential to better clarify their role in neurodegenerative disease and to
identify new mechanisms of disease. Examples include advances in small arterial
imaging using ultra high-field strength MRI (>3T), DTI measures of detailed structural
connectivity, magnetization transfer imaging assessment of white matter myelination,
imaging of blood-brain barrier permeability and of vascular reactivity, perfusion imaging,
imaging of retinal vessels, QSM and others. The advantages of multi-modal imaging
should be exploited for advancing understanding of pathophysiology. For example,
combining DTI and atrophy measures allows the study of the effects of vascular lesions
on distantly connected brain regions.85
Importantly, there is increasing interest in the clinical relevance of further small brain
infarct subtype, microinfarcts, which are very small ischaemic lesions found mostly in the
cortex at autopsy in older people and visible in occasional subjects on high field
MRI.86,87 Their true vascular pathological relationship to SVD is yet to be determined.
Although yet to be confirmed, it is possible that some tiny cortical DWI acute lesions are
29
microinfarcts.86 Microinfarcts appear to be highly clinically relevant, so neuroimaging
methods to measure microinfarcts or a validated close surrogate is required. Larger
cortical microinfarcts have been visualized on 7T MRI, which were sometimes visible on
conventional 3T MRI as well.88
Comprehensive studies are now required that account for both vascular and
neurodegenerative pathologies in patients followed over longer time periods from
younger ages. These studies should include (amongst others) multimodal MRI, amyloid
imaging with positron emission tomography (PET), detailed clinical testing, and
biomarkers from serum and CSF to allow disentangling of the crosstalk between
vascular and neurodegenerative pathologies and how these interact to cause clinical
symptoms in particular cognitive decline, gait impairment, physical disability and
depression. There is considerable need for more imaging-pathology correlation.30,52
Additionally, carefully conducted imaging studies with repeat short-term (e.g. monthly)
follow-up are required to study the progression of SVD-related imaging features and
their impact on brain tissue loss.
Conclusions
These neuroimaging standards for SVD are intended to harmonize current disparate
terminology and analysis methods. We encourage other researchers to adopt these
standards. They may serve as a useful introduction to the principles of SVD
neuroimaging, that may assist investigators seeking to incorporate measurement of SVD
into their own studies focused on neurodegenerative diseases or, even more broadly,
the pathological basis of ageing. These standards should facilitate across-study
30
comparisons of findings, accelerating translation of new findings into practice.
Additionally, standardised approaches could enable formal between-study metaanalyses, which are increasingly required to obtain the sample sizes needed for some
types of research such as genetic association studies. We suggest that our reporting
standards may prove a useful guide to authors, peer reviewers and editors, and may
elevate the methodological quality of neuroimaging studies of SVD just as analogous
reporting standards (e.g. the CONSORT guidelines) have elevated the quality of other
types of research. Finally, although the primary purpose of our standards was for
research we hope that these standards will positively influence clinical diagnosis and the
reporting of SVD lesions in routine clinical practice.
These standards were developed based on consensus among a relatively large group of
experts using rigorous methods. However, we acknowledge that in some aspects of this
rapidly evolving field, our recommendations are based on small studies, unvalidated
findings or expert opinion without a strong body of supporting evidence. It is clear that
future work is essential to validate these standards. In particular, the dearth of
radiological-pathological correlation studies is a key limitation to our understanding of
the neuroimaging of SVD. Additionally, it was recognized that best standards for SVD
neuroimaging will change over time and therefore periodic revision of these standards
will be required.
31
The Centres of Excellence in Neurodegeneration Vascular Imaging Standards
Work Group membership:
Coordinators: J. Wardlaw, M. Dichgans, E. Smith
External advisors: P. Gorelick (Chair), C. Chen, B. Norrving, M. van Buchem, C. Smith.
Recent small subcortical infarcts: JM. Wardlaw (chair), R. van Oostenbrugge, V.
Hachinski, B. Stephan, V. Mok, L. Pantoni, F Doubal.
Lacunes of presumed vascular origin: R. Lindley (chair), H. Chabriat, M. Breteler, C.
Brayne, V. Mok, O. Benavente
WMH of presumed vascular origin: C. Cordonnier (chair), SE. Black, C. De Carli, FE. de
Leeuw, F. Fazekas, J. O’Brien, L. Pantoni
PVS: F. Fazekas (chair), V. Hachinski, A. Viswanathan, GJ. Biessels, R. van
Oostenbrugge, F Barkhof.
