Fast Quantitative Magnetic Resonance Imaging

Case ID:

This technology is a novel Quantitative Magnetic Resonance Imaging (QMRI) method based on the application of a linear combination of RF excitation pulses and MR measurement sensitizing strategies following a nulling sequence. Multiple differentiated measurements can be made over the course of each repetition of the sequence. In theory, this allows for the rapid collection of a large amount of imaging data which is well suited for quantitative analysis. Additionally, the application of a nulling sequence makes the assumption that measurements are equally weighted when made at corresponding points in the sequence extremely robust. The fact that measurements can be assumed to be equally weighted also means that measurements can be repeated, allowing for improvement of signal-to-noise (SNR) through signal averaging. In addition, simulated results show that measurements made using this method are sensitive to changes in tissue composition.


The field of MRI concerned with generating quantitative maps of sample properties is known as quantitative MRI (QMRI). The use of QMRI in research and clinical practice constitutes a significant paradigm shift from the qualitative methods used to interpret property weighted images. Qualitative assessment methods are employed where images are sensitized or “weighted” to a particular property, e.g. T1, T2, or diffusion. Within the resulting image, relative intensity may differ from area to area. While weighting implies that contrast is thought to be primarily due to a certain property, it is accepted that other properties influence the intensities in the resulting image. By definition, attempts are not made to quantitatively determine contributions from other properties that are likely present. In QMRI, the objective is to correlate the quantified or measured value of a property of interest with a spatial location in a sample. This can be done in order to glean a better understanding of the chemical, structural, or dynamic properties of the sample. It could also identify improved imaging biomarkers thus enhancing the ability to extract information about the condition of a biological sample.


Status: issued U.S. patent #10,551,460

Patent Information:
Contact For More Information:
Jay Martin
Licensing Associate, Software and Copyright
The University of Arizona
Lead Inventor(s):
Gregory Russell
Theodore Trouard
Jean-Philippe Galons
Eriko Yoshimaru
data utilization
diagnostic tool