PT  - JOURNAL ARTICLE
AU  - Anne-Katrin Giese
AU  - Markus D. Schirmer
AU  - Kathleen L. Donahue
AU  - Lisa Cloonan
AU  - Robert Irie
AU  - Stefan Winzeck
AU  - Mark J.R.J. Bouts
AU  - Elissa C. McIntosh
AU  - Steven J. Mocking
AU  - Adrian V. Dalca
AU  - Ramesh Sridharan
AU  - Huichun Xu
AU  - Petrea Frid
AU  - Eva Giralt-Steinhauer
AU  - Lukas Holmegaard
AU  - Jaume Roquer
AU  - Johan Wasselius
AU  - John W. Cole
AU  - Patrick F. McArdle
AU  - Joseph P. Broderick
AU  - Jordi Jimenez-Conde
AU  - Christina Jern
AU  - Brett M. Kissela
AU  - Dawn O. Kleindorfer
AU  - Robin Lemmens
AU  - Arne Lindgren
AU  - James F. Meschia
AU  - Tatjana Rundek
AU  - Ralph L. Sacco
AU  - Reinhold Schmidt
AU  - Pankaj Sharma
AU  - Agnieszka Slowik
AU  - Vincent Thijs
AU  - Daniel Woo
AU  - Bradford B. Worrall
AU  - Steven J. Kittner
AU  - Braxton D. Mitchell
AU  - Jonathan Rosand
AU  - Polina Golland
AU  - Ona Wu
AU  - Natalia S. Rost
TI  - Design and rationale for examining neuroimaging genetics in ischemic stroke
AID  - 10.1212/NXG.0000000000000180
DP  - 2017 Oct 01
TA  - Neurology Genetics
PG  - e180
VI  - 3
IP  - 5
4099  - http://ng.neurology.org/content/3/5/e180.short
4100  - http://ng.neurology.org/content/3/5/e180.full
SO  - Neurol Genet2017 Oct 01; 3
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