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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...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2017
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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. |
format | Online Article Text |
id | pubmed-5328256 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
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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