{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,14]],"date-time":"2026-02-14T08:10:44Z","timestamp":1771056644648,"version":"3.50.1"},"reference-count":38,"publisher":"Wiley","issue":"2","license":[{"start":{"date-parts":[[2025,12,29]],"date-time":"2025-12-29T00:00:00Z","timestamp":1766966400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2025,12,29]],"date-time":"2025-12-29T00:00:00Z","timestamp":1766966400000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"funder":[{"DOI":"10.13039\/501100017649","name":"Hong Kong Government","doi-asserted-by":"publisher","award":["14112521"],"award-info":[{"award-number":["14112521"]}],"id":[{"id":"10.13039\/501100017649","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["analyticalsciencejournals.onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["NMR in Biomedicine"],"published-print":{"date-parts":[[2026,2]]},"abstract":"ABSTRACT<\/jats:title>\n \n The intravoxel incoherent motion (IVIM) three\u2010compartment model (3CM) potentially offers better classification for perfusion\u2010rich pathologies. However, 3CM is often associated with less fitting stability than the two\u2010compartment model (2CM). For liver intravoxel IVIM data, when the fit\u2010starting\n b<\/jats:italic>\n \u2010value is adjusted from 2\u2009s\/mm\n 2<\/jats:sup>\n to\n b<\/jats:italic>\n \n i<\/jats:italic>\n <\/jats:sub>\n s\/mm\n 2<\/jats:sup>\n ,\n PF<\/jats:italic>\n \n i<\/jats:italic>\n <\/jats:sub>\n , which indicates the perfusion fraction at\n b<\/jats:italic>\n \n i<\/jats:italic>\n <\/jats:sub>\n , gradually decreases as the initial fitting\n b<\/jats:italic>\n \u2010value\n b<\/jats:italic>\n \n i<\/jats:italic>\n <\/jats:sub>\n increases and eventually approaches zero. We define\n Y<\/jats:italic>\n \n i<\/jats:italic>\n <\/jats:sub>\n \u2009=\u2009ln [(1\u2009\u2212\u2009\n PF<\/jats:italic>\n \n i<\/jats:italic>\n <\/jats:sub>\n )\/\n PF<\/jats:italic>\n \n i<\/jats:italic>\n <\/jats:sub>\n ]. With a fitted line between\n Y<\/jats:italic>\n \n i<\/jats:italic>\n <\/jats:sub>\n and\n b<\/jats:italic>\n \n i<\/jats:italic>\n <\/jats:sub>\n , the intercept with the\n y<\/jats:italic>\n \u2010axis is the predicted value of\n Y<\/jats:italic>\n 0<\/jats:sub>\n that follows the bi\u2010exponential model. The\n PF<\/jats:italic>\n 0<\/jats:sub>\n calculated from it eliminates the signals of other very rapid perfusion components and retains a more stable perfusion fraction measurement. The slope of the fitted line is (\n D<\/jats:italic>\n \n fast<\/jats:italic>\n <\/jats:sub>\n \u2013\n D<\/jats:italic>\n \n slow<\/jats:italic>\n <\/jats:sub>\n ).\n D<\/jats:italic>\n \n slow<\/jats:italic>\n <\/jats:sub>\n can be calculated by the standard IVIM model. Because the\n Y<\/jats:italic>\n \n i<\/jats:italic>\n <\/jats:sub>\n fitting assumes that the signal attenuation is bi\u2010exponential, and the portion of the signal strength that exceeds the bi\u2010exponential model at very low\n b<\/jats:italic>\n \u2010values is not used, the perfusion fraction detected is the fast decay perfusion component (\n F<\/jats:italic>\n \n fast<\/jats:italic>\n <\/jats:sub>\n ) without the very fast decay perfusion component (\n F<\/jats:italic>\n \n vfast<\/jats:italic>\n <\/jats:sub>\n ). In our study on healthy livers,\n Dataset\u20101<\/jats:italic>\n with 3.0\u2009T data had 17 subjects scanned twice with a 10\u201312\u2009days' interval, and paired scan\u2013rescan had 13 subjects;\n Dataset\u20102<\/jats:italic>\n with 1.5\u2009T data