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Monitoring Breast Cancer Response to Neoadjuvant Chemotherapy Using Ultrasound Strain Elastography

Strain elastography was used to monitor response to neoadjuvant chemotherapy (NAC) in 92 patients with biopsy-proven, locally advanced breast cancer. Strain elastography data were collected before, during, and after NAC. Relative changes in tumor strain ratio (SR) were calculated over time, and resp...

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Autores principales: Fernandes, Jason, Sannachi, Lakshmanan, Tran, William T., Koven, Alexander, Watkins, Elyse, Hadizad, Farnoosh, Gandhi, Sonal, Wright, Frances, Curpen, Belinda, El Kaffas, Ahmed, Faltyn, Joanna, Sadeghi-Naini, Ali, Czarnota, Gregory
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Neoplasia Press 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6586920/
https://www.ncbi.nlm.nih.gov/pubmed/31226518
http://dx.doi.org/10.1016/j.tranon.2019.05.004
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author Fernandes, Jason
Sannachi, Lakshmanan
Tran, William T.
Koven, Alexander
Watkins, Elyse
Hadizad, Farnoosh
Gandhi, Sonal
Wright, Frances
Curpen, Belinda
El Kaffas, Ahmed
Faltyn, Joanna
Sadeghi-Naini, Ali
Czarnota, Gregory
author_facet Fernandes, Jason
Sannachi, Lakshmanan
Tran, William T.
Koven, Alexander
Watkins, Elyse
Hadizad, Farnoosh
Gandhi, Sonal
Wright, Frances
Curpen, Belinda
El Kaffas, Ahmed
Faltyn, Joanna
Sadeghi-Naini, Ali
Czarnota, Gregory
author_sort Fernandes, Jason
collection PubMed
description Strain elastography was used to monitor response to neoadjuvant chemotherapy (NAC) in 92 patients with biopsy-proven, locally advanced breast cancer. Strain elastography data were collected before, during, and after NAC. Relative changes in tumor strain ratio (SR) were calculated over time, and responder status was classified according to tumor size changes. Statistical analyses determined the significance of changes in SR over time and between response groups. Machine learning techniques, such as a naïve Bayes classifier, were used to evaluate the performance of the SR as a marker for Miller-Payne pathological endpoints. With pathological complete response (pCR) as an endpoint, a significant difference (P < .01) in the SR was observed between response groups as early as 2 weeks into NAC. Naïve Bayes classifiers predicted pCR with a sensitivity of 84%, specificity of 85%, and area under the curve of 81% at the preoperative scan. This study demonstrates that strain elastography may be predictive of NAC response in locally advanced breast cancer as early as 2 weeks into treatment, with high sensitivity and specificity, granting it the potential to be used for active monitoring of tumor response to chemotherapy.
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spelling pubmed-65869202019-06-27 Monitoring Breast Cancer Response to Neoadjuvant Chemotherapy Using Ultrasound Strain Elastography Fernandes, Jason Sannachi, Lakshmanan Tran, William T. Koven, Alexander Watkins, Elyse Hadizad, Farnoosh Gandhi, Sonal Wright, Frances Curpen, Belinda El Kaffas, Ahmed Faltyn, Joanna Sadeghi-Naini, Ali Czarnota, Gregory Transl Oncol Original article Strain elastography was used to monitor response to neoadjuvant chemotherapy (NAC) in 92 patients with biopsy-proven, locally advanced breast cancer. Strain elastography data were collected before, during, and after NAC. Relative changes in tumor strain ratio (SR) were calculated over time, and responder status was classified according to tumor size changes. Statistical analyses determined the significance of changes in SR over time and between response groups. Machine learning techniques, such as a naïve Bayes classifier, were used to evaluate the performance of the SR as a marker for Miller-Payne pathological endpoints. With pathological complete response (pCR) as an endpoint, a significant difference (P < .01) in the SR was observed between response groups as early as 2 weeks into NAC. Naïve Bayes classifiers predicted pCR with a sensitivity of 84%, specificity of 85%, and area under the curve of 81% at the preoperative scan. This study demonstrates that strain elastography may be predictive of NAC response in locally advanced breast cancer as early as 2 weeks into treatment, with high sensitivity and specificity, granting it the potential to be used for active monitoring of tumor response to chemotherapy. Neoplasia Press 2019-06-18 /pmc/articles/PMC6586920/ /pubmed/31226518 http://dx.doi.org/10.1016/j.tranon.2019.05.004 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 Original article
Fernandes, Jason
Sannachi, Lakshmanan
Tran, William T.
Koven, Alexander
Watkins, Elyse
Hadizad, Farnoosh
Gandhi, Sonal
Wright, Frances
Curpen, Belinda
El Kaffas, Ahmed
Faltyn, Joanna
Sadeghi-Naini, Ali
Czarnota, Gregory
Monitoring Breast Cancer Response to Neoadjuvant Chemotherapy Using Ultrasound Strain Elastography
title Monitoring Breast Cancer Response to Neoadjuvant Chemotherapy Using Ultrasound Strain Elastography
title_full Monitoring Breast Cancer Response to Neoadjuvant Chemotherapy Using Ultrasound Strain Elastography
title_fullStr Monitoring Breast Cancer Response to Neoadjuvant Chemotherapy Using Ultrasound Strain Elastography
title_full_unstemmed Monitoring Breast Cancer Response to Neoadjuvant Chemotherapy Using Ultrasound Strain Elastography
title_short Monitoring Breast Cancer Response to Neoadjuvant Chemotherapy Using Ultrasound Strain Elastography
title_sort monitoring breast cancer response to neoadjuvant chemotherapy using ultrasound strain elastography
topic Original article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6586920/
https://www.ncbi.nlm.nih.gov/pubmed/31226518
http://dx.doi.org/10.1016/j.tranon.2019.05.004
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