PET/MR Molecular Imaging of Cancer

Transcript

• 00:00My name is Pam Coons.
• 00:02I'm one of the GI
• 00:02medical oncologists. It's my pleasure
• 00:05to introduce doctor George El
• 00:07Fakhry,
• 00:08for today's,
• 00:10YCC Grand Rounds speaker.
• 00:12He is the I'm gonna
• 00:13do a brief introduction. I
• 00:14promised him I wouldn't. He
• 00:15has so many publications and
• 00:17awards, but I won't read
• 00:17all of them. So doctor
• 00:19Elfackery is the Elizabeth Mears
• 00:21and House
• 00:22Jamieson professor of radiology and
• 00:25biomedical engineering and of biomedical
• 00:27informatics and data science at
• 00:28Yale School of Medicine. He
• 00:30has been here almost exactly
• 00:32one year. Last year, October
• 00:33first was his anniversary.
• 00:35He also serves as a
• 00:36vice chair for scientific research
• 00:38in radiology and the director
• 00:39of the Yale Pet Center.
• 00:42He has a PhD in
• 00:43medical physics,
• 00:44an MS in biomedical engineering
• 00:46from the Paris Sud University,
• 00:48and an MS in electrical
• 00:50and com computer engineering
• 00:52from the University of Texas
• 00:54at Austin and a master's
• 00:55of engineering from a close
• 00:57central in France, and I
• 00:59probably mispronounced that. But he
• 01:01is internationally recognized,
• 01:03in quantitative
• 01:05molecular imaging for in vivo
• 01:06assessment,
• 01:08of pathophysiology
• 01:09in brain, cardiac, and oncologic
• 01:11disease.
• 01:12His current areas of research
• 01:14include high resolution PET MR
• 01:16imaging in a range of
• 01:17diseases,
• 01:19including neurodegenerative
• 01:20disease, traumatic brain injury, cardiac
• 01:22disease, and oncology. Cology. It's
• 01:24really
• 01:26personally, really a pleasure to
• 01:27partner with him as we
• 01:27think about pet imaging and
• 01:27oncology, my area of expertise
• 01:29in neuroendocrine
• 01:30tumors and as we think
• 01:31about really bringing some of
• 01:32his expertise,
• 01:33to clinic. So,
• 01:38thank you so much for
• 01:39joining us today.
• 01:42Thank you very much, Pam,
• 01:43for the kind introduction.
• 01:45I I was reminded it's
• 01:46almost a year I've been
• 01:48using nine months as an
• 01:49excuse that I'm not
• 01:51ready yet, but I guess
• 01:52that's run out now.
• 01:54So it's a pleasure to
• 01:55be here and to share
• 01:56with you,
• 01:57some of what PET NMR
• 01:59can do for you.
• 02:01Part of my job coming
• 02:02in here was to, go
• 02:03below the neck because the
• 02:05Pet Center is world renowned
• 02:07in neuroscience. And,
• 02:09we hope that,
• 02:12I'll give you a taste
• 02:12of what you can be
• 02:14doing with Pet, and with
• 02:15MR,
• 02:18in a center near near
• 02:19you. So I'd like to
• 02:21acknowledge,
• 02:23our funding that comes mostly
• 02:24from the NIH. And I
• 02:25would like to give a
• 02:26shout out to,
• 02:28not only the PET center
• 02:29that you see in this
• 02:30slide, but also the, the
• 02:32imaging group, at Yale. That
• 02:34was from Friday,
• 02:36where we had our first
• 02:38mini retreat. And, they're a
• 02:40pet center. There's an MR
• 02:42center. There's an image processing
• 02:43group over two hundred faculty
• 02:44and postdocs,
• 02:46that do anything that has
• 02:47to do with PET, MR,
• 02:48or optical in all parts
• 02:49of the brain.
• 02:51If you are interested in
• 02:52any of the imaging,
• 02:54all what I'll be showing
• 02:54today is available today at
• 02:56ATL.
• 02:58Some of it may be
• 02:59about to start, because nine,
• 03:01I just keep saying nine,
• 03:02eleven month is a short
• 03:04time. But, from for the
• 03:05most part, it's, all available
• 03:07now, as a revenue neutral
• 03:10core. So,
• 03:11please give me a a
• 03:12line if you're interested in
• 03:14any of this.
• 03:15This is the core I'm
• 03:16referring to, so
• 03:17we do everything from mice
• 03:19to men,
• 03:20including,
• 03:22some animals you may not
• 03:23recognize.
• 03:25Many, many of you are
• 03:26users of the core. I'm
• 03:27not gonna go through all
• 03:28the animals, but there's a
• 03:29woodchuck there and a rabbit.
• 03:32The,
• 03:33some of you are, actually
• 03:34users of the core.
