{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,14]],"date-time":"2026-10-14T16:19:33Z","timestamp":1791994773378,"version":"4.4.0"},"reference-count":81,"publisher":"Wiley","issue":"4","license":[{"start":{"date-parts":[[2026,4,10]],"date-time":"2026-04-10T00:00:00Z","timestamp":1775779200000},"content-version":"vor","delay-in-days":9,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T00:00:00Z","timestamp":1775001600000},"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":[[2026,4]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Multimaterial decomposition (MMD) in dual\u2010energy CT enables iodine quantification, critical for diagnostic applications. However, residual errors from noniodine materials in iodine maps limit accuracy, especially in complex thoracic regions and low\u2010dose\u00a0settings.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Purpose<\/jats:title>\n                    <jats:p>To evaluate iodine quantification accuracy and residual error using a principal component analysis multimaterial decomposition (PCA\u2010MMD) algorithm on dual\u2010energy CT data across different phantom sizes and radiation dose\u00a0levels.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>A thorax phantom containing iodine (2\u201320 mg\/mL) and calcium (50\u2013400 mg\/mL) inserts was scanned on a clinical photon\u2010counting CT system. Three phantom sizes (small: 20.9 cm, medium: 27.3 cm, large: 33.2\u2010cm water\u2010equivalent diameter) were imaged at dose levels ranging from 3 to 55 mGy. The PCA\u2010MMD algorithm applies a principal component analysis (PCA) transformation followed by direct geometric estimation with barycentric coordinates, thereby avoiding matrix inversion instability. Iodine quantification was evaluated using linear regression, root mean square error (RMSE), and coefficient of variation (CV). Residual error in noniodine regions was expressed as a percentage of the minimum detectable iodine concentration. The algorithm's performance was also evaluated through a clinical proof\u2010of\u2010concept study involving five patients, comparing virtual noncontrast (VNC) images to true noncontrast (TNC)\u00a0references.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>PCA\u2010MMD achieved near\u2010unity regression slopes (0.98\u20130.99, ) across all phantom sizes, reducing RMSE by up to 65% compared to the standard barycentric coordinate\u2010based MMD (0.10\u20130.39 vs. 0.20\u20130.72 mg\/mL). Residual error was markedly lower with PCA\u2010MMD (0.7\u20131.6%) than with the standard barycentric coordinate\u2010based MMD (16.1%\u201354.9%) under identical conditions. At 3 mGy, PCA\u2010MMD achieved an RMSE of 0.60 mg\/mL versus 0.95 mg\/mL for the standard barycentric coordinate\u2010based MMD. In the clinical cohort, PCA\u2010MMD significantly improved VNC accuracy, achieving a mean RMSE of 15.5 HU compared to 20.9 HU for the vendor\u2010specific algorithm (). Reproducibility was excellent, with 85% of the measurements showing a CV .<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>PCA\u2010MMD significantly improved iodine quantification accuracy and reduced residual error in both phantom and clinical settings. Its robustness across different dose levels supports its potential for clinical translation in quantitative dual\u2010energy CT\u00a0applications.