Cerebral microbleeds: JT. O’Brien (chair), D. Werring, M. Breteler, C.Cordonnier, R.
Lindley, R. Frayne,
Brain atrophy: GJ. Biessels (chair), N. Fox, I Kilimann, S. Greenberg, S. Teipel, SE.
Black, F. Barkof,
Image acquisition and analysis: R. Frayne, O. Speck, SE Black, M Duering, JM Wardlaw
Clinical relevance: O. Benavente, L. Pantoni
Other lesions: E. Smith (chair), D. Werring, A. Viswanathan
Future directions: M. Dichgans, M Duering,
We are grateful to M. Henderson, K. Shuler, L Thomas, I Wittko-Schneider, and Anna
Charlton for administrative support.
32
Author Contributions
All authors contributed through attendance at the two workshops, participation in specific
workgroups as listed, drafting and editing of the manuscript and approval for final
submission. JM Wardlaw, M. Dichgans, E. Smith co-ordinated the overall process,
obtained funding, organized the two workshops, co-ordinated the manuscript
preparation and finalized the manuscript for submission. External advisers were: P.
Gorelick, C. Chen, B Norrving, M van Buchem, C Smith, who attended the second
workshop, read the draft standards in detail, provided in depth critique, and approved
the final manuscript for submission. E Smith, F Doubal, M Dichgans, JM Wardlaw, A
Viswanathan, JT O’Brien, SE Black, RI Lindley performed literature searches.
Workgroup participants were: Recent small subcortical infarcts (JM. Wardlaw (chair), R.
van Oostenbrugge, V. Hachinski, B. Stephan, V. Mok, L. Pantoni, F Doubal), Lacunes of
presumed vascular origin (R. Lindley (chair), H. Chabriat, M. Breteler, C. Brayne, V. Mok,
O. Benavente), WMH of presumed vascular origin (C. Cordonnier (Chair), SE. Black, C.
De Carli, FE. de Leeuw, F. Fazekas, J.T. O’Brien, L. Pantoni), PVS (F. Fazekas (Chair),
V. Hachinski, A. Viswanathan, GJ. Biessels, R. van Oostenbrugge, F Barkhof) Cerebral
microbleeds (JT. O’Brien (chair), D. Werring, M. Breteler, C.Cordonnier, R. Lindley, R.
Frayne), Brain atrophy (GJ. Biessels (chair), N. Fox, I Kilimann, S. Greenberg, S. Teipel,
SE. Black, F. Barkof), Image acquisition and analysis: R. Frayne, O. Speck, SE Black, M
Duering, JM Wardlaw), Clinical relevance (O. Benavente, L. Pantoni), Other lesions (E.
Smith (chair), D. Werring, A. Viswanathan), Future directions (M. Dichgans, M Duering).
33
Conflicts of Interest
GJB consults for and receives research support from Boehringer Ingelheim. FF serves
on scientific advisory boards for Bayer-Schering, Biogen Idec, Genzyme, Merck Serono,
Pfizer, Novartis and Teva Pharmaceutical Industries Ltd. and as scientific advisor for
Perceptive Informatics; serves on the editorial boards of Cerebrovascular Diseases,
Multiple Sclerosis, the Polish Journal of Neurology and Neurosurgery, Stroke, and the
Swiss Archives of Neurology and Psychiatry; and has received speaker honoraria and
support from Biogen Idec, Bayer Schering, Merck Serono, Novartis, Sanofi-Aventis and
Teva Pharmaceutical Industries Ltd. He declares no specific conflict of interest with
submitted mansucript. RF receives related operating research funding from the CIHR,
the Alberta/Pfizer Translational Research Program , the Hotchkiss Brain Institute, and
the University of Calgary to support work in imaging small vessel disease. JTO has been
a consultant for GE Healthcare, Lilly, Bayer Healthcare and TauRx and has received
honoraria for talks from Pfizer, GE Healthcare, Eisai, Shire, Lundbeck, Lilly and Novartis.
SEB has had a financial relationship in the last two years in the form of: Contract
research funds to the Cognitive Neurology Research and Stroke Research Units: Pfizer
(Wyeth Research), GlaxoSmithKline, Lundbeck, Roche and Novartis. She has received
Speaker’s honoraria for CME: Pfizer, Eisai and Novartis and honoraria for ad hoc
consulting: Pfizer, Novartis, GlaxoSmithKline, Roche, Elan and Bristol Myers Squibb.