• 03:38There,
• 03:39you are in many, many
• 03:40departments, and we do everything
• 03:42from cell culture to phase
• 03:44one in the core.
• 03:46So I'd like to start
• 03:47with a quick slide about,
• 03:50maybe that's one of the
• 03:51very few about modalities,
• 03:53talking about PET NMR.
• 03:56To highlight that
• 03:57these two modalities are quite
• 03:59symbiotic in that
• 04:01PET is a very high
• 04:02sensitivity modality where we image
• 04:04picomolar concentrations. You'll hear me
• 04:05often during the talk today
• 04:07talk about,
• 04:09you know, measurements that are,
• 04:11at the cellular level.
• 04:13Something we cannot do with
• 04:14MR.
• 04:15We are nowhere near the
• 04:17picomolar or the nanomolar really,
• 04:20in MR.
• 04:21But in PET, we have
• 04:22a very poor resolution and
• 04:24everything is relative. I hope
• 04:25by the end of the
• 04:26talk, I would convince you
• 04:27that's not anymore the case
• 04:29because you'll see images with
• 04:30a one millimeter resolution in
• 04:32PET.
• 04:33But for all intents and
• 04:34purposes, our scanners today are
• 04:36in the four, five millimeter
• 04:37resolution whereas in MR,
• 04:39our resolution is exquisite.
• 04:42We can form many, many
• 04:44images in a very short
• 04:45time without any ionization.
• 04:47Quantitation is quantity is challenging
• 04:49in MR and that's what
• 04:50we do on a daily
• 04:51basis in PET. So you
• 04:53can see that the strength
• 04:54of PET and MR are
• 04:55really the weaknesses of the
• 04:57other modality. And what I'm
• 04:58gonna try to show you
• 04:59today is putting those together,
• 05:00there are a lot of
• 05:01things we can do in
• 05:02cancer
• 05:04that
• 05:05get us to the heart
• 05:06of many diseases.
• 05:07I tried to I will
• 05:09try to show this by
• 05:10body part
• 05:12in the spirit of a
• 05:13grand rounds. But you'll see
• 05:14that a lot of those,
• 05:15there's symbiosis between the two.
• 05:18Our efforts, are part of
• 05:20actually a center of excellence
• 05:22that is one of, twenty
• 05:23in the country. This is
• 05:24the one in Panama. It's
• 05:25the only one in Panama,
• 05:28in the nation. And there's
• 05:29several pieces we are
• 05:32supposed to be doing in
• 05:33this center. One of them
• 05:34is developing new targets, and
• 05:36I'll show you some of
• 05:37the radiochemistry for some of
• 05:38these targets,
• 05:39the ones that are in
• 05:40cancer.
• 05:42But they're also a whole
• 05:43component in terms of,
• 05:45image analysis and processing and
• 05:47in terms of dissemination.
• 05:49And I mentioned this because
• 05:51it is part of our
• 05:52job to,
• 05:54disseminate our work to as
• 05:56many users who are interested
• 05:57as possible,
• 05:58provided their NIH users per
• 06:00NIH rules. But, actually, we
• 06:02often break that rule and
• 06:03we work with everyone. So
• 06:04if you are interested in
• 06:05any of this, please do
• 06:07let me know and we
• 06:07can, discuss afterwards.
• 06:11So I thought I would
• 06:11start in the head because,
• 06:12well, it's,
• 06:14the highest up. And, as
• 06:15I mentioned, we do a
• 06:16lot of work's being done
• 06:17in the brain.
• 06:19And I would like to,
• 06:20I don't know if we're
• 06:21supposed to be monitoring the
• 06:22chat. Oh, this is for
• 06:24you guys. If you wanna
• 06:25have CME attendance, please text
• 06:26four six seven nine three.
• 06:29I think from here on
• 06:30out, we won't look at
• 06:30the chat until the end.
• 06:32So,
• 06:34I'd like to start with
• 06:35some work in MR spectroscopy
• 06:37actually.
• 06:38And this is a nice
• 06:39success story because there's been
• 06:40a lot of work going
• 06:41in my lab in this
• 06:42area led by Chang Ma.
• 06:44And there's a lot of
• 06:44work happening here at Yale
• 06:46in spectroscopy that I will
• 06:48feature some of, and you'll
• 06:49see how the two come
• 06:50together in terms of imaging.
• 06:52The basic idea is that
• 06:55for a long time, what
• 06:56we have done in spectroscopy
• 06:57is looking at a voxel.
• 06:58So if you if you
• 06:59knew where to look, you'll
• 07:01get a good answer. And
• 07:02what you'd hear often is
• 07:03spectroscopy has good potential, but
• 07:05it was never something that
• 07:06is done
• 07:08routinely in the clinic.
