How MR Fingerprinting Is Transforming Epilepsy Imaging, Surgical Evaluation, and Outcome Prediction

Irene Wang, PhD (00:00):

My name is Irene Wang and I'm a biomedical engineer by training. And my current role at Cleveland Clinic is that I am a staff scientist specialized in epilepsy imaging. I'm also the research director at Cleveland Clinic Epilepsy Center.

(00:17):

We're very passionate about using neuroimaging techniques to help patients with epilepsy, particularly those coming to our center for pre-surgical evaluation. So these are the patients who come to us after failing many medications, and we come up with surgical plans for their brain surgery. So my role as a research scientist is to work hand in hand, side by side with my clinician colleagues to come up with solutions, better planning strategies for our patients.

(00:52):

There's a lot of new imaging techniques that are being developed and a lot of these are being presented at this AES meeting. Let me start by telling you about our own group's work. We are pioneering this technique called MR fingerprinting, and this is a quantitative novel imaging technique that gives you tissue-specific, brain tissue information. So we use this information not only to help physicians visually analyze the images, but also we use post-processing techniques with these quantitative images as input to help us build better models for lesion detection, lesion characterization, and outcome prediction. So we're very excited about actually using this novel technology to help our patients.

(01:46):

When we say MR fingerprinting, this is a name for a new type of MR sequence that can be sensitive and specific to the tissue properties. Therefore, we give it the name MR fingerprinting. So I say “we”, but this actually came from our collaborator who is the inventor of the MR fingerprinting technology. And we collaborate together to make this new technology more suitable for pre-surgical evaluation in our epilepsy patients.

(02:23):

So what this MRF or MR fingerprinting technology is about is that it uses a pseudo-random acquisition. So when you go to a clinical MRI, you will hear the MRI goes “bang, bang, bang”. But in the pseudo-random acquisition, it is a pattern that gives you almost like a very bad violinist kind of sound of the MRI. So it's really a very clever engineering technique. So using that, we can excite different tissue types differently. And we record the signals from the different tissue types, every voxel of the brain. And then we call that distinct signal evolution the “fingerprint” of that voxel. So we do this exhaustively for every voxel of the brain, and then we compare these recorded signal from a dictionary, which is pre-simulated ahead of time. And we do a pattern matching technology to make the imaging faster because we don't rely on the sequence to arrive at a steady state, but we rely on the pattern matching. So this is a newer way to do MRI quantitatively and to do it in a tissue-specific manner.

(03:55):

So the dictionary is very interesting. The simulation is done in an exhaustive manner. We try to simulate with every possible combination of physiological value. So we try to capture it all. And we don't need to do this every time. We just do it one time, and the dictionary is ready. It's exactly like what you do with a dictionary; it has everything, right? And then you record the signals from normal brain or epileptic brain, and then you do this matching. You try to find that entry, and that's how you get your signal, and you get it very fast.