{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,17]],"date-time":"2026-08-17T23:06:01Z","timestamp":1787007961401,"version":"build-2736575974"},"reference-count":44,"publisher":"IOP Publishing","issue":"1","license":[{"start":{"date-parts":[[2026,1,23]],"date-time":"2026-01-23T00:00:00Z","timestamp":1769126400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/publishingsupport.iopscience.iop.org\/iop-standard\/v1"},{"start":{"date-parts":[[2026,1,23]],"date-time":"2026-01-23T00:00:00Z","timestamp":1769126400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/iopscience.iop.org\/info\/page\/text-and-data-mining"}],"content-domain":{"domain":["iopscience.iop.org"],"crossmark-restriction":false},"short-container-title":["J. Radiol. Prot."],"published-print":{"date-parts":[[2026,3,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>Accurate estimation of fetal dose during computed tomography (CT) examinations is essential to ensure fetal safety. This study presents a comparative analysis of six Monte Carlo software tools (VirtualDose CT, FetalDose.org, CODE, Waza-ari, ImPACT, and CT-Expo) for fetal dose estimation across various CT examinations, representing the largest number of tools assessed to date. By integrating reliability analysis with performance evaluation, the study improves the selection of fetal dose software tools in radiology practice. The tools were used to estimate fetal doses for 26 pregnant participants who underwent 27 CT examinations. Single and average measures intraclass correlation coefficient (ICC) values were calculated to assess both collective and pairwise reliability. Agreement between the most reliable tool pair was evaluated using a Bland\u2013Altman plot. Performance comparative analysis for the software tools in estimating fetal dose from CT was conducted via a weighted scoring method, considering accuracy, safety, and usability. The average measures ICC for all tools was 0.96 (95% CI: 0.91 \u2212 0.98), indicating excellent overall reliability, while the single measures ICC value of 0.80 (95% CI: 0.63 \u2212 0.90) reflected moderate to excellent reliability of an individual software tool with the others. VirtualDose CT and FetalDose.org showed the highest single measures ICC of 0.98 (95% CI: 0.96 \u2212 0.99), demonstrating a high reliability between both tools. The Bland\u2013Altman analysis for these two tools showed a mean difference of 0.79 and limits of confidence from \u22122.45 to 4.03, indicating a good agreement and further confirming their reliability. In terms of performance comparative analysis, VirtualDose CT outperformed the other tools with a total score of 485.25 based on the evaluation criteria. In conclusion, VirtualDose CT is recommended as the preferred software for fetal dose estimation in CT examinations due to its superior performance and reliability.<\/jats:p>","DOI":"10.1088\/1361-6498\/ae3774","type":"journal-article","created":{"date-parts":[[2026,1,13]],"date-time":"2026-01-13T22:49:50Z","timestamp":1768344590000},"page":"011503","update-policy":"https:\/\/doi.org\/10.1088\/crossmark-policy","source":"Crossref","is-referenced-by-count":1,"title":["A comparative evaluation of six Monte Carlo-based software tools for fetal dose estimation from CT examinations"],"prefix":"10.1088","volume":"46","author":[{"ORCID":"https:\/\/orcid.org\/0009-0001-0542-5345","authenticated-orcid":true,"given":"Huda","family":"Nasser","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Adnan","family":"Lahham","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"266","published-online":{"date-parts":[[2026,1,23]]},"reference":[{"key":"jrpae3774bib1","doi-asserted-by":"publisher","first-page":"312","DOI":"10.2967\/jnumed.122.263959","type":"journal-article","article-title":"Fetal dose from PET and CT in pregnant patients","volume":"64","author":"Burton","year":"2023","journal-title":"J. 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Published on behalf of SRP by IOP Publishing Limited. All rights, including for text and data mining, AI training, and similar technologies, are reserved.","name":"copyright_information","label":"Copyright Information"},{"value":"2025-10-19","name":"date_received","label":"Date Received","group":{"name":"publication_dates","label":"Publication dates"}},{"value":"2026-01-13","name":"date_accepted","label":"Date Accepted","group":{"name":"publication_dates","label":"Publication dates"}},{"value":"2026-01-23","name":"date_epub","label":"Online publication date","group":{"name":"publication_dates","label":"Publication dates"}}]}}