Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK.
Magn Reson Med. 2024 Jun;91(6):2229-2246. doi: 10.1002/mrm.30001. Epub 2024 Jan 24.
Dynamic (2D) MRS is a collection of techniques where acquisitions of spectra are repeated under varying experimental or physiological conditions. Dynamic MRS comprises a rich set of contrasts, including diffusion-weighted, relaxation-weighted, functional, edited, or hyperpolarized spectroscopy, leading to quantitative insights into multiple physiological or microstructural processes. Conventional approaches to dynamic MRS analysis ignore the shared information between spectra, and instead proceed by independently fitting noisy individual spectra before modeling temporal changes in the parameters. Here, we propose a universal dynamic MRS toolbox which allows simultaneous fitting of dynamic spectra of arbitrary type.
A simple user-interface allows information to be shared and precisely modeled across spectra to make inferences on both spectral and dynamic processes. We demonstrate and thoroughly evaluate our approach in three types of dynamic MRS techniques. Simulations of functional and edited MRS are used to demonstrate the advantages of dynamic fitting.
Analysis of synthetic functional H-MRS data shows a marked decrease in parameter uncertainty as predicted by prior work. Analysis with our tool replicates the results of two previously published studies using the original in vivo functional and diffusion-weighted data. Finally, joint spectral fitting with diffusion orientation models is demonstrated in synthetic data.
A toolbox for generalized and universal fitting of dynamic, interrelated MR spectra has been released and validated. The toolbox is shared as a fully open-source software with comprehensive documentation, example data, and tutorials.
动态（2D）MRS 是一系列技术的集合，其中在不同的实验或生理条件下重复采集光谱。动态 MRS 包括一系列丰富的对比，包括扩散加权、弛豫加权、功能、编辑或极化光谱学，从而对多种生理或微观结构过程进行定量分析。传统的动态 MRS 分析方法忽略了光谱之间的共享信息，而是在对参数进行建模之前，通过独立拟合噪声较大的单个光谱来进行。在这里，我们提出了一个通用的动态 MRS 工具箱，它允许对任意类型的动态光谱进行同时拟合。
一个简单的用户界面允许在光谱之间共享信息并进行精确建模，以便对光谱和动态过程进行推断。我们在三种类型的动态 MRS 技术中演示和彻底评估了我们的方法。功能和编辑 MRS 的模拟用于演示动态拟合的优势。
对合成功能 H-MRS 数据的分析表明，参数不确定性的显著降低与先前的工作预测一致。使用我们的工具对原始体内功能和扩散加权数据进行分析，复制了两项先前发表的研究的结果。最后，在合成数据中演示了与扩散方向模型的联合光谱拟合。
发布并验证了用于广义和通用的动态、相关的磁共振光谱拟合的工具箱。该工具箱作为一个完全开源的软件共享，具有全面的文档、示例数据和教程。