She holds no stocks or bonds. HC has received honoraria related to consultancy for
Servier, Lundbeck and Janssen Research and development. FEdL is supported by a
VIDI grant from ZonMW, The Netherlands Organisation for Health Research and
Development (grantnumber 016.126.351). LP is a member of the Editorial boards of:
34
Acta Neurologica Scandinavica, International Journal of Alzheimer Disease, and
Cerebrovascular Diseases and editor of the Vascular Cognitive Impairment section of
Stroke. ST served as a Member of the Advisory Board for Lilly Deutschland GmbH. MD
is a consultant for Bayer Vital GmbH; Boehringer Ingelheim Pharma GmbH & Co. KG;
Biologische Heilmittel Heel GmbH; Bristol-Myers Squibb GmbH & Co. KGaA; Ever
Neuro Pharma GmbH. He has received honoraria from Bayer Vital GmbH; Boehringer
Ingelheim Pharma GmbH & Co. KG; Biologische Heilmittel Heel GmbH; Bristol-Myers
Squibb GmbH & Co. KGaA; Lundbeck GmbH;
Sanofi-Aventis Deutschland GmbH;
Shire Deutschland GmbH; Deutsches Zentrum für Neurodegenerative Erkrankungen e.V.
(DZNE); Georg Thieme Verlag KG, UpToDate, W. Kohlhammer GmbH.
He has
received Principal Investigator/Research Funding (industry) from Bayer Vital GmbH;
Eisai Medical Research Inc.; Eisai Ltd.; Essex Pharma GmbH; Ferrer Internacional,
S.A.; ICON Clinical Research GmbH. All other authors declare that they have no
conflicts of interest.
35
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52
Table 1: Terms used previously to describe white matter hyperintensities of presumed vascular origin
Use of term
in titles and abstracts
Total No.*
%
Term
Variants of use of term
leukoaraiosis
350
31
275
24
217
19
136
12
leukoencephalopathy
ischemic leukoaraiosis, subcortical leukoaraiosis
MRI white matter lesions (WML), cerebral WML, T2 WML/WMLs,
cerebrovascular WML, subcortical WML, WML of Binswanger's disease,
cerebral WML of Binswanger's disease, confluent WML, intracranial WML
cerebral WMH, age-related WMH, brain WMH, MRI WMH
age-related cerebral white matter changes (WMC); age-related WMC,
cerebral WMC, changes in white matter, age-related changes in WM
subcortical ischemic leukoencephalopathy
76
7
white matter disease
age-related white matter disease (WMD), cerebral WMD, subcortical WMD
45
4
white matter damage
age-related WMD,
5
ischemic/ ischaemic white matter
ischemic subcortical WMD, chronic ischemic cerebral WMD, subcortical
4
disease
ischemic WMD
other terms (N=9)
17
Data were derived from structured literature search; for methodology see Supplemental material
*Number of instances term was mentioned at least once in the abstract or in the title. The total number of instances was N=1144
0
white matter lesions
white matter hyperintensity
white matter changes
0
1
53
Table 2: Glossary of proposed terms and definitions for neuroimaging features of SVD
Proposed term
Definition
Recent small subcortical infarct
neuroimaging evidence of infarction in the territory of a single perforating arteriole with imaging features or correlating
clinical symptoms consistent with a lesion occurring in the last few weeks
Lacune
of presumed vascular origin
round or ovoid, subcortical, fluid filled (similar signal to CSF) cavity between 3 mm and 15 mm in diameter, compatible
with a previous acute small small subcortical infarct or haemorrhage in the territory of a single perforating arteriole
White matter hyperintensity
of presumed vascular origin
signal abnormality of variable size in the white matter showing the following characteristics: hyperintense on T2-weighted
images like FLAIR without cavitation (signal different from CSF). Lesions in the subcortical gray matter or brain stem are
not included into this category unless explicitly stated – where deep grey matter and brainstem hyperintensities are
included as well, the collective name should be “subcortical hyperintensities”
Perivascular space
fluid filled space, which follows the typical course of a vessel penetrating / traversing the brain through gray or white
matter; has signal intensity similar to CSF on all sequences; has a round or ovoid shape with a diameter commonly not
exceeding 2 mm when imaged perpendicular to the course of the vessel
Cerebral microbleed
