Quantitative Imaging Biomarkers of Tissue Microstructure

Medical imaging is critical in clinical decision making. Imaging normally results in grayscale images reviewed by highly trained doctors. Despite their best efforts, subtle changes in the tissue may go undetected.

This shortcoming could be addressed by developing quantitative imaging biomarkers along with standardized scales and thresholds that differentiate pathological conditions. The challenge is to find imaging biomarkers that unmistakably differentiats such conditions. We propose to develop and validate imaging biomarkers that report on tissue microstructure using diffusion MRI.

The core idea is to vastly enhance precision by solving a fundamental problem with current encoding methods, which results in many tissue features being mapped to few observables.

Our solution is to enable multidimensional encoding and thereby disentangling previously inseparable features of the microstructure.

The four main goals are to (i) define novel imaging biomarkers, (ii) accelerate the image acquisition to meet clinical demands, (iii) validate the biomarkers for applications in oncology, and (iv) disseminate the methods.

A successful outcome would be highly impactful since more than 10 000 existing MRI scanners could be upgraded to provide the new imaging biomarkers. Applications are expected in neurology and oncology, for example, to improve tumour grading.