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“Après Mois, Le Déluge”: Preparing for the Coming Data Flood in the MRI-Guided Radiotherapy Era
Magnetic resonance imaging provides a sea of quantitative and semi-quantitative data. While radiation oncologists already navigate a pool of clinical (semantic) and imaging data, the tide will swell with the advent of hybrid MRI/linear accelerator devices and increasing interest in MRI-guided radiot...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6779062/ https://www.ncbi.nlm.nih.gov/pubmed/31632914 http://dx.doi.org/10.3389/fonc.2019.00983 |
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author | Kiser, Kendall J. Smith, Benjamin D. Wang, Jihong Fuller, Clifton D. |
author_facet | Kiser, Kendall J. Smith, Benjamin D. Wang, Jihong Fuller, Clifton D. |
author_sort | Kiser, Kendall J. |
collection | PubMed |
description | Magnetic resonance imaging provides a sea of quantitative and semi-quantitative data. While radiation oncologists already navigate a pool of clinical (semantic) and imaging data, the tide will swell with the advent of hybrid MRI/linear accelerator devices and increasing interest in MRI-guided radiotherapy (MRIgRT), including adaptive MRIgRT. The variety of MR sequences (of greater complexity than the single parameter Hounsfield unit of CT scanning routinely used in radiotherapy), the workflow of adaptive fractionation, and the sheer quantity of daily images acquired are challenges for scaling this technology. Biomedical informatics, which is the science of information in biomedicine, can provide helpful insights for this looming transition. Funneling MRIgRT data into clinically meaningful information streams requires committing to the flow of inter-institutional data accessibility and interoperability initiatives, standardizing MRIgRT dosimetry methods, streamlining MR linear accelerator workflow, and standardizing MRI acquisition and post-processing. This review will attempt to conceptually ford these topics using clinical informatics approaches as a theoretical bridge. |
format | Online Article Text |
id | pubmed-6779062 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-67790622019-10-18 “Après Mois, Le Déluge”: Preparing for the Coming Data Flood in the MRI-Guided Radiotherapy Era Kiser, Kendall J. Smith, Benjamin D. Wang, Jihong Fuller, Clifton D. Front Oncol Oncology Magnetic resonance imaging provides a sea of quantitative and semi-quantitative data. While radiation oncologists already navigate a pool of clinical (semantic) and imaging data, the tide will swell with the advent of hybrid MRI/linear accelerator devices and increasing interest in MRI-guided radiotherapy (MRIgRT), including adaptive MRIgRT. The variety of MR sequences (of greater complexity than the single parameter Hounsfield unit of CT scanning routinely used in radiotherapy), the workflow of adaptive fractionation, and the sheer quantity of daily images acquired are challenges for scaling this technology. Biomedical informatics, which is the science of information in biomedicine, can provide helpful insights for this looming transition. Funneling MRIgRT data into clinically meaningful information streams requires committing to the flow of inter-institutional data accessibility and interoperability initiatives, standardizing MRIgRT dosimetry methods, streamlining MR linear accelerator workflow, and standardizing MRI acquisition and post-processing. This review will attempt to conceptually ford these topics using clinical informatics approaches as a theoretical bridge. Frontiers Media S.A. 2019-09-30 /pmc/articles/PMC6779062/ /pubmed/31632914 http://dx.doi.org/10.3389/fonc.2019.00983 Text en Copyright © 2019 Kiser, Smith, Wang and Fuller. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Oncology Kiser, Kendall J. Smith, Benjamin D. Wang, Jihong Fuller, Clifton D. “Après Mois, Le Déluge”: Preparing for the Coming Data Flood in the MRI-Guided Radiotherapy Era |
title | “Après Mois, Le Déluge”: Preparing for the Coming Data Flood in the MRI-Guided Radiotherapy Era |
title_full | “Après Mois, Le Déluge”: Preparing for the Coming Data Flood in the MRI-Guided Radiotherapy Era |
title_fullStr | “Après Mois, Le Déluge”: Preparing for the Coming Data Flood in the MRI-Guided Radiotherapy Era |
title_full_unstemmed | “Après Mois, Le Déluge”: Preparing for the Coming Data Flood in the MRI-Guided Radiotherapy Era |
title_short | “Après Mois, Le Déluge”: Preparing for the Coming Data Flood in the MRI-Guided Radiotherapy Era |
title_sort | “après mois, le déluge”: preparing for the coming data flood in the mri-guided radiotherapy era |
topic | Oncology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6779062/ https://www.ncbi.nlm.nih.gov/pubmed/31632914 http://dx.doi.org/10.3389/fonc.2019.00983 |
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