small (usually 2 mm – 5 mm or sometimes 10 mm in size) areas of signal void with associated “blooming” on T2* or other
MR sequences sensitive to susceptibility effects
Brain atrophy
brain volume loss, not related to a specific macroscopic focal injury such as trauma or infarction . Thus, the latter is not
included in this measure unless explicitly stated
54
Table 3: Proposed image acquisition standards for neuroimaging features of SVD
Sequence
Purpose*
Orientation
Target slice
thickness/ in-plane
resolution
Comment
Minimum essential sequences, e.g. for clinical or large scale epidemiological studies, generally available on most MR scanners
T1-weighted
important for discriminating lacunes from dilated
PVS; for discriminating gray from white matter
and for studying brain atrophy
2D axial,
sagittal, or
coronal
3-5 mm/
1 mm x 1 mm
at least one sequence acquired in sagittal or
coronal plane is helpful in visualizing full extent
and orientation of lesions
Diffusion-weighted
imaging (DWI)
most sensitive sequences for acute ischaemic
lesions; positive up to several weeks after event
2D axial
3-5 mm/
2 mm x 2 mm
reduced signal on apparent diffusion coefficient map helps identifying recent from old
lesions
T2-weighted
Brain structure; differentiate lacunes from WMH
and PVS; identify old infarcts
2D axial
3-5mm/
1 mm x 1 mm
Fluid Attenuated
Inversion Recovery
(FLAIR)
identify WMH and established cortical or large
subcortical infarcts; differentiate WML from PVS
and lacunes
2D axial
3-5 mm/
1 mm x 1 mm
T2*-weighted gradient
echo recalled (T2*-w
GRE)
detect haemorrhage, cerebral microbleeds,
siderosis; measurement of intracranial
volume
2D axial
3-5 mm/
1 mm x 1 mm
only reliable routine sequence for detection of
haemorrhage
Other commonly available routine sequences, generally available on most MR scanners
Proton Densityweighted
detect WMH, infarcts, perivascular spaces(with
T2w dual echo),other pathologies
Magnetic resonance
angiography (MRA)
ICA, vertebral, basilar or MCA/ACA/PCA
stenosis or other pathology
2D axial
3-5 mm/
2 mm x 2 mm
post contrast or
3D time of flight for
intracranial
3D, axial, coronal,
sagittal
reconstruction; 1 mm
isotropic voxels
now largely replaced by FLAIR
only large vessels visible at 1.5 or 3T; see
below for perforating arterioles.
Sequences often available on commercial clinical MR scanners; used more for research studies at present but some techniques have rapidly emerging use in
clinical protocols
Diffusion tensor
imaging (DTI) with 6
gradient direction
diffusion encoding
diagnose recent infarct; allows measurement of
mean diffusivity and fractional anisotropy
Susceptibility-weighted
imaging (SWI) or
equivalent
very sensitive to haemosiderin, measurement of
intracranial volume
2D axial
3-5 mm
2 mm x 2 mm
2D or 3D axial
2D: 3-5 mm/
2 mm x 2 mm
3D: 1 mm isotropic
voxels
more detailed characterisation than DWI;
acquisition time doubled
visualises more CMBs than T2* GRE imaging
and more sensitive to artifacts including
motion.
55
Research only sequences (i.e. require research expertise)
Isotropic volumetric
T2-w
display fine detail of PVS
Isotropic volumetric 3D
T1-w (eg using MPRAGE)
Improved volumetric brain measurements –
global and regional
Isotropic volumetric
FLAIR
identification of WMH; cortical or subcortical
infarcts
Advanced DTI with >6
direction diffusion
encoding (e.g. 32 or
more diffusion
encoding directions)
provides refined/superior quantitative measure
of microscopic tissue changes
Magnetisation Transfer
Ratio (MTR)
sensitive to demyelination and axonal loss
T1 mapping
determine water content of tissue
Permeability imaging
estimate permeability of the blood-brain barrier
Arterial spin labeling
(ASL) perfusion
imaging
measure tissue perfusion – quantitative, with
assumptions
Perfusion imaging
(dynamic contrast
enhancement, DCE, or
dynamic susceptibility
contrast, DSC)
provides semi-quantitative measures of blood
perfusion in tissue perfusion
functional MRI (fMRI)
measure brain function in response to task or
stimulus or at rest of default mode networks
3D axial
1 mm isotropic
voxels
allows post-acquisition reformatting, potentially
could replace 2D T2-w imaging if signal-tonoise is judged adequate.
