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◆ Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine2026-01-01

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, Yumiko Motoi, Madoka Nakajima, Koji Murakami, Atsushi Shima, Manabu Kubota, Berkin Bilgic, Koji Kamagata, Nobukatsu Sawamoto, Osamu Abe, Yuji Nakamoto, Shigeki Aoki

一句话结论 · In one sentence

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.

原始摘要(英文原文)· Original 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: This 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 B1 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.
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Brain Amyloid Burden Mapping Using MR Fingerprinting Aided by Deep Learning. — 科研速览 Science Skim