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DOI 10.1016/j.ultrasmedbio.2022.08.018

Медицинская библиотека · Ultrasound in medicine & biology · 2022

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

СтатьяПоддержка исследования: вне правительства СШАПоддержка NIH: внешняя программаПеревод пока не подготовлен

Аннотация

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.

Для цитирования: 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.. Ultrasound in medicine & biology. 2022. DOI: 10.1016/j.ultrasmedbio.2022.08.018.

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