3D axial
1 mm isotropic
voxels
allows post-acquisition reformatting, potentially
could replace 2D T1-w imaging if signal-tonoise is judged adequate
3D axial
1 mm isotropic
voxels
allows post-acquisition reformatting, potentially
could replace 2D FLAIR imaging if signal-tonoise is judged adequate; more homogeneous
CSF suppression
allows for tractography, connectome, and more
accurate measure of mean diffusivity and
fractional anisotropy
2D axial
3-5 mm/
2 mm x 2 mm
2D axial
3-5 mm/
1 mm x 1 mm
requires experience in acquisition and
interpretation; two measurements (with and
without MT-pulse)
axial
3-5 mm/
2 mm x 2 mm
requires experience in acquisition and
interpretation;
axial; sequential
pre- and postcontrast
3-5 mm/
2 mm x 2 mm
requires intravenous contrast injection;
complex image processing; methods improving
rapidly at present
2D axial
3-5 mm/
2 mm x 2 mm
complex to set up and run accurately; requires
post processing; optimum processing
strategies not yet confirmed; does not require
contrast injection.
2D axial
3-5 mm/
2 mm x 2 mm
requires intravenous injection of contrast agent
and post processing; optimum acquisition
and/or processing not yet confirmed for T1
(dynamic contrast enhancement, DCE) or T2*
(dynamic susceptibility contrast, DSC)
approaches
2D axial
3-5 mm/
2 mm x 2 mm
complex set up, acquisition and processing
56
Quantitative
susceptibility mapping
(QSM)
provides quantitation of susceptibility changes
independent of scanner or acquisition
parameters
Micro-atheroma- /
arteriolar imaging
for visualizing perforating arteriolar anatomy and
atheroma
2D or 3D axial
2D: 3 mm – 5 mm/
2 mm x 2 mm
or
3D: 1 mm isotropic
voxels
uses an SWI-like acquisition but requires very
complex post-processing methodology
required; post processing strategies currently
under investigation
uncertain,
emerging method
uncertain, emerging
method
promising experimental approach that requires
>3 T scanner
*Note that MR at 3 Tesla (T) is preferred to 1.5T; although these standards are listed as minimum essential through to research only applications,
these categories are not absolute, the purposes are variable, and will vary with investigator interest, expertise and available technology.
2D: two-dimensional, 3D: three-dimensional; ACA = anterior cerebral artery, CMB = cerebral microbleeds, ICA = internal carotid artery, MCA =
middle cerebral artery, MP-RAGE = magnetization-prepared rapid acquisition with gradient echo, PCA = posterior cerebral artery, PVS =
perivascular spaces, WMH = white matter hyperintensities.
57
Table 4: Proposed analysis standards for neuroimaging features of SVD
Measures of interest
Recent small subcortical infarcts
number (multiplicity may indicate
causes other than SVD)89,90
size (max. diameter)
volume
location (anatomical region; vascular
territory)
shape (round, ovoid, tubular)
swelling (indicates recent not old)
Lacune of presumed vascular origin
number (single or multiple)
Qualitative
various coding schemes available
for location:
anatomical: e.g. centrum
semiovale, corona radiata, basal
ganglia, thalamus, internal
capsule, external capsule, optic
radiation, cerebellum, brain stem
possible but
impractical for size
and volume
various coding schemes available
for shape and for location:
anatomical: e.g. lentiform nucleus,
thalamus, internal capsule,
centrum semiovale, brain stem
protocols for
quantitative
measurements
available, require
manual correction
ex vacuo effect
White matter hyperintensities
volume
location (anatomical region)
number
Accuracy, reliability,
feasibility
cross-sectional and
longitudinal: recent small
subcortical infarcts are
typically detected in the setting
of an acute clinical event but
may also be an incidental
finding
easy to identify on DWI,
reliability depends on time
between infarct
occurrence and imaging
cross-sectional and
longitudinal: particular care is
required to differentiate
lacunes from PVS
differentiation from PVS
may be difficult
longitudinal:
difference imaging helps
identifying incident lacunes
location (anatomical region)
evidence of previous hemorrhage
Study design
more difficult on other
sequences or on CT
without longitudinal data
vascular territory: e.g. middle
cerebral artery, posterior cerebral
artery, internal carotid artery,
basilar artery
size (max. diameter)
shape (round, ovoid, tubular, other)
Quantitative
prominent ex-vacuo effect
indicates lesion was originally
larger (e.g. striatocapsular
infarct)20
various coding schemes available
for location:
anatomical: e.g. perivascular,
deep, subcortical, brain stem;
or centrum semiovale, corona
radiata, internal capsule, external
capsule, optic radiation, brain
stem;
or frontal, temporal, parietal,
occipital
various visual rating
scores91-96 and
protocols for
quantitative
measurements84,97-100
available, the two
approaches are
complementary81,82
