Literature DB >> 31609325

Brain Infarct Segmentation and Registration on MRI or CT for Lesion-symptom Mapping.

J Matthijs Biesbroek1, Hugo J Kuijf2, Nick A Weaver3, Lei Zhao4, Marco Duering5, Geert Jan Biessels3.   

Abstract

In lesion-symptom mapping (LSM), brain function is inferred by relating the location of acquired brain lesions to behavioral or cognitive symptoms in a group of patients. With recent advances in brain imaging and image processing, LSM has become a popular tool in cognitive neuroscience. LSM can provide fundamental insights into the functional architecture of the human brain for a variety of cognitive and non-cognitive functions. A crucial step in performing LSM studies is the segmentation of lesions on brains scans of a large group of patients and registration of each scan to a common stereotaxic space (also called standard space or a standardized brain template). Described here is an open-access, standardized method for infarct segmentation and registration for the purpose of LSM, as well as a detailed and hands-on walkthrough based on exemplary cases. A comprehensive tutorial for the manual segmentation of brain infarcts on CT scans and DWI or FLAIR MRI sequences is provided, including criteria for infarct identification and pitfalls for different scan types. The registration software provides multiple registration schemes that can be used for processing of CT and MRI data with heterogeneous acquisition parameters. A tutorial on using this registration software and performing visual quality checks and manual corrections (which are needed in some cases) is provided. This approach provides researchers with a framework for the entire process of brain image processing required to perform an LSM study, from gathering of the data to final quality checks of the results.

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Year:  2019        PMID: 31609325     DOI: 10.3791/59653

Source DB:  PubMed          Journal:  J Vis Exp        ISSN: 1940-087X            Impact factor:   1.355


  2 in total

1.  Association of Lesion Location and Fatigue Symptoms After Ischemic Stroke: A VLSM Study.

Authors:  Jinjing Wang; Mengmeng Gu; Lulu Xiao; Shiyi Jiang; Dawei Yin; Ye He; Peng Wang; Wen Sun; Xinfeng Liu
Journal:  Front Aging Neurosci       Date:  2022-06-29       Impact factor: 5.702

2.  Network impact score is an independent predictor of post-stroke cognitive impairment: A multicenter cohort study in 2341 patients with acute ischemic stroke.

Authors:  J Matthijs Biesbroek; Nick A Weaver; Hugo P Aben; Hugo J Kuijf; Jill Abrigo; Hee-Joon Bae; Mélanie Barbay; Jonathan G Best; Régis Bordet; Francesca M Chappell; Christopher P L H Chen; Thibaut Dondaine; Ruben S van der Giessen; Olivier Godefroy; Bibek Gyanwali; Olivia K L Hamilton; Saima Hilal; Irene M C Huenges Wajer; Yeonwook Kang; L Jaap Kappelle; Beom Joon Kim; Sebastian Köhler; Paul L M de Kort; Peter J Koudstaal; Gregory Kuchcinski; Bonnie Y K Lam; Byung-Chul Lee; Keon-Joo Lee; Jae-Sung Lim; Renaud Lopes; Stephen D J Makin; Anne-Marie Mendyk; Vincent C T Mok; Mi Sun Oh; Robert J van Oostenbrugge; Martine Roussel; Lin Shi; Julie Staals; Maria Del C Valdés-Hernández; Narayanaswamy Venketasubramanian; Frans R J Verhey; Joanna M Wardlaw; David J Werring; Xu Xin; Kyung-Ho Yu; Martine J E van Zandvoort; Lei Zhao; Geert Jan Biessels
Journal:  Neuroimage Clin       Date:  2022-04-27       Impact factor: 4.891

  2 in total

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