{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,19]],"date-time":"2026-03-19T04:18:08Z","timestamp":1773893888094,"version":"3.50.1"},"reference-count":29,"publisher":"Wiley","issue":"1","license":[{"start":{"date-parts":[[2026,1,8]],"date-time":"2026-01-08T00:00:00Z","timestamp":1767830400000},"content-version":"vor","delay-in-days":7,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"content-domain":{"domain":["aapm.onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Medical Physics"],"published-print":{"date-parts":[[2026,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Virtual clinical trials provide an efficient alternative to clinical imaging trials for evaluating imaging technologies. In x\u2010ray simulations, however, modeling material\u2010specific attenuation becomes computationally intensive as anatomical complexity and material heterogeneity in digital phantoms increase. Parameterization models offer a potential solution by representing material properties with a compact set of coefficients.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Purpose<\/jats:title>\n                    <jats:p>To develop and validate an x\u2010ray simulation framework that models material attenuation using parameterization models, reducing computational cost while maintaining accuracy.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>Material attenuation was modeled with a five\u2010coefficient parameterization derived from physical cross\u2010section data. Unlike conventional ray\u2010tracing, which projects each material separately, the proposed method projects only the five parameter maps, making computational cost independent of phantom complexity. This framework was evaluated in two scenarios: breast imaging with 10 compressed breast phantoms with varying fibro\u2010glandular content, and whole\u2010body imaging with head and abdomen phantoms. Accuracy was assessed by computing percent errors in attenuation coefficients, sinograms, and reconstructed images relative to the conventional approach. For whole\u2010body imaging only, additional analyses included the impact of resolution loss and noise, the comparison with errors introduced by different projector models to place results in the context of standard simulation variability, and computational time measurements.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Across all materials and both applications, the maximum attenuation coefficient error was 0.007% (breast skin tissue), far below reported biological variability. Projection and reconstruction errors remained within\u00a0\u00b1\u00a00.006% for all cases. In whole\u2010body imaging, these errors were well below those from projector model differences (\u00b1\u00a00.5%), and image modification routines further concentrated the error distribution around zero. Simulation times decreased significantly, with acceleration factors scaling linearly with the number of materials within the phantoms.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>The proposed framework achieves accurate and efficient simulation of material attenuation in x\u2010ray imaging, especially in anatomically complex scenarios. Validated in both breast and whole\u2010body imaging, it offers a robust and efficient alternative to conventional methods, supporting the development of advanced virtual clinical trials and spectral imaging research.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1002\/mp.70255","type":"journal-article","created":{"date-parts":[[2026,1,9]],"date-time":"2026-01-09T02:17:30Z","timestamp":1767925050000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Computationally efficient x\u2010ray simulation framework using parameterized material attenuation models in anatomically detailed imaging"],"prefix":"10.1002","volume":"53","author":[{"given":"Martina","family":"Nassi","sequence":"first","affiliation":[{"name":"Department of Medical Imaging Radboud University Medical Center  Nijmegen the Netherlands"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mikhail","family":"Mikerov","sequence":"additional","affiliation":[{"name":"Department of Medical Imaging Radboud University Medical Center  Nijmegen the Netherlands"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Koen","family":"Michielsen","sequence":"additional","affiliation":[{"name":"Department of Medical Imaging Radboud University Medical Center  Nijmegen the Netherlands"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ioannis","family":"Sechopoulos","sequence":"additional","affiliation":[{"name":"Department of Medical Imaging Radboud University Medical Center  Nijmegen the Netherlands"},{"name":"Dutch Expert Centre for Screening (LRCB)  Nijmegen the Netherlands"},{"name":"Technical Medical Centre University of Twente  Enschede the Netherlands"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","published-online":{"date-parts":[[2026,1,8]]},"reference":[{"key":"e_1_2_8_2_1","doi-asserted-by":"publisher","DOI":"10.1118\/1.4794178"},{"key":"e_1_2_8_3_1","doi-asserted-by":"publisher","DOI":"10.1117\/1.JMI.7.4.042805"},{"key":"e_1_2_8_4_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.cpc.2013.10.034"},{"key":"e_1_2_8_5_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.nima.2019.06.069"},{"key":"e_1_2_8_6_1","doi-asserted-by":"publisher","DOI":"10.48550\/arXiv.2405.11133"},{"key":"e_1_2_8_7_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.radmeas.2010.08.008"},{"key":"e_1_2_8_8_1","doi-asserted-by":"publisher","DOI":"10.1080\/14786441008635242"},{"key":"e_1_2_8_9_1","doi-asserted-by":"publisher","DOI":"10.1118\/1.594199"},{"key":"e_1_2_8_10_1","doi-asserted-by":"publisher","DOI":"10.1118\/1.598175"},{"key":"e_1_2_8_11_1","unstructured":"ColtonD KressR.Inverse Acoustic and Electromagnetic Scattering Theory.Springer International Publishing.2019. doi:10.1007\/978\u20103\u2010030\u201030351\u20108"},{"key":"e_1_2_8_12_1","doi-asserted-by":"publisher","DOI":"10.48550\/arXiv.math\u2010ph\/0401050"},{"key":"e_1_2_8_13_1","doi-asserted-by":"publisher","DOI":"10.1016\/0370\u20101573(81)90014\u20104"},{"key":"e_1_2_8_14_1","doi-asserted-by":"publisher","DOI":"10.1088\/0031\u20109155\/48\/20\/009"},{"key":"e_1_2_8_15_1","doi-asserted-by":"publisher","DOI":"10.1088\/0031\u20109155\/49\/2\/009"},{"key":"e_1_2_8_16_1","doi-asserted-by":"publisher","DOI":"10.1051\/jphystap:0190100100065300"},{"key":"e_1_2_8_17_1","unstructured":"NewvilleM easyXAFS WhittingtonN et\u00a0al.xraypy\/XrayDB: X\u2011ray Reference Data in SQLite [software]. 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