outputs should be
visually reviewed by
an experienced rater
for mimics, artifacts,
focal infarcts and
aim for high observer
agreement before
undertaking actual ratings
General
comment
mimics include acute
inflammatory MS
plaques
acute lesions usually
have increased signal
on DWI and reduced
signal on apparent
diffusion coefficient
images
hypointense rim on
T2* suggests previous
small deep
haemorrhage
cross-sectional and
longitudinal: consider masking
recent small subcortical
lesions, lacunes, and PVS
when measuring WMH volume
to avoid inflating WMH
volumes
inter and Intra-rater
reliability for both
qualitative and quantitative
analysis of WMH quite
high if performed by
trained raters, with ICCs
generally above 0.90
careful visual checking
at all stages of
computational analysis
required to avoid
problems from excess
lesion distortion by e g
bias field correction
longitudinal:
difference imaging may help
identifying new white matter
lesions
visual rating scores may
have ceiling or floor
effects, so performance
may differ with more or
less disease
consider regular
‘recalibration’ against
standard examples
when rating large
numbers of scans
58
Measures of interest
Study design
Accuracy, reliability,
feasibility
visual scores rate
number of lesions in
basal ganglia, centrum
semiovale, midbrain
etc.42,45,46
cross-sectional: consider
masking PVS when measuring
WMH volume, although this
may be difficult
difficult to determine,
especially when numerous
and in the presence of
WMH
various thresholdbased methods are in
development
longitudinal:
little experience
semi-automated approaches,
which segment cerebral
microbleeds as an extra tissue
class or radial symmetry and mask
out areas of mineralization are
being described101,102 but are
experimental at the present time
and require validation
several visual scores
available60,60,103,103,104,10
cross-sectional and
longitudinal: consider using
visual scores
currently, there are no
methods for
automated detection
longitudinal:
no specific scores for
longitudinal studies
If scans are not suited for
volumetric techniques or if such
techniques are not available,
qualitative rating scales may
provide an alternative105,106
(semi-) automated
quantitative methods
preferred but visual
checking and manual
editing is commonly
needed to avoid
including the orbits
and excluding the
brain stem from the
whole brain
volume68,84,107
(sub-)regional brain
volume computational
methods are in
development but their
cross-sectional: brain atrophy
can be estimated by
comparison with the inner skull
volume (an estimate of
maximum brain size in youth);
all intracranial contents must
be included in the ICV
measure including veins and
meninges which expand to
take up space left by a
shrinking brain75
Qualitative
Quantitative
General
comment
mislabeling
Perivascular spaces
number (multiplicity)
location (anatomical region)
anatomical:
midbrain, hippocampus, basal
ganglia, centrum semiovale
size (max. diameter)
shape (see text)
Cerebral microbleeds
number (few or multiple)
location (lobar, deep, or infratentorial;
anatomical region)
size
Brain atrophy
whole brain (should be adjusted for
intracranial volume, ICV)
regional (hippocampus, specific gyri,
lobes. should be adjusted for whole
brain volume)
cortical or subcortical
superficial or deep (sulcal or
ventricular enlargement; ditto
adjustment)
4
longitudinal:
Serial brain volumes can be
measured; a registration-
can be difficult to
distinguish from
lacunes
giant PVS may reach
size >2cm, most
commonly located
below putamen
there is some variability in
inter-rater agreement on
presence/absence of one
or two microbleeds, but
reasonable
agreement
(i.e. 0.8) between the
numbers of microbleeds,
reliability can be improved
through
the
use
of
standardized
60,103,104
scales
lobar and deep
cerebral microbleeds
may have different risk
factors and causes
(e.g. lobar cerebral
microbleeds are
associated with
cerebral amyloid
angiopathy)
computational approaches
have high reliability
consider masking
recent small
subcortical lesions,
lacunes, and PVS
when measuring brain
volume.77,108 Specific
standards are
emerging for
hippocampal volume
measurement110
visual rating is more varied
but can be improved with
reference to a standard
visual template106
subcortical and cortical
vascular lesions affect the
reliability of automated
volumetric techniques,78
particularly in subjects with
a high lesion load
59
Measures of interest
Qualitative
Quantitative
Study design
reliability, especially in
diseased populations,
has yet to be
determined77,77,108,108
based approach is currently
preferred although the field is
rapidly advancing109
Accuracy, reliability,
feasibility
General
comment
60
Table 5: Proposed reporting standards for neuroimaging features of SVD
Aspect
Studies should report on:
