{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,29]],"date-time":"2026-09-29T16:04:55Z","timestamp":1790697895502,"version":"4.1.0"},"reference-count":18,"publisher":"Wiley","issue":"5","license":[{"start":{"date-parts":[[2026,5,21]],"date-time":"2026-05-21T00:00:00Z","timestamp":1779321600000},"content-version":"vor","delay-in-days":20,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T00:00:00Z","timestamp":1777593600000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"content-domain":{"domain":["aapm.onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["J Applied Clin Med Phys"],"published-print":{"date-parts":[[2026,5]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Metal artifacts in computed tomography (CT) significantly compromise image quality and CT number (CTN) accuracy, which may influence downstream applications such as radiation therapy workflows. Although commercial metal artifact reduction (MAR) algorithms are widely used, their performance varies across vendors and clinical scenarios, and standardized methods for quantitative comparison remain limited.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Purpose<\/jats:title>\n                    <jats:p>This study quantitatively compares four commercial MAR algorithms using standardized metrics and a novel analytical approach.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>\n                      A custom\u2010designed resin phantom with interchangeable inserts (solid water, aluminum, titanium, and stainless steel) was scanned using four CT systems: Canon, GE, Philips, and Siemens. Each system's proprietary MAR algorithm was applied to obtain artifact\u2010reduced image sets. Quantitative analysis employed complementary methods: (1) circular profile analysis measuring mean CTN deviations at concentric distances from metal objects; (2) geometric accuracy assessment of metal objects; and (3) volumetric artifact characterization using analysis of severe artifact voxels and composite error metric (\n                      <jats:italic>M<\/jats:italic>\n                      \u2010error index) that integrates both artifact extent and intensity. Color maps and accumulated histograms of \u0394CTN values between pre\u2010 and post\u2010MAR images were used to characterized artifact patterns and MAR performance.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      All four MAR methods showed minimal |\u0394CTN| at mid (2.80\u00a0cm) and far (3.80\u00a0cm) distances but showed pronounced increases in |\u0394CTN| near the metal interface at the closest radius (1.27\u00a0cm). Smart\u2010MAR exhibited the highest CTN deviation for aluminum (16.83 HU), while O\u2010MAR showed the largest deviations for titanium and stainless steel (42.40 and 42.60 HU). Quantitative evaluation showed that single\u2010energy metal artifact reduction (SEMAR) and iterative metal artifact reduction (iMAR) achieved the most consistent geometric accuracy (&lt;5%) across all metals. O\u2010MAR showed the highest accuracy for titanium (approximately 0.36%) but larger deviations for aluminum (approximately 9%), while Smart\u2010MAR exhibited the greatest errors exceeding 19% for both titanium and stainless steel. SEMAR, Smart\u2010MAR, and iMAR showed lower\n                      <jats:italic>M<\/jats:italic>\n                      Error values (0.00\u20130.83) than O\u2010MAR, which showed significantly higher values (1.15\u20132.45).\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>SEMAR and iMAR achieved the most consistent geometric accuracy (&lt;5% error) and artifact suppression across all metals, while O\u2010MAR demonstrated material\u2010dependent performance with substantial residual artifacts near metal interfaces. These phantom\u2010based benchmarks provide vendor\u2010neutral performance data on MAR performance under controlled settings.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1002\/acm2.70631","type":"journal-article","created":{"date-parts":[[2026,5,22]],"date-time":"2026-05-22T06:40:26Z","timestamp":1779432026000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Quantitative phantom\u2010based comparison of commercial CT metal artifact reduction algorithms"],"prefix":"10.1002","volume":"27","author":[{"ORCID":"https:\/\/orcid.org\/0009-0001-2682-269X","authenticated-orcid":false,"given":"Beechui","family":"Koo","sequence":"first","affiliation":[{"name":"Department of Radiation and Cellular Oncology University of Chicago  Chicago Illinois USA"},{"name":"Data Science Institute University of Chicago  Chicago Illinois 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J.","family":"Das","sequence":"additional","affiliation":[{"name":"Department of Radiation Oncology Northwestern Memorial Hospital, Northwestern University Feinberg School of Medicine  Chicago Illinois USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Siyong","family":"Kim","sequence":"additional","affiliation":[{"name":"Department of Radiation and Oncology Virginia Commonwealth University  Richmond Virginia USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7209-4104","authenticated-orcid":false,"given":"James J.","family":"Sohn","sequence":"additional","affiliation":[{"name":"Department of Radiation and Cellular Oncology University of Chicago  Chicago Illinois USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2026,5,21]]},"reference":[{"issue":"2","key":"e_1_2_11_2_1","first-page":"767","article-title":"CT artifacts: causes and reduction 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