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At the MRS Hackathon, we will collaborate on smaller and bigger projects that will benefit the MRS community. You can join a project or pitch an idea of your own to the attendees! If you'd like to get a head start and have your project pitch listed below, contact us!
At the MRS Hackathon, we will collaborate on smaller and bigger projects that will benefit the MRS community. You can join a project or pitch an idea of your own to the attendees! If you'd like to get a head start and have your project pitch listed below, contact us!
Collaborative Multi-center Pre-clinical MRS study (CoMP-MRS)
Collaborative Multi-center Pre-clinical MRS study (CoMP-MRS)
In this international collaborative project, we seek to gather the rodent (rat and mouse) MRS community toward performing a multi-center comparison of 1H MRS techniques with the final goal of developing and establishing guidelines for best practices in preclinical MRS. Inspired by the multi-site fMRI study of the rat brain led by Joanes Grandjean, we want to examine the distribution of neurochemical concentrations and spectral quality measures at the population level within the healthy rodent brain across sites, as well as establish best practices for preclinical MRS methods.
Fit2fit: A Systematic Review of Reported Control Parameters in single-voxel 1H-MRS Analyses of the Human Brain
Fit2fit: A Systematic Review of Reported Control Parameters in single-voxel 1H-MRS Analyses of the Human Brain
The objective of this study is to systematically examine and document the input parameters reported in single-voxel 1H-MRS spectral modeling and fitting software. This research aims to provide a comprehensive understanding of the analytical practices in this domain by identifying which modeling and fitting parameters are consistently reported and utilized in the analysis of data from single-voxel 1H-MRS studies of the human brain. The study will also explore the variations in these parameters across different studies, highlighting common practices and discrepancies in the field.
Impact of Segmentation Software Variability on Simulated MRS Data
Impact of Segmentation Software Variability on Simulated MRS Data
This study investigates the effect of segmentation software variability on metabolite quantification in millimolar (mM) units using simulated Magnetic Resonance Spectroscopy (MRS) data. We will simulate MRS data and estimate metabolite levels using different tissue estimates generated by manual segmentation and four other software programs. By comparing the metabolite levels across these methods, the study aims to quantify the impact of segmentation choices on the accuracy of MRS data analysis. This project brings us one step closer to building a control file generator.
MRS Education for ALL!!!!
MRS Education for ALL!!!!
As part of our MRSHub.org website, we’ve created an online working MRS book, a comprehensive resource designed to support newcomers and seasoned researchers in the field. Our website contains information, videos, book suggestions, basically everything we believe will help facilitate an understanding of MRS.
However, we’re not done yet!!
That’s where you come in!
We’re looking for individuals to to help us improve and expand this resource, making it more comprehensive, more user-friendly, and accessible to everyone for free! Your insights and contributions can help us create the ultimate MRS resource!
Feel free to get started with ideas. Follow this link to our current website.
Synthetic MRS
Synthetic MRS
Produce comprehensive and universal summary/recommendations for simulating synthetic spectra with use case-specific recommendations when necessary
Create a community-based synthetic data generator tool (based on the information we gather in step 1)
Reproducibility Made EasY (REMY) tool
Reproducibility Made EasY (REMY) tool
Several consensus papers by MRS experts have addressed data collection, analysis, and reporting standards. Despite this, the usage of the MRSinMRS standardized reporting criteria remain sparsely utilized, impeding research rigor and reproducibility. To overcome this, the ‘Reproducibility Made Easy’ software automates table population and methods section generation, streamlining the process with a single raw dataset, removing manual data entry.
We would like to extend this tool with several functions and would love to collaborate with you!
Standardized multi-language processing library
Standardized multi-language processing library
One of the main reasons why MRS is still not widely used for multi-site clinical studies is the enormous diversity in data processing methods. Virtually every lab has tailor-made 'in-house' code that they have sometimes cultivated for decades. Unfortunately, MRS metabolite concentration estimates are extremely sensitive to details of data processing, modeling, and quantification workflows.
This project aims to create a standardized library of basic and advanced data processing classes in the most widely used programming languages (Python, MATLAB, R, C++). The foundational building blocks of this library will be the basic MRS processing steps (zero-filling, line-broadening, concatenating and splitting transients, etc.). As the library grows, more complex methods will be incorporated.
We will build all classes around the new NIfTI-MRS data storage specification to ensure optimal interoperability and translatability of processing workflows.
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