CLC number:
On-line Access: 2024-10-30
Received: 2024-03-11
Revision Accepted: 2024-06-02
Crosschecked: 2024-10-30
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Citations: Bibtex RefMan EndNote GB/T7714
Ruicheng BA, Liyi KANG, Dan WU. Time-dependent diffusion magnetic resonance imaging: measurement, modeling, and applications[J]. Journal of Zhejiang University Science A, 2024, 25(10): 765-787.
@article{title="Time-dependent diffusion magnetic resonance imaging: measurement, modeling, and applications",
author="Ruicheng BA, Liyi KANG, Dan WU",
journal="Journal of Zhejiang University Science A",
volume="25",
number="10",
pages="765-787",
year="2024",
publisher="Zhejiang University Press & Springer",
doi="10.1631/jzus.A2400139"
}
%0 Journal Article
%T Time-dependent diffusion magnetic resonance imaging: measurement, modeling, and applications
%A Ruicheng BA
%A Liyi KANG
%A Dan WU
%J Journal of Zhejiang University SCIENCE A
%V 25
%N 10
%P 765-787
%@ 1673-565X
%D 2024
%I Zhejiang University Press & Springer
%DOI 10.1631/jzus.A2400139
TY - JOUR
T1 - Time-dependent diffusion magnetic resonance imaging: measurement, modeling, and applications
A1 - Ruicheng BA
A1 - Liyi KANG
A1 - Dan WU
J0 - Journal of Zhejiang University Science A
VL - 25
IS - 10
SP - 765
EP - 787
%@ 1673-565X
Y1 - 2024
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/jzus.A2400139
Abstract: Increasingly, attention is being directed towards time-dependent diffusion magnetic resonance imaging (TDDMRI), a method that reveals time-related changes in the diffusional behavior of water molecules in biological tissues, thereby enabling us to probe related microstructure events. With ongoing improvements in hardware and advanced pulse sequences, significant progress has been made in applying TDDMRI to clinical research. The development of accurate mathematical models and computational methods has bolstered theoretical support for TDDMRI and elevated our understanding of molecular diffusion. In this review, we introduce the concept and basic physics of TDDMRI, and then focus on the measurement strategies and modeling approaches in short- and long-diffusion-time domains. Finally, we discuss the challenges in this field, including the requirement for efficient scanning and data processing technologies, the development of more precise models depicting time-dependent molecular diffusion, and critical clinical applications.
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