- demographic details of the research subjects and reference population from which they were drawn
- proportions with vascular risk factors and how measured
- stroke and its subtype(s) as well as other vascular disease
Study sample
- timing of imaging and clinical assessments in relation to disease presentation (if relevant)
- any clinical or imaging follow-up with time intervals
- for studies on cognition or specific physical functions: details of test versions used, who administered them, their training
- for cognitive studies: assessment of premorbid cognitive ability and of depression
- scanner characteristics (type and manufacturer, field strength, coils, high order shim and use of shimming routines, quality
assurance (QA) protocol for scanner and frequency of QA assessment), high order shim and use of shimming routines, quality
assurance (QA) protocol for scanner and frequency of QA assessment)
Image
acquisition
- use of multiple scanners
- change of scanners or change to a scanner system during study
- MRI sequences, acquisition parameters ( including as appropriate: repetition time, echo time, inversion time, echo train length),
acquisition and reconstruction matrices, field-of-view), slice thickness including gaps and scanning plane, details of selected
options (tailored excitation pulses, parallel imaging, flow compensation, preparation pulses, etc.), total acquisition time. If a work
in progress package is used, as much information as possible should be provided
- use and qualification of a central analysis facility, or training procedure across multiple analysis centres
- whether analyses were done blinded to initial presentation or other data (specify) that might bias interpretation
- details of qualitative visual rating and quantitative computational methods including web-address if available for download, or
appendix describing the method in detail
Image analysis /
postprocessing
- for visual rating scales: whether images were rated centrally by a single or small number of readers; the raters’ background (e.g.
neurology, psychiatry, neuroradiology, radiology) and experience; rater reliability (intra and inter-rater)
- for studies using computational image analysis programs: training of the analyst(s), any expert supervision and the background of
the expert; repeatability
- statistical methods used in data analysis
- ideally: sample size estimation
61
- for recent small subcortical infarcts (rSSI): specify whether infarcts are symptomatic or not, location, size, shape, and number; the
delay from stroke to imaging, and the proportion with visible acute lesion on DWI and/or FLAIR/T2
- for lacunes of presumed vascular origin: location, size, shape and number; distinguish haemorrhagic lesions from lacunes; for
volumetric methods state whether lacunes are counted as part of the CSF volume, as part of the WMH volume or as separate
‘lacune volume’
SVD-specific
aspects
- for white matter hyperintensities (WMH) of presumed vascular origin: specify if grey matter and brain stem hyperintensities are
included (and if so refer to all hyperintensities collectively as ‘; rating scale or volume measurement software used, observer
reliability; whether the WMH volume was adjusted for intracranial or brain volume and how this was done; whether lacunes were
included into WMH or measured separately, and whether acute lesions were masked
- for perivascular spaces: separate between PVS of the basal ganglia and white matter; describe how qualitative aspects
considered (number, location,size etc.) are defined; observer reliability of the rating scale
- for cerebral microbleeds: number and distribution as divided into lobar, deep and infratentorial (brain stem and cerebellum); full
details of image acquisition parameters; standardized rating scales applied
- for atrophy: rating scale or method of volume measurement and whether corrected for intracranial volume and if so how
62
Table 6: Future Challenges in imaging SVD-related changes
Aspect
Recent small subcortical
infarcts (rSSI)
Lacunes of presumed
vascular origin
White matter
hyperintensities (WMH) of
presumed vascular origin
Perivascular spaces
(PVS)
Questions to be addressed:
- how can different aetiological subtypes (e.g. embolic, parent or branch artery atheroma, intrinsic SVD), be better
differentiated by neuroimaging?
- what proportion of infarcts cavitate, become WMH, or subsequently disappear on conventional MR scans and what are the
factors determining conversion in one or the other direction.
- how can the methods for distinguishing lacunes from PVS be improved?
- how do secondary degenerative changes in the vicinity of lacunes influence their size and shape over longer time periods?
- how important is the presence of a hyperintense rim for differentiating lacunes from other small cystic structures, e.g. PVS?
