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Evaluation of the MVCT-based radiomic features as prognostic factor in patients with head and neck squamous cell carcinoma

BACKGROUND: Megavoltage computed tomography (MVCT) images acquired during each radiotherapy session may be useful for delta radiomics. However, no studies have examined whether the MVCT-based radiomics has prognostic power. Therefore, the purpose of this study was to examine the prognostic power of...

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Autores principales: Abe, Kota, Kadoya, Noriyuki, Ito, Kei, Tanaka, Shohei, Nakajima, Yujiro, Hashimoto, Shimpei, Suda, Yuhi, Uno, Takashi, Jingu, Keiichi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10391970/
https://www.ncbi.nlm.nih.gov/pubmed/37528392
http://dx.doi.org/10.1186/s12880-023-01055-w
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author Abe, Kota
Kadoya, Noriyuki
Ito, Kei
Tanaka, Shohei
Nakajima, Yujiro
Hashimoto, Shimpei
Suda, Yuhi
Uno, Takashi
Jingu, Keiichi
author_facet Abe, Kota
Kadoya, Noriyuki
Ito, Kei
Tanaka, Shohei
Nakajima, Yujiro
Hashimoto, Shimpei
Suda, Yuhi
Uno, Takashi
Jingu, Keiichi
author_sort Abe, Kota
collection PubMed
description BACKGROUND: Megavoltage computed tomography (MVCT) images acquired during each radiotherapy session may be useful for delta radiomics. However, no studies have examined whether the MVCT-based radiomics has prognostic power. Therefore, the purpose of this study was to examine the prognostic power of the MVCT-based radiomics for head and neck squamous cell carcinoma (HNSCC) patients. METHODS: 100 HNSCC patients who received definitive radiotherapy were analyzed and divided into two groups: training (n = 70) and test (n = 30) sets. MVCT images obtained using TomoTherapy for the first fraction of radiotherapy and planning kilovoltage CT (kVCT) images obtained using Aquilion LB CT scanner were analyzed. Primary gross tumor volume (GTV) was propagated from kVCT to MVCT images using rigid registration, and 107 radiomic features were extracted from the GTV in MVCT and kVCT images. Least absolute shrinkage and selection operator (LASSO) Cox regression model was used to examine the association between overall survival (OS) and rad score calculated for each patient by weighting the feature value through the coefficient when features were selected. Then, the predictive values of MVCT-based and kVCT-based rad score and patient-, treatment-, and tumor-specific factors were evaluated. RESULTS: C-indices of the rad score for MVCT- and kVCT-based radiomics were 0.667 and 0.685, respectively. The C-indices of 6 clinical factors were 0.538–0.622. The 3-year OS was significantly different between high- and low-risk groups according to the MVCT-based rad score (50% vs. 83%; p < 0.01). CONCLUSIONS: Our results suggested that MVCT-based radiomics had stronger prognostic power than any single clinical factor and was a useful prognostic factor when predicting OS in HNSCC patients. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12880-023-01055-w.
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spelling pubmed-103919702023-08-02 Evaluation of the MVCT-based radiomic features as prognostic factor in patients with head and neck squamous cell carcinoma Abe, Kota Kadoya, Noriyuki Ito, Kei Tanaka, Shohei Nakajima, Yujiro Hashimoto, Shimpei Suda, Yuhi Uno, Takashi Jingu, Keiichi BMC Med Imaging Research BACKGROUND: Megavoltage computed tomography (MVCT) images acquired during each radiotherapy session may be useful for delta radiomics. However, no studies have examined whether the MVCT-based radiomics has prognostic power. Therefore, the purpose of this study was to examine the prognostic power of the MVCT-based radiomics for head and neck squamous cell carcinoma (HNSCC) patients. METHODS: 100 HNSCC patients who received definitive radiotherapy were analyzed and divided into two groups: training (n = 70) and test (n = 30) sets. MVCT images obtained using TomoTherapy for the first fraction of radiotherapy and planning kilovoltage CT (kVCT) images obtained using Aquilion LB CT scanner were analyzed. Primary gross tumor volume (GTV) was propagated from kVCT to MVCT images using rigid registration, and 107 radiomic features were extracted from the GTV in MVCT and kVCT images. Least absolute shrinkage and selection operator (LASSO) Cox regression model was used to examine the association between overall survival (OS) and rad score calculated for each patient by weighting the feature value through the coefficient when features were selected. Then, the predictive values of MVCT-based and kVCT-based rad score and patient-, treatment-, and tumor-specific factors were evaluated. RESULTS: C-indices of the rad score for MVCT- and kVCT-based radiomics were 0.667 and 0.685, respectively. The C-indices of 6 clinical factors were 0.538–0.622. The 3-year OS was significantly different between high- and low-risk groups according to the MVCT-based rad score (50% vs. 83%; p < 0.01). CONCLUSIONS: Our results suggested that MVCT-based radiomics had stronger prognostic power than any single clinical factor and was a useful prognostic factor when predicting OS in HNSCC patients. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12880-023-01055-w. BioMed Central 2023-08-01 /pmc/articles/PMC10391970/ /pubmed/37528392 http://dx.doi.org/10.1186/s12880-023-01055-w Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Abe, Kota
Kadoya, Noriyuki
Ito, Kei
Tanaka, Shohei
Nakajima, Yujiro
Hashimoto, Shimpei
Suda, Yuhi
Uno, Takashi
Jingu, Keiichi
Evaluation of the MVCT-based radiomic features as prognostic factor in patients with head and neck squamous cell carcinoma
title Evaluation of the MVCT-based radiomic features as prognostic factor in patients with head and neck squamous cell carcinoma
title_full Evaluation of the MVCT-based radiomic features as prognostic factor in patients with head and neck squamous cell carcinoma
title_fullStr Evaluation of the MVCT-based radiomic features as prognostic factor in patients with head and neck squamous cell carcinoma
title_full_unstemmed Evaluation of the MVCT-based radiomic features as prognostic factor in patients with head and neck squamous cell carcinoma
title_short Evaluation of the MVCT-based radiomic features as prognostic factor in patients with head and neck squamous cell carcinoma
title_sort evaluation of the mvct-based radiomic features as prognostic factor in patients with head and neck squamous cell carcinoma
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10391970/
https://www.ncbi.nlm.nih.gov/pubmed/37528392
http://dx.doi.org/10.1186/s12880-023-01055-w
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