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A concept for holistic whole body MRI data analysis, Imiomics

PURPOSE: To present and evaluate a whole-body image analysis concept, Imiomics (imaging–omics) and an image registration method that enables Imiomics analyses by deforming all image data to a common coordinate system, so that the information in each voxel can be compared between persons or within a...

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Autores principales: Strand, Robin, Malmberg, Filip, Johansson, Lars, Lind, Lars, Sundbom, Magnus, Ahlström, Håkan, Kullberg, Joel
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5328256/
https://www.ncbi.nlm.nih.gov/pubmed/28241015
http://dx.doi.org/10.1371/journal.pone.0169966
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author Strand, Robin
Malmberg, Filip
Johansson, Lars
Lind, Lars
Sundbom, Magnus
Ahlström, Håkan
Kullberg, Joel
author_facet Strand, Robin
Malmberg, Filip
Johansson, Lars
Lind, Lars
Sundbom, Magnus
Ahlström, Håkan
Kullberg, Joel
author_sort Strand, Robin
collection PubMed
description PURPOSE: To present and evaluate a whole-body image analysis concept, Imiomics (imaging–omics) and an image registration method that enables Imiomics analyses by deforming all image data to a common coordinate system, so that the information in each voxel can be compared between persons or within a person over time and integrated with non-imaging data. METHODS: The presented image registration method utilizes relative elasticity constraints of different tissue obtained from whole-body water-fat MRI. The registration method is evaluated by inverse consistency and Dice coefficients and the Imiomics concept is evaluated by example analyses of importance for metabolic research using non-imaging parameters where we know what to expect. The example analyses include whole body imaging atlas creation, anomaly detection, and cross-sectional and longitudinal analysis. RESULTS: The image registration method evaluation on 128 subjects shows low inverse consistency errors and high Dice coefficients. Also, the statistical atlas with fat content intensity values shows low standard deviation values, indicating successful deformations to the common coordinate system. The example analyses show expected associations and correlations which agree with explicit measurements, and thereby illustrate the usefulness of the proposed Imiomics concept. CONCLUSIONS: The registration method is well-suited for Imiomics analyses, which enable analyses of relationships to non-imaging data, e.g. clinical data, in new types of holistic targeted and untargeted big-data analysis.
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spelling pubmed-53282562017-03-09 A concept for holistic whole body MRI data analysis, Imiomics Strand, Robin Malmberg, Filip Johansson, Lars Lind, Lars Sundbom, Magnus Ahlström, Håkan Kullberg, Joel PLoS One Research Article PURPOSE: To present and evaluate a whole-body image analysis concept, Imiomics (imaging–omics) and an image registration method that enables Imiomics analyses by deforming all image data to a common coordinate system, so that the information in each voxel can be compared between persons or within a person over time and integrated with non-imaging data. METHODS: The presented image registration method utilizes relative elasticity constraints of different tissue obtained from whole-body water-fat MRI. The registration method is evaluated by inverse consistency and Dice coefficients and the Imiomics concept is evaluated by example analyses of importance for metabolic research using non-imaging parameters where we know what to expect. The example analyses include whole body imaging atlas creation, anomaly detection, and cross-sectional and longitudinal analysis. RESULTS: The image registration method evaluation on 128 subjects shows low inverse consistency errors and high Dice coefficients. Also, the statistical atlas with fat content intensity values shows low standard deviation values, indicating successful deformations to the common coordinate system. The example analyses show expected associations and correlations which agree with explicit measurements, and thereby illustrate the usefulness of the proposed Imiomics concept. CONCLUSIONS: The registration method is well-suited for Imiomics analyses, which enable analyses of relationships to non-imaging data, e.g. clinical data, in new types of holistic targeted and untargeted big-data analysis. Public Library of Science 2017-02-27 /pmc/articles/PMC5328256/ /pubmed/28241015 http://dx.doi.org/10.1371/journal.pone.0169966 Text en © 2017 Strand et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Strand, Robin
Malmberg, Filip
Johansson, Lars
Lind, Lars
Sundbom, Magnus
Ahlström, Håkan
Kullberg, Joel
A concept for holistic whole body MRI data analysis, Imiomics
title A concept for holistic whole body MRI data analysis, Imiomics
title_full A concept for holistic whole body MRI data analysis, Imiomics
title_fullStr A concept for holistic whole body MRI data analysis, Imiomics
title_full_unstemmed A concept for holistic whole body MRI data analysis, Imiomics
title_short A concept for holistic whole body MRI data analysis, Imiomics
title_sort concept for holistic whole body mri data analysis, imiomics
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5328256/
https://www.ncbi.nlm.nih.gov/pubmed/28241015
http://dx.doi.org/10.1371/journal.pone.0169966
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