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Harmonic motion imaging of human breast masses: an in vivo clinical feasibility

Non-invasive diagnosis of breast cancer is still challenging due to the low specificity of the imaging modalities that calls for unnecessary biopsies. The diagnostic accuracy can be improved by assessing the breast tissue mechanical properties associated with pathological changes. Harmonic motion im...

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Autores principales: Saharkhiz, Niloufar, Ha, Richard, Taback, Bret, Li, Xiaoyue Judy, Weber, Rachel, Nabavizadeh, Alireza, Lee, Stephen A., Hibshoosh, Hanina, Gatti, Vittorio, Kamimura, Hermes A. S., Konofagou, Elisa E.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7498461/
https://www.ncbi.nlm.nih.gov/pubmed/32943648
http://dx.doi.org/10.1038/s41598-020-71960-5
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author Saharkhiz, Niloufar
Ha, Richard
Taback, Bret
Li, Xiaoyue Judy
Weber, Rachel
Nabavizadeh, Alireza
Lee, Stephen A.
Hibshoosh, Hanina
Gatti, Vittorio
Kamimura, Hermes A. S.
Konofagou, Elisa E.
author_facet Saharkhiz, Niloufar
Ha, Richard
Taback, Bret
Li, Xiaoyue Judy
Weber, Rachel
Nabavizadeh, Alireza
Lee, Stephen A.
Hibshoosh, Hanina
Gatti, Vittorio
Kamimura, Hermes A. S.
Konofagou, Elisa E.
author_sort Saharkhiz, Niloufar
collection PubMed
description Non-invasive diagnosis of breast cancer is still challenging due to the low specificity of the imaging modalities that calls for unnecessary biopsies. The diagnostic accuracy can be improved by assessing the breast tissue mechanical properties associated with pathological changes. Harmonic motion imaging (HMI) is an elasticity imaging technique that uses acoustic radiation force to evaluate the localized mechanical properties of the underlying tissue. Herein, we studied the in vivo feasibility of a clinical HMI system to differentiate breast tumors based on their relative HMI displacements, in human subjects. We performed HMI scans in 10 female subjects with breast masses: five benign and five malignant masses. Results revealed that both benign and malignant masses were stiffer than the surrounding tissues. However, malignant tumors underwent lower mean HMI displacement (1.1 ± 0.5 µm) compared to benign tumors (3.6 ± 1.5 µm) and the adjacent non-cancerous tissue (6.4 ± 2.5 µm), which allowed to differentiate between tumor types. Additionally, the excised breast specimens of the same patients (n = 5) were imaged post-surgically, where there was an excellent agreement between the in vivo and ex vivo findings, confirmed with histology. Higher displacement contrast between cancerous and non-cancerous tissue was found ex vivo, potentially due to the lower nonlinearity in the elastic properties of ex vivo tissue. This preliminary study lays the foundation for the potential complementary application of HMI in clinical practice in conjunction with the B-mode to classify suspicious breast masses.
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spelling pubmed-74984612020-09-18 Harmonic motion imaging of human breast masses: an in vivo clinical feasibility Saharkhiz, Niloufar Ha, Richard Taback, Bret Li, Xiaoyue Judy Weber, Rachel Nabavizadeh, Alireza Lee, Stephen A. Hibshoosh, Hanina Gatti, Vittorio Kamimura, Hermes A. S. Konofagou, Elisa E. Sci Rep Article Non-invasive diagnosis of breast cancer is still challenging due to the low specificity of the imaging modalities that calls for unnecessary biopsies. The diagnostic accuracy can be improved by assessing the breast tissue mechanical properties associated with pathological changes. Harmonic motion imaging (HMI) is an elasticity imaging technique that uses acoustic radiation force to evaluate the localized mechanical properties of the underlying tissue. Herein, we studied the in vivo feasibility of a clinical HMI system to differentiate breast tumors based on their relative HMI displacements, in human subjects. We performed HMI scans in 10 female subjects with breast masses: five benign and five malignant masses. Results revealed that both benign and malignant masses were stiffer than the surrounding tissues. However, malignant tumors underwent lower mean HMI displacement (1.1 ± 0.5 µm) compared to benign tumors (3.6 ± 1.5 µm) and the adjacent non-cancerous tissue (6.4 ± 2.5 µm), which allowed to differentiate between tumor types. Additionally, the excised breast specimens of the same patients (n = 5) were imaged post-surgically, where there was an excellent agreement between the in vivo and ex vivo findings, confirmed with histology. Higher displacement contrast between cancerous and non-cancerous tissue was found ex vivo, potentially due to the lower nonlinearity in the elastic properties of ex vivo tissue. This preliminary study lays the foundation for the potential complementary application of HMI in clinical practice in conjunction with the B-mode to classify suspicious breast masses. Nature Publishing Group UK 2020-09-17 /pmc/articles/PMC7498461/ /pubmed/32943648 http://dx.doi.org/10.1038/s41598-020-71960-5 Text en © This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply 2020 https://creativecommons.org/licenses/by/4.0/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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Saharkhiz, Niloufar
Ha, Richard
Taback, Bret
Li, Xiaoyue Judy
Weber, Rachel
Nabavizadeh, Alireza
Lee, Stephen A.
Hibshoosh, Hanina
Gatti, Vittorio
Kamimura, Hermes A. S.
Konofagou, Elisa E.
Harmonic motion imaging of human breast masses: an in vivo clinical feasibility
title Harmonic motion imaging of human breast masses: an in vivo clinical feasibility
title_full Harmonic motion imaging of human breast masses: an in vivo clinical feasibility
title_fullStr Harmonic motion imaging of human breast masses: an in vivo clinical feasibility
title_full_unstemmed Harmonic motion imaging of human breast masses: an in vivo clinical feasibility
title_short Harmonic motion imaging of human breast masses: an in vivo clinical feasibility
title_sort harmonic motion imaging of human breast masses: an in vivo clinical feasibility
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7498461/
https://www.ncbi.nlm.nih.gov/pubmed/32943648
http://dx.doi.org/10.1038/s41598-020-71960-5
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