{
  "abstract": "PURPOSE: To develop and externally validate a non-invasive framework for quantifying brain amyloid-β (Aβ) deposition using magnetic resonance fingerprinting (MRF) and neural network-based decoding, with positron emission tomography (PET) as the reference standard. METHODS: correction, covering the whole brain in 9.5 min. PET images were co-registered to the MRF space, and regional amyloid load was calculated using an automated template-based pipeline. An inverse mapping function was implemented to convert MRF signals into amyloid burden maps. Repeatability, agreement with PET-based centiloid values, and associations with cognitive scores were evaluated. RESULTS: The generated amyloid maps were visually similar to PET images. Test-retest analysis showed high repeatability, with a coefficient of variation of 1.8 ± 1.3% and an intraclass correlation coefficient of 0.84. In the external test set, MRF-based measurements correlated significantly with PET centiloid scores (Spearman's ρ = 0.589, P = 0.015) and Montreal Cognitive Assessment scores (ρ = -0.543, P = 0.020). CONCLUSION: The proposed framework enables non-invasive Aβ mapping using a clinically feasible MRI protocol and may support repeated assessment for monitoring during anti-amyloid treatment.",
  "abstract_shown": true,
  "affiliations": [],
  "article_type": null,
  "arxiv": null,
  "author_total": 21,
  "authors": [
    {
      "name": "Shohei Fujita"
    },
    {
      "name": "Yasutaka Fushimi"
    },
    {
      "name": "Yujiro Otsuka"
    },
    {
      "name": "Katsutoshi Murata"
    },
    {
      "name": "Guido Buonincontri"
    },
    {
      "name": "Gregor Koerzdoerfer"
    },
    {
      "name": "Mathias Nittka"
    },
    {
      "name": "Issei Fukunaga"
    },
    {
      "name": "Kaito Takabayashi"
    },
    {
      "name": "Akifumi Hagiwara"
    },
    {
      "name": "Yumiko Motoi"
    },
    {
      "name": "Madoka Nakajima"
    },
    {
      "name": "Koji Murakami"
    },
    {
      "name": "Atsushi Shima"
    },
    {
      "name": "Manabu Kubota"
    },
    {
      "name": "Berkin Bilgic"
    },
    {
      "name": "Koji Kamagata"
    },
    {
      "name": "Nobukatsu Sawamoto"
    },
    {
      "name": "Osamu Abe"
    },
    {
      "name": "Yuji Nakamoto"
    },
    {
      "name": "Shigeki Aoki"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/4a7wtbbka8fv0.bib",
  "cited_by": 0,
  "doi": "10.2463/mrms.mp.2026-0112",
  "fulltext_url": "https://www.jstage.jst.go.jp/article/mrms/25/4/25_mp.2026-0112/_article",
  "id": "4a7wtbbka8fv0",
  "issns": [
    "1880-2206",
    "1347-3182"
  ],
  "landing_url": "https://www.jstage.jst.go.jp/article/mrms/25/4/25_mp.2026-0112/_article",
  "language": null,
  "licence": "CC-BY",
  "licence_label": "CC BY",
  "licence_source": "journal",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "jstage-journal",
      "medicine/imaging"
    ],
    [
      "openalex",
      "2741|Advanced MRI Techniques and Applications"
    ]
  ],
  "openalex": "W7203833716",
  "pdf_url": "https://www.jstage.jst.go.jp/article/mrms/25/4/25_mp.2026-0112/_pdf",
  "pmcid": null,
  "pmid": null,
  "published": "2026-08-21",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/4a7wtbbka8fv0.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:17:42Z",
      "native_id": "10.2463/mrms.mp.2026-0112",
      "source": "jstage",
      "url": "https://www.jstage.jst.go.jp/article/mrms/25/4/25_mp.2026-0112/_article"
    }
  ],
  "subjects": [
    {
      "field": "medicine",
      "origin": "openalex:2741|Advanced MRI Techniques and Applications",
      "subfield": "imaging"
    }
  ],
  "title": "Brain Amyloid Burden Mapping Using MR Fingerprinting Aided by Deep Learning",
  "title_text": "Brain Amyloid Burden Mapping Using MR Fingerprinting Aided by Deep Learning",
  "type": "peer-reviewed",
  "updated_at": "2026-10-30T12:17:42Z",
  "url": "https://research.draconitic.com/paper/4a7wtbbka8fv0",
  "venue": "Magnetic Resonance in Medical Sciences",
  "versions": []
}