title: Rationale, design and methodology of the image analysis protocol for studies of patients with cerebral small vessel disease and mild stroke.
abstract: BACKGROUND
  Cerebral small vessel disease (SVD) is common in ageing and patients with dementia and stroke. Its manifestations on magnetic resonance imaging (MRI) include white matter hyperintensities, lacunes, microbleeds, perivascular spaces, small subcortical infarcts, and brain atrophy. Many studies focus only on one of these manifestations. A protocol for the differential assessment of all these features is, therefore, needed.
  
  
  OBJECTIVE
  To identify ways of quantifying imaging markers in research of patients with SVD and operationalize the recommendations from the STandards for ReportIng Vascular changes on nEuroimaging guidelines. Here, we report the rationale, design, and methodology of a brain image analysis protocol based on our experience from observational longitudinal studies of patients with nondisabling stroke.
  
  
  METHODS
  The MRI analysis protocol is designed to provide quantitative and qualitative measures of disease evolution including: acute and old stroke lesions, lacunes, tissue loss due to stroke, perivascular spaces, microbleeds, macrohemorrhages, iron deposition in basal ganglia, substantia nigra and brain stem, brain atrophy, and white matter hyperintensities, with the latter separated into intense and less intense. Quantitative measures of tissue integrity such as diffusion fractional anisotropy, mean diffusivity, and the longitudinal relaxation time are assessed in regions of interest manually placed in anatomically and functionally relevant locations, and in others derived from feature extraction pipelines and tissue segmentation methods. Morphological changes that relate to cognitive deficits after stroke, analyzed through shape models of subcortical structures, complete the multiparametric image analysis protocol.
  
  
  RESULTS
  Final outcomes include guidance for identifying ways to minimize bias and confounds in the assessment of SVD and stroke imaging biomarkers. It is intended that this information will inform the design of studies to examine the underlying pathophysiology of SVD and stroke, and to provide reliable, quantitative outcomes in trials of new therapies and preventative strategies.
authors.affiliation: Department of Neuroimaging Sciences Centre for Clinical Brain Sciences University of Edinburgh Edinburgh UK.
authors.forename: Maria Del C
authors.identifier: 0000-0003-2771-6546
authors.initials: Mdel C
authors.lastname: Valdés Hernández
authors.affiliation: Department of Cardiovascular Sciences University of Sheffield Sheffield UK.
authors.forename: Paul A
authors.initials: PA
authors.lastname: Armitage
authors.affiliation: Department of Neuroimaging Sciences Centre for Clinical Brain Sciences University of Edinburgh Edinburgh UK.
authors.forename: Michael J
authors.initials: MJ
authors.lastname: Thrippleton
authors.affiliation: Department of Neuroimaging Sciences Centre for Clinical Brain Sciences University of Edinburgh Edinburgh UK.
authors.forename: Francesca
authors.initials: F
authors.lastname: Chappell
authors.affiliation: Department of Neuroimaging Sciences Centre for Clinical Brain Sciences University of Edinburgh Edinburgh UK.
authors.forename: Elaine
authors.initials: E
authors.lastname: Sandeman
authors.affiliation: Department of Neuroimaging Sciences Centre for Clinical Brain Sciences University of Edinburgh Edinburgh UK.
authors.forename: Susana
authors.initials: S
authors.lastname: Muñoz Maniega
authors.affiliation: Department of Neuroimaging Sciences Centre for Clinical Brain Sciences University of Edinburgh Edinburgh UK.
authors.forename: Kirsten
authors.initials: K
authors.lastname: Shuler
authors.affiliation: Department of Neuroimaging Sciences Centre for Clinical Brain Sciences University of Edinburgh Edinburgh UK.
authors.forename: Joanna M
authors.initials: JM
authors.lastname: Wardlaw
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D001921:Brain / Q000473:pathology*; D059345:Cerebral Small Vessel Diseases / Q000473:pathology*; D002985:Clinical Protocols; D003430:Cross-Sectional Studies; D005500:Follow-Up Studies; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods* / Q000592:standards; D016014:Linear Models; D008137:Longitudinal Studies; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008875:Middle Aged; D017711:Nonlinear Dynamics; D064887:Observational Studies as Topic; D010363:Pattern Recognition, Automated / Q000379:methods; D017410:Practice Guidelines as Topic; D015203:Reproducibility of Results; D012984:Software; D020521:Stroke / Q000473:pathology*
keywords: Blood–brain barrier; MRI; image analysis; protocol; small vessel disease; stroke