RT Journal Article
SR Electronic
T1 Design and rationale for examining neuroimaging genetics in ischemic stroke
JF Neurology Genetics
JO Neurol Genet
FD Lippincott Williams & Wilkins
SP e180
DO 10.1212/NXG.0000000000000180
VO 3
IS 5
A1 Anne-Katrin Giese
A1 Markus D. Schirmer
A1 Kathleen L. Donahue
A1 Lisa Cloonan
A1 Robert Irie
A1 Stefan Winzeck
A1 Mark J.R.J. Bouts
A1 Elissa C. McIntosh
A1 Steven J. Mocking
A1 Adrian V. Dalca
A1 Ramesh Sridharan
A1 Huichun Xu
A1 Petrea Frid
A1 Eva Giralt-Steinhauer
A1 Lukas Holmegaard
A1 Jaume Roquer
A1 Johan Wasselius
A1 John W. Cole
A1 Patrick F. McArdle
A1 Joseph P. Broderick
A1 Jordi Jimenez-Conde
A1 Christina Jern
A1 Brett M. Kissela
A1 Dawn O. Kleindorfer
A1 Robin Lemmens
A1 Arne Lindgren
A1 James F. Meschia
A1 Tatjana Rundek
A1 Ralph L. Sacco
A1 Reinhold Schmidt
A1 Pankaj Sharma
A1 Agnieszka Slowik
A1 Vincent Thijs
A1 Daniel Woo
A1 Bradford B. Worrall
A1 Steven J. Kittner
A1 Braxton D. Mitchell
A1 Jonathan Rosand
A1 Polina Golland
A1 Ona Wu
A1 Natalia S. Rost
YR 2017
UL http://ng.neurology.org/content/3/5/e180.abstract
AB Objective: To describe the design and rationale for the genetic analysis of acute and chronic cerebrovascular neuroimaging phenotypes detected on clinical MRI in patients with acute ischemic stroke (AIS) within the scope of the MRI–GENetics Interface Exploration (MRI-GENIE) study.Methods: MRI-GENIE capitalizes on the existing infrastructure of the Stroke Genetics Network (SiGN). In total, 12 international SiGN sites contributed MRIs of 3,301 patients with AIS. Detailed clinical phenotyping with the web-based Causative Classification of Stroke (CCS) system and genome-wide genotyping data were available for all participants. Neuroimaging analyses include the manual and automated assessments of established MRI markers. A high-throughput MRI analysis pipeline for the automated assessment of cerebrovascular lesions on clinical scans will be developed in a subset of scans for both acute and chronic lesions, validated against gold standard, and applied to all available scans. The extracted neuroimaging phenotypes will improve characterization of acute and chronic cerebrovascular lesions in ischemic stroke, including CCS subtypes, and their effect on functional outcomes after stroke. Moreover, genetic testing will uncover variants associated with acute and chronic MRI manifestations of cerebrovascular disease.Conclusions: The MRI-GENIE study aims to develop, validate, and distribute the MRI analysis platform for scans acquired as part of clinical care for patients with AIS, which will lead to (1) novel genetic discoveries in ischemic stroke, (2) strategies for personalized stroke risk assessment, and (3) personalized stroke outcome assessment.ADC=apparent diffusion coefficient; AIS=acute ischemic stroke; CE=cardioembolic; CCS=Causative Classification of Stroke; CCSc=causative CCS; DICOM=Digital Imaging and Communications in Medicine; DWI=diffusion-weighted imaging; DWIv=DWI volume; FLAIR=fluid-attenuated inversion recovery; GISCOME=Genetics of Ischemic Stroke Functional Outcome; GWAS=genome-wide association studies; ICC=intraclass correlation coefficient; LAA=large artery atherosclerosis; MGH=Massachusetts General Hospital; MRI-GENIE=MRI–GENetics Interface Exploration; mRS=modified Rankin Scale; PHI=protected health information; QC=quality control; SAO=small artery occlusion; SiGN=Stroke Genetics Network; SNP=single nucleotide polymorphism; SWI=susceptibility-weighted imaging; TOAST=Trial of Org 10172 Acute Stroke Treatment; VLSM=voxel-based lesion–symptom mapping; WMHv=white matter hyperintensity volume; XNAT=eXtensible Neuroimaging Archive Toolkit