{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,4]],"date-time":"2026-09-04T03:43:04Z","timestamp":1788493384948,"version":"build-2803163510"},"reference-count":38,"publisher":"Oxford University Press (OUP)","issue":"1134","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022,6,1]]},"abstract":"<jats:sec>\n                  <jats:title>Objective<\/jats:title>\n                  <jats:p>This study aims to establish risk of breast cancer based on breast density among Saudi women and to compare cancer prediction using different breast density methods.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Methods<\/jats:title>\n                  <jats:p>1140 pseudonymised screening mammograms from Saudi females were retrospectively collected. Breast density was assessed using Breast Imaging Reporting and Data System (BI-RADS) density categories and visual analogue scale (VAS) of 285 cases and 855 controls matched on age and body mass index. In a subset of 160 cases and 480 controls density was estimated by two automated methods, Volpara Density\u2122 and predicted VAS (pVAS). Odds ratios (ORs) between the highest and second categories in BI-RADS and Volpara density grades, and highest vs lowest quartiles in VAS, pVAS and Volpara Density\u2122, were estimated using conditional logistic regression.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Results:<\/jats:title>\n                  <jats:p>For BI-RADS, the OR was 6.69 (95% CI 2.79\u201316.06) in the highest vs second category and OR = 4.78 (95% CI 3.01\u20137.58) in the highest vs lowest quartile for VAS. In the subset, VAS was the strongest predictor OR = 7.54 (95% CI 3.86\u201314.74), followed by pVAS using raw images OR = 5.38 (95% CI 2.68\u201310.77) and Volpara Density \u2122 OR = 3.55, (95% CI 1.86\u20136.75) for highest vs lowest quartiles. The matched concordance index for VAS was 0.70 (95% CI 0.65\u20130.75) demonstrating better discrimination between cases and controls than all other methods.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Conclusion<\/jats:title>\n                  <jats:p>Increased mammographic density was strongly associated with risk of breast cancer among Saudi women. Radiologists\u2019 visual assessment of breast density is superior to automated methods. However, pVAS and Volpara Density \u2122 also significantly predicted breast cancer risk based on breast density.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Advances in knowledge<\/jats:title>\n                  <jats:p>Our study established an association between breast density and breast cancer in a Saudi population and compared the performance of automated methods. This provides a stepping-stone towards personalised screening using automated breast density methods.<\/jats:p>\n               <\/jats:sec>","DOI":"10.1259\/bjr.20211197","type":"journal-article","created":{"date-parts":[[2022,2,23]],"date-time":"2022-02-23T17:00:52Z","timestamp":1645635652000},"source":"Crossref","is-referenced-by-count":9,"title":["Mammographic breast density and breast cancer risk in the Saudi population: a case\u2013control study using visual and automated methods"],"prefix":"10.1093","volume":"95","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6646-6378","authenticated-orcid":false,"given":"Areej S","family":"Aloufi","sequence":"first","affiliation":[{"name":"Division of Informatics, Imaging and Data Sciences, Faculty of Biology, Medicine and Health, University of Manchester , Manchester , UK"},{"name":"Department of Radiological Sciences, College of Applied Medical Sciences, King Saud University , Riyadh , Kingdom of Saudi Arabia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Abdulrahman N","family":"AlNaeem","sequence":"additional","affiliation":[{"name":"Department of Women\u2019s Imaging, King Fahad Medical City , Riyadh , Kingdom of Saudi Arabia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Abeer S","family":"Almousa","sequence":"additional","affiliation":[{"name":"Department of Women\u2019s Imaging, King Fahad Medical City , Riyadh , Kingdom of Saudi Arabia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Amani M","family":"Hashem","sequence":"additional","affiliation":[{"name":"Department of Breast Imaging, King Khaled University Hospital , Riyadh , Kingdom of Saudi Arabia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mehreen A","family":"Malik","sequence":"additional","affiliation":[{"name":"Department of Breast Imaging, King Khaled University Hospital , Riyadh , Kingdom of Saudi 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E","family":"Squires","sequence":"additional","affiliation":[{"name":"Division of Informatics, Imaging and Data Sciences, Faculty of Biology, Medicine and Health, University of Manchester , Manchester , UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Khalid S","family":"Alzimami","sequence":"additional","affiliation":[{"name":"Department of Radiological Sciences, College of Applied Medical Sciences, King Saud University , Riyadh , Kingdom of Saudi Arabia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Elaine F","family":"Harkness","sequence":"additional","affiliation":[{"name":"Division of Informatics, Imaging and Data Sciences, Faculty of Biology, Medicine and Health, University of Manchester , Manchester , UK"},{"name":"Nightingale Breast Screening Centre & Prevent Breast Cancer Unit, Wythenshawe Hospital, Manchester University NHS Foundation Trust, , Manchester M23 9LT , UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Susan M","family":"Astley","sequence":"additional","affiliation":[{"name":"Division of Informatics, Imaging and Data Sciences, Faculty of Biology, Medicine and Health, University of Manchester , Manchester , UK"},{"name":"Nightingale Breast Screening Centre & Prevent Breast Cancer Unit, Wythenshawe Hospital, Manchester University NHS Foundation Trust, , Manchester M23 9LT , UK"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2022,3,9]]},"reference":[{"key":"2024050216142412000_b1","unstructured":"Saudi Cancer Registry\n          \n.\nCancer Incidence Report Saudi Arabia\n.\n2019\n.\nAvailable from\n:\nhttps:\/\/nhic.gov.sa\/en\/eServices\/Documents\/2016.pdf"},{"key":"2024050216142412000_b2","unstructured":"Globocan\n          \n.\nPOPULATION FACT SHEETS: World Health organization\n.\n2020\n.\nAvailable 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