MAGNETIC RESONANCE TECHNOLOGIES AND CAPABILITIES AT YALE

Transcript

• 00:00Thanks, everyone. I'm Dustin.
• 00:02I have the pleasure of
• 00:04introducing,
• 00:04doctor Henk de Fader,
• 00:06who'll be talking a little
• 00:07bit about, complimentary
• 00:09stuff we have on the
• 00:10MR side.
• 00:12Henk graduated from Ghent University
• 00:13in Belgium and earned his
• 00:15PhD
• 00:15in Idoven,
• 00:17University of Technology in the
• 00:18Netherlands.
• 00:19After that, he came to
• 00:21us, in radiology as a
• 00:22post doc and became an
• 00:23assistant professor in two thousand
• 00:25eighteen. His research focuses on
• 00:27applying advanced
• 00:29MR techniques to study metabolism
• 00:31and Vivo.
• 00:38Yeah. Thank you for the
• 00:39introduction. And, yes, indeed, I,
• 00:42somewhat naively accepted the challenge
• 00:44to talk about everything MR
• 00:46at Yale.
• 00:47And I, figured I used
• 00:49the list of Nobel Prizes
• 00:50awarded,
• 00:51later to MR in the
• 00:53past to illustrate
• 00:54how far MR reaches and
• 00:56and and is really a
• 00:58topic in many different fields.
• 01:00But, of course, today, we're
• 01:01gonna talk about the applications
• 01:02in vivo, which is, mostly
• 01:04MR, imaging, but also MR
• 01:06spectroscopic imaging. And in case
• 01:08you're not familiar with that,
• 01:10I'll quickly introduce that. So
• 01:11our MR images are based
• 01:13mostly on the detection of
• 01:14water signal and we have
• 01:15very high concentrations
• 01:17of water in our tissue
• 01:18that allows us to generate
• 01:20these anatomical images with
• 01:22very sharp and lots of
• 01:24detail. When we detect,
• 01:26metabolites with MR spectroscopy,
• 01:28we're dealing with concentrations that
• 01:29are several thousand times lower.
• 01:31You see all these different
• 01:32peaks in the spectrum. From
• 01:33there, we can,
• 01:35make maps metabolic maps. So
• 01:37this provide the biochemistry
• 01:38information,
• 01:39but understandably
• 01:41at a much lower spatial
• 01:42resolution,
• 01:43than water.
• 01:45So talking about the activities
• 01:46that happen in the Magnetic
• 01:47Resonance Research Center, which is
• 01:49under the leadership of doc
• 01:50Constable and doctor Ruffman,
• 01:52which houses about twelve faculty
• 01:54that all have,
• 01:56very actively funded research programs
• 01:58as you can see here.
• 02:00And this is really what
• 02:01drives the technology
• 02:02that, eventually becomes available to
• 02:04a lot of the users
• 02:06at Yale and and outside.
• 02:08So we use MRI scanners
• 02:10as our tool,
• 02:12to answer scientific questions and
• 02:14also try to improve diagnostics
• 02:15as MRI is used in
• 02:16the clinic. And there's even
• 02:18an occasional
• 02:19situation where the MR scanner
• 02:21is the therapeutic tool.
• 02:24This is a pretty general
• 02:26explanation that probably can be
• 02:27applied to any MR research
• 02:29center
• 02:30in the world.
• 02:32I think where Yale sets
• 02:34itself apart from a lot
• 02:35of centers is,
• 02:37the width, like, the the
• 02:38range of applications
• 02:40where we're focusing on as
• 02:41well as the depth. And
• 02:42with that, I mean, the
• 02:43the extent where people go
• 02:45to really customize,
• 02:48the hardware,
• 02:49modify the scanners so it
• 02:51can do what we think
• 02:52it needs to do, to
• 02:53answer our questions.
• 02:54And for you to appreciate
• 02:56that and some of the
• 02:56examples I'm gonna show, I
• 02:58wanted to quickly go through,
• 03:00the basic workings of an
• 03:01MRI scanner. This would be
• 03:03a clinical whole body scanner.
• 03:04If you would cut that
• 03:05open, you would see a
• 03:06giant
• 03:07superconducting
• 03:08magnet that is always on.
• 03:10A little safety alert. Don't
• 03:11let anybody tell you differently.
• 03:13And then a number of
• 03:14other,
• 03:15tube like structures, all different
• 03:17kind of coils, gradient coils,
• 03:18shim coils, or the frequency
• 03:20coils.
