RMMSC at CU Using Enhanced MRI Processing Technology to Measure Brain Volume

A new and enhanced way of processing MRI scans will allow doctors at the Rocky Mountain MS Center at University of Colorado to view patients’ scans in a whole new way. With this new technology, the brain volumes of patients can be quantified to give patients and their doctors more information, to help them maximize lifelong brain health and brain reserve. As part of this new MRI processing patients will be able to see color-coded MRI images showing the different parts of the brain, and reports will show how brain volume changes over time. We recently sat down with Dr. Justin Honce to discuss this new technology. Dr. Honce is an Assistant Professor of Radiology, Program Director for the Neuroradiology Fellowship, and Director of the UCDenver Clinical functional MRI & Diffusion Tensor Imaging program at the University of Colorado. Dr. Honce, please tell us more about the MRI processing technology that you are using for patients at the RMMSC at University of Colorado. axAs part of RMMSC’s overall approach to maximize lifelong brain health, it is very important to track brain volumes if at all possible, so we decided look for a product that might allow us to start doing that. We would like to use this approach in concert with all of the other data that we are collecting, such as through our patient reported outcomes (PROs) program.

Through the PRO program, patients answer a series of questionnaires covering quality-of-life factors such as depression, anxiety, cognition and mobility. Their answers will make up the baseline data, which will be used as a comparison for later responses, and will provide a picture of quality-of-life trends in the patient population overall. Our goal is to add quantitative brain volume to that data so that it can all be part of the same integrated system.

In order to measure brain volumes, the high resolution imaging is necessary. All MRIs for multiple sclerosis obtained at our hospital includes such high resolution 3D T1 data and has been a part of our protocol for the last few years. On T1-weighted images, CSF and fluid appear dark and gray matter is darker than white matter. We have been using this 3D T1 data for other research projects such as one of our recent abstracts at ECTRIMS.


But to move brain volume calculation out of the research and into clinic, new software was needed and as of October, we have licensed a product called NeuroQuant to allow us to perform brain volume analysis on every one of our patients who gets an MRI.


What will this new product mean for patients at the clinic?

corThis means that when the doctor sees a patient in clinic they can look at their MRI and the reports from the NeuroQuant software and see what their current brain volume is. If you are a patient and you’d like to see the color coded brain volume scan image, simply request it from your provider at the time of your visit.

The nice thing about the product is that it will also stratify where you are based on an age matched normal population, not an MS population. So the doctor will be able to say your brain volume is X, so that means, compared to normalized brain volume, you are in the first standard deviation or you are in the second deviation, etc.

And, as patients get new scans over time, we can actually track how their brain volume changes over time. While we are still in the evaluation stage what we hope to discover is whether stable patients on current treatments are losing brain faster than normal. For instance, if you’re tracking a patient who is on natalizumab (Tysabri) and doing great but the patient’s brain volume is still going down faster than normal, it might be time to deal with that unmet disease burden - whether that means using other medications, cognitive therapies, or lifestyle adjustments such as exercise and diet. So that’s the hope – to make this very relevant on an individual patient basis. And we are hopeful that it will help us stratify patients to some extent. Indeed, there is some good evidence that if you have a larger brain volume vs. a smaller brain volume, you typically respond better to therapies. We may also be able to stratify patients in terms of those who may need more aggressive therapies than others.

It sounds like this approach may be helpful from both a clinical care perspective and a research perspective?

sagWe very much hope so - it’s a bit of an exploratory approach that we are trying. We are trialing this piece of software to assess key questions to determine how best to move forward, including: How well does it work in clinical practice? Is it fully precise enough? Down the line, is it something that we’ll want to do on everyone?

How do you think this approach could potentially impact patient care and further research over time?

The key research question is determining if there is unmet disease burden. Right now we have a lot of very good drugs that work fairly well, but not perfectly. Patients receiving these highly effective therapies usually don’t have the new lesions that you normally see and clinically they seem relatively stable, with the ups and downs that the MS patients typically experience.

But what this technique may be able to show is that if your brain is still atrophying at a greater rate than normalized brain volume loss, we should really be addressing that. So, for example, just getting Tysabri isn’t enough. You’re still losing brain volume at a faster rate. So we’re identifying unmet disease burden and strategies for addressing that. So looking at other therapies or strategies – for instance, maybe that means you should escalate therapies.

It is important to choose the drug that has the greatest evidence for maximizing brain reserve – keeping the brain volume as high as they can. And so the more we can show that these patients look relatively stable but their brain volume is decreasing, the more you know you are not maximally treating these patients.

In addition, right now, you bring a patient in and it’s very hard to predict how you should treat them in some ways. We hope this will allow us to stratifying people by brain volumes, and that perhaps we can start figuring out patient by patient what makes sense. For example, if your brain volume is middle of the road, we can start treating you the way we treat any patient that comes in, but if you’re in the extreme margins we may approach treatment differently. For example, if your brain volume is on the high end, maybe we can be less aggressive with you and still have the same outcomes. Or if you’re in that lower end of brain volume, then we may decide that means we need to be more aggressive.

Tracking volumes is a part of the idea of moving into big data science: the idea that we can start collecting quantitative data and use that in analysis and research and for helping the individual patients. It’s a very exciting endeavor, and it will be very interesting to see what we are able to learn and how we are able to further improve individual patient care going forward.