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Regional CBF differences by Alzheimer's disease (AD) stages, their accuracy for AD classification, and CBF trajectory slopes were compared between generated data (Siemens) and acquired data (General Electric).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>RESULTS<\/jats:title>\n                    <jats:p>The diffusion model generated M0 images with high fidelity (SSIM\u00a0=\u00a00.918\u00a0\u00b1\u00a00.023, PSNR\u00a0=\u00a031.361\u00a0\u00b1\u00a02.537) and minimal CBF bias (mean difference is 0.21\u00a0\u00b1\u00a01.58\u00a0mL\/100\u00a0g\/min). Both generated and acquired CBF showed similar spatial patterns and decreasing trends with AD progression in specific AD\u2010related regions. Generated CBF also improved accuracy in classifying AD stages compared to qualitative perfusion images.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>CONCLUSION<\/jats:title>\n                    <jats:p>This study shows the potential of diffusion models for imputing missing modalities in large\u2010scale studies exploring the use of ASL as a biomarker of AD.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Highlights<\/jats:title>\n                    <jats:p>\n                      <jats:list list-type=\"bullet\">\n                        <jats:list-item>\n                          <jats:p>Using latent diffusion model, we can generate M0 image from control image in arterial spin labeling (ASL) with high fidelity.<\/jats:p>\n                        <\/jats:list-item>\n                        <jats:list-item>\n                          <jats:p>The generated M0 can be used for cerebral blood flow (CBF) quantification in Alzheimer's Disease Neuroimaging Initiative dataset.<\/jats:p>\n                        <\/jats:list-item>\n                        <jats:list-item>\n                          <jats:p>The performance of classification between Alzheimer's disease (AD) patients and cognitive normal people is better when using generated CBF maps than using non\u2010quantitative perfusion images.<\/jats:p>\n                        <\/jats:list-item>\n                        <jats:list-item>\n                          <jats:p>ASL CBF decreases with AD progression in key AD\u2010related brain regions.<\/jats:p>\n                        <\/jats:list-item>\n                      <\/jats:list>\n                    <\/jats:p>\n                  <\/jats:sec>","DOI":"10.1002\/dad2.70214","type":"journal-article","created":{"date-parts":[[2025,10,30]],"date-time":"2025-10-30T08:53:56Z","timestamp":1761814436000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Generative diffusion model enables quantification of calibration\u2010free arterial spin labeling perfusion magnetic resonance imaging data in an Alzheimer's disease cohort"],"prefix":"10.1002","volume":"17","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3343-3895","authenticated-orcid":false,"given":"Qinyang","family":"Shou","sequence":"first","affiliation":[{"name":"Laboratory of Functional MRI Technology (LOFT) Stevens Neuroimaging and Informatics Institute University of Southern California  Los Angeles California USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Steven","family":"Cen","sequence":"additional","affiliation":[{"name":"Department of Neurology Keck School of Medicine University of Southern California  Los Angeles California USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Nan\u2010kuei","family":"Chen","sequence":"additional","affiliation":[{"name":"Department of Biomedical Engineering University of Arizona  Tucson Arizona USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"John M","family":"Ringman","sequence":"additional","affiliation":[{"name":"Department of Neurology Keck School of Medicine University of Southern California  Los Angeles California USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hosung","family":"Kim","sequence":"additional","affiliation":[{"name":"Laboratory of Neuro Imaging (LONI) Stevens Neuroimaging and Informatics Institute University of Southern California  Los Angeles California USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"suffix":"Jr","given":"Clifford R.","family":"Jack","sequence":"additional","affiliation":[{"name":"Department of Radiology Mayo Clinic  Rochester Minnesota USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Bret J.","family":"Borowski","sequence":"additional","affiliation":[{"name":"Department of Radiology Mayo Clinic  Rochester Minnesota USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Matthew L.","family":"Senjem","sequence":"additional","affiliation":[{"name":"Department of Radiology Mayo Clinic  Rochester Minnesota USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Arvin","family":"Arani","sequence":"additional","affiliation":[{"name":"Department of Radiology Mayo Clinic  Rochester Minnesota USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0840-7062","authenticated-orcid":false,"given":"Danny J. J.","family":"Wang","sequence":"additional","affiliation":[{"name":"Laboratory of Functional MRI Technology (LOFT) Stevens Neuroimaging and Informatics Institute University of Southern California  Los Angeles California USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"name":"and for the Alzheimer's Disease Neuroimaging Initiative","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","published-online":{"date-parts":[[2025,10,30]]},"reference":[{"key":"e_1_2_10_2_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jalz.2011.03.003"},{"key":"e_1_2_10_3_1","doi-asserted-by":"publisher","DOI":"10.1186\/s13195\u2010023\u201001314\u20106"},{"key":"e_1_2_10_4_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41380\u2010020\u20100721\u20109"},{"key":"e_1_2_10_5_1","doi-asserted-by":"crossref","unstructured":"Salvad\u00f3G HorieK Barth\u00e9lemyNR et\u00a0al.Disease staging of Alzheimer's disease using a CSF\u2010based biomarker model.Nature Aging.2024;4.5:694\u2010708. doi:10.1038\/s43587\u2010024\u201000599\u2010y","DOI":"10.1038\/s43587-024-00599-y"},{"key":"e_1_2_10_6_1","doi-asserted-by":"crossref","unstructured":"AlsopDC DetreJA GolayX et\u00a0al.Recommended implementation of arterial spin labeled perfusion MRI for clinical applications: a consensus of the ISMRM perfusion study group and the European Consortium for ASL in dementia.Magn Reson Med.2015;73.1:102\u2010116. doi:10.1002\/mrm.25197","DOI":"10.1002\/mrm.25197"},{"key":"e_1_2_10_7_1","doi-asserted-by":"publisher","DOI":"10.1097\/WCO.0b013e328354ff0a"},{"key":"e_1_2_10_8_1","doi-asserted-by":"publisher","DOI":"10.1007\/s11682\u2010022\u201000750\u20106"},{"key":"e_1_2_10_9_1","doi-asserted-by":"publisher","DOI":"10.3233\/JAD\u2010210199"},{"key":"e_1_2_10_10_1","doi-asserted-by":"publisher","DOI":"10.3233\/JAD\u2010141467"},{"key":"e_1_2_10_11_1","first-page":"6840","article-title":"Denoising diffusion probabilistic models","volume":"33","author":"Ho J","year":"2020","journal-title":"Adv Neural Inf Process Syst"},{"key":"e_1_2_10_12_1","first-page":"1","article-title":"Cascaded diffusion models for high fidelity image generation","volume":"23","author":"Ho J","year":"2022","journal-title":"J Mach Learn Res"},{"key":"e_1_2_10_13_1","first-page":"8780","article-title":"Diffusion models beat GANs on image synthesis","volume":"34","author":"Dhariwal P","year":"2021","journal-title":"Adv Neural Inf Process Syst"},{"key":"e_1_2_10_14_1","doi-asserted-by":"crossref","unstructured":"RombachR BlattmannA LorenzD EsserP OmmerB High\u2010resolution image synthesis with latent diffusion models. 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