{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,17]],"date-time":"2026-08-17T16:24:47Z","timestamp":1786983887169,"version":"build-2736575974"},"reference-count":29,"publisher":"Elsevier BV","issue":"12","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"}],"funder":[{"DOI":"10.13039\/100017633","name":"Shanghai Anti Cancer Association","doi-asserted-by":"publisher","award":["SACA CY22C15"],"award-info":[{"award-number":["SACA CY22C15"]}],"id":[{"id":"10.13039\/100017633","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["academicradiology.org","clinicalkey.com","clinicalkey.com.au","clinicalkey.es","clinicalkey.fr","clinicalkey.jp","elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Academic Radiology"],"published-print":{"date-parts":[[2025,12]]},"DOI":"10.1016\/j.acra.2025.09.018","type":"journal-article","created":{"date-parts":[[2025,10,9]],"date-time":"2025-10-09T07:04:39Z","timestamp":1759993479000},"page":"7562-7572","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":1,"title":["Image Quality Improvement and Artificial Intelligence Performance in Pulmonary Embolism Detection at Deep Learning Reconstruction-Based Ultra-low Radiation Dose CT Pulmonary Angiography"],"prefix":"10.1016","volume":"32","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6641-6162","authenticated-orcid":false,"given":"Jinjuan","family":"Lu","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Leilei","family":"Shen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chun","family":"Zhou","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhenghong","family":"Bi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiaodan","family":"Ye","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zicheng","family":"Zhao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mengsu","family":"Zeng","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6908-3674","authenticated-orcid":false,"given":"Mingliang","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"issue":"2","key":"10.1016\/j.acra.2025.09.018_bib1","doi-asserted-by":"crossref","first-page":"111","DOI":"10.1055\/s-0044-1779011","article-title":"Pulmonary embolism: an update based on the revised AWMF-S2k guideline","volume":"44","author":"Opitz","year":"2024","journal-title":"Hamostaseologie"},{"key":"10.1016\/j.acra.2025.09.018_bib2","doi-asserted-by":"crossref","unstructured":"Pulmonary embolism. Nat Rev Dis Primers. 2018;4:18031. doi:\u00a010.1038\/nrdp.2018.31.","DOI":"10.1038\/nrdp.2018.31"},{"issue":"2","key":"10.1016\/j.acra.2025.09.018_bib3","doi-asserted-by":"crossref","first-page":"342","DOI":"10.1016\/j.chest.2018.10.040","article-title":"Trends in hospitalization and in-hospital mortality from VTE, 2007 to 2016, in China","volume":"155","author":"Zhang","year":"2019","journal-title":"Chest"},{"issue":"1","key":"10.1016\/j.acra.2025.09.018_bib4","doi-asserted-by":"crossref","first-page":"529","DOI":"10.3390\/tomography8010042","article-title":"Acute pulmonary embolism: prognostic role of computed tomography pulmonary angiography (CTPA)","volume":"8","author":"Zantonelli","year":"2022","journal-title":"Tomography"},{"key":"10.1016\/j.acra.2025.09.018_bib5","doi-asserted-by":"crossref","first-page":"127","DOI":"10.1016\/j.ejim.2020.03.004","article-title":"The post-pulmonary embolism (Post-PE syndrome)","volume":"76","author":"Alonso-Mart\u00ednez","year":"2020","journal-title":"Eur J Intern Med"},{"issue":"3","key":"10.1016\/j.acra.2025.09.018_bib6","doi-asserted-by":"crossref","DOI":"10.1183\/13993003.01647-2019","volume":"54","author":"Konstantinides","year":"2019","journal-title":"Eur Respir J"},{"key":"10.1016\/j.acra.2025.09.018_bib7","article-title":"Four-year cumulative radiation exposure in patients undergoing computed tomography angiography for suspected pulmonary embolism","volume":"2013","author":"Takahashi","year":"2013","journal-title":"Radiol Res Pract"},{"key":"10.1016\/j.acra.2025.09.018_bib8","doi-asserted-by":"crossref","DOI":"10.1016\/j.ejrad.2020.109426","article-title":"Effects of radiation dose reduction on diagnostic performance of 3rd generation dual source CT pulmonary angiography","volume":"134","author":"Winkelmann","year":"2021","journal-title":"Eur J