- to what extent do perivascular and deep WMH differ in terms of mechanisms and clinical consequences? to address this
clear definitions and standardized protocols for distinguishing perivascular from deep WMH are needed
- how can newer imaging techniques such as measurements of T1 water content aid in better characterizing WMH and
determining their impact on connected brain regions (e.g. cortex) and clinical symptoms?
- Is there pathological or epidemiological justification for distinguishing between hyperintensities in grey matter and those in
white matter?
- what are the mechanisms underlying (multiple) PVS?
- what is the relationship between PVS diameter, risk factors and potential clinical consequences? Can a PVS diameter be
identified such that PVS of greater diameter can be considered to be pathologically enlarged?
- how do PVS relate to SVD-related vascular and parenchymal lesions?
- how do PVS relate to brain atrophy and neurodegenerative pathology?
- how can the protocols for detecting and quantifying PVS be improved?
- what are the clinical consequences of PVS?
- what is the clinical utility of rating PVS
- how do different neurodegenerative or vascular pathologies influence the pathology, spatial distribution and imaging
appearance of microbleeds?
how reliable, sensitive or specific is the distribution of CMB to amyloid angiopathy or hypertension?
Cerebral Microbleeds
(CMB)
- what is their predictive value with respect to cognitive and functional decline?
- what is their clinical utility with respect to guiding treatment decisions (e.g. use of thrombolysis and antithrombotic therapy)?
- how do different protocols for imaging and quantifying microbleeds compare and how can findings obtained through
different protocols be integrated into a common read-out?
63
Brain atrophy
- to what extent do SVD-related vascular lesions affect measures of brain atrophy (cortical, subcortical, gray versus white
matter?)
- to what extent does brain atrophy (cortical, subcortical, gray and white matter) impact on volumetric measures of vascular
lesions?
- what are the mechanisms underlying secondary brain atrophy mediated by vascular lesions?
- what are the clinical consequences of secondary brain atrophy mediated by vascular lesions?
Other vascular lesions
- what is their frequency in neurodegenerative disease?
Microinfarcts
- what are their clinical consequences?
- what are the imaging signatures of acute microinfarcts on clinical scanning at 1.5 and 3.0 Tesla?
- what is the frequency in Alzheimer’s disease?
- how frequently does acute sulcal subarachnoid hemorrhage lead to siderosis?
Superficial siderosis
- to what extent do these lesions affect cortical neuronal function?
- what are their clinical consequences, including the frequency of subsequent symptomatic subarachnoid or intracerebral
hemorrhage?
- how can direct imaging of small intracerebral arteries be improved?
- how can subtle changes of vascular origin be differentiated from changes mediated by other pathologies e.g.
neurodegeneration and what are the exact histopathological substrates?
- to what extent do SVD-related lesions cause secondary neurodegeneration and what are the underlying mechanisms?
General
- how do vascular lesions interact with neurodegenerative pathology in causing cognitive decline and other clinical
manifestations, in particular, physical disability, gait disturbance, and depression?
- is there any suitable imaging scale that allows integrating multiple SVD-related imaging findings and what is the utility of this
scale for research and for clinical practice (e.g. for risk prediction and treatment stratification)?
- how can imaging of vascular manifestations be used to improve the selection of patients included into future clinical trials
and in measuring their outcome?
- how can the protocols for measuring BBB integrity be improved and how do SVD-related and neurodegenerative pathology
interact in influencing BBB integrity?
- what is the relationship between alterations in cerebral blood flow and volume with ischemic brain pathology?
64
Figure 1: Variable fates of SVD-related lesions and convergence of aetiologically
different acute lesions to result in similar late appearances on MRI: arrows indicate
possible late fates of acute MR imaging findings; black arrows indicate common fates of
recent small subcortical infarcts; solid grey arrows indicate less common and grey
dashed arrows indicate least common late fates, according to best available current
knowledge.
65
Figure 2: Characteristics of SVD-related MR imaging findings: illustrative examples
(upper panel) and schematic representation (middle panel) of MR features of different
SVD-related changes on typical scans are shown together with a summary of imaging
characteristics (lower panel) for individual lesions;  = increased signal; = decreased
signal; = isointense signal
66
Figure 3: Secondary brain atrophy in a 55 year old patient with documented SVD. The
follow-up scan (T1-weighted image) shows marked sulcal widening (white arrowheads)
particularly in occipital brain regions as well as ventricular enlargement (black
arrowheads) in the absence of new infarctions during follow-up. The FLAIR image (left
panel) shows marked WMH.
67