• 03:21That's the hardware component. The
• 03:22software component is basically where
• 03:24we drive these, different hardware
• 03:27components, specifically those coils, in
• 03:29a very accurate timed way.
• 03:31This is how you manipulate
• 03:32a signal,
• 03:34of the MR scanner to
• 03:35give us the contrast that
• 03:36we want and the information
• 03:37that we want.
• 03:38Next up is image reconstruction
• 03:40and then sometimes there's also
• 03:41quite some post processing involved.
• 03:44So now that you're experts
• 03:45on all this, let's go
• 03:46and look at a bunch
• 03:47of applications. First, in the
• 03:49basic science questions answering oh,
• 03:52we got two questions. So
• 03:53the first one, of course,
• 03:54is neuroscience, takes a big
• 03:55part of, the the main
• 03:59basic science questions, and that's
• 04:01because of functional,
• 04:02MR
• 04:03imaging. It's a technique that
• 04:04allows to detect active brain
• 04:05regions and allows to detect
• 04:07networks or how certain reaches
• 04:09of the brain,
• 04:10work in in in synchronicity.
• 04:12And this is just an
• 04:13example of how those networks
• 04:15can be detected. In this
• 04:16case, it's in, opioid use
• 04:18disorder.
• 04:19Now this can also be
• 04:20done in animal models.
• 04:22Here you see four activation
• 04:24maps and four different sensory,
• 04:26methods. So these are
• 04:28ranging from four paw all
• 04:29the way to olfactory bulb
• 04:31stimulation.
• 04:33The animal systems can even
• 04:34be combined with non MR
• 04:37technologies. So here you see
• 04:38a combination of the fMRI
• 04:40in, in mice
• 04:42in a setup that's compatible
• 04:43with NMR to also do,
• 04:45calcium imaging.
• 04:47This is still a very
• 04:48minimally invasive technique, so it
• 04:49allows for longitudinal
• 04:51studies as was, illustrated here
• 04:53in this Alzheimer model.
• 04:56Those were
• 04:58mapping networks in the brain
• 04:59based on the function, but
• 05:01we can also purely use
• 05:02the anatomy itself. Here's an
• 05:04example of fiber tracking. That's
• 05:06a post processing method that
• 05:07relies on diffusion weighted MRI
• 05:09data, and this was applied,
• 05:12in a in a project
• 05:13focused on neurodevelopment. And, again,
• 05:15leveraging the noninvasiveness
• 05:16of MRI, you can see
• 05:18that these data were acquired
• 05:19during different gestational stages all
• 05:21the way from fetuses to
• 05:23neonates.
• 05:24And this is also possible
• 05:26in animal studies as well.
• 05:27Same kind of data, different,
• 05:30illustrate or,
• 05:31visualization.
• 05:33This is now an example
• 05:34of using an MRI scanner
• 05:36as a therapeutic tool. This
• 05:38is real time fMRI neurofeedback.
• 05:40This involves a,
• 05:42task study in the scanner,
• 05:44and the signal is super
• 05:46quickly processed that can be
• 05:47presented to the patient itself.
• 05:49Basically, you see your own
• 05:50brain at work, and this
• 05:52is a tool that's been
• 05:53used mostly in psychiatric diseases
• 05:55to retrain,
• 05:56certain,
• 05:58responses to certain stimuli.
• 06:01Now let's focus a bit
• 06:02more on diagnostic imaging that
• 06:03we're trying to improve. So
• 06:05here you see an example
• 06:06of cardiac imaging with a
• 06:07a short axis
• 06:08image to the heart. This
• 06:10specific application
• 06:11mapped
• 06:13the parameter, a magnetic parameter
• 06:14in the blood and that
• 06:15resulted in an improved biomarker
• 06:18for detection of pulmonary hypertension,
• 06:20something that I was told
• 06:21is pretty hard to diagnose
• 06:24noninvasively.
• 06:25And now an example where
• 06:27we go even further. So
• 06:28here, novel hardware as well
• 06:30as,
• 06:31software as well as reconstruction
• 06:33are are modified. So remember
• 06:34these these structures, these tube
• 06:36like structures in the MR
• 06:37scanner, gradient coils. Now this
• 06:39is the gradient coil
• 06:41over here. Looks completely different,
• 06:43but it allows for very
• 06:44high
• 06:45gradient being applied to the
• 06:47prostate
• 06:48And, suddenly, these images that
• 06:50would not be possible within
• 06:51a regular MRI scanner become
• 06:53high quality and increase the
• 06:54detection of, prostate cancer.
