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CT-based ventilation imaging in radiation oncology
A form of lung function imaging is emerging that uses phase-resolved four-dimensional CT (4DCT or breath-hold CT) images along with image processing techniques to generate lung function maps that provide a surrogate of lung ventilation. CT-based ventilation (referred to as CT-ventilation) research h...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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The British Institute of Radiology.
2019
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7592480/ https://www.ncbi.nlm.nih.gov/pubmed/33178925 http://dx.doi.org/10.1259/bjro.20180035 |
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author | Vinogradskiy, Yevgeniy |
author_facet | Vinogradskiy, Yevgeniy |
author_sort | Vinogradskiy, Yevgeniy |
collection | PubMed |
description | A form of lung function imaging is emerging that uses phase-resolved four-dimensional CT (4DCT or breath-hold CT) images along with image processing techniques to generate lung function maps that provide a surrogate of lung ventilation. CT-based ventilation (referred to as CT-ventilation) research has gained momentum in Radiation Oncology because many lung cancer patients undergo four-dimensional CT simulation as part of the standard treatment planning process. Therefore, generating CT-ventilation images provides functional information without burdening the patient with an extra imaging procedure. CT-ventilation has progressed from an image processing calculation methodology, to validation efforts, to retrospective demonstration of clinical utility in Radiation Oncology. In particular, CT-ventilation has been proposed for two main clinical applications: functional avoidance radiation therapy and thoracic dose–response assessment. The idea of functional avoidance radiation therapy is to preferentially spare functional portions of the lung (as measured by CT-ventilation) during radiation therapy with the hypothesis that reducing dose to functional portions of the lung will lead to reduced rates of radiation-related thoracic toxicity. The idea of imaging-based dose–response assessment is to evaluate pre- to post-treatment CT-ventilation-based imaging changes. The hypothesis is that early, imaging-change-based response can be an early predictor of subsequent thoracic toxicity. Based on the retrospective evidence, the clinical applications of CT-ventilation have progressed from the retrospective setting to on-going prospective clinical trials. This review will cover basic CT-ventilation calculation methodologies, validation efforts, presentation of clinical applications, summarize on-going clinical trials, review potential uncertainties and shortcomings of CT-ventilation, and discuss future directions of CT-ventilation research. |
format | Online Article Text |
id | pubmed-7592480 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | The British Institute of Radiology. |
record_format | MEDLINE/PubMed |
spelling | pubmed-75924802020-11-10 CT-based ventilation imaging in radiation oncology Vinogradskiy, Yevgeniy BJR Open Review Article A form of lung function imaging is emerging that uses phase-resolved four-dimensional CT (4DCT or breath-hold CT) images along with image processing techniques to generate lung function maps that provide a surrogate of lung ventilation. CT-based ventilation (referred to as CT-ventilation) research has gained momentum in Radiation Oncology because many lung cancer patients undergo four-dimensional CT simulation as part of the standard treatment planning process. Therefore, generating CT-ventilation images provides functional information without burdening the patient with an extra imaging procedure. CT-ventilation has progressed from an image processing calculation methodology, to validation efforts, to retrospective demonstration of clinical utility in Radiation Oncology. In particular, CT-ventilation has been proposed for two main clinical applications: functional avoidance radiation therapy and thoracic dose–response assessment. The idea of functional avoidance radiation therapy is to preferentially spare functional portions of the lung (as measured by CT-ventilation) during radiation therapy with the hypothesis that reducing dose to functional portions of the lung will lead to reduced rates of radiation-related thoracic toxicity. The idea of imaging-based dose–response assessment is to evaluate pre- to post-treatment CT-ventilation-based imaging changes. The hypothesis is that early, imaging-change-based response can be an early predictor of subsequent thoracic toxicity. Based on the retrospective evidence, the clinical applications of CT-ventilation have progressed from the retrospective setting to on-going prospective clinical trials. This review will cover basic CT-ventilation calculation methodologies, validation efforts, presentation of clinical applications, summarize on-going clinical trials, review potential uncertainties and shortcomings of CT-ventilation, and discuss future directions of CT-ventilation research. The British Institute of Radiology. 2019-04-05 /pmc/articles/PMC7592480/ /pubmed/33178925 http://dx.doi.org/10.1259/bjro.20180035 Text en © 2019 The Authors. Published by the British Institute of Radiology This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution and reprhttp://creativecommons.org/licenses/by-nc/4.0/, which permits unrestricted non-commercial reuse, provided the original author and source are credited. |
spellingShingle | Review Article Vinogradskiy, Yevgeniy CT-based ventilation imaging in radiation oncology |
title | CT-based ventilation imaging in radiation oncology |
title_full | CT-based ventilation imaging in radiation oncology |
title_fullStr | CT-based ventilation imaging in radiation oncology |
title_full_unstemmed | CT-based ventilation imaging in radiation oncology |
title_short | CT-based ventilation imaging in radiation oncology |
title_sort | ct-based ventilation imaging in radiation oncology |
topic | Review Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7592480/ https://www.ncbi.nlm.nih.gov/pubmed/33178925 http://dx.doi.org/10.1259/bjro.20180035 |
work_keys_str_mv | AT vinogradskiyyevgeniy ctbasedventilationimaginginradiationoncology |