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qMRLab: Quantitative MRI analysis, under one umbrella

Agah Karakuzu, Mathieu Boudreau, Tanguy Duval, Tommy Boshkovski, Ilana Leppert, Jean-François Cabana, Ian Gagnon, Pascale Beliveau, G. Pike, Julien Cohen-Adad and Nikola Stikov

Article (2020)

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Magnetic resonance imaging (MRI) has revolutionized the way we look at the human body. However, conventional MR scanners are not measurement devices. They produce digital images represented by “shades of grey”, and the intensity of the shades depends on the way the images are acquired. This is why it is difficult to compare images acquired at different clinical sites, limiting the diagnostic, prognostic, and scientific potential of the technology. Quantitative MRI (qMRI) aims to overcome this problem by assigning units to MR images, ensuring that the values represent a measurable quantity that can be reproduced within and across sites. While the vision for quantitative MRI is to overcome site-dependent variations, this is still a challenge due to variability in the hardware and software used by MR vendors to produce quantitative MRI maps. Although qMRI has yet to enter mainstream clinical use, imaging scientists see great promise in the technique’s potential to characterize tissue microstructure. However, most qMRI tools for fundamental research are developed in-house and are difficult to port across sites, which in turn hampers their standardization, reproducibility, and widespread adoption. To tackle this problem, we developed qMRLab, an open-source software package that provides a wide selection of qMRI methods for data fitting, simulation and protocol optimization Figure 1. It not only brings qMRI under one umbrella, but also facilitates its use through documentation that features online executable notebooks, a user friendly graphical user interface (GUI), interactive tutorials and blog posts.

Uncontrolled Keywords

quantitative magnetic resonance imaging ; mri ; neuroimaging

Subjects: 1900 Biomedical engineering > 1901 Biomedical technology
2700 Information technology > 2700 Information technology
Department: Institut de génie biomédical
Department of Electrical Engineering
Research Center: NeuroPoly - Laboratoire de Recherche en Neuroimagerie
Funders: Canada First Research Excellence Fund through the TransMedTech Institute, Montreal Heart Institute Foundation, Canadian Open Neuroscience Platform (Brain Canada PSG), Quebec Bio-imaging Network, Natural Sciences and Engineering Research Council of Canada, Fonds de Recherche du Québec, Fonds de Recherche du Québec - Santé, Canadian Institute of Health Research, Canada Research Chair in Quantitative Magnetic Resonance Imaging, CAIP Chair in Health Brain Aging, Courtois NeuroMod projec, International Society for Magnetic Resonance in Medicine (ISMRM Research Exchange Grant)
Grant number: NS, 8436-0501, JCA, 5886, 35450, NS, 2016-06774, RGPIN-2019-07244, JCA, 2015-PR-182754, NS, FRSQ-36759, FRSQ-3525, JCA, 28826, JCA, FDN-143263, GBP, FDN-332796, 950-23081
PolyPublie URL: https://publications.polymtl.ca/10640/
Journal Title: Journal of Open Source Software (vol. 5, no. 53)
Publisher: Open Journals
DOI: 10.21105/joss.02343
Official URL: https://doi.org/10.21105/joss.02343
Date Deposited: 01 Mar 2023 16:23
Last Modified: 04 Nov 2023 13:06
Cite in APA 7: Karakuzu, A., Boudreau, M., Duval, T., Boshkovski, T., Leppert, I., Cabana, J.-F., Gagnon, I., Beliveau, P., Pike, G., Cohen-Adad, J., & Stikov, N. (2020). qMRLab: Quantitative MRI analysis, under one umbrella. Journal of Open Source Software, 5(53), 2343 (4 pages). https://doi.org/10.21105/joss.02343


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