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COHERENCE METRICS FOR READER-INDEPENDENT DIFFERENTIATION OF CYSTIC FROM SOLID BREAST MASSES IN ULTRASOUND IMAGES
Traditional breast ultrasound imaging is a low-cost, real-time and portable method to assist with breast cancer screening and diagnosis, with particular benefits for patients with dense breast tissue. We previously demonstrated that incorporating coherence-based beamforming additionally improves the...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9712258/ https://www.ncbi.nlm.nih.gov/pubmed/36333154 http://dx.doi.org/10.1016/j.ultrasmedbio.2022.08.018 |
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author | WIACEK, ALYCEN OLUYEMI, ENIOLA MYERS, KELLY AMBINDER, EMILY BELL, MUYINATU A. LEDIJU |
author_facet | WIACEK, ALYCEN OLUYEMI, ENIOLA MYERS, KELLY AMBINDER, EMILY BELL, MUYINATU A. LEDIJU |
author_sort | WIACEK, ALYCEN |
collection | PubMed |
description | Traditional breast ultrasound imaging is a low-cost, real-time and portable method to assist with breast cancer screening and diagnosis, with particular benefits for patients with dense breast tissue. We previously demonstrated that incorporating coherence-based beamforming additionally improves the distinction of fluid-filled from solid breast masses, based on qualitative image interpretation by board-certified radiologists. However, variable sensitivity (range: 0.71–1.00 when detecting fluid-filled masses) was achieved by the individual radiologist readers. Therefore, we propose two objective coherence metrics, lag-one coherence (LOC) and coherence length (CL), to quantitatively determine the content of breast masses without requiring reader assessment. Data acquired from 31 breast masses were analyzed. Ideal separation (i.e., 1.00 sensitivity and specificity) was achieved between fluid-filled and solid breast masses based on the mean or median LOC value within each mass. When separated based on mean and median CL values, the sensitivity/specificity decreased to 1.00/0.95 and 0.92/0.89, respectively. The greatest sensitivity and specificity were achieved in dense, rather than non-dense, breast tissue. These results support the introduction of an objective, reader-independent method for automated diagnoses of cystic breast masses. |
format | Online Article Text |
id | pubmed-9712258 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
record_format | MEDLINE/PubMed |
spelling | pubmed-97122582023-01-01 COHERENCE METRICS FOR READER-INDEPENDENT DIFFERENTIATION OF CYSTIC FROM SOLID BREAST MASSES IN ULTRASOUND IMAGES WIACEK, ALYCEN OLUYEMI, ENIOLA MYERS, KELLY AMBINDER, EMILY BELL, MUYINATU A. LEDIJU Ultrasound Med Biol Article Traditional breast ultrasound imaging is a low-cost, real-time and portable method to assist with breast cancer screening and diagnosis, with particular benefits for patients with dense breast tissue. We previously demonstrated that incorporating coherence-based beamforming additionally improves the distinction of fluid-filled from solid breast masses, based on qualitative image interpretation by board-certified radiologists. However, variable sensitivity (range: 0.71–1.00 when detecting fluid-filled masses) was achieved by the individual radiologist readers. Therefore, we propose two objective coherence metrics, lag-one coherence (LOC) and coherence length (CL), to quantitatively determine the content of breast masses without requiring reader assessment. Data acquired from 31 breast masses were analyzed. Ideal separation (i.e., 1.00 sensitivity and specificity) was achieved between fluid-filled and solid breast masses based on the mean or median LOC value within each mass. When separated based on mean and median CL values, the sensitivity/specificity decreased to 1.00/0.95 and 0.92/0.89, respectively. The greatest sensitivity and specificity were achieved in dense, rather than non-dense, breast tissue. These results support the introduction of an objective, reader-independent method for automated diagnoses of cystic breast masses. 2023-01 2022-11-01 /pmc/articles/PMC9712258/ /pubmed/36333154 http://dx.doi.org/10.1016/j.ultrasmedbio.2022.08.018 Text en https://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/ (https://creativecommons.org/licenses/by-nc-nd/4.0/) ). |
spellingShingle | Article WIACEK, ALYCEN OLUYEMI, ENIOLA MYERS, KELLY AMBINDER, EMILY BELL, MUYINATU A. LEDIJU COHERENCE METRICS FOR READER-INDEPENDENT DIFFERENTIATION OF CYSTIC FROM SOLID BREAST MASSES IN ULTRASOUND IMAGES |
title | COHERENCE METRICS FOR READER-INDEPENDENT DIFFERENTIATION OF CYSTIC FROM SOLID BREAST MASSES IN ULTRASOUND IMAGES |
title_full | COHERENCE METRICS FOR READER-INDEPENDENT DIFFERENTIATION OF CYSTIC FROM SOLID BREAST MASSES IN ULTRASOUND IMAGES |
title_fullStr | COHERENCE METRICS FOR READER-INDEPENDENT DIFFERENTIATION OF CYSTIC FROM SOLID BREAST MASSES IN ULTRASOUND IMAGES |
title_full_unstemmed | COHERENCE METRICS FOR READER-INDEPENDENT DIFFERENTIATION OF CYSTIC FROM SOLID BREAST MASSES IN ULTRASOUND IMAGES |
title_short | COHERENCE METRICS FOR READER-INDEPENDENT DIFFERENTIATION OF CYSTIC FROM SOLID BREAST MASSES IN ULTRASOUND IMAGES |
title_sort | coherence metrics for reader-independent differentiation of cystic from solid breast masses in ultrasound images |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9712258/ https://www.ncbi.nlm.nih.gov/pubmed/36333154 http://dx.doi.org/10.1016/j.ultrasmedbio.2022.08.018 |
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