Synopsis

Keywords: Image acquisition: Quantification

This lecture will provide an overview of the basic quantitative MRI techniques employed in neuroimaging. It aims to familiarize the audience with the theoretical principles and practical considerations of using quantitative imaging techniques. Specifically, we will cover methods to estimate longitudinal relaxation time (T1), transverse relaxation time (T2) as well as methods for studying the microstructure such as myelin water fraction imaging and diffusion and quantitative susceptibility mapping (QSM).

What to expect in this lecture

The current trend towards precision medicine and personalized healthcare involves the collection and analysis of patient data from multiple streams including pathology, genomics, environmental, and lifestyle information among others, aiming to provide a more precise approach for the prevention, diagnosis and treatment of disease. MR imaging can also add important information, but is more difficult to integrate due to the large variability in image appearance and qualitative nature of the exams and interpretation. Quantitative MRI holds the promise of improving the reproducibility of imaging data that is needed in the framework of precision medicine, but doesn’t come without challenges.
This lecture will provide an overview of the basic quantitative MRI techniques employed in neuroimaging. It aims to familiarize the audience with the theoretical principles and practical considerations of using quantitative imaging techniques. Specifically, we will cover methods to estimate relaxation times (T1, T2, T2*), methods for studying the tissue microstructure such as myelin water fraction imaging and diffusion, as well as quantitative susceptibility mapping (QSM). The data acquisition and parameter estimation approaches will be explained, highlighting some of the remaining challenges limiting the widespread clinical application of these approaches.

Acknowledgements

No acknowledgement found.

References

N. Seiberlich, V. Gulani, F. Calamante, A. Campbell-Washburn, M. Doneva, H. Hu, and S. Sourbron Quantitative Magnetic Resonance Imaging, Volume 1. Academic Press, 2020