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1002\/mp.70407","type":"journal-article","created":{"date-parts":[[2026,4,10]],"date-time":"2026-04-10T10:47:34Z","timestamp":1775818054000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Accurate iodine quantification and residual error reduction with principal component analysis multimaterial decomposition using spectral CT"],"prefix":"10.1002","volume":"53","author":[{"given":"Hamidreza","family":"Khodajou\u2010Chokami","sequence":"first","affiliation":[{"name":"Department of Radiological Sciences University of California at Irvine Irvine California USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Huanjun","family":"Ding","sequence":"additional","affiliation":[{"name":"Department of Radiological Sciences University of California at Irvine Irvine California USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sabee","family":"Molloi","sequence":"additional","affiliation":[{"name":"Department of Radiological Sciences University of California at Irvine Irvine California USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2026,4,10]]},"reference":[{"key":"e_1_2_8_2_1","doi-asserted-by":"publisher","DOI":"10.1148\/radiol.2015142631"},{"key":"e_1_2_8_3_1","doi-asserted-by":"publisher","DOI":"10.1148\/radiol.2018172656"},{"key":"e_1_2_8_4_1","doi-asserted-by":"publisher","DOI":"10.1109\/TRPMS.2020.3020212"},{"key":"e_1_2_8_5_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ejrad.2023.110829"},{"key":"e_1_2_8_6_1","doi-asserted-by":"publisher","DOI":"10.1002\/acm2.13468"},{"key":"e_1_2_8_7_1","doi-asserted-by":"publisher","DOI":"10.1002\/mp.14241"},{"key":"e_1_2_8_8_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ejrad.2016.06.023"},{"key":"e_1_2_8_9_1","doi-asserted-by":"publisher","DOI":"10.1186\/s41747-022-00313-w"},{"key":"e_1_2_8_10_1","doi-asserted-by":"publisher","DOI":"10.1002\/acm2.13471"},{"key":"e_1_2_8_11_1","doi-asserted-by":"publisher","DOI":"10.1148\/radiol.2019182870"},{"key":"e_1_2_8_12_1","doi-asserted-by":"publisher","DOI":"10.2214\/AJR.16.17308"},{"key":"e_1_2_8_13_1","doi-asserted-by":"publisher","DOI":"10.1186\/s42492-022-00125-0"},{"key":"e_1_2_8_14_1","doi-asserted-by":"publisher","DOI":"10.1148\/rg.2016160079"},{"key":"e_1_2_8_15_1","doi-asserted-by":"publisher","DOI":"10.2214\/AJR.19.21818"},{"key":"e_1_2_8_16_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jcmg.2018.02.019"},{"key":"e_1_2_8_17_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.acra.2019.02.013"},{"key":"e_1_2_8_18_1","doi-asserted-by":"publisher","DOI":"10.1002\/acm2.13161"},{"key":"e_1_2_8_19_1","doi-asserted-by":"publisher","DOI":"10.1007\/s00330-017-4752-9"},{"key":"e_1_2_8_20_1","doi-asserted-by":"publisher","DOI":"10.1118\/1.3097632"},{"key":"e_1_2_8_21_1","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2013.2281719"},{"key":"e_1_2_8_22_1","doi-asserted-by":"publisher","DOI":"10.1118\/1.4947485"},{"key":"e_1_2_8_23_1","doi-asserted-by":"publisher","DOI":"10.1117\/1.JMI.6.4.044004"},{"key":"e_1_2_8_24_1","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2014.2320284"},{"key":"e_1_2_8_25_1","doi-asserted-by":"publisher","DOI":"10.1088\/1361-6560\/aa7122"},{"key":"e_1_2_8_26_1","doi-asserted-by":"publisher","DOI":"10.1002\/mp.15227"},{"key":"e_1_2_8_27_1","doi-asserted-by":"publisher","DOI":"10.1002\/mp.17679"},{"key":"e_1_2_8_28_1","doi-asserted-by":"publisher","DOI":"10.1148\/rycan.2021200097"},{"key":"e_1_2_8_29_1","doi-asserted-by":"publisher","DOI":"10.3390\/jcdd10090363"},{"key":"e_1_2_8_30_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10278-017-9954-9"},{"key":"e_1_2_8_31_1","unstructured":"AAPM Task Group 220.Use of Water Equivalent Diameter for Calculating Patient Size and Size\u2010Specific Dose Estimates (SSDE) in CT. Technical Report. Report No. 220.American Association of Physicists in Medicine;2014.https:\/\/www.aapm.org\/pubs\/reports\/RPT_220.pdf"},{"key":"e_1_2_8_32_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ejrad.2019.02.012"},{"key":"e_1_2_8_33_1","unstructured":"American Association of Physicists in Medicine (AAPM) Task Group 204.Size\u2010Specific Dose Estimates (SSDE) in Pediatric and Adult Body CT Examinations. Technical Report. Report No. 204.American Association of Physicists in