{
  "abstract": "Introduction\n\nRegional tau is strongly associated with Alzheimer's disease (AD) symptoms, but tau positron emission tomography (PET) is not routinely available, limiting early risk stratification.Methods\n\nWe trained a deep learning model to predict regional tau PET standardized uptake value ratios (SUVRs) from magnetic resonance imaging (MRI) with and without basic demographics using public cohorts (Alzheimer's Disease Neuroimaging Initiative [ADNI], Open Access Series of Imaging Studies 3 [OASIS3-tau], Anti-Amyloid Treatment in Asymptomatic Alzheimer's Disease Study [A4], Harvard Aging Brain Study [HABS]). Mean absolute error (MAE), Pearson r, area-under-the-receiver-operating-curve (AUC), and comparison with cognitive testing were assessed in external test sets (SCAN, Stanford University).Results\n\nThe model achieved an MAE of 0.14 (95% confidence interval [CI]: 0.12-0.16) and r = 0.72 for an early uptake region (Braak I-IV), and an MAE of 0.14 (95% CI: 0.12-0.17) and r = 0.71 for a late uptake region (Braak V-VI). AUCs for binary tau positivity in these regions were 0.87 (95% CI: 0.83-0.90) and 0.88 (95% CI: 0.84-0.91), respectively.Discussion\n\nPredicting regional tau burden from magnetic resonance imaging (MRI) is feasible and may enable scalable tau-informed clinical AD care.",
  "abstract_shown": true,
  "affiliations": [
    "Department of Radiology, Stanford University, Stanford, California, USA.",
    "Department of Radiology, Washington University in St. Louis, St. Louis, Missouri, USA.",
    "Department of Neurology and Neurological Sciences, Stanford University, Stanford, California, USA.",
    "Department of Epidemiology and Population Health, Stanford University, Stanford, California, USA."
  ],
  "article_type": "research article",
  "arxiv": null,
  "author_total": 9,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "Donghoon Kim",
      "orcid": "0000-0002-5479-2707"
    },
    {
      "affs": [
        0
      ],
      "name": "Brandon C Ho"
    },
    {
      "affs": [
        0
      ],
      "name": "Henk van Voorst"
    },
    {
      "affs": [
        0
      ],
      "name": "Yongkai Liu"
    },
    {
      "affs": [
        1
      ],
      "name": "Tammie L S Benzinger"
    },
    {
      "affs": [
        2
      ],
      "name": "Sharon Sha"
    },
    {
      "affs": [
        2
      ],
      "name": "Elizabeth Mormino"
    },
    {
      "affs": [
        3
      ],
      "name": "Victor W Henderson"
    },
    {
      "affs": [
        0
      ],
      "name": "Greg Zaharchuk"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/4472vhrfa402d.bib",
  "cited_by": 0,
  "doi": "10.1002/alz.71911",
  "fulltext_url": "https://europepmc.org/articles/PMC13722605",
  "id": "4472vhrfa402d",
  "issns": [
    "1552-5260",
    "1552-5279"
  ],
  "landing_url": "https://europepmc.org/article/MED/42963328",
  "language": "eng",
  "licence": "CC-BY-NC-ND",
  "licence_label": "CC BY-NC-ND",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by-nc-nd/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "heading",
      "Research Article"
    ],
    [
      "openalex",
      "2738|Dementia and Cognitive Impairment Research"
    ]
  ],
  "openalex": "W7225011459",
  "pdf_url": "https://europepmc.org/articles/PMC13722605?pdf=render",
  "pmcid": "PMC13722605",
  "pmid": "42963328",
  "published": "2026-10-01",
  "publisher": "Wiley",
  "ris": "https://research.draconitic.com/paper/4472vhrfa402d.ris",
  "sources": [
    {
      "first_seen": "2026-11-02T03:21:43Z",
      "native_id": "MED:42963328",
      "source": "europepmc",
      "url": "https://europepmc.org/article/MED/42963328"
    },
    {
      "first_seen": "2026-11-04T12:21:23Z",
      "native_id": "PMC13722605",
      "source": "pmc",
      "url": "https://doi.org/10.1002/alz.71911"
    }
  ],
  "subjects": [
    {
      "field": "medicine",
      "origin": "openalex:2738|Dementia and Cognitive Impairment Research",
      "subfield": "psychiatry"
    }
  ],
  "title": "Deep learning-based prediction of regional brain Tau PET burden from MRI.",
  "title_text": "Deep learning-based prediction of regional brain Tau PET burden from MRI.",
  "type": "peer-reviewed",
  "updated_at": "2026-11-04T12:21:23Z",
  "url": "https://research.draconitic.com/paper/4472vhrfa402d",
  "venue": "Alzheimer's & dementia : the journal of the Alzheimer's Association",
  "versions": []
}