{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,11,7]],"date-time":"2026-11-07T06:02:53Z","timestamp":1794031373143,"version":"4.8.0"},"reference-count":26,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2025,12,1]],"date-time":"2025-12-01T00:00:00Z","timestamp":1764547200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2025,12,1]],"date-time":"2025-12-01T00:00:00Z","timestamp":1764547200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2025,7,25]],"date-time":"2025-07-25T00:00:00Z","timestamp":1753401600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["clinicalkey.com","clinicalkey.com.au","clinicalkey.es","clinicalkey.fr","clinicalkey.jp","ejropen.com","elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["European Journal of Radiology Open"],"published-print":{"date-parts":[[2025,12]]},"DOI":"10.1016\/j.ejro.2025.100674","type":"journal-article","created":{"date-parts":[[2025,7,30]],"date-time":"2025-07-30T09:18:00Z","timestamp":1753867080000},"page":"100674","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":8,"special_numbering":"C","title":["AI-driven assessment of over-scanning in chest CT: A systematic review and meta-analysis"],"prefix":"10.1016","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0009-0003-9206-9418","authenticated-orcid":false,"given":"Mo\u2019men","family":"Bani-Ahmad","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Andrew","family":"England","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Laura","family":"McLaughlin","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Marwan","family":"Alshipli","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kholoud","family":"Alzyoud","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8570-1161","authenticated-orcid":false,"given":"Yasser H.","family":"Hadi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7045-2190","authenticated-orcid":false,"given":"Mark","family":"McEntee","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"key":"10.1016\/j.ejro.2025.100674_bib1","doi-asserted-by":"crossref","DOI":"10.1016\/j.crad.2020.03.002","article-title":"The characteristics and clinical value of chest CT images of novel coronavirus pneumonia","volume":"75","author":"Zhao","year":"2020","journal-title":"Clin. Radiol."},{"key":"10.1016\/j.ejro.2025.100674_bib2","doi-asserted-by":"crossref","DOI":"10.1186\/s12880-024-01457-4","article-title":"Trends in CT examination utilization in the emergency department during and after the COVID-19 pandemic","volume":"24","author":"Kempter","year":"2024","journal-title":"BMC Med. Imaging"},{"key":"10.1016\/j.ejro.2025.100674_bib3","doi-asserted-by":"crossref","DOI":"10.1378\/chest.11-2863","article-title":"Radiation and chest CT scan examinations","volume":"142","author":"Sarma","year":"2012","journal-title":"Chest"},{"key":"10.1016\/j.ejro.2025.100674_bib4","doi-asserted-by":"crossref","DOI":"10.3390\/medicina60121952","article-title":"Optimizing scan range in computed tomography of kidneys, ureters, and bladder: a retrospective study on reducing overscanning","volume":"60","author":"Bin Owien","year":"2024","journal-title":"Medicina"},{"key":"10.1016\/j.ejro.2025.100674_bib5","doi-asserted-by":"crossref","DOI":"10.1016\/j.ejmp.2020.07.014","article-title":"Estimates of the number of patients with high cumulative doses through recurrent CT exams in 35 OECD countries","volume":"76","author":"Rehani","year":"2020","journal-title":"Phys. Med."},{"key":"10.1016\/j.ejro.2025.100674_bib6","doi-asserted-by":"crossref","DOI":"10.1001\/jamainternmed.2025.0505","article-title":"Projected lifetime cancer risks from current computed tomography imaging","author":"Smith-Bindman","year":"2025","journal-title":"JAMA Intern. Med."},{"key":"10.1016\/j.ejro.2025.100674_bib7","doi-asserted-by":"crossref","DOI":"10.2214\/AJR.07.2556","article-title":"Radiation dose reduction in chest CT: a review","volume":"190","author":"Kubo","year":"2008","journal-title":"Am. J. Roentgenol."},{"key":"10.1016\/j.ejro.2025.100674_bib8","doi-asserted-by":"crossref","DOI":"10.1016\/j.jacr.2013.05.032","article-title":"CT scan parameters and radiation dose: practical advice for radiologists","volume":"10","author":"Raman","year":"2013","journal-title":"J. Am. Coll. Radiol."},{"key":"10.1016\/j.ejro.2025.100674_bib9","doi-asserted-by":"crossref","DOI":"10.1007\/s00330-023-09971-9","article-title":"Deep learning\u2013based scan range optimization can reduce radiation exposure in coronary CT angiography","volume":"34","author":"Demircio\u011flu","year":"2023","journal-title":"Eur. Radiol."},{"key":"10.1016\/j.ejro.2025.100674_bib10","doi-asserted-by":"crossref","DOI":"10.1016\/j.radphyschem.2023.111133","article-title":"The effect of overranging on patient effective dose and organs\u2019 doses during parathyroid CT examinations utilising Monte Carlo software","volume":"212","author":"Dimitroukas","year":"2023","journal-title":"Radiat. Phys. Chem."},{"key":"10.1016\/j.ejro.2025.100674_bib11","doi-asserted-by":"crossref","DOI":"10.1016\/j.radi.2024.09.059","article-title":"Localiser radiographs in CT: current practice, radiation dose, image quality and clinical applications","volume":"30","author":"Al-Hayek","year":"2024","journal-title":"Radiography"},{"key":"10.1016\/j.ejro.2025.100674_bib12","doi-asserted-by":"crossref","DOI":"10.1148\/ryai.2021200211","article-title":"Automatic scan range delimitation in chest CT using deep learning","volume":"3","author":"Demircio\u011flu","year":"2021","journal-title":"Radio. Artif. Intell."