Literature DB >> 30176374

A group-level comparison of volumetric and combined volumetric-surface normalization for whole brain analyses of myelin and iron maps.

Antonietta Canna1, Sara Ponticorvo1, Andrea G Russo1, Renzo Manara1, Francesco Di Salle2, Renato Saponiero3, Martina F Callaghan4, Nikolaus Weiskopf5, Fabrizio Esposito6.   

Abstract

Quantitative MRI (qMRI) provides surrogate brain maps of myelin and iron content. After spatial normalization to a common standard brain space, these may be used to detect altered myelination and iron accumulation in clinical populations. Here, volumetric and combined volumetric and surface-based (CVS) normalization were compared to identify which procedure would afford the greatest sensitivity to inter-regional differences (contrast), and the lowest inter-subject variability (under normal conditions), of myelin- and iron-related qMRI parameters, in whole-brain group-level studies. Ten healthy volunteers were scanned twice at 3 Tesla. Three-dimensional T1-weighted, T2-weighted and multi-parametric mapping sequences for brain qMRI were used to map myelin and iron content over the whole brain. Parameter maps were spatially normalized using volumetric (DARTEL) and CVS procedures. Tissue probability weighting and isotropic Gaussian smoothing were integrated in DARTEL for voxel-based quantification (VBQ). Contrasts, coefficients of variations and sensitivity to detecting differences in the parameters were estimated in standard space for each approach on region of interest (ROI) and voxel-by-voxel bases. The contrast between cortical and subcortical ROIs with respectively different myelin and iron content was higher following CVS, compared to DARTEL-VBQ, normalization. Across cortical voxels, the inter-individual variability of myelin and iron qMRI maps were comparable between CVS (with no smoothing) and DARTEL-VBQ (with smoothing). CVS normalization of qMRI maps preserves higher myelin and iron contrast than DARTEL-VBQ over the entire brain, while exhibiting comparable variability in the cerebral cortex without extra smoothing. Thus, CVS may prove useful for detecting small microstructural differences in whole-brain group-level qMRI studies.
Copyright © 2018 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Group-level mapping; Iron mapping; Myelin mapping; Quantitative MRI; Surface normalization; Volumetric normalization; Whole brain mapping

Mesh:

Substances:

Year:  2018        PMID: 30176374     DOI: 10.1016/j.mri.2018.08.021

Source DB:  PubMed          Journal:  Magn Reson Imaging        ISSN: 0730-725X            Impact factor:   2.546


  5 in total

1.  Magnetic Resonance T1w/T2w Ratio in the Putamen and Cerebellum as a Marker of Cognitive Impairment in MSA: a Longitudinal Study.

Authors:  Sofia Cuoco; Sara Ponticorvo; Rossella Bisogno; Renzo Manara; Fabrizio Esposito; Gianfranco Di Salle; Francesco Di Salle; Marianna Amboni; Roberto Erro; Marina Picillo; Paolo Barone; Maria Teresa Pellecchia
Journal:  Cerebellum       Date:  2022-08-19       Impact factor: 3.648

2.  Magnetic resonance T1w/T2w ratio and voxel-based morphometry in multiple system atrophy.

Authors:  S Ponticorvo; R Manara; M C Russillo; R Erro; M Picillo; G Di Salle; F Di Salle; P Barone; F Esposito; M T Pellecchia
Journal:  Sci Rep       Date:  2021-11-04       Impact factor: 4.379

3.  hMRI - A toolbox for quantitative MRI in neuroscience and clinical research.

Authors:  Karsten Tabelow; Evelyne Balteau; John Ashburner; Martina F Callaghan; Bogdan Draganski; Gunther Helms; Ferath Kherif; Tobias Leutritz; Antoine Lutti; Christophe Phillips; Enrico Reimer; Lars Ruthotto; Maryam Seif; Nikolaus Weiskopf; Gabriel Ziegler; Siawoosh Mohammadi
Journal:  Neuroimage       Date:  2019-01-21       Impact factor: 6.556

4.  Brain iron content in systemic iron overload: A beta-thalassemia quantitative MRI study.

Authors:  Renzo Manara; Sara Ponticorvo; Immacolata Tartaglione; Gianluca Femina; Andrea Elefante; Camilla Russo; Pasquale Alessandro Carafa; Mario Cirillo; Maddalena Casale; Angela Ciancio; Rosanna Di Concilio; Elisa De Michele; Nikolaus Weiskopf; Francesco Di Salle; Silverio Perrotta; Fabrizio Esposito
Journal:  Neuroimage Clin       Date:  2019-10-25       Impact factor: 4.881

5.  Structural Alterations in Deep Brain Structures in Type 1 Diabetes.

Authors:  Pavel Filip; Antonietta Canna; Amir Moheet; Petr Bednarik; Heidi Grohn; Xiufeng Li; Anjali F Kumar; Evan Olawsky; Lynn E Eberly; Elizabeth R Seaquist; Silvia Mangia
Journal:  Diabetes       Date:  2020-08-24       Impact factor: 9.461

  5 in total

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