{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,2]],"date-time":"2026-06-02T14:24:32Z","timestamp":1780410272608,"version":"3.54.1"},"reference-count":26,"publisher":"SAGE Publications","issue":"6","license":[{"start":{"date-parts":[[2026,4,28]],"date-time":"2026-04-28T00:00:00Z","timestamp":1777334400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Acta Radiol"],"published-print":{"date-parts":[[2026,6]]},"abstract":"<jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Quality control (QC) in mammography is crucial for breast imaging and it relies predominantly on subjective assessment of image quality (IQ) in phantom.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Purpose<\/jats:title>\n                    <jats:p>To validate the efficacy of automated software assessment in comparison with human observers.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Material and Methods<\/jats:title>\n                    <jats:p>A total of 80 processed images of the ACR DM phantom were collected from mammography systems supplied by five different vendors. IQ was assessed using in-house developed software and 11 human observers (five experts and six non-experts). Three different target objects of various sizes and shapes were scored (six fibers, six speck groups, six masses) for each image.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>The software assessment demonstrated good to moderate agreement with the human observers\u2019 scoring of target objects, especially with expert observers. The intraclass correlation coefficient (ICC) values between the software and all observers were 0.77, 0.61, and 0.78 for fibers, speck groups, and masses, respectively. There was variability in the scoring of low contrast objects, especially with non-expert observers. Meanwhile, high contrast objects (e.g. specks) showed the highest visibility rate and received more consistent scores. The comparison between the software and all observers indicated mean differences of 0.53 for fibers, 0.27 for specks, and 0.36 for masses.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>The software assessment effectively scored the phantom IQ, demonstrating comparability to assessments made by human observers, regardless of the image acquisition factors and manufacturers\u2019 design specifications. This software should therefore ensure consistent IQ assessment that mitigates the limitations of subjective human assessment in mammography quality testing.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1177\/02841851261425207","type":"journal-article","created":{"date-parts":[[2026,4,29]],"date-time":"2026-04-29T03:10:56Z","timestamp":1777432256000},"page":"528-539","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":0,"title":["Quality control of mammographic systems using ACR digital mammography (DM) phantom images: a comparative study of automated and human observer scoring"],"prefix":"10.1177","volume":"67","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5509-4564","authenticated-orcid":false,"given":"Zeyad","family":"Alawaji","sequence":"first","affiliation":[{"name":"Qassim University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Seyedamir","family":"Tavakoli Taba","sequence":"additional","affiliation":[{"name":"The University of Sydney"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Abdulaziz S","family":"Alshabibi","sequence":"additional","affiliation":[{"name":"The College of Applied Medical Sciences of King Saud University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lucy","family":"Cartwright","sequence":"additional","affiliation":[{"name":"Medical Physics Department, Western Sydney Local Health District, Westmead, NSW, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"William","family":"Rae","sequence":"additional","affiliation":[{"name":"The University of Sydney"},{"name":"Medical Imaging Department, Prince of Wales Hospital, Randwick, NSW, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"179","published-online":{"date-parts":[[2026,4,28]]},"reference":[{"key":"e_1_3_3_2_2","doi-asserted-by":"publisher","DOI":"10.1001\/jama.2015.13183"},{"key":"e_1_3_3_3_2","doi-asserted-by":"publisher","DOI":"10.1159\/000503715"},{"key":"e_1_3_3_4_2","volume-title":"Historical trends in image quality and mean glandular dose in digital mammographyProc SPIE 11513, 15th International Workshop on Breast Imaging (IWBI2020)","author":"Mackenzie A","year":"2020","unstructured":"Mackenzie A, Khan R, Young K. Historical trends in image quality and mean glandular dose in digital mammography. In: Proc SPIE 11513, 15th International Workshop on Breast Imaging (IWBI2020); 2020. DOI: https:\/\/doi.org\/10.1117\/12.2550568."},{"key":"e_1_3_3_5_2","doi-asserted-by":"publisher","DOI":"10.1148\/radiol.13122581"},{"key":"e_1_3_3_6_2","doi-asserted-by":"publisher","DOI":"10.1148\/radiol.2021204379"},{"key":"e_1_3_3_7_2","doi-asserted-by":"publisher","DOI":"10.1007\/s13244-013-0269-1"},{"key":"e_1_3_3_8_2","volume-title":"Digital mammography quality control manual","author":"Berns EA","year":"2018","unstructured":"Berns EA, Pfeiffer DE, Butler PF, et al. Digital mammography quality control manual. Reston, VA: American College of Radiology, 2018."},{"key":"e_1_3_3_9_2","volume-title":"Guidelines for quality control testing for digital (CR & DR) mammography","author":"RANZCR","year":"2018","unstructured":"RANZCR. Guidelines for quality control testing for digital (CR & DR) mammography. Sydney, Australia: The Royal Australian and New Zealand College of Radiologists, 2018."},{"key":"e_1_3_3_10_2","doi-asserted-by":"publisher","DOI":"10.2217\/iim.10.63"},{"key":"e_1_3_3_11_2","doi-asserted-by":"publisher","DOI":"10.1002\/acm2.13431"},{"key":"e_1_3_3_12_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.ejrad.2019.05.014"},{"key":"e_1_3_3_13_2","doi-asserted-by":"publisher","DOI":"10.1088\/1361-6560\/ac9a35"},{"key":"e_1_3_3_14_2","doi-asserted-by":"publisher","DOI":"10.1177\/0284185118776502"},{"key":"e_1_3_3_15_2","doi-asserted-by":"publisher","DOI":"10.1118\/1.3687159"},{"key":"e_1_3_3_16_2","doi-asserted-by":"publisher","DOI":"10.1088\/0031-9155\/57\/21\/7177"},{"key":"e_1_3_3_17_2","doi-asserted-by":"publisher","DOI":"10.1186\/s12880-022-00944-w"},{"key":"e_1_3_3_18_2","doi-asserted-by":"publisher","DOI":"10.1016\/S1076-6332(03)80345-8"},{"key":"e_1_3_3_19_2","first-page":"737","article-title":"Quality control for digital mammography: part II","volume":"33","author":"Yaffe MJ","year":"2006","unstructured":"Yaffe MJ, Bloomquist AK, Mawdsley GE, et al. 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