{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,29]],"date-time":"2026-09-29T03:59:13Z","timestamp":1790654353643,"version":"4.1.0"},"reference-count":70,"publisher":"Wiley","issue":"6","license":[{"start":{"date-parts":[[2026,8,4]],"date-time":"2026-08-04T00:00:00Z","timestamp":1785801600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2026,8,4]],"date-time":"2026-08-04T00:00:00Z","timestamp":1785801600000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"funder":[{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["R00NS123229"],"award-info":[{"award-number":["R00NS123229"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["R01NS136369"],"award-info":[{"award-number":["R01NS136369"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Magnetic Resonance in Med"],"published-print":{"date-parts":[[2026,12]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Purpose<\/jats:title>\n                    <jats:p>QQ, a recently proposed oxygen extraction fraction (OEF) mapping technique combining quantitative susceptibility mapping (QSM) and quantitative blood oxygen level\u2010dependent (qBOLD) (QSM\u2009+\u2009qBOLD\u2009=\u2009QQ), generates OEF maps noninvasively from a single routine MRI sequence, without requiring vascular challenges used in other OEF approaches. A deep learning approach, QQ\u2010NET, further enables rapid 3D OEF reconstruction (\u02dc1.5\u2009min), but it is trained on a fixed echo\u2010time (TE) scheme and must be retrained whenever acquisition protocols differ, limiting its clinical applicability. This study introduces QQ\u2010F, a novel deep learning approach designed to eliminate the need for retraining.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>QQ\u2010F incorporates a feature extraction unit that derives QQ model\u2010related features as inputs, rather than relying directly on raw signals. For a fair comparison, QQ\u2010F was trained using the same 3D multi\u2010echo gradient echo (mGRE) dataset as QQ\u2010NET, acquired from 26 ischemic stroke patients. Both models were tested using simulations and data from 24 multiple sclerosis (MS) and 30 dementia patients acquired with varying TE sequences.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>In simulations, QQ\u2010F provided more accurate OEF maps than QQ\u2010NET with lower mean absolute error. In patient datasets\u2013particularly dementia datasets, where TE values differed substantially from QQ\u2010NET's training protocol\u2014QQ\u2010F yielded significantly higher lesion\u2010to\u2010normal tissue contrast than QQ\u2010NET, indicating superior robustness to acquisition variability.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>QQ\u2010F enables deep learning\u2010based QQ OEF mapping across diverse MR acquisition protocols without retraining, thereby enhancing the clinical scalability of QQ\u2010based OEF mapping.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1002\/mrm.70524","type":"journal-article","created":{"date-parts":[[2026,8,5]],"date-time":"2026-08-05T05:11:47Z","timestamp":1785906707000},"page":"2812-2821","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["A Generalized Approach to Solving Deep Learning\u2010Based Quantitative Susceptibility Mapping and Quantitative Blood Oxygen Level Dependent Magnitude (\n                    <scp>QSM<\/scp>\n                    \u2009+\u2009\n                    <scp>qBOLD<\/scp>\n                    or\n                    <scp>QQ<\/scp>\n                    ) for Oxygen Extraction Fraction (\n                    <scp>OEF<\/scp>\n                    ) Mapping Across Diverse Acquisition Schemes"],"prefix":"10.1002","volume":"96","author":[{"ORCID":"https:\/\/orcid.org\/0009-0008-8186-341X","authenticated-orcid":false,"given":"Tian","family":"Qiu","sequence":"first","affiliation":[{"name":"Department of Biomedical Engineering George Washington University  Washington DC USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ada","family":"Ally","sequence":"additional","affiliation":[{"name":"Department of Biomedical Engineering State University of New York at Buffalo  Buffalo New York USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Arpita","family":"Misra","sequence":"additional","affiliation":[{"name":"Department of Biomedical Engineering George Washington University  Washington DC USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Gloria C.","family":"Chiang","sequence":"additional","affiliation":[{"name":"Department of Radiology Weill Cornell Medicine  New York New York USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1411-7694","authenticated-orcid":false,"given":"Thanh D.","family":"Nguyen","sequence":"additional","affiliation":[{"name":"Department of Radiology Weill Cornell Medicine  New York New York USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Susan A.","family":"Gauthier","sequence":"additional","affiliation":[{"name":"Department of Radiology Weill Cornell Medicine  New York New York USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shun","family":"Zhang","sequence":"additional","affiliation":[{"name":"Department of Radiology Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology  Wuhan Hubei China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1404-8526","authenticated-orcid":false,"given":"Yi","family":"Wang","sequence":"additional","affiliation":[{"name":"Department of Radiology Weill Cornell Medicine  New York New York USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Junghun","family":"Cho","sequence":"additional","affiliation":[{"name":"Department of Biomedical Engineering George Washington University  Washington DC USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2026,8,4]]},"reference":[{"key":"e_1_2_8_2_1","doi-asserted-by":"publisher","DOI":"10.1093\/brain\/awf047"},{"key":"e_1_2_8_3_1","doi-asserted-by":"publisher","DOI":"10.1161\/strokeaha.112.663716"},{"key":"e_1_2_8_4_1","doi-asserted-by":"publisher","DOI":"10.3174\/ajnr.A3668"},{"key":"e_1_2_8_5_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2023.120189"},{"key":"e_1_2_8_6_1","doi-asserted-by":"publisher","DOI":"10.1002\/mrm.21627"},{"key":"e_1_2_8_7_1","doi-asserted-by":"publisher","DOI":"10.1002\/mrm.22946"},{"key":"e_1_2_8_8_1","doi-asserted-by":"publisher","DOI":"10.1002\/mrm.24145"},{"key":"e_1_2_8_9_1","doi-asserted-by":"publisher","DOI":"10.1002\/mrm.28410"},{"key":"e_1_2_8_10_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2011.12.017"},{"key":"e_1_2_8_11_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2011.12.056"},{"key":"e_1_2_8_12_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2012.02.022"},{"key":"e_1_2_8_13_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2013.06.008"},{"key":"e_1_2_8_14_1","doi-asserted-by":"publisher","DOI":"10.1002\/mrm.21108"},{"key":"e_1_2_8_15_1","doi-asserted-by":"publisher","DOI":"10.1002\/nbm.2839"},{"key":"e_1_2_8_16_1","doi-asserted-by":"publisher","DOI":"10.1002\/mrm.25610"},{"key":"e_1_2_8_17_1","doi-asserted-by":"publisher","DOI":"10.1002\/mrm.28390"},{"key":"e_1_2_8_18_1","doi-asserted-by":"publisher","DOI":"10.1002\/mrm.26657"},{"key":"e_1_2_8_19_1","doi-asserted-by":"publisher","DOI":"10.1002\/mrm.27907"},{"key":"e_1_2_8_20_1","doi-asserted-by":"publisher","DOI":"10.1002\/mrm.26253"},{"key":"e_1_2_8_21_1","doi-asserted-by":"publisher","DOI":"10.1002\/mrm.27135"},{"key":"e_1_2_8_22_1","doi-asserted-by":"publisher","DOI":"10.1177\/0271678x20973951"},{"key":"e_1_2_8_23_1","doi-asserted-by":"publisher","DOI":"10.1002\/mrm.28447"},{"key":"e_1_2_8_24_1","doi-asserted-by":"publisher","DOI":"10.1177\/0271678x241298584"},{"key":"e_1_2_8_25_1","doi-asserted-by":"publisher","DOI":"10.1002\/mrm.27804"},{"key":"e_1_2_8_26_1","doi-asserted-by":"publisher","DOI":"10.1111\/jon.12990"},{"key":"e_1_2_8_27_1","doi-asserted-by":"publisher","DOI":"10.3389\/fnins.2020.535441"},{"key":"e_1_2_8_28_1","doi-asserted-by":"publisher","DOI":"10.3389\/fnins.2021.736891"},{"key":"e_1_2_8_29_1","doi-asserted-by":"publisher","DOI":"10.1007\/s00330-022-08713-7"},{"key":"e_1_2_8_30_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.clinimag.2023.02.001"},{"key":"e_1_2_8_31_1","doi-asserted-by":"publisher","DOI":"10.3390\/cancers15174298"},{"key":"e_1_2_8_32_1","doi-asserted-by":"publisher","DOI":"10.1177\/0271678X211048031"},{"key":"e_1_2_8_33_1","doi-asserted-by":"publisher","DOI":"10.3389\/fnins.2021.716031"},{"key":"e_1_2_8_34_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2024.120903"},{"key":"e_1_2_8_35_1","doi-asserted-by":"publisher","DOI":"10.1007\/s00330-025-11435-1"},{"key":"e_1_2_8_36_1","doi-asserted-by":"publisher","DOI":"10.3348\/kjr.2022.0652"},{"key":"e_1_2_8_37_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10072-024-07463-2"},{"key":"e_1_2_8_38_1","doi-asserted-by":"publisher","DOI":"10.1093\/brain\/awae383"},{"key":"e_1_2_8_39_1","doi-asserted-by":"publisher","DOI":"10.1136\/lupus-2025-001522"},{"key":"e_1_2_8_40_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2025.121241"},{"key":"e_1_2_8_41_1","doi-asserted-by":"publisher","DOI":"10.3389\/fnins.2026.1754415"},{"key":"e_1_2_8_42_1","doi-asserted-by":"publisher","DOI":"10.1002\/mrm.27882"},{"key":"e_1_2_8_43_1","doi-asserted-by":"publisher","DOI":"10.1002\/mrm.27967"},{"key":"e_1_2_8_44_1","doi-asserted-by":"publisher","DOI":"10.1002\/mrm.28875"},{"key":"e_1_2_8_45_1","doi-asserted-by":"publisher","DOI":"10.3390\/bioengineering11020131"},{"key":"e_1_2_8_46_1","doi-asserted-by":"publisher","DOI":"10.1002\/mrm.29057"},{"key":"e_1_2_8_47_1","doi-asserted-by":"publisher","DOI":"10.1002\/ana.22366"},{"key":"e_1_2_8_48_1","unstructured":"A.Misra