用AI加速MRI，精准定量帕金森病小鼠脑内多种代谢物。
Quantitative multi-metabolite imaging of Parkinson's disease using AI boosted molecular MRI
- 结合快速扫描与深度学习重建，实现多代谢物定量成像。
- 在MPTP模型小鼠中成功量化谷氨酸、蛋白质等四种成分。
- 结果与组织学和磁共振波谱一致，发现潜在生物标志物。
传统帕金森病（PD）分子成像方法依赖放射性同位素、扫描时间长或空间分辨率低。基于饱和转移的PD磁共振成像（MRI）虽提供生化信息，但图像对比度为半定量且不特异。本文结合快速分子MRI采集与深度学习重建，在急性MPTP小鼠模型中实现了谷氨酸、可移动蛋白、半固态及可移动大分子的多代谢物定量。定量参数图与组织学及磁共振波谱结果总体一致，表明半固态磁化转移（MT）、酰胺及脂肪族弛豫核奥尔赫瑟效应（rNOE）质子体积分数可能作为帕金森病生物标志物。
原文摘要 · Abstract (English)
Traditional approaches for molecular imaging of Parkinson's disease (PD) in vivo require radioactive isotopes, lengthy scan times, or deliver only low spatial resolution. Recent advances in saturation transfer-based PD magnetic resonance imaging (MRI) have provided biochemical insights, although the image contrast is semi-quantitative and nonspecific. Here, we combined a rapid molecular MRI acquisition paradigm with deep learning based reconstruction for multi-metabolite quantification of glutamate, mobile proteins, semisolid, and mobile macromolecules in an acute MPTP (1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine) mouse model. The quantitative parameter maps are in general agreement with the histology and MR spectroscopy, and demonstrate that semisolid magnetization transfer (MT), amide, and aliphatic relayed nuclear Overhauser effect (rNOE) proton volume fractions may serve as PD biomarkers.
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