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CT acquisition parameters were analyzed from a large, international CT dose registry. Scans were analyzed separately in adults and children, and by approach (helical or axial), resulting in four strata. K-means clustering, an unsupervised machine learning approach, assigned the scans into clusters based on the following acquisition parameters: Tube current, voltage, collimation, scan length, and for helical scans, pitch. Effective patient diameter, unadjusted and patient size-adjusted dose-length product (DLP), and volume CT dose index (CTDI\n                      <jats:sub>vol<\/jats:sub>\n                      ) were compared across clusters.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>864,182 CT scans in adults and 40,027 scans in children between January 1, 2015, and March 11, 2021, were included in the analysis. Scans were classified into seven helical and six axial clusters in adults, six helical and four axial clusters in children. In all four strata, the mean size-adjusted DLP varied more than two-fold, and up to 3.4-fold, across the clusters. For example, for adult helical scans (the largest strata), the size-adjusted DLP ranged from 372 mGy\u00b7cm to 998 mGy\u00b7cm (relative dose 2.7) across clusters. Clusters with the lowest radiation generally utilized lower tube current and voltage, but protocols utilized various approaches to result in lower doses.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>There remains a large variation in the radiation dose within frequently used head CT acquisition techniques. Clustering analysis enables identifying protocols with lower doses.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Key Points<\/jats:title>\n                    <jats:p>\n                      <jats:bold>\n                        <jats:italic>Question<\/jats:italic>\n                      <\/jats:bold>\n                      <jats:italic>Is there a large variation in the doses used for routine head CT, and can we identify best-practice, lowest dose approaches for scanning?<\/jats:italic>\n                    <\/jats:p>\n                    <jats:p>\n                      <jats:bold>\n                        <jats:italic>Findings<\/jats:italic>\n                      <\/jats:bold>\n                      <jats:italic>Across each stratum (adult\/pediatric, helical\/axial), the mean size-adjusted DLP varied by more than two-fold across the CT scan clusters, reflecting significant differences in radiation<\/jats:italic>\n                      .\n                    <\/jats:p>\n                    <jats:p>\n                      <jats:bold>\n                        <jats:italic>Clinical relevance<\/jats:italic>\n                      <\/jats:bold>\n                      <jats:italic>Many routine head CT acquisition techniques use excessive radiation doses. Standardizing practice to the lowest dose clusters would result in significant reductions in patient dose.<\/jats:italic>\n                    <\/jats:p>\n                  <\/jats:sec>","DOI":"10.1007\/s00330-026-12842-8","type":"journal-article","created":{"date-parts":[[2026,9,2]],"date-time":"2026-09-02T11:27:33Z","timestamp":1788348453000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Identifying optimal dose head CT acquisition techniques through cluster analysis from 904,209 scans"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0009-0009-8533-6016","authenticated-orcid":false,"given":"Berk","family":"Yildirim","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Denise","family":"Bos","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Taewoon","family":"Kang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Carly","family":"Stewart","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Timothy P.","family":"Szczykutowicz","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Rebecca","family":"Smith-Bindman","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,9,2]]},"reference":[{"key":"12842_CR1","doi-asserted-by":"publisher","first-page":"423","DOI":"10.1093\/rpd\/ncac069","volume":"198","author":"SE Abdou","year":"2022","unstructured":"Abdou SE, Salama DH, Ahmad KA et al (2022) 2021 National diagnostic reference levels for paediatric computed tomography in Egypt. 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IAEA, Vienna"}],"container-title":["European Radiology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00330-026-12842-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00330-026-12842-8","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00330-026-12842-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,9,2]],"date-time":"2026-09-02T11:27:35Z","timestamp":1788348455000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s00330-026-12842-8"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,9,2]]},"references-count":53,"alternative-id":["12842"],"URL":"https:\/\/doi.org\/10.1007\/s00330-026-12842-8","relation":{},"ISSN":["1432-1084"],"issn-type":[{"value":"1432-1084","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,9,2]]},"assertion":[{"value":"26 January 2026","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"25 June 2026","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"2 August 2026","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"2 September 2026","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"The scientific guarantor of this publication is Dr. Rebecca Smith-Bindman.","order":1,"name":"Ethics","label":"Guarantor","group":{"name":"EthicsHeading","label":"Compliance with ethical standards"}},{"value":"R.S.B. is a co-founder and T.P.S. is a consultant of Alara Imaging, Inc., a company focused on improving the clinical and operational aspects of health systems, including collecting and reporting CT radiation dose and image quality as part of payer-led quality programs. Alara Imaging had no role in the study. The other authors of this manuscript declare no relationships with any companies whose products or services may be related to the subject matter of the article. T.P.S. receives research support from Canon Medical Systems and GE HealthCare, consulting fees from Alara Imaging, Imalogix, and Aidoc; royalties from Medical Physics Publishing and royalties related to intellectual property from Qaelum; founder of RadUnity.","order":2,"name":"Ethics","label":"Conflict of interest","group":{"name":"EthicsHeading","label":"Compliance with ethical standards"}},{"value":"T.K. has significant biostatistical expertise and performed the statistical analysis for this paper.","order":3,"name":"Ethics","label":"Statistics and biometry","group":{"name":"EthicsHeading","label":"Compliance with ethical standards"}},{"value":"This project was approved by the UCSF Institutional Review Board with a waiver of informed consent for all subjects. The waiver was approved for three reasons: the attempt to contact subjects poses a greater risk than the study itself; the large number of records required makes it impracticable to contact all potential subjects; and the researchers do not know the identity of the study subjects and therefore cannot contact them.","order":4,"name":"Ethics","label":"Informed consent","group":{"name":"EthicsHeading","label":"Compliance with ethical standards"}},{"value":"Institutional Review Board approval was obtained from the University of California and contributing health institutions.","order":5,"name":"Ethics","label":"Ethical approval","group":{"name":"EthicsHeading","label":"Compliance with ethical standards"}},{"value":"As these data come from a CT radiation dose registry, some of the CT exams included in this study may be represented in previous publications, including the following: (1) Smith-Bindman et al [\n                      \n                      ], (2) Smith-Bindman et al [\n                      \n                      ], and (3) Smith-Bindman et al [\n                      \n                      ].","order":6,"name":"Ethics","label":"Study subjects or cohorts overlap","group":{"name":"EthicsHeading","label":"Compliance with ethical standards"}},{"order":7,"name":"Ethics","label":"Methodology","group":{"name":"EthicsHeading","label":"Compliance with ethical standards"}}]}}