Radiol"},{"key":"10.1016\/j.acra.2025.09.018_bib9","first-page":"Doc06","article-title":"Radiation exposure by medical X-ray applications","volume":"20","author":"Buchberger","year":"2022","journal-title":"Ger Med Sci"},{"key":"10.1016\/j.acra.2025.09.018_bib10","series-title":"Radioactivity in the Environment","doi-asserted-by":"crossref","first-page":"143","DOI":"10.1016\/B978-0-08-045015-5.00009-5","article-title":"Chapter 9 - ALARA: what is reasonably achievable?","author":"Hansson","year":"2013"},{"issue":"2","key":"10.1016\/j.acra.2025.09.018_bib11","doi-asserted-by":"crossref","first-page":"499","DOI":"10.1148\/radiol.15142047","article-title":"Degradation of CT low-contrast spatial resolution due to the use of iterative reconstruction and reduced dose levels","volume":"276","author":"McCollough","year":"2015","journal-title":"Radiology"},{"issue":"3","key":"10.1016\/j.acra.2025.09.018_bib12","doi-asserted-by":"crossref","DOI":"10.1148\/radiol.221257","article-title":"Deep learning image reconstruction for CT: technical principles and clinical prospects","volume":"306","author":"Koetzier","year":"2023","journal-title":"Radiology"},{"issue":"7","key":"10.1016\/j.acra.2025.09.018_bib13","doi-asserted-by":"crossref","first-page":"286","DOI":"10.1002\/acm2.13318","article-title":"Image quality improvement with deep learning-based reconstruction on abdominal ultrahigh-resolution CT: a\u00a0phantom study","volume":"22","author":"Shirasaka","year":"2021","journal-title":"J Appl Clin Med Phys"},{"issue":"3","key":"10.1016\/j.acra.2025.09.018_bib14","doi-asserted-by":"crossref","first-page":"566","DOI":"10.2214\/AJR.19.21809","article-title":"Image quality and lesion detection on deep learning reconstruction and iterative reconstruction of submillisievert chest and abdominal CT","volume":"214","author":"Singh","year":"2020","journal-title":"AJR Am J Roentgenol"},{"issue":"11","key":"10.1016\/j.acra.2025.09.018_bib15","doi-asserted-by":"crossref","first-page":"6163","DOI":"10.1007\/s00330-019-06170-3","article-title":"Deep learning reconstruction improves image quality of abdominal ultra-high-resolution CT","volume":"29","author":"Akagi","year":"2019","journal-title":"Eur Radiol"},{"issue":"8","key":"10.1016\/j.acra.2025.09.018_bib16","doi-asserted-by":"crossref","first-page":"5498","DOI":"10.1007\/s00330-020-07668-x","article-title":"Deep learning-based reconstruction may improve non-contrast cerebral CT imaging compared to other current reconstruction algorithms","volume":"31","author":"Oostveen","year":"2021","journal-title":"Eur Radiol"},{"issue":"9","key":"10.1016\/j.acra.2025.09.018_bib17","doi-asserted-by":"crossref","first-page":"5954","DOI":"10.1007\/s00330-022-08739-x","article-title":"Value of deep learning reconstruction at ultra-low-dose CT for evaluation of urolithiasis","volume":"32","author":"Zhang","year":"2022","journal-title":"Eur Radiol"},{"issue":"3","key":"10.1016\/j.acra.2025.09.018_bib18","doi-asserted-by":"crossref","first-page":"282","DOI":"10.3390\/diagnostics15030282","article-title":"Artificial intelligence-empowered radiology-current status and critical review","volume":"15","author":"Obuchowicz","year":"2025","journal-title":"Diagnostics"},{"issue":"12","key":"10.1016\/j.acra.2025.09.018_bib19","doi-asserted-by":"crossref","first-page":"6545","DOI":"10.1007\/s00330-020-06998-0","article-title":"Automated detection of pulmonary embolism in CT pulmonary angiograms using an AI-powered algorithm","volume":"30","author":"Weikert","year":"2020","journal-title":"Eur Radiol"},{"issue":"1","key":"10.1016\/j.acra.2025.09.018_bib20","doi-asserted-by":"crossref","first-page":"102","DOI":"10.1186\/s13244-023-01454-1","article-title":"Retrospective batch analysis to evaluate the diagnostic accuracy of a clinically deployed AI algorithm for the detection of acute pulmonary embolism on CTPA","volume":"14","author":"Langius-Wiffen","year":"2023","journal-title":"Insights Imaging"},{"issue":"9","key":"10.1016\/j.acra.2025.09.018_bib21","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pone.0162716","article-title":"Ultra low dose CT pulmonary angiography with iterative reconstruction","volume":"11","author":"Sauter","year":"2016","journal-title":"PLoS