Evidence map›Paper›PMID 42633943›Full record

ArticleMagnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine2026

Brain Amyloid Burden Mapping Using MR Fingerprinting Aided by Deep Learning.

Shohei Fujita, Yasutaka Fushimi, Yujiro Otsuka, Katsutoshi Murata, Guido Buonincontri, Gregor Koerzdoerfer, Mathias Nittka, Issei Fukunaga, Kaito Takabayashi, Akifumi Hagiwara and 11 more

Abstract readMulticenter StudyValidation Study
PubMed Full text at PMC Publisher
In one paragraph

Article in Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

21 authors.

Shohei FujitaDepartment of Radiology, Juntendo University, Tokyo, Japan.
Yasutaka FushimiDepartment of Diagnostic Imaging and Nuclear Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Kyoto, Japan.
Yujiro OtsukaDepartment of Radiology, Juntendo University, Tokyo, Japan.
Katsutoshi MurataSiemens Healthcare K.K., Tokyo, Japan.
Guido BuonincontriResearch & Clinical Translation, Magnetic Resonance, Siemens Healthineers, Erlangen Bavaria, Germany.
Gregor KoerzdoerferSiemens Medical Solutions, New York NY, USA.
Mathias NittkaResearch & Clinical Translation, Magnetic Resonance, Siemens Healthineers, Erlangen Bavaria, Germany.
Issei FukunagaDepartment of Radiology, Juntendo University, Tokyo, Japan.
Kaito TakabayashiDepartment of Radiology, Juntendo University, Tokyo, Japan.
Akifumi HagiwaraDepartment of Radiology, Juntendo University, Tokyo, Japan.
Yumiko MotoiDepartment of Neurology, Juntendo University, Tokyo, Japan.
Madoka NakajimaThe Medical Center for Dementia, Juntendo University, Tokyo, Japan.
Koji MurakamiDivision of Nuclear Medicine, Department of Radiology, Juntendo University, Tokyo, Japan.
Atsushi ShimaDepartment of Human Health Sciences, Graduate School of Medicine, Kyoto University, Kyoto, Kyoto, Japan.
Manabu KubotaDepartment of Psychiatry, Graduate School of Medicine, Kyoto University, Kyoto, Kyoto, Japan.
Berkin BilgicAthinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston MA, USA.
Koji KamagataDepartment of Radiology, Juntendo University, Tokyo, Japan.
Nobukatsu SawamotoDepartment of Human Health Sciences, Graduate School of Medicine, Kyoto University, Kyoto, Kyoto, Japan.
Osamu AbeDepartment of Radiology, The University of Tokyo, Tokyo, Japan.
Yuji NakamotoDepartment of Diagnostic Imaging and Nuclear Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Kyoto, Japan.
Shigeki AokiDepartment of Radiology, Juntendo University, Tokyo, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeTo 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.

methodsThis prospective multi-site study included 44 participants from 2 sites who had undergone, or were scheduled to undergo, Aβ PET within 1 year. MRF was performed on a 3T MR system using a 2D fast imaging with steady-state precession sequence with B

resultsThe 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).

conclusionThe proposed framework enables non-invasive Aβ mapping using a clinically feasible MRI protocol and may support repeated assessment for monitoring during anti-amyloid treatment.

Indexed as

Amyloid beta-PeptidesBrainBrain MappingDeep LearningMagnetic Resonance ImagingAlzheimer DiseaseFemaleHumansMalePositron-Emission TomographyProspective StudiesReproducibility of ResultsAmyloid beta-PeptidesAlzheimer’s diseaseamyloid-βmagnetic resonance fingerprintingneural networkspositron emission tomography

Identifiers

PMID42633943
PMCPMC13678289

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.