},{"key":"10.1016\/j.ejro.2025.100674_bib13","doi-asserted-by":"crossref","first-page":"1541","DOI":"10.1016\/j.acra.2021.12.001","article-title":"Development of deep learning-based automatic scan range setting model for lung cancer screening low-dose CT imaging","volume":"29","author":"Ruan","year":"2022","journal-title":"Acad. Radiol."},{"key":"10.1016\/j.ejro.2025.100674_bib14","doi-asserted-by":"crossref","DOI":"10.1007\/s00330-011-2332-y","article-title":"Excess radiation and organ dose in chest and abdominal CT due to CT acquisition beyond expected anatomical boundaries","volume":"22","author":"Zanca","year":"2012","journal-title":"Eur. Radiol."},{"key":"10.1016\/j.ejro.2025.100674_bib15","doi-asserted-by":"crossref","DOI":"10.1007\/s00330-020-07510-4","article-title":"Excessive z-axis scan coverage in body CT: frequency and causes","volume":"31","author":"Yar","year":"2021","journal-title":"Eur. Radiol."},{"key":"10.1016\/j.ejro.2025.100674_bib16","doi-asserted-by":"crossref","DOI":"10.1016\/j.ejrad.2018.03.005","article-title":"Over-scanning in chest CT: comparison of practice among six hospitals and its impact on radiation dose","volume":"102","author":"Schwartz","year":"2018","journal-title":"Eur. J. Radiol."},{"key":"10.1016\/j.ejro.2025.100674_bib17","doi-asserted-by":"crossref","DOI":"10.1007\/s00330-019-06394-3","article-title":"The relationship between CT scout landmarks and lung boundaries on chest CT: guidelines for minimizing excess z-axis scan length","volume":"30","author":"Cohen","year":"2020","journal-title":"Eur. Radiol."},{"key":"10.1016\/j.ejro.2025.100674_bib18","doi-asserted-by":"crossref","DOI":"10.1016\/j.clinimag.2019.11.020","article-title":"Retrospective analysis of 1118 outpatient chest CT scans to determine factors associated with excess scan length","volume":"62","author":"Cohen","year":"2020","journal-title":"Clin. Imaging"},{"key":"10.1016\/j.ejro.2025.100674_bib19","doi-asserted-by":"crossref","DOI":"10.1016\/j.diii.2018.11.001","article-title":"Convolutional neural network evaluation of over-scanning in lung computed tomography","volume":"100","author":"Colevray","year":"2019","journal-title":"Diagn. Interv. Imaging"},{"key":"10.1016\/j.ejro.2025.100674_bib20","doi-asserted-by":"crossref","DOI":"10.1186\/s13244-021-01105-3","article-title":"Deep learning-based fully automated Z-axis coverage range definition from scout scans to eliminate overscanning in chest CT imaging","volume":"12","author":"Salimi","year":"2021","journal-title":"Insights Imaging"},{"key":"10.1016\/j.ejro.2025.100674_bib21","doi-asserted-by":"crossref","DOI":"10.1007\/s10278-019-00233-z","article-title":"Investigation of low-dose CT lung cancer screening scan \u201cover-range\u201d issue using machine learning methods","volume":"32","author":"Huo","year":"2019","journal-title":"J. Digit. Imaging"},{"key":"10.1016\/j.ejro.2025.100674_bib22","doi-asserted-by":"crossref","DOI":"10.3390\/diagnostics12081844","article-title":"Radiologist-trained and -tested (R2.2.4) deep learning models for identifying anatomical landmarks in chest CT","volume":"12","author":"Kaviani","year":"2022","journal-title":"Diagnostics"},{"key":"10.1016\/j.ejro.2025.100674_bib23","article-title":"Development of deep learning-assisted overscan decision algorithm in low-dose chest CT: application to lung cancer screening in Korean National CT accreditation program","volume":"17","author":"Kim","year":"2022","journal-title":"PLoS One"},{"key":"10.1016\/j.ejro.2025.100674_bib24","doi-asserted-by":"crossref","DOI":"10.1186\/s13643-021-01626-4","article-title":"The PRISMA 2020 statement: an updated guideline for reporting systematic reviews","volume":"10","author":"Page","year":"2021","journal-title":"Syst. Rev."},{"key":"10.1016\/j.ejro.2025.100674_bib25","doi-asserted-by":"crossref","DOI":"10.1148\/ryai.240300","article-title":"Checklist for artificial intelligence in medical imaging (CLAIM): 2024 update","volume":"6","author":"Tejani","year":"2024","journal-title":"Radiol. Artif. Intell."},{"key":"10.1016\/j.ejro.2025.100674_bib26","doi-asserted-by":"crossref","DOI":"10.7326\/0003-4819-155-8-201110180-00009","article-title":"QUADAS-2: a revised tool for the quality assessment of diagnostic accuracy studies","volume":"155","author":"Whiting","year":"2011","journal-title":"Ann. Intern. Med."}],"container-title":["European Journal of Radiology Open"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S2352047725000413?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S2352047725000413?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,4,8]],"date-time":"2026-04-08T17:37:51Z","timestamp":1775669871000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S2352047725000413"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,12]]},"references-count":26,"alternative-id":["S2352047725000413"],"URL":"https:\/\/doi.org\/10.1016\/j.ejro.2025.100674","relation":{},"ISSN":["2352-0477"],"issn-type":[{"value":"2352-0477","type":"print"}],"subject":[],"published":{"date-parts":[[2025,12]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"AI-driven assessment of over-scanning in chest CT: A systematic review and meta-analysis","name":"articletitle","label":"Article Title"},{"value":"European Journal of Radiology Open","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.ejro.2025.100674","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2025 The Author(s). Published by Elsevier Ltd.","name":"copyright","label":"Copyright"}],"article-number":"100674"}}