One"},{"issue":"7","key":"10.1016\/j.acra.2025.09.018_bib22","doi-asserted-by":"crossref","first-page":"1251","DOI":"10.3390\/diagnostics11071251","article-title":"Diagnostic performance of a contrast-enhanced ultra-low-dose high-pitch CT protocol with reduced scan range for detection of pulmonary embolisms","volume":"11","author":"Brendlin","year":"2021","journal-title":"Diagnostics"},{"issue":"5","key":"10.1016\/j.acra.2025.09.018_bib23","doi-asserted-by":"crossref","first-page":"729","DOI":"10.1097\/RCT.0000000000001347","article-title":"A novel computed tomography image reconstruction for improving visualization of pulmonary vasculature: comparison between preprocessing and postprocessing images using a contrast enhancement boost technique","volume":"46","author":"Otgonbaatar","year":"2022","journal-title":"J Comput Assist Tomogr"},{"issue":"3","key":"10.1016\/j.acra.2025.09.018_bib24","doi-asserted-by":"crossref","first-page":"1950","DOI":"10.21037\/qims-24-1412","article-title":"Quantitative assessment and risk stratification of random acute pulmonary embolism cases using a deep learning model based on computed tomography pulmonary angiography images","volume":"15","author":"Qiao","year":"2025","journal-title":"Quant Imaging Med Surg"},{"key":"10.1016\/j.acra.2025.09.018_bib25","doi-asserted-by":"crossref","unstructured":"McCollough C.H., Chairperson D., Cody S., Edyvean R., Geise B., Gould N., Keat W., Huda P., Judy W.H., Kalender M., Mcnitt-Gray R., Morin T., Payne S., Stern L., Rothenberg P., Shrimpton J., Timmer C, Wilson. The Measurement, Reporting, and Management of Radiation Dose in CT. 2008.","DOI":"10.37206\/97"},{"key":"10.1016\/j.acra.2025.09.018_bib26","doi-asserted-by":"crossref","unstructured":"Boone J.M., Strauss K.J., Cody D.D., McCollough C.H., McNitt-Gray M.F., Toth T.L., Goske M.J., Frush D.P. Size-Specific Dose Estimates (SSDE) in Pediatric and Adult Body CT Examinations. 2011.","DOI":"10.37206\/143"},{"issue":"7","key":"10.1016\/j.acra.2025.09.018_bib27","doi-asserted-by":"crossref","first-page":"4700","DOI":"10.1007\/s00330-020-07566-2","article-title":"Diagnostic value of deep learning reconstruction for radiation dose reduction at abdominal ultra-high-resolution CT","volume":"31","author":"Nakamura","year":"2021","journal-title":"Eur Radiol"},{"issue":"1","key":"10.1016\/j.acra.2025.09.018_bib28","doi-asserted-by":"crossref","DOI":"10.1148\/radiol.230702","article-title":"Prospective evaluation of AI triage of pulmonary emboli on CT pulmonary angiograms","volume":"309","author":"Rothenberg","year":"2023","journal-title":"Radiology"},{"issue":"6","key":"10.1016\/j.acra.2025.09.018_bib29","doi-asserted-by":"crossref","first-page":"895","DOI":"10.2214\/AJR.22.27895","article-title":"Detection of incidental pulmonary embolism on conventional contrast-enhanced chest CT: comparison of an artificial intelligence algorithm and clinical reports","volume":"219","author":"Batra","year":"2022","journal-title":"AJR Am J Roentgenol"}],"container-title":["Academic Radiology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1076633225008980?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1076633225008980?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,3,7]],"date-time":"2026-03-07T11:16:59Z","timestamp":1772882219000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S1076633225008980"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,12]]},"references-count":29,"journal-issue":{"issue":"12","published-print":{"date-parts":[[2025,12]]}},"alternative-id":["S1076633225008980"],"URL":"https:\/\/doi.org\/10.1016\/j.acra.2025.09.018","relation":{},"ISSN":["1076-6332"],"issn-type":[{"value":"1076-6332","type":"print"}],"subject":[],"published":{"date-parts":[[2025,12]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Image Quality Improvement and Artificial Intelligence Performance in Pulmonary Embolism Detection at Deep Learning Reconstruction-Based Ultra-low Radiation Dose CT Pulmonary Angiography","name":"articletitle","label":"Article Title"},{"value":"Academic Radiology","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.acra.2025.09.018","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2025 The Association of Academic Radiology. Published by Elsevier Inc. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}]}}