Universal dynamic fitting of magnetic resonance spectroscopy

Area of Science:

• Biomedical Engineering
• Medical Imaging
• Spectroscopy

Background:

• Dynamic Magnetic Resonance Spectroscopy (MRS) involves repeated spectral acquisitions under varying conditions.
• Conventional analysis methods independently fit individual spectra, ignoring shared information and increasing uncertainty.
• Dynamic MRS offers rich contrasts for quantitative insights into physiological and microstructural processes.

Purpose of the Study:

• To develop a universal toolbox for simultaneous fitting of dynamic MRS data of arbitrary types.
• To enable precise modeling and sharing of information across spectra for improved inferences.
• To overcome limitations of conventional methods that analyze spectra independently.

Main Methods:

• Development of a user-friendly toolbox for generalized and universal fitting of dynamic MR spectra.
• Simultaneous fitting of interrelated spectra, allowing for shared information modeling.
• Demonstration and evaluation using simulations of functional and edited MRS, and in vivo functional and diffusion-weighted data.

Main Results:

• Simulations of functional proton MRS (¹H-MRS) data showed a significant decrease in parameter uncertainty.
• The toolbox successfully replicated findings from two prior studies using existing in vivo data.
• Joint spectral fitting with diffusion orientation models was demonstrated in synthetic datasets.

Conclusions:

• A validated, open-source toolbox for fitting dynamic, interrelated MR spectra has been released.
• The software provides comprehensive documentation, example data, and tutorials for user accessibility.
• This tool offers a generalized approach to dynamic MRS analysis, enhancing quantitative insights.