{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,18]],"date-time":"2026-09-18T05:11:58Z","timestamp":1789708318622,"version":"4.0.1"},"reference-count":20,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2025,8,25]],"date-time":"2025-08-25T00:00:00Z","timestamp":1756080000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Philips Healthcare","award":["Exhibit B-HE-29"],"award-info":[{"award-number":["Exhibit B-HE-29"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Tomography"],"abstract":"<jats:p>Objective: The objective of this study was to compare the performance and robustness of a deep learning reconstruction method against established alternatives for soft tissue CT image reconstruction. Materials and Methods: Images were generated from portal venous phase chest\u2013abdomen\u2013pelvis CT scans (n = 99) acquired on a dual-layer spectral detector CT using filtered back projection, iterative model reconstruction (IMR), and deep learning reconstruction (DLR) with three parameter settings, namely \u2018standard\u2019, \u2018sharper\u2019, and \u2018smoother\u2019. Experienced raters performed a quantitative assessment by considering attenuation stability and image noise levels in ten representative structures across all reconstruction methods, as well as a qualitative assessment using a four-point Likert scale (1 = poor, 2 = fair, 3 = good, 4 = excellent) for their overall perception of \u2018smoother\u2019 DLR and IMR images. One scan was excluded due to cachexia, which limited the quantitative measurements. Results: The inter-rater reliability for quantitative measurements ranged from moderate to excellent (r = 0.63\u20130.96). Attenuation values did not differ significantly between reconstruction methods except for DLR against IMR in the psoas muscle (mean + 3.0 HU, p &lt; 0.001). Image noise levels differed significantly between reconstruction methods for all structures (all p &lt; 0.001) and were lower than FBP with any DLR parameter setting. Image noise levels with \u2018smoother\u2019 DLR were predominantly lower than or equal to IMR, while they were higher with \u2018standard\u2019 DLR and \u2018sharper\u2019 DLR. The \u2018smoother\u2019 DLR images received a higher mean rating for overall image quality than the IMR images (3.7 vs. 2.3, p &lt; 0.001). Conclusions: \u2018Smoother\u2019 DLR images were perceived by experienced readers as having improved quality compared to FBP and IMR while also exhibiting objectively lower or equivalent noise levels.<\/jats:p>","DOI":"10.3390\/tomography11090094","type":"journal-article","created":{"date-parts":[[2025,8,26]],"date-time":"2025-08-26T06:26:31Z","timestamp":1756189591000},"page":"94","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Performance of a Deep Learning Reconstruction Method on Clinical Chest\u2013Abdomen\u2013Pelvis Scans from a Dual-Layer Detector CT System"],"prefix":"10.3390","volume":"11","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9675-803X","authenticated-orcid":false,"given":"Christopher","family":"Schuppert","sequence":"first","affiliation":[{"name":"Department of Diagnostic and Interventional Radiology, Medical Center, Faculty of Medicine, University of Freiburg, 79106 Freiburg, Germany"},{"name":"Clinic of Diagnostic and Interventional Radiology, Heidelberg University Hospital, 69120 Heidelberg, Germany"},{"name":"Translational Lung Research Center Heidelberg (TLRC), German Center for Lung Research (DZL), Heidelberg University Hospital, 69120 Heidelberg, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5012-1191","authenticated-orcid":false,"given":"Stefanie","family":"Rahn","sequence":"additional","affiliation":[{"name":"Clinic of Diagnostic and Interventional Radiology, Heidelberg University Hospital, 69120 Heidelberg, Germany"},{"name":"Translational Lung Research Center Heidelberg (TLRC), German Center for Lung Research (DZL), Heidelberg University Hospital, 69120 Heidelberg, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8095-9382","authenticated-orcid":false,"given":"Nikolas D.","family":"Schnellb\u00e4cher","sequence":"additional","affiliation":[{"name":"Philips GmbH Innovative Technologies, 22335 Hamburg, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Frank","family":"Bergner","sequence":"additional","affiliation":[{"name":"Philips GmbH Innovative Technologies, 22335 Hamburg, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Michael","family":"Grass","sequence":"additional","affiliation":[{"name":"Philips GmbH Innovative Technologies, 22335 Hamburg, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hans-Ulrich","family":"Kauczor","sequence":"additional","affiliation":[{"name":"Clinic of Diagnostic and Interventional Radiology, Heidelberg University Hospital, 69120 Heidelberg, Germany"},{"name":"Translational Lung Research Center Heidelberg (TLRC), German Center for Lung Research (DZL), Heidelberg University Hospital, 69120 Heidelberg, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6759-6326","authenticated-orcid":false,"given":"Stephan","family":"Skornitzke","sequence":"additional","affiliation":[{"name":"Clinic of Diagnostic and Interventional Radiology, Heidelberg University Hospital, 69120 Heidelberg, Germany"},{"name":"Translational Lung Research Center Heidelberg (TLRC), German Center for Lung Research (DZL), Heidelberg University Hospital, 69120 Heidelberg, Germany"},{"name":"Philips GmbH Innovative Technologies, 22335 Hamburg, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tim F.","family":"Weber","sequence":"additional","affiliation":[{"name":"Clinic of Diagnostic and Interventional Radiology, Heidelberg University Hospital, 69120 Heidelberg, Germany"},{"name":"Translational Lung Research Center Heidelberg (TLRC), German Center for Lung Research (DZL), Heidelberg University Hospital, 69120 Heidelberg, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2561-3404","authenticated-orcid":false,"given":"Thuy D.","family":"Do","sequence":"additional","affiliation":[{"name":"Clinic of Diagnostic and Interventional Radiology, Heidelberg University Hospital, 69120 Heidelberg, Germany"},{"name":"Translational Lung Research Center Heidelberg (TLRC), German Center for Lung Research (DZL), Heidelberg University Hospital, 69120 Heidelberg, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2025,8,25]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1061","DOI":"10.1007\/s00117-011-2244-5","article-title":"Principles of multidetector-row computed tomography. 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