{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,24]],"date-time":"2026-10-24T11:41:28Z","timestamp":1792842088388,"version":"4.5.0"},"reference-count":52,"publisher":"Springer Science and Business Media LLC","issue":"3","license":[{"start":{"date-parts":[[2026,1,19]],"date-time":"2026-01-19T00:00:00Z","timestamp":1768780800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2026,1,19]],"date-time":"2026-01-19T00:00:00Z","timestamp":1768780800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"DOI":"10.13039\/501100006447","name":"University of Zurich","doi-asserted-by":"crossref","id":[{"id":"10.13039\/501100006447","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Pediatr Radiol"],"abstract":"<jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Radiation dose reduction is essential in paediatric lung computed tomography (CT). Advances in energy-integrating detector CT and deep-learning reconstruction may enable ultra-low-dose imaging comparable to photon-counting CT.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Objective<\/jats:title>\n                    <jats:p>To evaluate the radiation dose and performance of an ultra-low-dose lung CT protocol using a wide-detector energy-integrating CT system in paediatric patients, focusing on effective radiation dose and diagnostic image quality.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Materials and methods<\/jats:title>\n                    <jats:p>A total of 277 low-dose lung CT scans from 106 paediatric patients (age range, 113\u00a0days to 17.85\u00a0years) were retrospectively analysed. All scans were acquired in axial mode using a 256-slice-multidetector CT scanner with deep learning image reconstruction and attenuation-based Auto Prescription. Radiation dose parameters, including volume CT dose index, dose-length product, size-specific dose estimate, and effective dose, were calculated. Signal-to-noise ratio and contrast-to-noise ratio were assessed in standardised anatomical regions. Patients were stratified by age, and statistical analysis was conducted to evaluate dose trends and image quality metrics.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      There were significant differences between all age groups for all dose parameters (Kruskal\u2013Wallis test,\n                      <jats:italic>P<\/jats:italic>\n                      &lt;0.05). The median effective dose increased with age, ranging from 0.12\u00a0mSv (interquartile range (IQR) 0.09\u20130.14\u00a0mSv) in the 0\u20135-year group to 0.23\u00a0mSv (IQR 0.21\u20130.25\u00a0mSv) in adolescents aged 15 years to\u2009&lt;18\u00a0years. Contrast-to-noise ratio and signal-to-noise ratio exhibited age-dependent variation with a small increase in older age groups. One-sided non-inferiority testing demonstrated that the signal-to-noise ratio and contrast-to-noise ratio in the youngest age group (0\u20135\u00a0years) were not significantly inferior to those in the\u2009\u226515-year group (\n                      <jats:italic>P<\/jats:italic>\n                      &lt;0.05). All examinations were deemed diagnostically sufficient by board-certified paediatric radiologists. Non-disruptive artefacts such as cardiac motion and step artefacts occurred frequently but did not impair interpretation.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>Ultra-low-dose lung CT using wide-detector energy-integrating CT with deep-learning image reconstruction allows for routine diagnostic imaging in children at radiation doses ranging from 0.12\u00a0mSv to 0.23\u00a0mSv, comparable to those reported for newer photon-counting CT systems. This approach provides a robust, clinically viable strategy for minimizing radiation exposure while maintaining diagnostic image quality.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Graphical abstract<\/jats:title>\n                  <\/jats:sec>","DOI":"10.1007\/s00247-025-06503-z","type":"journal-article","created":{"date-parts":[[2026,1,19]],"date-time":"2026-01-19T09:05:58Z","timestamp":1768813558000},"page":"536-544","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Attenuation-based ultra-low-dose lung computed tomography at 0.1 mSv to 0.3\u00a0mSv effective dose in children"],"prefix":"10.1007","volume":"56","author":[{"given":"Max-Johann","family":"Sturm","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Christian J.","family":"Kellenberger","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Franco","family":"Rupcich","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sebastian","family":"Tschauner","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Michael","family":"Zellner","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,1,19]]},"reference":[{"key":"6503_CR1","doi-asserted-by":"publisher","first-page":"581","DOI":"10.1007\/s00247-022-05526-0","volume":"53","author":"E Nagy","year":"2023","unstructured":"Nagy E, Tschauner S, Schramek C, Sorantin E (2023) Paediatric CT made easy. 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