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Evaluating the Necessity of Adaptive RT and the Role of Deformable Image Registration in Lung Cancer with Different Pathologic Classifications
Background: This study aimed to analyze differential radiotherapy (RT) responses according to the pathological type of lung cancer to see the possibility of applying adaptive radiotherapy (ART). Methods: ART planning with resampled-computed tomography was conducted for a total of 30 patients (20 non...
Autores principales: | , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10527903/ https://www.ncbi.nlm.nih.gov/pubmed/37761323 http://dx.doi.org/10.3390/diagnostics13182956 |
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author | Kim, Woo Chul Won, Yong Kyun Lee, Sang Mi Heo, Nam Hun Yeo, Seung-Gu Chang, Ah Ram Bae, Sun Hyun Kim, Jae Sik Yoo, Ik Dong Hong, Sun-pyo Min, Chul Kee Jo, In Young Kim, Eun Seog |
author_facet | Kim, Woo Chul Won, Yong Kyun Lee, Sang Mi Heo, Nam Hun Yeo, Seung-Gu Chang, Ah Ram Bae, Sun Hyun Kim, Jae Sik Yoo, Ik Dong Hong, Sun-pyo Min, Chul Kee Jo, In Young Kim, Eun Seog |
author_sort | Kim, Woo Chul |
collection | PubMed |
description | Background: This study aimed to analyze differential radiotherapy (RT) responses according to the pathological type of lung cancer to see the possibility of applying adaptive radiotherapy (ART). Methods: ART planning with resampled-computed tomography was conducted for a total of 30 patients (20 non-small-cell lung cancer patients and 10 small-cell lung cancer patients) using a deformable image registration technique to reveal gross tumor volume (GTV) changes according to the duration of RT. Results: The small-cell lung cancer group demonstrated an average GTV reduction of 20.95% after the first week of initial treatment (p = 0.001), whereas the adenocarcinoma and squamous cell carcinoma groups showed an average volume reduction of 20.47% (p = 0.015) and 12.68% in the second week. The application of ART according to the timing of GTV reduction has been shown to affect changes in radiation dose irradiated to normal tissues. This suggests that ART applications may have to be different depending on pathological differences in lung cancer. Conclusion: Through these results, the present study proposes the possibility of personalized treatment options for individual patients by individualizing ART based on specific radiation responses by pathologic types of lung cancer. |
format | Online Article Text |
id | pubmed-10527903 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-105279032023-09-28 Evaluating the Necessity of Adaptive RT and the Role of Deformable Image Registration in Lung Cancer with Different Pathologic Classifications Kim, Woo Chul Won, Yong Kyun Lee, Sang Mi Heo, Nam Hun Yeo, Seung-Gu Chang, Ah Ram Bae, Sun Hyun Kim, Jae Sik Yoo, Ik Dong Hong, Sun-pyo Min, Chul Kee Jo, In Young Kim, Eun Seog Diagnostics (Basel) Article Background: This study aimed to analyze differential radiotherapy (RT) responses according to the pathological type of lung cancer to see the possibility of applying adaptive radiotherapy (ART). Methods: ART planning with resampled-computed tomography was conducted for a total of 30 patients (20 non-small-cell lung cancer patients and 10 small-cell lung cancer patients) using a deformable image registration technique to reveal gross tumor volume (GTV) changes according to the duration of RT. Results: The small-cell lung cancer group demonstrated an average GTV reduction of 20.95% after the first week of initial treatment (p = 0.001), whereas the adenocarcinoma and squamous cell carcinoma groups showed an average volume reduction of 20.47% (p = 0.015) and 12.68% in the second week. The application of ART according to the timing of GTV reduction has been shown to affect changes in radiation dose irradiated to normal tissues. This suggests that ART applications may have to be different depending on pathological differences in lung cancer. Conclusion: Through these results, the present study proposes the possibility of personalized treatment options for individual patients by individualizing ART based on specific radiation responses by pathologic types of lung cancer. MDPI 2023-09-15 /pmc/articles/PMC10527903/ /pubmed/37761323 http://dx.doi.org/10.3390/diagnostics13182956 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Kim, Woo Chul Won, Yong Kyun Lee, Sang Mi Heo, Nam Hun Yeo, Seung-Gu Chang, Ah Ram Bae, Sun Hyun Kim, Jae Sik Yoo, Ik Dong Hong, Sun-pyo Min, Chul Kee Jo, In Young Kim, Eun Seog Evaluating the Necessity of Adaptive RT and the Role of Deformable Image Registration in Lung Cancer with Different Pathologic Classifications |
title | Evaluating the Necessity of Adaptive RT and the Role of Deformable Image Registration in Lung Cancer with Different Pathologic Classifications |
title_full | Evaluating the Necessity of Adaptive RT and the Role of Deformable Image Registration in Lung Cancer with Different Pathologic Classifications |
title_fullStr | Evaluating the Necessity of Adaptive RT and the Role of Deformable Image Registration in Lung Cancer with Different Pathologic Classifications |
title_full_unstemmed | Evaluating the Necessity of Adaptive RT and the Role of Deformable Image Registration in Lung Cancer with Different Pathologic Classifications |
title_short | Evaluating the Necessity of Adaptive RT and the Role of Deformable Image Registration in Lung Cancer with Different Pathologic Classifications |
title_sort | evaluating the necessity of adaptive rt and the role of deformable image registration in lung cancer with different pathologic classifications |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10527903/ https://www.ncbi.nlm.nih.gov/pubmed/37761323 http://dx.doi.org/10.3390/diagnostics13182956 |
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