Y.Wang G. C.Chiang et al. \u201cOxygen Extraction Fraction Is Differently Associated With Pathological Biomarkers in Alzheimer's Disease and Non\u2010Alzheimer's Dementias \u201d inProceedings of the 33rd Annual Meeting of ISMRM(2025) 3141."},{"key":"e_1_2_8_49_1","doi-asserted-by":"publisher","DOI":"10.1002\/mrm.24272"},{"key":"e_1_2_8_50_1","doi-asserted-by":"publisher","DOI":"10.1002\/nbm.1670"},{"key":"e_1_2_8_51_1","doi-asserted-by":"publisher","DOI":"10.1002\/mrm.22187"},{"key":"e_1_2_8_52_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2011.08.082"},{"key":"e_1_2_8_53_1","doi-asserted-by":"publisher","DOI":"10.1002\/mrm.25358"},{"key":"e_1_2_8_54_1","doi-asserted-by":"publisher","DOI":"10.1002\/mrm.26946"},{"key":"e_1_2_8_55_1","doi-asserted-by":"publisher","DOI":"10.1016\/S1361-8415(01)00036-6"},{"key":"e_1_2_8_56_1","doi-asserted-by":"publisher","DOI":"10.1006\/nimg.2002.1132"},{"key":"e_1_2_8_57_1","doi-asserted-by":"publisher","DOI":"10.1002\/mrm.10257"},{"key":"e_1_2_8_58_1","doi-asserted-by":"publisher","DOI":"10.1002\/mrm.1072"},{"key":"e_1_2_8_59_1","doi-asserted-by":"publisher","DOI":"10.1002\/mrm.25463"},{"key":"e_1_2_8_60_1","unstructured":"X.UlrichandD. A.Yablonskiy \u201cEnhancing Image Contrast in Human Brain by Voxel Spread Function Method \u201din Proceedings of the 22nd Annual Meeting of ISMRM (Milan Italy: 2014) 10\u201316."},{"key":"e_1_2_8_61_1","doi-asserted-by":"publisher","DOI":"10.1002\/mrm.1910320610"},{"key":"e_1_2_8_62_1","doi-asserted-by":"publisher","DOI":"10.1097\/00004647-200008000-00008"},{"key":"e_1_2_8_63_1","doi-asserted-by":"crossref","unstructured":"O.Ronneberger P.Fischer andT.Brox \u201cU\u2010Net: Convolutional Networks for Biomedical Image Segmentation \u201din Medical Image Computing and Computer\u2010Assisted Intervention\u2013MICCAI 2015: 18th International Conference Munich Germany Proceedings part III 18(Springer: 2015) 234\u2013241.","DOI":"10.1007\/978-3-319-24574-4_28"},{"key":"e_1_2_8_64_1","unstructured":"H. P.Gavin \u201cThe Levenberg\u2010Marquardt Algorithm for Nonlinear Least Squares Curve\u2010Fitting Problems \u201dDepartment of Civil and Environmental Engineering Duke University August 2019 (3) 1\u201323."},{"key":"e_1_2_8_65_1","doi-asserted-by":"publisher","DOI":"10.1002\/mrm.25198"},{"key":"e_1_2_8_66_1","doi-asserted-by":"publisher","DOI":"10.1002\/mrm.25420"},{"key":"e_1_2_8_67_1","doi-asserted-by":"publisher","DOI":"10.1001\/jamaneurol.2019.2399"},{"key":"e_1_2_8_68_1","doi-asserted-by":"publisher","DOI":"10.1002\/acn3.51338"},{"key":"e_1_2_8_69_1","doi-asserted-by":"publisher","DOI":"10.1161\/strokeaha.121.035674"},{"key":"e_1_2_8_70_1","doi-asserted-by":"publisher","DOI":"10.1177\/0271678x221105986"},{"key":"e_1_2_8_71_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2018.02.027"}],"container-title":["Magnetic Resonance in Medicine"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/pdf\/10.1002\/mrm.70524","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/full-xml\/10.1002\/mrm.70524","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/pdf\/10.1002\/mrm.70524","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,9,29]],"date-time":"2026-09-29T03:43:52Z","timestamp":1790653432000},"score":1,"resource":{"primary":{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/10.1002\/mrm.70524"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,8,4]]},"references-count":70,"journal-issue":{"issue":"6","published-print":{"date-parts":[[2026,12]]}},"alternative-id":["10.1002\/mrm.70524"],"URL":"https:\/\/doi.org\/10.1002\/mrm.70524","archive":["Portico"],"relation":{},"ISSN":["0740-3194","1522-2594"],"issn-type":[{"value":"0740-3194","type":"print"},{"value":"1522-2594","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,8,4]]},"assertion":[{"value":"2026-02-20","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2026-07-09","order":2,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2026-08-04","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}