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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...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Nature Publishing Group UK
2020
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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. |
format | Online Article Text |
id | pubmed-7498461 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
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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