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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| Vydané v: | Scientific reports Ročník 10; číslo 1; s. 15254 |
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| Hlavní autori: | , , , , , , , , , , |
| Médium: | Journal Article |
| Jazyk: | English |
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London
Nature Publishing Group UK
17.09.2020
Nature Publishing Group |
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| ISSN: | 2045-2322, 2045-2322 |
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| Abstract | 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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| AbstractList | 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. 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.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. 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. |
| ArticleNumber | 15254 |
| Author | Saharkhiz, Niloufar Taback, Bret Ha, Richard Hibshoosh, Hanina Kamimura, Hermes A. S. Konofagou, Elisa E. Li, Xiaoyue Judy Gatti, Vittorio Nabavizadeh, Alireza Lee, Stephen A. Weber, Rachel |
| Author_xml | – sequence: 1 givenname: Niloufar surname: Saharkhiz fullname: Saharkhiz, Niloufar organization: Department of Biomedical Engineering, Columbia University – sequence: 2 givenname: Richard surname: Ha fullname: Ha, Richard organization: Department of Radiology, New-York-Presbyterian/Columbia University Medical Center – sequence: 3 givenname: Bret surname: Taback fullname: Taback, Bret organization: Department of Surgery, New-York-Presbyterian/Columbia University Medical Center – sequence: 4 givenname: Xiaoyue Judy surname: Li fullname: Li, Xiaoyue Judy organization: Department of Biomedical Engineering, Columbia University – sequence: 5 givenname: Rachel surname: Weber fullname: Weber, Rachel organization: Department of Biomedical Engineering, Columbia University – sequence: 6 givenname: Alireza surname: Nabavizadeh fullname: Nabavizadeh, Alireza organization: Department of Biomedical Engineering, Columbia University – sequence: 7 givenname: Stephen A. surname: Lee fullname: Lee, Stephen A. organization: Department of Biomedical Engineering, Columbia University – sequence: 8 givenname: Hanina surname: Hibshoosh fullname: Hibshoosh, Hanina organization: Department of Pathology and Cell Biology, New-York-Presbyterian/Columbia University Medical Center – sequence: 9 givenname: Vittorio surname: Gatti fullname: Gatti, Vittorio organization: Department of Biomedical Engineering, Columbia University – sequence: 10 givenname: Hermes A. S. surname: Kamimura fullname: Kamimura, Hermes A. S. organization: Department of Biomedical Engineering, Columbia University – sequence: 11 givenname: Elisa E. surname: Konofagou fullname: Konofagou, Elisa E. email: ek2191@columbia.edu organization: Department of Biomedical Engineering, Columbia University, Department of Radiology, New-York-Presbyterian/Columbia University Medical Center |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/32943648$$D View this record in MEDLINE/PubMed |
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| CitedBy_id | crossref_primary_10_1109_TBME_2022_3211465 crossref_primary_10_1016_j_ultrasmedbio_2024_09_021 crossref_primary_10_1109_TMI_2021_3055779 crossref_primary_10_1016_j_ultrasmedbio_2023_03_025 crossref_primary_10_1109_TMI_2022_3178897 crossref_primary_10_1088_1361_6560_abddd1 crossref_primary_10_1109_TUFFC_2023_3329729 crossref_primary_10_1146_annurev_bioeng_103023_111151 crossref_primary_10_1016_j_ultrasmedbio_2023_09_012 |
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| Title | Harmonic motion imaging of human breast masses: an in vivo clinical feasibility |
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