{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,15]],"date-time":"2026-02-15T11:05:59Z","timestamp":1771153559163,"version":"3.50.1"},"reference-count":8,"publisher":"Wiley","issue":"10","license":[{"start":{"date-parts":[[2025,10,14]],"date-time":"2025-10-14T00:00:00Z","timestamp":1760400000000},"content-version":"vor","delay-in-days":13,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2025,10,1]],"date-time":"2025-10-01T00:00:00Z","timestamp":1759276800000},"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":[[2025,10]]},"abstract":"\n Background<\/jats:title>\n The recently introduced CMS quality measure for computed tomography (CT) requires compliance with two key metrics, radiation dose and image quality, across 18 exam categories. However, the method for calculating global noise (GN) remains undefined, with references to the \u201cDuke method\u201d and \u201cWisconsin method\u201d as possible options. This lack of clarity raises concerns regarding standardization, compliance, and clinical relevance.<\/jats:p>\n <\/jats:sec>\n \n Purpose<\/jats:title>\n To compare GN calculation methods proposed in the Duke and Wisconsin papers and evaluate their variability across clinical CT protocols.<\/jats:p>\n <\/jats:sec>\n \n Methods<\/jats:title>\n A retrospective analysis of 719 CT exams was performed across seven protocols, including five abdominal and two chest categories. One protocol (chest PE) included exams reconstructed with both smooth and sharp kernels. Five GN metrics were evaluated: Duke_tissue_mode, Wisconsin_tissue_mean, Wisconsin_tissue_mode, Wisconsin_air_mean, and Wisconsin_air_mode. Statistical differences were assessed using the Friedman test with pairwise Wilcoxon signed\u2010rank tests, and Pearson correlation matrices were used to evaluate agreement.<\/jats:p>\n <\/jats:sec>\n \n Results<\/jats:title>\n \n Significant differences (\n p<\/jats:italic>\n \u00a0<\u00a00.05) were observed across GN metrics in all protocols, with Wisconsin_tissue_mean consistently producing the highest values. Correlation analysis showed strong agreement (\n r<\/jats:italic>\n \u00a0>\u00a00.7) for renal stone, chest w\/o, and abdomen\/pelvis protocols, but weaker correlations for urogram, renal mass, and enterography. Mode\u2010based metrics showed higher agreement (\n r<\/jats:italic>\n \u00a0>\u00a00.9), suggesting dose dependency. In the chest PE protocol, the smooth kernel yielded GN values well below the CMS threshold, while the sharp kernel exceeded the threshold in tissue\u2010based metrics.\n <\/jats:p>\n <\/jats:sec>\n \n Conclusions<\/jats:title>\n Significant variability across GN metrics highlights the need for a standardized, clinically relevant method. Without clear definitions, the CMS measure's effectiveness in ensuring image quality and dose management may be compromised, an issue also raised by the AAPM\u2010commissioned panel.<\/jats:p>\n <\/jats:sec>","DOI":"10.1002\/acm2.70288","type":"journal-article","created":{"date-parts":[[2025,10,15]],"date-time":"2025-10-15T04:30:33Z","timestamp":1760502633000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["A comparative evaluation of CT global noise calculation methods for clinical image quality assessment"],"prefix":"10.1002","volume":"26","author":[{"ORCID":"https:\/\/orcid.org\/0009-0009-1807-1687","authenticated-orcid":false,"given":"Charles M","family":"Weaver","sequence":"first","affiliation":[{"name":"Division of Diagnostic and Nuclear Medical Physics Department of Radiology University of Kentucky College of Medicine Lexington Kentucky USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6838-849X","authenticated-orcid":false,"given":"Gary","family":"Ge","sequence":"additional","affiliation":[{"name":"Division of Diagnostic and Nuclear Medical Physics Department of Radiology University of Kentucky College of Medicine Lexington Kentucky USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Alexander","family":"Alsalihi","sequence":"additional","affiliation":[{"name":"Division of Diagnostic and Nuclear Medical Physics Department of Radiology University of Kentucky College of Medicine Lexington Kentucky USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2006-9964","authenticated-orcid":false,"given":"Jie","family":"Zhang","sequence":"additional","affiliation":[{"name":"Division of Diagnostic and Nuclear Medical Physics Department of Radiology University of Kentucky College of Medicine Lexington Kentucky USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","published-online":{"date-parts":[[2025,10,14]]},"reference":[{"key":"e_1_2_9_2_1","unstructured":"Excessive radiation dose or inadequate image quality for diagnostic computed tomography (CT) in adults.eCQI Resource Center;2025. CMS1074v3 May 6 2025. Accessed June 1 2025. Available from:https:\/\/ecqi.healthit.gov\/ecqm\/ec\/2026\/cms1056v3"},{"key":"e_1_2_9_3_1","doi-asserted-by":"publisher","DOI":"10.2214\/AJR.14.13613"},{"key":"e_1_2_9_4_1","doi-asserted-by":"publisher","DOI":"10.1002\/mp.12240"},{"key":"e_1_2_9_5_1","unstructured":"Excessive radiation dose or inadequate image quality for diagnostic computed tomography (CT) in adults (clinician level). Measure #3633e.National Quality Forum;2022August 2 2022. Accessed on November 6 2024. Available from:https:\/\/www.qualityforum.org\/QPS\/3633e"},{"key":"e_1_2_9_6_1","doi-asserted-by":"publisher","DOI":"10.1148\/radiol.2021210591"},{"key":"e_1_2_9_7_1","doi-asserted-by":"publisher","DOI":"10.1148\/radiol.15142047"},{"key":"e_1_2_9_8_1","doi-asserted-by":"publisher","DOI":"10.2214\/AJR.24.32458"},{"issue":"25","key":"e_1_2_9_9_1","first-page":"00440","article-title":"Patient size estimation methods for CMS size\u2010adjusted dose reporting: variability, challenges, and recommendations","volume":"1546","author":"Ge G","year":"2025","journal-title":"J Am Coll Radiol"}],"container-title":["Journal of Applied Clinical Medical Physics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/aapm.onlinelibrary.wiley.com\/doi\/pdf\/10.1002\/acm2.70288","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/aapm.onlinelibrary.wiley.com\/doi\/full-xml\/10.1002\/acm2.70288","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/aapm.onlinelibrary.wiley.com\/doi\/pdf\/10.1002\/acm2.70288","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,2,15]],"date-time":"2026-02-15T10:50:43Z","timestamp":1771152643000},"score":1,"resource":{"primary":{"URL":"https:\/\/aapm.onlinelibrary.wiley.com\/doi\/10.1002\/acm2.70288"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,10]]},"references-count":8,"journal-issue":{"issue":"10","published-print":{"date-parts":[[2025,10]]}},"alternative-id":["10.1002\/acm2.70288"],"URL":"https:\/\/doi.org\/10.1002\/acm2.70288","archive":["Portico"],"relation":{},"ISSN":["1526-9914","1526-9914"],"issn-type":[{"value":"1526-9914","type":"print"},{"value":"1526-9914","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,10]]},"assertion":[{"value":"2025-05-02","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2025-09-04","order":2,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2025-10-14","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}],"article-number":"e70288"}}