UNMET NEED
Accurate quantitative magnetic resonance imaging (qMRI) is gradually becoming indispensable in clinical diagnostics and research. It’s application on preclinical MRI scanners, however, is hampered by the use of strong imaging gradients, which act to increase the effects of molecular diffusion, leading to bias of the measured signals. This inherent bias makes qMRI techniques irreproducible and imprecise when applied on preclinical scanners.

OUR SOLUTION
The lab of Dr. Noam Ben-Eliezer has recently developed a new qMRI platform that incorporates diffusion effects and compensates the corresponding signal biases, thereby providing improved accuracy and reproducibility of measures qMRI values on preclinical MRI scanners.
The platform is composed of a series of MRI measurements, followed by a new data processing algorithm. By retrieving the exact scan setting and measuring the diffusion properties of the imaged tissues it is now possible to calculate the signal bias and utilize it to correct the measured signal. This calculation is done using a new signal model accounting for the spin-physics and hardware imperfections affecting the MRI scan.   

APPLICATIONS
Our new qMRI platform actualizes the true power of preclinical MRI scanners and therefore provides reliable quantitative MRI outputs that are objective and repeatable. Hence, potential customers include:
• MRI vendors
• Research institutes
• Hospitals and medical centers
• Pharma and bio-tech companies
• Any company which uses preclinical MRI scanners

STATUS
The platform was successfully validated on two state-of-the-art preclinical scanners (horizontal 7T scanner, and a vertical 9.4 T scanner).