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Delta-radiomics features during radiotherapy improve the prediction of late xerostomia

The response of the major salivary glands, the parotid glands, to radiation dose is patient-specific. This study was designed to investigate whether parotid gland changes seen in weekly CT during treatment, quantified by delta-radiomics features (Δfeatures), could improve the prediction of moderate-...

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Autores principales: van Dijk, Lisanne V., Langendijk, Johannes A., Zhai, Tian-Tian, Vedelaar, Thea A., Noordzij, Walter, Steenbakkers, Roel J. H. M., Sijtsema, Nanna M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6713775/
https://www.ncbi.nlm.nih.gov/pubmed/31462719
http://dx.doi.org/10.1038/s41598-019-48184-3
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author van Dijk, Lisanne V.
Langendijk, Johannes A.
Zhai, Tian-Tian
Vedelaar, Thea A.
Noordzij, Walter
Steenbakkers, Roel J. H. M.
Sijtsema, Nanna M.
author_facet van Dijk, Lisanne V.
Langendijk, Johannes A.
Zhai, Tian-Tian
Vedelaar, Thea A.
Noordzij, Walter
Steenbakkers, Roel J. H. M.
Sijtsema, Nanna M.
author_sort van Dijk, Lisanne V.
collection PubMed
description The response of the major salivary glands, the parotid glands, to radiation dose is patient-specific. This study was designed to investigate whether parotid gland changes seen in weekly CT during treatment, quantified by delta-radiomics features (Δfeatures), could improve the prediction of moderate-to-severe xerostomia at 12 months after radiotherapy (Xer(12m)). Parotid gland Δfeatures were extracted from in total 68 planning and 340 weekly CTs, representing geometric, intensity and texture characteristics. Bootstrapped forward variable selection was performed to identify the best predictors of Xer(12m). The predictive contribution of the resulting Δfeatures to a pre-treatment reference model, based on contralateral parotid gland mean dose and baseline xerostomia scores (Xer(baseline)) only, was evaluated. Xer(12m) was reported by 26 (38%) of the 68 patients included. The most predictive Δfeature was the contralateral parotid gland surface change, which was significantly associated with Xer(12m) for all weeks (p < 0.04), but performed best for week 3 (ΔPG-surface(w3); p < 0.001). Moreover, ∆PG-surface(w3) showed a significant predictive contribution in addition to the pre-treatment reference model (likelihood-ratio test; p = 0.003), resulting in a significantly better model performance (AUC(train) = 0.92; AUC(test) = 0.93) compared to that of the pre-treatment model (AUC(train) = 0.82; AUC(test) = 0.82). These results suggest that mid-treatment parotid gland changes substantially improve the prediction of late radiation-induced xerostomia.
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spelling pubmed-67137752019-09-13 Delta-radiomics features during radiotherapy improve the prediction of late xerostomia van Dijk, Lisanne V. Langendijk, Johannes A. Zhai, Tian-Tian Vedelaar, Thea A. Noordzij, Walter Steenbakkers, Roel J. H. M. Sijtsema, Nanna M. Sci Rep Article The response of the major salivary glands, the parotid glands, to radiation dose is patient-specific. This study was designed to investigate whether parotid gland changes seen in weekly CT during treatment, quantified by delta-radiomics features (Δfeatures), could improve the prediction of moderate-to-severe xerostomia at 12 months after radiotherapy (Xer(12m)). Parotid gland Δfeatures were extracted from in total 68 planning and 340 weekly CTs, representing geometric, intensity and texture characteristics. Bootstrapped forward variable selection was performed to identify the best predictors of Xer(12m). The predictive contribution of the resulting Δfeatures to a pre-treatment reference model, based on contralateral parotid gland mean dose and baseline xerostomia scores (Xer(baseline)) only, was evaluated. Xer(12m) was reported by 26 (38%) of the 68 patients included. The most predictive Δfeature was the contralateral parotid gland surface change, which was significantly associated with Xer(12m) for all weeks (p < 0.04), but performed best for week 3 (ΔPG-surface(w3); p < 0.001). Moreover, ∆PG-surface(w3) showed a significant predictive contribution in addition to the pre-treatment reference model (likelihood-ratio test; p = 0.003), resulting in a significantly better model performance (AUC(train) = 0.92; AUC(test) = 0.93) compared to that of the pre-treatment model (AUC(train) = 0.82; AUC(test) = 0.82). These results suggest that mid-treatment parotid gland changes substantially improve the prediction of late radiation-induced xerostomia. Nature Publishing Group UK 2019-08-28 /pmc/articles/PMC6713775/ /pubmed/31462719 http://dx.doi.org/10.1038/s41598-019-48184-3 Text en © The Author(s) 2019 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 license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
van Dijk, Lisanne V.
Langendijk, Johannes A.
Zhai, Tian-Tian
Vedelaar, Thea A.
Noordzij, Walter
Steenbakkers, Roel J. H. M.
Sijtsema, Nanna M.
Delta-radiomics features during radiotherapy improve the prediction of late xerostomia
title Delta-radiomics features during radiotherapy improve the prediction of late xerostomia
title_full Delta-radiomics features during radiotherapy improve the prediction of late xerostomia
title_fullStr Delta-radiomics features during radiotherapy improve the prediction of late xerostomia
title_full_unstemmed Delta-radiomics features during radiotherapy improve the prediction of late xerostomia
title_short Delta-radiomics features during radiotherapy improve the prediction of late xerostomia
title_sort delta-radiomics features during radiotherapy improve the prediction of late xerostomia
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6713775/
https://www.ncbi.nlm.nih.gov/pubmed/31462719
http://dx.doi.org/10.1038/s41598-019-48184-3
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