{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,22]],"date-time":"2026-09-22T00:16:50Z","timestamp":1790036210208,"version":"4.0.1"},"reference-count":42,"publisher":"American Society of Clinical Oncology (ASCO)","issue":"8","content-domain":{"domain":["ascopubs.org"],"crossmark-restriction":true},"short-container-title":["JCO Clin Cancer Inform"],"published-print":{"date-parts":[[2024,11]]},"abstract":"<jats:sec>\n            <jats:title>PURPOSE<\/jats:title>\n            <jats:p>Breast density is a widely established independent breast cancer risk factor. With the increasing utilization of digital breast tomosynthesis (DBT) in breast cancer screening, there is an opportunity to estimate volumetric breast density (VBD) routinely. However, current available methods extrapolate VBD from two-dimensional (2D) images acquired using DBT and\/or depend on the existence of raw DBT data, which is rarely archived by clinical centers because of storage constraints.<\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>METHODS<\/jats:title>\n            <jats:p>\n              We retrospectively analyzed 1,080 nonactionable three-dimensional (3D) reconstructed DBT screening examinations acquired between 2011 and 2016. Reference tissue segmentations were generated using previously validated software that uses 3D reconstructed slices and raw 2D DBT data. We developed a deep learning (DL) model that segments dense and fatty breast tissue from background. We then applied this model to estimate %VBD and absolute dense volume (ADV) in cm\n              <jats:sup>3<\/jats:sup>\n              in a separate case-control sample (180 cases and 654 controls). We created two conditional logistic regression models, relating each model-derived density measurement to likelihood of contralateral breast cancer diagnosis, adjusted for age, BMI, family history, and menopausal status.\n            <\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>RESULTS<\/jats:title>\n            <jats:p>\n              The DL model achieved unweighted and weighted Dice scores of 0.88 (standard deviation [SD] = 0.08) and 0.76 (SD = 0.15), respectively, on the held-out test set, demonstrating good agreement between the model and 3D reference segmentations. There was a significant association between the odds of breast cancer diagnosis and model-derived VBD (odds ratio [OR], 1.41 [95 % CI, 1.13 to 1.77];\n              <jats:italic>P<\/jats:italic>\n              = .002), with an AUC of 0.65 (95% CI, 0.60 to 0.69). ADV was also significantly associated with breast cancer diagnosis (OR, 1.45 [95% CI, 1.22 to 1.73];\n              <jats:italic>P<\/jats:italic>\n              &lt; .001) with an AUC of 0.67 (95% CI, 0.62 to 0.71).\n            <\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>CONCLUSION<\/jats:title>\n            <jats:p>DL-derived density measures derived from 3D reconstructed DBT images are associated with breast cancer diagnosis.<\/jats:p>\n          <\/jats:sec>","DOI":"10.1200\/cci.24.00103","type":"journal-article","created":{"date-parts":[[2024,12,9]],"date-time":"2024-12-09T21:00:29Z","timestamp":1733778029000},"update-policy":"https:\/\/doi.org\/10.1200\/crossmark","source":"Crossref","is-referenced-by-count":6,"title":["Volumetric Breast Density Estimation From Three-Dimensional Reconstructed Digital Breast Tomosynthesis Images Using Deep 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Center, New York, NY"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5067-8835","authenticated-orcid":true,"given":"Eric A.","family":"Cohen","sequence":"additional","affiliation":[{"name":"Center for Biomedical Image Computing and Analytics (CBICA), University of Pennsylvania, Philadelphia, PA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2243-8487","authenticated-orcid":true,"given":"Sarthak","family":"Pati","sequence":"additional","affiliation":[{"name":"Department of Pathology and Laboratory Medicine, Indiana University School of Medicine, Indianapolis, IN"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lauren","family":"Pantalone","sequence":"additional","affiliation":[{"name":"Center for Biomedical Image Computing and Analytics (CBICA), University of Pennsylvania, Philadelphia, PA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Spyridon","family":"Bakas","sequence":"additional","affiliation":[{"name":"Department of Surgery, Division of Endocrine and Oncologic Surgery, Hospital of the University of Pennsylvania, Philadelphia, PA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4328-7307","authenticated-orcid":true,"given":"Ari","family":"Brooks","sequence":"additional","affiliation":[{"name":"Department of Surgery, Division of Endocrine and Oncologic Surgery, Hospital of the University of Pennsylvania, Philadelphia, PA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1962-9322","authenticated-orcid":true,"given":"Celine M.","family":"Vachon","sequence":"additional","affiliation":[{"name":"Department of Quantitative Health Sciences, Division of Epidemiology, Mayo Clinic, Rochester, MN"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9331-644X","authenticated-orcid":true,"given":"Emily F.","family":"Conant","sequence":"additional","affiliation":[{"name":"Department of Radiology, Hospital of the University of Pennsylvania, Philadelphia, PA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3359-7195","authenticated-orcid":true,"given":"Aimilia","family":"Gastounioti","sequence":"additional","affiliation":[{"name":"Mallinckrodt Institute of Radiology, Washington University School of Medicine, St Louis, MO"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9031-5126","authenticated-orcid":true,"given":"Despina","family":"Kontos","sequence":"additional","affiliation":[{"name":"Department of Radiology, Columbia University Irving Medical Center, New York, 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