• 06:58It can go even go
• 06:59further. Here, the shape of
• 07:00the magnet is completely different
• 07:01than what we're used to.
• 07:02So here, they envision a,
• 07:04point of care, kind of
• 07:06an MRI seat,
• 07:08with the idea that, could
• 07:10be used for lower abdominal
• 07:12imaging. And the same work,
• 07:13led to the
• 07:16to the project where the
• 07:17focus is on an affordable
• 07:18breast MRI scanner, which mentioned
• 07:20before. This is a future
• 07:24illustration of how this could
• 07:25look and, again, completely different
• 07:27way of looking at magnets,
• 07:29and dedicated to, the specific
• 07:31application.
• 07:33Here we see an overview
• 07:34of high quality,
• 07:36proton MRI combined with lots
• 07:37of structural MRI.
• 07:39This is a project very
• 07:41hard on acquisition and then
• 07:42reconstruction
• 07:43to improve the quality of
• 07:45of these data. And another
• 07:47approach also in MRSI, we
• 07:48again use a different type
• 07:50of hardware. This looks like
• 07:51the same tunnel stripe, like
• 07:53structure, but trust me, there's
• 07:55a completely different way to
• 07:56apply all these different gradients
• 07:58and manipulate the magnetic field
• 08:01and basically allowing for,
• 08:03high data quality in areas
• 08:05that otherwise
• 08:06are not really used for
• 08:08spectroscopic
• 08:09imaging.
• 08:11This is now an an
• 08:12interesting combination where proton MRI
• 08:14is applied preclinically but in
• 08:16combination with a contrast agent,
• 08:18and it's a contrast agent
• 08:19itself that is detected.
• 08:20This contrast agent provides a
• 08:22readout of extracellular pH. So
• 08:24now you can make these
• 08:25pH maps,
• 08:26characterizing the tumor microenvironment
• 08:28as is done in in
• 08:29several of these animal models
• 08:31of cancer as well as,
• 08:32kidney disease.
• 08:33And when this is combined
• 08:36with yet another method simultaneously
• 08:38imaging sodium,
• 08:40We now get maps that
• 08:41are based on,
• 08:42to the acidity map, the
• 08:44pH based map, as well
• 08:45as the salinity map.
• 08:47Two aspects that they're linked
• 08:48to, a phenotype of brain
• 08:50tumors, one being more invasive,
• 08:52one being more proliferative. And
• 08:53the idea is that this
• 08:54could be guiding therapy.
• 08:56Oops.
• 08:57Oh, boy.
• 09:00Since these tumors go to
• 09:02different cycle of,
• 09:03proliferation
• 09:04as well as invasion.
• 09:06Tumor slides.
• 09:09Yale has always been at
• 09:11the forefront of using stable
• 09:13isotopes combined with MR spectroscopy
• 09:15to study,
• 09:17metabolism in vivo. Here's an
• 09:18example of using thirteen c
• 09:20labeled acetate.
• 09:21The context is alcohol dependence
• 09:23and recovery. I'm not gonna
• 09:25go into detail of that.
• 09:26I just wanna show that
• 09:27these are are very complex
• 09:29studies, but very rich in
• 09:30information.
• 09:31And while I'm kind of
• 09:32grouping these into diagnostics, that
• 09:34doesn't really make sense because
• 09:35this is about a two
• 09:36hour scan. So this is
• 09:37definitely a basic science, approach.
• 09:41This is a little bit
• 09:41different for, the last iteration
• 09:44where we now use deuterium
• 09:45as a stable isotope.
• 09:46This is a lot easier
• 09:47than the thirteen c studies.
• 09:49So here, we do have
• 09:50the ambition to make something
• 09:51that is possible in a
• 09:53clinical setting. So our application
• 09:55in patients includes just drinking
• 09:57the deuterium labeled tracer,
• 09:59mapping the glucose metabolism in
• 10:01forty five minutes, as you
• 10:02can see illustrated here in
• 10:04these brain tumors. But even
• 10:05a forty five minute scan
• 10:06is too long, so now
• 10:07the acquisitions are actually interleaved
• 10:09with the anatomical MRI so
• 10:11that there's no extra time
• 10:12needed in, such a scan.
• 10:15Okay. I thank you for
• 10:17sticking with me to this
• 10:18fire hose delivery
• 10:19of all these different technologies,
• 10:21and, thank you for your
• 10:22time.