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Longitudinal radiomics of cone-beam CT images from non-small cell lung cancer patients: Evaluation of the added prognostic value for overall survival and locoregional recurrence
BACKGROUND AND PURPOSE: The prognostic value of radiomics for non-small cell lung cancer (NSCLC) patients has been investigated for images acquired prior to treatment, but no prognostic model has been developed that includes the change of radiomic features during treatment. Therefore, the aim of thi...
Autores principales: | , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier Scientific Publishers
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6598851/ https://www.ncbi.nlm.nih.gov/pubmed/31015133 http://dx.doi.org/10.1016/j.radonc.2019.03.032 |
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author | van Timmeren, Janna E. van Elmpt, Wouter Leijenaar, Ralph T.H. Reymen, Bart Monshouwer, René Bussink, Johan Paelinck, Leen Bogaert, Evelien De Wagter, Carlos Elhaseen, Elamin Lievens, Yolande Hansen, Olfred Brink, Carsten Lambin, Philippe |
author_facet | van Timmeren, Janna E. van Elmpt, Wouter Leijenaar, Ralph T.H. Reymen, Bart Monshouwer, René Bussink, Johan Paelinck, Leen Bogaert, Evelien De Wagter, Carlos Elhaseen, Elamin Lievens, Yolande Hansen, Olfred Brink, Carsten Lambin, Philippe |
author_sort | van Timmeren, Janna E. |
collection | PubMed |
description | BACKGROUND AND PURPOSE: The prognostic value of radiomics for non-small cell lung cancer (NSCLC) patients has been investigated for images acquired prior to treatment, but no prognostic model has been developed that includes the change of radiomic features during treatment. Therefore, the aim of this study was to investigate the potential added prognostic value of a longitudinal radiomics approach using cone-beam computed tomography (CBCT) for NSCLC patients. MATERIALS AND METHODS: This retrospective study includes a training dataset of 141 stage I–IV NSCLC patients and three external validation datasets of 94, 61 and 41 patients, all treated with curative intended (chemo)radiotherapy. The change of radiomic features extracted from CBCT images was summarized as the slope of a linear regression. The CBCT slope-features and CT-extracted features were used as input for a Cox proportional hazards model. Moreover, prognostic performance of clinical parameters was investigated for overall survival and locoregional recurrence. Model performances were assessed using the Kaplan–Meier curves and c-index. RESULTS: The radiomics model contained only CT-derived features and reached a c-index of 0.63 for overall survival and could be validated on the first validation dataset. No model for locoregional recurrence could be developed that validated on the validation datasets. The clinical parameters model could not be validated for either overall survival or locoregional recurrence. CONCLUSION: In this study we could not confirm our hypothesis that longitudinal CBCT-extracted radiomic features contribute to improved prognostic information. Moreover, performance of baseline radiomic features or clinical parameters was poor, probably affected by heterogeneity within and between datasets. |
format | Online Article Text |
id | pubmed-6598851 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Elsevier Scientific Publishers |
record_format | MEDLINE/PubMed |
spelling | pubmed-65988512019-07-11 Longitudinal radiomics of cone-beam CT images from non-small cell lung cancer patients: Evaluation of the added prognostic value for overall survival and locoregional recurrence van Timmeren, Janna E. van Elmpt, Wouter Leijenaar, Ralph T.H. Reymen, Bart Monshouwer, René Bussink, Johan Paelinck, Leen Bogaert, Evelien De Wagter, Carlos Elhaseen, Elamin Lievens, Yolande Hansen, Olfred Brink, Carsten Lambin, Philippe Radiother Oncol Article BACKGROUND AND PURPOSE: The prognostic value of radiomics for non-small cell lung cancer (NSCLC) patients has been investigated for images acquired prior to treatment, but no prognostic model has been developed that includes the change of radiomic features during treatment. Therefore, the aim of this study was to investigate the potential added prognostic value of a longitudinal radiomics approach using cone-beam computed tomography (CBCT) for NSCLC patients. MATERIALS AND METHODS: This retrospective study includes a training dataset of 141 stage I–IV NSCLC patients and three external validation datasets of 94, 61 and 41 patients, all treated with curative intended (chemo)radiotherapy. The change of radiomic features extracted from CBCT images was summarized as the slope of a linear regression. The CBCT slope-features and CT-extracted features were used as input for a Cox proportional hazards model. Moreover, prognostic performance of clinical parameters was investigated for overall survival and locoregional recurrence. Model performances were assessed using the Kaplan–Meier curves and c-index. RESULTS: The radiomics model contained only CT-derived features and reached a c-index of 0.63 for overall survival and could be validated on the first validation dataset. No model for locoregional recurrence could be developed that validated on the validation datasets. The clinical parameters model could not be validated for either overall survival or locoregional recurrence. CONCLUSION: In this study we could not confirm our hypothesis that longitudinal CBCT-extracted radiomic features contribute to improved prognostic information. Moreover, performance of baseline radiomic features or clinical parameters was poor, probably affected by heterogeneity within and between datasets. Elsevier Scientific Publishers 2019-07 /pmc/articles/PMC6598851/ /pubmed/31015133 http://dx.doi.org/10.1016/j.radonc.2019.03.032 Text en © 2019 The Authors http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Article van Timmeren, Janna E. van Elmpt, Wouter Leijenaar, Ralph T.H. Reymen, Bart Monshouwer, René Bussink, Johan Paelinck, Leen Bogaert, Evelien De Wagter, Carlos Elhaseen, Elamin Lievens, Yolande Hansen, Olfred Brink, Carsten Lambin, Philippe Longitudinal radiomics of cone-beam CT images from non-small cell lung cancer patients: Evaluation of the added prognostic value for overall survival and locoregional recurrence |
title | Longitudinal radiomics of cone-beam CT images from non-small cell lung cancer patients: Evaluation of the added prognostic value for overall survival and locoregional recurrence |
title_full | Longitudinal radiomics of cone-beam CT images from non-small cell lung cancer patients: Evaluation of the added prognostic value for overall survival and locoregional recurrence |
title_fullStr | Longitudinal radiomics of cone-beam CT images from non-small cell lung cancer patients: Evaluation of the added prognostic value for overall survival and locoregional recurrence |
title_full_unstemmed | Longitudinal radiomics of cone-beam CT images from non-small cell lung cancer patients: Evaluation of the added prognostic value for overall survival and locoregional recurrence |
title_short | Longitudinal radiomics of cone-beam CT images from non-small cell lung cancer patients: Evaluation of the added prognostic value for overall survival and locoregional recurrence |
title_sort | longitudinal radiomics of cone-beam ct images from non-small cell lung cancer patients: evaluation of the added prognostic value for overall survival and locoregional recurrence |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6598851/ https://www.ncbi.nlm.nih.gov/pubmed/31015133 http://dx.doi.org/10.1016/j.radonc.2019.03.032 |
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