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Med. Biol."],"published-print":{"date-parts":[[2026,5,14]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>\n                    <jats:italic>Objective.<\/jats:italic>\n                    This study assessed computed tomography (CT) number consistency in different materials and tissues as x-ray tube potential, scanner model and manufacturer, and phantom size were varied. We investigated using virtual monoenergetic imagings (VMIs) to improve CT number consistency compared to single-energy (SE) images.\n                    <jats:italic>Approach.<\/jats:italic>\n                    Four clinically-relevant material inserts (calcium, adipose, iodine, soft tissue) were placed into two phantom sizes (28 cm and 40 cm width) and scanned at each available tube potential on three CT scanners with distinct methods of spectral data collection. SE images and VMIs were reconstructed for each scan. The average CT number of each insert was calculated for each image series, and the consistency of this average value across different combinations of scan parameters was compared between VMIs and SE images using coefficient of variation (COV), median, range and a linear model estimating scanner-based CT number differences.\n                    <jats:italic>Main results.<\/jats:italic>\n                    The COV for calcium, adipose, iodine and soft tissue inserts decreased from 10.1%, 9.7%, 28.8%, and 6.2% in SE images to 1.6%, 3.1%, 2.9%, and 5.7% in VMIs, respectively. When only tube potential was changed, the median standard deviation in insert average CT number decreased in VMIs compared to SE images in all materials. VMIs decreased the range of insert values between phantom sizes. VMIs decreased CT number variation due to scanner in both phantom sizes for iodine and in the calcium, 28 cm phantom. Inter-manufacturer differences in VMI CT numbers were observed in low density materials and the 40 cm phantom.\n                    <jats:italic>Significance.<\/jats:italic>\n                    Scan parameter variation affects CT numbers, negatively impacting quantitative imaging consistency and downstream patient metrics. This limits measurement standardization in serial studies, diverse cohorts, and between hospitals with data collection differences. VMIs from spectral CT can reduce this variability by providing more consistent material CT numbers relative to changes in tube potential, scanner model, and patient size.\n                  <\/jats:p>","DOI":"10.1088\/1361-6560\/ae6749","type":"journal-article","created":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T00:38:19Z","timestamp":1777595899000},"page":"09NT02","update-policy":"https:\/\/doi.org\/10.1088\/crossmark-policy","source":"Crossref","is-referenced-by-count":1,"title":["Mitigating CT number variability between scanners, tube potentials, and patient sizes using spectral CT virtual monoenergetic imaging"],"prefix":"10.1088","volume":"71","author":[{"ORCID":"https:\/\/orcid.org\/0009-0007-4203-710X","authenticated-orcid":true,"given":"Aeden K","family":"Davis","sequence":"first","affiliation":[{"name":"Department of Radiology"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5346-332X","authenticated-orcid":false,"given":"Cynthia H","family":"McCollough","sequence":"additional","affiliation":[{"name":"Department of Radiology"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1267-8735","authenticated-orcid":true,"given":"Fang-Shu","family":"Ou","sequence":"additional","affiliation":[{"name":"Division of Clinical Trials and Biostatistics"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8314-3642","authenticated-orcid":true,"given":"Kishore","family":"Rajendran","sequence":"additional","affiliation":[{"name":"Department of Radiology"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6453-9481","authenticated-orcid":true,"given":"Shuai","family":"Leng","sequence":"additional","affiliation":[{"name":"Department of Radiology"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"266","published-online":{"date-parts":[[2026,5,14]]},"reference":[{"key":"pmbae6749bib1","doi-asserted-by":"publisher","first-page":"423","DOI":"10.1016\/j.jcct.2025.05.003","type":"journal-article","article-title":"Plaque quantification from coronary computed tomography angiography in predicting cardiovascular events: a systematic review and meta-analysis","volume":"19","author":"Bell","year":"2025","journal-title":"J. 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All rights, including for text and data mining, AI training, and similar technologies, are reserved.","name":"copyright_information","label":"Copyright Information"},{"value":"2025-11-25","name":"date_received","label":"Date Received","group":{"name":"publication_dates","label":"Publication dates"}},{"value":"2026-04-30","name":"date_accepted","label":"Date Accepted","group":{"name":"publication_dates","label":"Publication dates"}},{"value":"2026-05-14","name":"date_epub","label":"Online publication date","group":{"name":"publication_dates","label":"Publication dates"}}]}}