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QMRI-based Image-processing Tool for Biophysical Tissue Signatures

Mezer Aviv, HUJI, Faculty of Science, The Edmond and Lily Safra Center for Brain Sciences

Categories

Life Science and Biotechnology

Technology Keywords:

MRI, quantitative MRI, Imaging, brain structure, lipids, white matter, gray matter, aging, multiple sclerosis, Alzheimer, neurodegenerative, diagnostic

Development Stage:

Characteristic proof of concept

 

 

 

Our Innovation

A novel qMRI-based approach that provides tissue-specific measurements and reveals the unique tissue signature with a high sensitivity to lipid and macromolecular content for different brain regions and various processes in the normal and diseased brain.

Highlights

  • The human brain is comprised of water, proteins and lipids,  which are distributed in different regions of the brain and in various pathological states. As yet, it remains a major challenge to localize and quantify these molecules using non-invasive methods
  •  MRI signals are often designed to reveal qualitative tissue contrast. Quantitative MRI (qMRI) methods offer clinical and scientific advantages, as they aim to characterize the structural and biological properties of brain tissue.
  • We suggest a qMRI-based method that is dependent on the non-water content and provides a new transformation of qMRI measurements that enhanced their sensitivity to the lipid and macromolecular content
  • Joining multiple qMRI parameters introduces a new possibility to measure, in-vivo, the molecular signatures of different brain regions

Key features

  • Non-invasive, quantitative characterization of brain structure molecular composition and its associated changes
  • Offers new MRI contrast measurements than can reveal clinically-important information about the brain
  • Add-on software that can used with existing MRI scanners

The Opportunity

  • The future of MRI is moving towards using quantitative methods that will capture structural and biological properties of the tissue. This method improve the specificity and interpretability of it.
  • The qMRI signature application is promising for characterizing and quantifying changes in neurological disorders such as MS and Alzheimer,  and will detect and quantify changes in the diseased brain that were not visible using conventional MR

Contact for more information:

Mel Larrosa
VP Business Development Healthcare
+972-2-6586692
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