Medicine;2011.https:\/\/www.aapm.org\/pubs\/reports\/rpt_204.pdf"},{"key":"e_1_2_8_34_1","doi-asserted-by":"publisher","DOI":"10.1097\/RLI.0000000000000956"},{"key":"e_1_2_8_35_1","doi-asserted-by":"publisher","DOI":"10.1016\/0010-4825(76)90069-X"},{"key":"e_1_2_8_36_1","doi-asserted-by":"publisher","DOI":"10.1016\/0020-708X(82)90248-4"},{"key":"e_1_2_8_37_1","doi-asserted-by":"publisher","DOI":"10.1002\/mp.14204"},{"key":"e_1_2_8_38_1","unstructured":"BergerMJ HubbellJH SeltzerSM et\u00a0al.XCOM: Photon Cross\u2010Section Database. National Institute of Standards and Technology (NIST).2010. Accessed March 30 2026.https:\/\/physics.nist.gov\/PhysRefData\/Xcom\/html\/xcom1.html"},{"key":"e_1_2_8_39_1","doi-asserted-by":"publisher","DOI":"10.1118\/1.3658568"},{"key":"e_1_2_8_40_1","doi-asserted-by":"publisher","DOI":"10.1148\/radiol.2018172361"},{"key":"e_1_2_8_41_1","doi-asserted-by":"crossref","unstructured":"Samei E BakalyarD BoedekerK et\u00a0al.Performance Evaluation of Computed Tomography Systems. The Report of AAPM Task Group 233. Report No. 233.American Association of Physicists in Medicine;2019.","DOI":"10.37206\/186"},{"key":"e_1_2_8_42_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-024-81735-x"},{"key":"e_1_2_8_43_1","doi-asserted-by":"crossref","unstructured":"NiehoffJH WoeltjenMM LaukampKR BorggrefeJ KroegerJR.Virtual Non-Contrast versus True Non-Contrast Computed Tomography: Initial Experiences with a Photon Counting Scanner Approved for Clinical Use. Diagnostics.2021;11(12):2377.https:\/\/www.mdpi.com\/2075-4418\/11\/12\/2377","DOI":"10.3390\/diagnostics11122377"},{"key":"e_1_2_8_44_1","doi-asserted-by":"publisher","DOI":"10.1186\/s41747-021-00217-1"},{"key":"e_1_2_8_45_1","doi-asserted-by":"publisher","DOI":"10.2478\/msr-2022-0033"},{"key":"e_1_2_8_46_1","doi-asserted-by":"publisher","DOI":"10.1007\/s11604-021-01233-2"},{"key":"e_1_2_8_47_1","doi-asserted-by":"publisher","DOI":"10.3390\/tomography9010017"},{"key":"e_1_2_8_48_1","doi-asserted-by":"publisher","DOI":"10.1148\/ryai.230024"},{"key":"e_1_2_8_49_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.imu.2017.08.001"},{"key":"e_1_2_8_50_1","doi-asserted-by":"publisher","DOI":"10.1117\/1.OE.58.1.013104"},{"issue":"3","key":"e_1_2_8_51_1","first-page":"461","article-title":"Multi\u2010material decomposition of spectral CT images via fully convolutional DenseNets","volume":"27","author":"Wu X","year":"2019","journal-title":"J Xray Sci Technol"},{"key":"e_1_2_8_52_1","doi-asserted-by":"crossref","unstructured":"XingY GaoH ShenL.Physically interpretable deep learning reconstruction for photon counting spectral CT. In:Deep Learning for Advanced X\u2010ray Detection and Imaging Applications.Springer;2025:21\u201042.","DOI":"10.1007\/978-3-031-75653-5_2"},{"key":"e_1_2_8_53_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-025-09739-9"},{"key":"e_1_2_8_54_1","doi-asserted-by":"publisher","DOI":"10.1109\/TRPMS.2023.3314131"},{"key":"e_1_2_8_55_1","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2021.3056150"},{"key":"e_1_2_8_56_1","unstructured":"EguizabalA \u00d6ktemO PerssonMU.Deep learning for material decomposition in photon\u2010counting CT.arXiv preprint arXiv:2208.03360.2022."},{"key":"e_1_2_8_57_1","doi-asserted-by":"publisher","DOI":"10.1118\/1.4870375"},{"key":"e_1_2_8_58_1","doi-asserted-by":"publisher","DOI":"10.1002\/mp.13001"},{"key":"e_1_2_8_59_1","doi-asserted-by":"publisher","DOI":"10.1002\/mp.12096"},{"key":"e_1_2_8_60_1","doi-asserted-by":"crossref","unstructured":"WangJ PerelliA.End\u2010to\u2010end model\u2010based deep learning for dual\u2010energy computed tomography material decomposition. In:2024 IEEE International Symposium on Biomedical Imaging (ISBI).IEEE;2024:1\u20105.","DOI":"10.1109\/ISBI56570.2024.10635736"},{"key":"e_1_2_8_61_1","article-title":"Direct dual\u2010energy CT material decomposition using model\u2010based denoising diffusion model","author":"Xu H","year":"2025","journal-title":"arXiv preprint