had 20 subjects scanned twice during the same scan session, and paired scan\u2013rescan had 17 subjects. For the 2CM, IVIM parameters\n D<\/jats:italic>\n \n slow<\/jats:italic>\n <\/jats:sub>\n ,\n D<\/jats:italic>\n \n fast<\/jats:italic>\n <\/jats:sub>\n , and\n PF<\/jats:italic>\n \n i<\/jats:italic>\n <\/jats:sub>\n were obtained with a nonlinear least square (NLLSQ) fit. Parameters obtained with segmented fitting were used for\n Y<\/jats:italic>\n \n i<\/jats:italic>\n <\/jats:sub>\n analysis. Results show that conventional fitting and\n Yi<\/jats:italic>\n fitting derived very comparable IVIM parameters in mean value.\n D<\/jats:italic>\n \n fast<\/jats:italic>\n <\/jats:sub>\n obtained with\n Y<\/jats:italic>\n \n i<\/jats:italic>\n <\/jats:sub>\n fitting showed better scan\u2013rescan stability than conventional segmented fitting. Perfusion fraction parameters showed more favorable scan\u2013rescan stability with\n Y<\/jats:italic>\n \n i<\/jats:italic>\n <\/jats:sub>\n fitting.\n <\/jats:p>","DOI":"10.1002\/nbm.70221","type":"journal-article","created":{"date-parts":[[2025,12,30]],"date-time":"2025-12-30T03:38:21Z","timestamp":1767065901000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["A New Approach for Estimating Liver IVIM Fast Diffusion Coefficient in Two\u2010Compartment Model and Fast Diffusion Fraction in Three\u2010Compartment Model: Theory and In\u00a0Vivo Validation of Two Centers' Data"],"prefix":"10.1002","volume":"39","author":[{"given":"Fu\u2010Zhao","family":"Ma","sequence":"first","affiliation":[{"name":"Department of Imaging and Interventional Radiology, Faculty of Medicine The Chinese University of Hong Kong Hong Kong SAR China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5697-0717","authenticated-orcid":false,"given":"Y\u00ec\u00a0Xi\u00e1ng\u00a0J.","family":"W\u00e1ng","sequence":"additional","affiliation":[{"name":"Department of Imaging and Interventional Radiology, Faculty of Medicine The Chinese University of Hong Kong Hong Kong SAR China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","published-online":{"date-parts":[[2025,12,29]]},"reference":[{"key":"e_1_2_11_2_1","doi-asserted-by":"publisher","DOI":"10.1148\/radiology.161.2.3763909"},{"key":"e_1_2_11_3_1","doi-asserted-by":"publisher","DOI":"10.1002\/jmri.1880010103"},{"key":"e_1_2_11_4_1","doi-asserted-by":"publisher","DOI":"10.1007\/s00330-014-3554-6"},{"key":"e_1_2_11_5_1","doi-asserted-by":"publisher","DOI":"10.3390\/diagnostics11020379"},{"key":"e_1_2_11_6_1","doi-asserted-by":"publisher","DOI":"10.1002\/nbm.3852"},{"key":"e_1_2_11_7_1","doi-asserted-by":"publisher","DOI":"10.1002\/nbm.4155"},{"key":"e_1_2_11_8_1","doi-asserted-by":"publisher","DOI":"10.1177\/0271678X16681310"},{"key":"e_1_2_11_9_1","doi-asserted-by":"publisher","DOI":"10.1002\/jmri.25519"},{"key":"e_1_2_11_10_1","doi-asserted-by":"publisher","DOI":"10.1002\/jmri.28858"},{"key":"e_1_2_11_11_1","doi-asserted-by":"publisher","DOI":"10.2147\/JHC.S433948"},{"key":"e_1_2_11_12_1","doi-asserted-by":"publisher","DOI":"10.1002\/mrm.28582"},{"key":"e_1_2_11_13_1","doi-asserted-by":"publisher","DOI":"10.1002\/mrm.28996"},{"key":"e_1_2_11_14_1","doi-asserted-by":"publisher","DOI":"10.1002\/jmri.26730"},{"key":"e_1_2_11_15_1","first-page":"107","article-title":"Diffusion\u2010Weighted MRI of the Liver: Challenges and Some Solutions for the Quantification of Apparent Diffusion Coefficient and Intravoxel Incoherent Motion","volume":"11","author":"Wang Y. 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