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For g-SoS, ultrasonic waves were transmitted from varying transducer locations and the image misalignments between these were then related analytically to breast SoS. To test reproducibility, two consecutive g-SoS acquisitions each were taken at two similar breast locations by the same operator.<\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>Results<\/jats:title>\n            <jats:p>Measurements were found highly repeatable, with a mean absolute difference\u2009\u00b1\u2009standard deviation of 3.16\u2009\u00b1\u20093.79\u2009m\/s. Multiple measurements were combined yielding a single g-SoS estimate per each patient, which strongly correlated to m-ACR categories (Spearman\u2019s\u2009=\u20090.773). The g-SoS values for categories A-D were 1459.6\u2009\u00b1\u20090.74, 1475.6\u2009\u00b1\u200915.92, 1515.6\u2009\u00b1\u200927.10, and 1545.7\u2009\u00b1\u200920.62, with all groups (except A-B) being significantly different from each other. Dense breasts (m-ACR C&amp;D) were classified with 100% specificity at 78% sensitivity, with an area under the curve (AUC) of 0.931. Extremely dense breasts (m-ACR D) were classified with 100% sensitivity at 77.5% specificity (AUC\u2009=\u20090.906).<\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>Conclusion<\/jats:title>\n            <jats:p>Quantitative g-SoS measurement of the breast was shown feasible and repeatable using conventional US machines, with values correlating strongly with m-ACR assessments.<\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>Key Points<\/jats:title>\n            <jats:p>\n              <jats:bold>\n                <jats:italic>Question<\/jats:italic>\n              <\/jats:bold>\n              <jats:italic>Breast density is a strong predictor of risk for breast cancer, which frequently develops in dense tissue regions. Therefore, density assessment calls for refined non-ionizing methods.<\/jats:italic>\n            <\/jats:p>\n            <jats:p>\n              <jats:bold>\n                <jats:italic>Findings<\/jats:italic>\n              <\/jats:bold>\n              <jats:italic>Quantitative global speed-of-sound (g-SoS) measurement of the breast is shown to be feasible using conventional US machines, repeatable, and able to classify breast density\u00a0with high accuracy.<\/jats:italic>\n            <\/jats:p>\n            <jats:p>\n              <jats:bold>\n                <jats:italic>Clinical relevance<\/jats:italic>\n              <\/jats:bold>\n              <jats:italic>Being effective in classifying dense breasts, where mammography has reduced sensitivity, g-SoS can help stratify patients for alternative modalities. Ideal day for mammography or MRI can be determined by monitoring g-SoS. Furthermore, g-SoS can be integrated into personalized risk assessment.<\/jats:italic>\n            <\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>Graphical Abstract<\/jats:title>\n          <\/jats:sec>","DOI":"10.1007\/s00330-024-11335-w","type":"journal-article","created":{"date-parts":[[2025,1,11]],"date-time":"2025-01-11T11:51:38Z","timestamp":1736596298000},"page":"1490-1501","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":12,"title":["Breast density assessment via quantitative sound-speed measurement using conventional ultrasound transducers"],"prefix":"10.1007","volume":"35","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1737-0756","authenticated-orcid":false,"given":"Can Deniz","family":"Bezek","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0004-5136-9171","authenticated-orcid":false,"given":"Monika","family":"Farkas","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1539-6493","authenticated-orcid":false,"given":"Dieter","family":"Schweizer","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3636-8697","authenticated-orcid":false,"given":"Rahel A.","family":"Kubik-Huch","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8639-7373","authenticated-orcid":false,"given":"Orcun","family":"Goksel","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2025,1,11]]},"reference":[{"key":"11335_CR1","unstructured":"D\u2019Orsi CJ, Sickles EA, Mendelson EB et al (2013) ACR BI-RADS\u00ae Atlas, Breast Imaging Reporting and Data System. 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