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Early prediction of therapy responses and outcomes in breast cancer patients using quantitative ultrasound spectral texture

Early alterations in textural characteristics of quantitative ultrasound spectral parametric maps, in conjunction with changes in their mean values, are demonstrated here, for the first time, to be capable of predicting ultimate clinical/pathologic responses of breast cancer patients to chemotherapy...

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Autores principales: Sadeghi-Naini, Ali, Sannachi, Lakshmanan, Pritchard, Kathleen, Trudeau, Maureen, Gandhi, Sonal, Wright, Frances C., Zubovits, Judit, Yaffe, Martin J., Kolios, Michael C., Czarnota, Gregory J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Impact Journals LLC 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4116498/
https://www.ncbi.nlm.nih.gov/pubmed/24939867
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author Sadeghi-Naini, Ali
Sannachi, Lakshmanan
Pritchard, Kathleen
Trudeau, Maureen
Gandhi, Sonal
Wright, Frances C.
Zubovits, Judit
Yaffe, Martin J.
Kolios, Michael C.
Czarnota, Gregory J.
author_facet Sadeghi-Naini, Ali
Sannachi, Lakshmanan
Pritchard, Kathleen
Trudeau, Maureen
Gandhi, Sonal
Wright, Frances C.
Zubovits, Judit
Yaffe, Martin J.
Kolios, Michael C.
Czarnota, Gregory J.
author_sort Sadeghi-Naini, Ali
collection PubMed
description Early alterations in textural characteristics of quantitative ultrasound spectral parametric maps, in conjunction with changes in their mean values, are demonstrated here, for the first time, to be capable of predicting ultimate clinical/pathologic responses of breast cancer patients to chemotherapy. Mechanisms of cell death, induced by chemotherapy within tumor, introduce morphological alterations in cancerous cells, resulting in measurable changes in tissue echogenicity. We have demonstrated that the development of such changes is reflected in early alterations in textural characteristics of quantitative ultrasound spectral parametric maps, followed by consequent changes in their mean values. The spectral/textural biomarkers derived on this basis have been demonstrated as non-invasive surrogates of breast cancer chemotherapy response. Particularly, spectral biomarkers sensitive to the size and concentration of acoustic scatterers could predict treatment response of patients with up to 80% of sensitivity and specificity (p=0.050), after one week within 3-4 months of chemotherapy. However, textural biomarkers characterizing heterogeneities in distribution of acoustic scatterers, could differentiate between treatment responding and non-responding patients with up to 100% sensitivity and 93% specificity (p=0.002). Such early prediction permits offering effective alternatives to standard treatment, or switching to a salvage therapy, for refractory patients.
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spelling pubmed-41164982014-08-04 Early prediction of therapy responses and outcomes in breast cancer patients using quantitative ultrasound spectral texture Sadeghi-Naini, Ali Sannachi, Lakshmanan Pritchard, Kathleen Trudeau, Maureen Gandhi, Sonal Wright, Frances C. Zubovits, Judit Yaffe, Martin J. Kolios, Michael C. Czarnota, Gregory J. Oncotarget Research Paper Early alterations in textural characteristics of quantitative ultrasound spectral parametric maps, in conjunction with changes in their mean values, are demonstrated here, for the first time, to be capable of predicting ultimate clinical/pathologic responses of breast cancer patients to chemotherapy. Mechanisms of cell death, induced by chemotherapy within tumor, introduce morphological alterations in cancerous cells, resulting in measurable changes in tissue echogenicity. We have demonstrated that the development of such changes is reflected in early alterations in textural characteristics of quantitative ultrasound spectral parametric maps, followed by consequent changes in their mean values. The spectral/textural biomarkers derived on this basis have been demonstrated as non-invasive surrogates of breast cancer chemotherapy response. Particularly, spectral biomarkers sensitive to the size and concentration of acoustic scatterers could predict treatment response of patients with up to 80% of sensitivity and specificity (p=0.050), after one week within 3-4 months of chemotherapy. However, textural biomarkers characterizing heterogeneities in distribution of acoustic scatterers, could differentiate between treatment responding and non-responding patients with up to 100% sensitivity and 93% specificity (p=0.002). Such early prediction permits offering effective alternatives to standard treatment, or switching to a salvage therapy, for refractory patients. Impact Journals LLC 2014-05-07 /pmc/articles/PMC4116498/ /pubmed/24939867 Text en Copyright: © 2014 Sadeghi-Naini et al. http://creativecommons.org/licenses/by/2.5/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Paper
Sadeghi-Naini, Ali
Sannachi, Lakshmanan
Pritchard, Kathleen
Trudeau, Maureen
Gandhi, Sonal
Wright, Frances C.
Zubovits, Judit
Yaffe, Martin J.
Kolios, Michael C.
Czarnota, Gregory J.
Early prediction of therapy responses and outcomes in breast cancer patients using quantitative ultrasound spectral texture
title Early prediction of therapy responses and outcomes in breast cancer patients using quantitative ultrasound spectral texture
title_full Early prediction of therapy responses and outcomes in breast cancer patients using quantitative ultrasound spectral texture
title_fullStr Early prediction of therapy responses and outcomes in breast cancer patients using quantitative ultrasound spectral texture
title_full_unstemmed Early prediction of therapy responses and outcomes in breast cancer patients using quantitative ultrasound spectral texture
title_short Early prediction of therapy responses and outcomes in breast cancer patients using quantitative ultrasound spectral texture
title_sort early prediction of therapy responses and outcomes in breast cancer patients using quantitative ultrasound spectral texture
topic Research Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4116498/
https://www.ncbi.nlm.nih.gov/pubmed/24939867
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