Literature DB >> 28274834

Resolution considerations in imaging of the cortical layers.

Shlomi Lifshits1, Omri Tomer2, Ittai Shamir3, Daniel Barazany4, Galia Tsarfaty5, Saharon Rosset1, Yaniv Assaf6.   

Abstract

The cortical layers are a finger print of brain development, function, connectivity and pathology. Obviously, the formation of the layers and their composition is essential to cognition and behavior. The layers were traditionally measured by histological means but recent studies utilizing MRI suggested that T1 relaxation imaging consist of enough contrast to separate the layers. Indeed extreme resolution, post mortem, studies demonstrated this phenomenon. Yet, one of the limiting factors of using T1 MRI to visualize the layers in neuroimaging research is partial volume effect. This happen when the image resolution is not high enough and two or more layers resides within the same voxel. In this paper we demonstrate that due to the physical small thickness of the layers it is highly unlikely that high resolution imaging could resolve the layers. By contrast, we suggest that low resolution multi T1 mapping conjugate with composition analysis could provide practical means for measuring the T1 layers. We suggest an acquisition platform that is clinically feasible and could quantify measures of the layers. The key feature of the suggested platform is that separation of the layers is better achieved in the T1 relaxation domain rather than in the spatial image domain.
Copyright © 2017 Elsevier Inc. All rights reserved.

Keywords:  Brain parcellation; Cortical layers; MRI resolution; Partial volume effect; T1 relaxation

Mesh:

Year:  2017        PMID: 28274834     DOI: 10.1016/j.neuroimage.2017.02.086

Source DB:  PubMed          Journal:  Neuroimage        ISSN: 1053-8119            Impact factor:   6.556


  6 in total

Review 1.  An MRI-Based, Data-Driven Model of Cortical Laminar Connectivity.

Authors:  Ittai Shamir; Yaniv Assaf
Journal:  Neuroinformatics       Date:  2020-09-19

2.  Modelling the laminar connectome of the human brain.

Authors:  Ittai Shamir; Omri Tomer; Ronnie Krupnik; Yaniv Assaf
Journal:  Brain Struct Funct       Date:  2022-06-03       Impact factor: 3.270

3.  Modelling Cortical Laminar Connectivity in the Macaque Brain.

Authors:  Ittai Shamir; Yaniv Assaf
Journal:  Neuroinformatics       Date:  2021-08-14

4.  Widespread cortical dyslamination in epilepsy patients with malformations of cortical development.

Authors:  David Tanne; Yaniv Assaf; Eyal Lotan; Omri Tomer; Ido Tavor; Ilan Blatt; Hadassah Goldberg-Stern; Chen Hoffmann; Galia Tsarfaty
Journal:  Neuroradiology       Date:  2020-09-25       Impact factor: 2.804

5.  In vivo measurements of lamination patterns in the human cortex.

Authors:  Omri Tomer; Daniel Barazany; Zvi Baratz; Galia Tsarfaty; Yaniv Assaf
Journal:  Hum Brain Mapp       Date:  2022-03-11       Impact factor: 5.399

6.  Identification of Laminar Composition in Cerebral Cortex Using Low-Resolution Magnetic Resonance Images and Trust Region Optimization Algorithm.

Authors:  Jakub Jamárik; Lubomír Vojtíšek; Vendula Churová; Tomáš Kašpárek; Daniel Schwarz
Journal:  Diagnostics (Basel)       Date:  2021-12-23
  6 in total

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