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Quantitative ultrasound delta-radiomics during radiotherapy for monitoring treatment responses in head and neck malignancies
AIM: We investigated quantitative ultrasound (QUS) in patients with node-positive head and neck malignancies for monitoring responses to radical radiotherapy (RT). MATERIALS & METHODS: QUS spectral and texture parameters were acquired from metastatic lymph nodes 24 h, 1 and 4 weeks after startin...
Autores principales: | , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Future Science Ltd
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7668124/ https://www.ncbi.nlm.nih.gov/pubmed/33235811 http://dx.doi.org/10.2144/fsoa-2020-0073 |
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author | Tran, William T Suraweera, Harini Quiaoit, Karina DiCenzo, Daniel Fatima, Kashuf Jang, Deok Bhardwaj, Divya Kolios, Christopher Karam, Irene Poon, Ian Sannachi, Lakshmanan Gangeh, Mehrdad Sadeghi-Naini, Ali Dasgupta, Archya Czarnota, Gregory J |
author_facet | Tran, William T Suraweera, Harini Quiaoit, Karina DiCenzo, Daniel Fatima, Kashuf Jang, Deok Bhardwaj, Divya Kolios, Christopher Karam, Irene Poon, Ian Sannachi, Lakshmanan Gangeh, Mehrdad Sadeghi-Naini, Ali Dasgupta, Archya Czarnota, Gregory J |
author_sort | Tran, William T |
collection | PubMed |
description | AIM: We investigated quantitative ultrasound (QUS) in patients with node-positive head and neck malignancies for monitoring responses to radical radiotherapy (RT). MATERIALS & METHODS: QUS spectral and texture parameters were acquired from metastatic lymph nodes 24 h, 1 and 4 weeks after starting RT. K-nearest neighbor and naive-Bayes machine-learning classifiers were used to build prediction models for each time point. Response was detected after 3 months of RT, and patients were classified into complete and partial responders. RESULTS: Single-feature naive-Bayes classification performed best with a prediction accuracy of 80, 86 and 85% at 24 h, week 1 and 4, respectively. CONCLUSION: QUS-radiomics can predict RT response at 3 months as early as 24 h with reasonable accuracy, which further improves into 1 week of treatment. |
format | Online Article Text |
id | pubmed-7668124 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Future Science Ltd |
record_format | MEDLINE/PubMed |
spelling | pubmed-76681242020-11-23 Quantitative ultrasound delta-radiomics during radiotherapy for monitoring treatment responses in head and neck malignancies Tran, William T Suraweera, Harini Quiaoit, Karina DiCenzo, Daniel Fatima, Kashuf Jang, Deok Bhardwaj, Divya Kolios, Christopher Karam, Irene Poon, Ian Sannachi, Lakshmanan Gangeh, Mehrdad Sadeghi-Naini, Ali Dasgupta, Archya Czarnota, Gregory J Future Sci OA Research Article AIM: We investigated quantitative ultrasound (QUS) in patients with node-positive head and neck malignancies for monitoring responses to radical radiotherapy (RT). MATERIALS & METHODS: QUS spectral and texture parameters were acquired from metastatic lymph nodes 24 h, 1 and 4 weeks after starting RT. K-nearest neighbor and naive-Bayes machine-learning classifiers were used to build prediction models for each time point. Response was detected after 3 months of RT, and patients were classified into complete and partial responders. RESULTS: Single-feature naive-Bayes classification performed best with a prediction accuracy of 80, 86 and 85% at 24 h, week 1 and 4, respectively. CONCLUSION: QUS-radiomics can predict RT response at 3 months as early as 24 h with reasonable accuracy, which further improves into 1 week of treatment. Future Science Ltd 2020-09-04 /pmc/articles/PMC7668124/ /pubmed/33235811 http://dx.doi.org/10.2144/fsoa-2020-0073 Text en © 2020 Gregory J Czarnota This work is licensed under the Creative Commons Attribution 4.0 License (http://creativecommons.org/licenses/by/4.0/) |
spellingShingle | Research Article Tran, William T Suraweera, Harini Quiaoit, Karina DiCenzo, Daniel Fatima, Kashuf Jang, Deok Bhardwaj, Divya Kolios, Christopher Karam, Irene Poon, Ian Sannachi, Lakshmanan Gangeh, Mehrdad Sadeghi-Naini, Ali Dasgupta, Archya Czarnota, Gregory J Quantitative ultrasound delta-radiomics during radiotherapy for monitoring treatment responses in head and neck malignancies |
title | Quantitative ultrasound delta-radiomics during radiotherapy for monitoring treatment responses in head and neck malignancies |
title_full | Quantitative ultrasound delta-radiomics during radiotherapy for monitoring treatment responses in head and neck malignancies |
title_fullStr | Quantitative ultrasound delta-radiomics during radiotherapy for monitoring treatment responses in head and neck malignancies |
title_full_unstemmed | Quantitative ultrasound delta-radiomics during radiotherapy for monitoring treatment responses in head and neck malignancies |
title_short | Quantitative ultrasound delta-radiomics during radiotherapy for monitoring treatment responses in head and neck malignancies |
title_sort | quantitative ultrasound delta-radiomics during radiotherapy for monitoring treatment responses in head and neck malignancies |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7668124/ https://www.ncbi.nlm.nih.gov/pubmed/33235811 http://dx.doi.org/10.2144/fsoa-2020-0073 |
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