arXiv:2507.18012"},{"key":"e_1_2_8_62_1","doi-asserted-by":"publisher","DOI":"10.1109\/TBME.2020.3013491"},{"key":"e_1_2_8_63_1","doi-asserted-by":"publisher","DOI":"10.1148\/radiol.10100231"},{"key":"e_1_2_8_64_1","doi-asserted-by":"publisher","DOI":"10.1186\/s42492-020-00052-y"},{"key":"e_1_2_8_65_1","doi-asserted-by":"publisher","DOI":"10.1088\/1361-6560\/aba7d2"},{"key":"e_1_2_8_66_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-022-21193-5"},{"key":"e_1_2_8_67_1","doi-asserted-by":"publisher","DOI":"10.1148\/radiol.2017170896"},{"key":"e_1_2_8_68_1","doi-asserted-by":"publisher","DOI":"10.1007\/s00330-013-3040-6"},{"key":"e_1_2_8_69_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-019-42330-7"},{"key":"e_1_2_8_70_1","doi-asserted-by":"publisher","DOI":"10.1186\/s41747-021-00224-2"},{"key":"e_1_2_8_71_1","doi-asserted-by":"publisher","DOI":"10.1007\/s00261-025-05098-1"},{"key":"e_1_2_8_72_1","doi-asserted-by":"crossref","unstructured":"Khodajou\u2010ChokamiH BitarafanA DylovDV BaghshahMS HosseiniSA.Personalized computational human phantoms via a hybrid model\u2010based deep learning method. In:2020 IEEE International Symposium on Medical Measurements and Applications (MeMeA).IEEE;2020:1\u20106.","DOI":"10.1109\/MeMeA49120.2020.9137114"},{"key":"e_1_2_8_73_1","doi-asserted-by":"crossref","unstructured":"Khodajou\u2010ChokamiH DylovDV.Data fusion approach for constructing unsupervised augmented voxel\u2010based statistical anthropomorphic phantoms. In:2019 IEEE International Conference on Bioinformatics and Biomedicine (BIBM).IEEE;2019:1508\u20101512.","DOI":"10.1109\/BIBM47256.2019.8983359"},{"key":"e_1_2_8_74_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10554-023-03040-4"},{"key":"e_1_2_8_75_1","doi-asserted-by":"publisher","DOI":"10.3390\/bioengineering11040301"},{"key":"e_1_2_8_76_1","doi-asserted-by":"publisher","DOI":"10.1007\/s00330-024-10934-x"},{"key":"e_1_2_8_77_1","unstructured":"AAPM Alliance for Quality CT.AAPM Computed tomography automatic exposure control education slides. Accessed March 30 2026.https:\/\/www.aapm.org\/pubs\/CTProtocols\/documents\/GECTAECEducationSlides.pdf"},{"key":"e_1_2_8_78_1","doi-asserted-by":"crossref","unstructured":"McColloughC BakalyarDM BostaniM et\u00a0al.Use of Water Equivalent Diameter for Calculating Patient Size and Size\u2010Specific Dose Estimates (SSDE) in CT: the Report of AAPM Task group 220. AAPM Report.2014:6.","DOI":"10.37206\/146"},{"key":"e_1_2_8_79_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-024-66657-y"},{"key":"e_1_2_8_80_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jcct.2013.01.004"},{"key":"e_1_2_8_81_1","doi-asserted-by":"publisher","DOI":"10.1002\/acm2.12754"},{"key":"e_1_2_8_82_1","doi-asserted-by":"publisher","DOI":"10.5152\/dir.2019.18412"}],"container-title":["Medical Physics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/aapm.onlinelibrary.wiley.com\/doi\/pdf\/10.1002\/mp.70407","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/aapm.onlinelibrary.wiley.com\/doi\/full-xml\/10.1002\/mp.70407","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/aapm.onlinelibrary.wiley.com\/doi\/pdf\/10.1002\/mp.70407","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,7,3]],"date-time":"2026-07-03T21:25:09Z","timestamp":1783113909000},"score":1,"resource":{"primary":{"URL":"https:\/\/aapm.onlinelibrary.wiley.com\/doi\/10.1002\/mp.70407"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,4]]},"references-count":81,"journal-issue":{"issue":"4","published-print":{"date-parts":[[2026,4]]}},"alternative-id":["10.1002\/mp.70407"],"URL":"https:\/\/doi.org\/10.1002\/mp.70407","archive":["Portico"],"relation":{},"ISSN":["0094-2405","2473-4209"],"issn-type":[{"value":"0094-2405","type":"print"},{"value":"2473-4209","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,4]]},"assertion":[{"value":"2025-10-16","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2026-03-12","order":2,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2026-04-10","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}],"article-number":"e70407"}}