A Time-Dependent Diffusion MRI Framework for Clinical Characterisation of Human Brain Cellular Architecture
· 2026-09-05 · 原文
DOI：10.64898/2026.09.02.26362017v1?rss=1
Diffusion-weighted MRI, beyond the commonly used diffusion tensor framework, offers a unique window into tissue microstructure in vivo, yet its clinical adoption has remained limited. Major barriers include the complexity of diffusion MRI sequence design, lengthy acquisition protocols, and the challenges associated with robust estimation of high-dimensional microstructural model parameters. Here, we address these limitations by combining optimised diffusion encoding with state-of-the-art simulation-based inference, establishing a clinically feasible framework for multi-compartment diffusion modelling. We validate the approach through i) in-depth in silico experiments and ii) in vivo studies made up of both human and rodent data. The resulting microstructural metrics are robust, reproducibl
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1. 人话版
Diffusion-weighted MRI, beyond the commonly used diffusion tensor framework, offers a unique window into tissue microstructure in vivo, yet its clinical adoption has remained limited.
Major barriers include the complexity of diffusion MRI sequence design, lengthy acquisition protocols, and the challenges associated with robust estimation of high-dimensional microstructural model parameters.
2. 领域脉络
来源板块：板块一 · 研究前沿。
3. 机制拆解
We validate the approach through i) in-depth in silico experiments and ii) in vivo studies made up of both human and rodent data.
The resulting microstructural metrics are robust, reproducibl
4. 证据与数字
摘要未给出量化结果——留意原文的实验与数据。
5. 反例与边界
Here, we address these limitations by combining optimised diffusion encoding with state-of-the-art simulation-based inference, establishing a clinically feasible framework for multi-compartment diffusion modelling.
6. 跨领域连接与意外收获
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7. 可复用方法
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8. 术语表
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