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Automated customized retrieval of radiotherapy data for clinical trials, audit and research
OBJECTIVE: To enable fast and customizable automated collection of radiotherapy (RT) data from tomotherapy storage. METHODS: Human-readable data maps (TagMaps) were created to generate DICOM-RT (Digital Imaging and Communications in Medicine standard for Radiation Therapy) data from tomotherapy arch...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The British Institute of Radiology.
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5965461/ https://www.ncbi.nlm.nih.gov/pubmed/29125328 http://dx.doi.org/10.1259/bjr.20170651 |
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author | Romanchikova, Marina Harrison, Karl Burnet, Neil G Hoole, Andrew CF Sutcliffe, Michael PF Parker, Michael Andrew Jena, Rajesh Thomas, Simon James |
author_facet | Romanchikova, Marina Harrison, Karl Burnet, Neil G Hoole, Andrew CF Sutcliffe, Michael PF Parker, Michael Andrew Jena, Rajesh Thomas, Simon James |
author_sort | Romanchikova, Marina |
collection | PubMed |
description | OBJECTIVE: To enable fast and customizable automated collection of radiotherapy (RT) data from tomotherapy storage. METHODS: Human-readable data maps (TagMaps) were created to generate DICOM-RT (Digital Imaging and Communications in Medicine standard for Radiation Therapy) data from tomotherapy archives, and provided access to “hidden” information comprising delivery sinograms, positional corrections and adaptive-RT doses. RESULTS: 797 data sets totalling 25,000 scans were batch-exported in 31.5 h. All archived information was restored, including the data not available via commercial software. The exported data were DICOM-compliant and compatible with major commercial tools including RayStation, Pinnacle and ProSoma. The export ran without operator interventions. CONCLUSION: The TagMap method for DICOM-RT data modelling produced software that was many times faster than the vendor’s solution, required minimal operator input and delivered high volumes of vendor-identical DICOM data. The approach is applicable to many clinical and research data processing scenarios and can be adapted to recover DICOM-RT data from other proprietary storage types such as Elekta, Pinnacle or ProSoma. ADVANCES IN KNOWLEDGE: A novel method to translate data from proprietary storage to DICOM-RT is presented. It provides access to the data hidden in electronic archives, offers a working solution to the issues of data migration and vendor lock-in and paves the way for large-scale imaging and radiomics studies. |
format | Online Article Text |
id | pubmed-5965461 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | The British Institute of Radiology. |
record_format | MEDLINE/PubMed |
spelling | pubmed-59654612019-03-01 Automated customized retrieval of radiotherapy data for clinical trials, audit and research Romanchikova, Marina Harrison, Karl Burnet, Neil G Hoole, Andrew CF Sutcliffe, Michael PF Parker, Michael Andrew Jena, Rajesh Thomas, Simon James Br J Radiol Short Communication OBJECTIVE: To enable fast and customizable automated collection of radiotherapy (RT) data from tomotherapy storage. METHODS: Human-readable data maps (TagMaps) were created to generate DICOM-RT (Digital Imaging and Communications in Medicine standard for Radiation Therapy) data from tomotherapy archives, and provided access to “hidden” information comprising delivery sinograms, positional corrections and adaptive-RT doses. RESULTS: 797 data sets totalling 25,000 scans were batch-exported in 31.5 h. All archived information was restored, including the data not available via commercial software. The exported data were DICOM-compliant and compatible with major commercial tools including RayStation, Pinnacle and ProSoma. The export ran without operator interventions. CONCLUSION: The TagMap method for DICOM-RT data modelling produced software that was many times faster than the vendor’s solution, required minimal operator input and delivered high volumes of vendor-identical DICOM data. The approach is applicable to many clinical and research data processing scenarios and can be adapted to recover DICOM-RT data from other proprietary storage types such as Elekta, Pinnacle or ProSoma. ADVANCES IN KNOWLEDGE: A novel method to translate data from proprietary storage to DICOM-RT is presented. It provides access to the data hidden in electronic archives, offers a working solution to the issues of data migration and vendor lock-in and paves the way for large-scale imaging and radiomics studies. The British Institute of Radiology. 2018-03 2018-01-31 /pmc/articles/PMC5965461/ /pubmed/29125328 http://dx.doi.org/10.1259/bjr.20170651 Text en © 2018 The Authors. Published by the British Institute of Radiology. https://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution 4.0 Unported License https://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 | Short Communication Romanchikova, Marina Harrison, Karl Burnet, Neil G Hoole, Andrew CF Sutcliffe, Michael PF Parker, Michael Andrew Jena, Rajesh Thomas, Simon James Automated customized retrieval of radiotherapy data for clinical trials, audit and research |
title | Automated customized retrieval of radiotherapy data for clinical trials, audit and research |
title_full | Automated customized retrieval of radiotherapy data for clinical trials, audit and research |
title_fullStr | Automated customized retrieval of radiotherapy data for clinical trials, audit and research |
title_full_unstemmed | Automated customized retrieval of radiotherapy data for clinical trials, audit and research |
title_short | Automated customized retrieval of radiotherapy data for clinical trials, audit and research |
title_sort | automated customized retrieval of radiotherapy data for clinical trials, audit and research |
topic | Short Communication |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5965461/ https://www.ncbi.nlm.nih.gov/pubmed/29125328 http://dx.doi.org/10.1259/bjr.20170651 |
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