{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"institution":[{"name":"bioRxiv"}],"indexed":{"date-parts":[[2026,5,5]],"date-time":"2026-05-05T06:12:03Z","timestamp":1777961523477,"version":"3.51.4"},"posted":{"date-parts":[[2026,4,30]]},"group-title":"Bioengineering","reference-count":33,"publisher":"openRxiv","license":[{"start":{"date-parts":[[2026,4,30]],"date-time":"2026-04-30T00:00:00Z","timestamp":1777507200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nd\/4.0\/"}],"funder":[{"name":"NIH","award":["P30AG072931-03S1"],"award-info":[{"award-number":["P30AG072931-03S1"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"accepted":{"date-parts":[[2026,4,30]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                <jats:sec>\n                  <jats:title>Purpose<\/jats:title>\n                  <jats:p>\n                    In principle, combined T\n                    <jats:sub>2<\/jats:sub>\n                    \u2013Diffusion (D) MRI has the microstructural and chemical sensitivity to detect axonal and myelin water changes in Alzheimer\u2019s disease and related dementias (ADRD), but its practical implementation may be hindered by demanding hardware requirements. This work assesses the feasibility and accuracy of T\n                    <jats:sub>2<\/jats:sub>\n                    \u2013D for ex vivo analysis of WM lesions in ADRD tissue.\n                  <\/jats:p>\n                <\/jats:sec>\n                <jats:sec>\n                  <jats:title>Methods<\/jats:title>\n                  <jats:p>\n                    A thawed ex vivo brain sample from the Michigan Brain Bank and a T\n                    <jats:sub>2<\/jats:sub>\n                    \u2013D phantom were scanned at 7T using a combined diffusion relaxometry (CDR) sequence. A non-negative least squares (NNLS) conventional data processing pipeline was used to disentangle water pools with unique T\n                    <jats:sub>2<\/jats:sub>\n                    \u2013D signatures. Simulations examined the effects of minimum TE and SNR on recovery of myelin water (short T\n                    <jats:sub>2<\/jats:sub>\n                    , slow diffusion).\n                  <\/jats:p>\n                <\/jats:sec>\n                <jats:sec>\n                  <jats:title>Results<\/jats:title>\n                  <jats:p>\n                    Across tissue types, T\n                    <jats:sub>2<\/jats:sub>\n                    \u2013D data consistently resolved three spectral components. Phantom experiments showed detection of short T\n                    <jats:sub>2<\/jats:sub>\n                    and slow diffusion features similar to those observed in ADRD ex vivo tissue, and confirmed CDR\u2019s ability to accurately resolve multiple components. Simulations indicated reliable T\n                    <jats:sub>2<\/jats:sub>\n                    \u2013D recovery for myelin with SNR\n                    <jats:italic>&gt;<\/jats:italic>\n                    30 dB and minimum TE\n                    <jats:italic>&lt;<\/jats:italic>\n                    25 ms.\n                  <\/jats:p>\n                <\/jats:sec>\n                <jats:sec>\n                  <jats:title>Conclusion<\/jats:title>\n                  <jats:p>\n                    Strong T\n                    <jats:sub>2<\/jats:sub>\n                    and D weighting could be combined to capture the expected axonal, myelin, and extracellular (EC) regions in T\n                    <jats:sub>2<\/jats:sub>\n                    \u2013D space. The observed short-T\n                    <jats:sub>2<\/jats:sub>\n                    , restricted-D components are therefore unlikely to be artifacts and instead support interpretations as physically meaningful myelin and axonal water signatures.\n                  <\/jats:p>\n                <\/jats:sec>","DOI":"10.64898\/2026.04.27.721146","type":"posted-content","created":{"date-parts":[[2026,4,30]],"date-time":"2026-04-30T22:40:12Z","timestamp":1777588812000},"source":"Crossref","is-referenced-by-count":0,"title":["Phantom- and simulation-based validation of combined diffusion relaxometry in ex vivo ADRD white matter"],"prefix":"10.64898","author":[{"ORCID":"https:\/\/orcid.org\/0009-0001-4507-8464","authenticated-orcid":false,"given":"Andrea","family":"Jacobson","sequence":"first","affiliation":[{"name":"Department of Biomedical, Engineering, University of Michigan, Ann Arbor, MI, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0004-5546-1274","authenticated-orcid":false,"given":"Amaya","family":"Murguia","sequence":"additional","affiliation":[{"name":"Department of Electrical Engineering, and Computer Science, University of Michigan, Ann Arbor, MI, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4714-4031","authenticated-orcid":false,"given":"Scott D.","family":"Swanson","sequence":"additional","affiliation":[{"name":"Department of Radiology, Michigan, Medicine, University of Michigan, Ann Arbor, MI, USA"},{"name":"Department of Biophysics, University of Michigan, Ann Arbor, MI, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2058-3579","authenticated-orcid":false,"given":"Jon-Fredrik","family":"Nielsen","sequence":"additional","affiliation":[{"name":"Department of Biomedical, Engineering, University of Michigan, Ann Arbor, MI, USA"},{"name":"Department of Electrical Engineering, and Computer Science, University of Michigan, Ann Arbor, MI, USA"},{"name":"Department of Radiology, Michigan, Medicine, University of Michigan, Ann Arbor, MI, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9998-3315","authenticated-orcid":false,"given":"Jeffrey A.","family":"Fessler","sequence":"additional","affiliation":[{"name":"Department of Biomedical, Engineering, University of Michigan, Ann Arbor, MI, USA"},{"name":"Department of Electrical Engineering, and Computer Science, University of Michigan, Ann Arbor, MI, USA"},{"name":"Department of Radiology, Michigan, Medicine, University of Michigan, Ann Arbor, MI, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8215-6513","authenticated-orcid":false,"given":"Navid","family":"Seraji-Bozorgzad","sequence":"additional","affiliation":[{"name":"Department of Neurology, University of Michigan, Ann Arbor, MI, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"54368","reference":[{"key":"2026050422350597000_2026.04.27.721146v1.1","doi-asserted-by":"publisher","DOI":"10.37765\/ajmc.2020.88482"},{"key":"2026050422350597000_2026.04.27.721146v1.2","doi-asserted-by":"publisher","DOI":"10.3390\/MOLECULES25245789"},{"key":"2026050422350597000_2026.04.27.721146v1.3","unstructured":"Disease Control Centers, Prevention. 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