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The tissue team's main focus is on quantitative myocardial tissue characterization for the diagnosis and risk prediction of patients with cardiomyopathies or other diseases that may affect the cardiac tissue.



Validation of S.M.A.R.T. sequences

S.M.A.R.T. stands for Simultaneous Multi-parametric Acquisition and Reconstruction Techniques. These techniques encompass a group of CMR methods that acquire multiple CMR parameters at once including T1 and T2 parametric maps, cine images, and more. This project involves collaboration with MR sequence developers to test the clinical applicability of S.M.A.R.T. In addition, our group collaborates with industry partners to develop post-processing softwares that can visualize, automatically segment, and calculate quantitative metrics from images acquired using these methods.


Multi-parametric analysis of CMR techniques

This project is focussed on developing an automated, contrast-free, comprehensive assessment of CMR exams using CMR images obtained before contrast injection. We use advanced statistical methods to combine the quantitative metrics obtained from contrast-free images to try to classify pathology or predict the extent of irreversible myocardial tissue damage, typically assessed using contrast-CMR.




DART-CA is a study geared towards further exploring the dynamic properties of gadolinium on CMR in order to diagnose cardiac amyloidosis earlier. This will be done with the help of artificial intelligence and the development of a deep learning algorithm for future validation.



There are two main studies under the ZMR umbrella of our research group. One aims to observe whether z-scores can improve comparability of T1 and T2 mapping values across CMR scanners, field strengths, and sequences from different vendors in the same participant rather than different participants. The other study aims to assess the diagnostic value of T1 and T2 mapping z-scores in identifying various cardiomyopathies. Both studies will also explore sources of variation in mapping techniques and assess to what extent z-scores can correct them.

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