• 07:09I hope today I'll I'll
• 07:10convince you that now there's
• 07:11quite a bit that you
• 07:12can do in the clinic
• 07:13without a major burden for
• 07:15your,
• 07:16for your workflow.
• 07:19This is just to show
• 07:20you that the trick and
• 07:21what I'll be showing you
• 07:22in terms of imaging
• 07:23is not to image the
• 07:25whole space,
• 07:26but to only image what
• 07:28we're interested in in terms
• 07:29of metabolites,
• 07:31because that allows us then
• 07:33in our reconstruction of the
• 07:34image to go much faster.
• 07:36And instead of, having, you
• 07:38know, a one scan or
• 07:39one voxel,
• 07:40to have a quantitative t
• 07:42one, t two, and, myelin
• 07:44water fraction and everything else
• 07:45you're interested in,
• 07:47in a time that is
• 07:48very reasonable,
• 07:50for MR, about eight minutes,
• 07:51but with a resolution that
• 07:53is very good. We're talking
• 07:54about, you know, one by
• 07:55one by two millimeters
• 07:57or two by two by
• 07:58three millimeters.
• 07:59And from that, we can
• 08:00estimate then the,
• 08:02all of the,
• 08:03different metabolites we can add.
• 08:05We're showing you here choline,
• 08:07creatidine,
• 08:08CAI, glutamate,
• 08:09glutamine.
• 08:12I will have very few
• 08:13images in normal subjects only
• 08:15just to make a case.
• 08:16I know this is a
• 08:16cancer round, but this is
• 08:17one of them.
• 08:19And now we look at
• 08:20a brain tumor, and you
• 08:21can see that,
• 08:23now the value of having
• 08:24a whole image of spectroscopy
• 08:26as opposed to a whole,
• 08:28voxel spectroscopy,
• 08:30is that now we can
• 08:31assess in the entire brain,
• 08:33the different signatures of the
• 08:35tumor, the tumor rim, the
• 08:37necrosis necrotic component, and the
• 08:39edema, which have different signatures.
• 08:42We can push this, further
• 08:45and look
• 08:46at,
• 08:47actually, this is a little
• 08:48longer now. It's, it's twelve
• 08:50minutes, but, you can see
• 08:52here that,
• 08:54the signature on the different,
• 08:56metabolic components,
• 08:57for example, the lactate and
• 08:59the choline are very different
• 09:00for the same tumor.
• 09:02And that allows you to
• 09:03start having some insight into,
• 09:06you know, what is the
• 09:07hypoxic component, what is the
• 09:08two HD or the IDH
• 09:10mutation,
• 09:11for that
• 09:12for that glioma in this
• 09:13case.
• 09:15And then this is in
• 09:16the Maersh spectroscopy side.
• 09:18We can also add the
• 09:19PET. Just one more slide
• 09:21to show you that this
• 09:22is not just a pretty
• 09:24image.
• 09:24What I'm showing you here
• 09:26is the,
• 09:27on top is the the
• 09:28clinical t one weighted and
• 09:30FLAIR t two.
• 09:31And in the middle row
• 09:32is the quantitative t one
• 09:34t two maps.
• 09:36And,
• 09:37in the bottom are the,
• 09:39NAA choline lactate.
• 09:41It's not just a pretty
• 09:42image. You can see that
• 09:44the discrimination we have and
• 09:46this is the manual annotation
• 09:48by the,
• 09:49neuroradiologist.
• 09:50You see the discrimination between
• 09:52the,
• 09:53edema and the tumor
• 09:55is done much better
• 09:56when you have access,
• 09:59to your, metabolic images from
• 10:01MRSI
• 10:02than it is when you
• 10:03have access only to your
• 10:05clinical MR. It is not
• 10:07as different when you're looking
• 10:08at the lesion versus normal.
• 10:10There, it's pretty clear.
• 10:12I want you to look
• 10:12at the green
• 10:14curve and the blue curve.
• 10:15These are the receiving operating
• 10:17characteristics. So the ROC curves
• 10:19for,
• 10:20what is true.
• 10:21And you can see that
• 10:22we do a lot better
• 10:23when we have
• 10:25the MR,
• 10:26s information compared to when
• 10:28we have only the MR
• 10:29information.
• 10:31And next, we're gonna look
• 10:32also at, we can add
• 10:34the PET.
• 10:36And we can see that
• 10:37in this case,
• 10:38we're looking at an amino
• 10:40acid, the, fluoroethyl,
• 10:41tyrosine
• 10:42in addition to tyrosine in
• 10:44addition to the MRSI.
• 10:46And and I hope you
• 10:47can see where I'm going
• 10:48with this. The idea is
• 10:49that now
• 10:51we can see on the
• 10:52t two flare, well, the
• 10:53entire tumor plus edema.
• 10:55You can see on spectroscopy
• 10:56the areas that are, this
• 10:58is a low grade glioma.
• 10:59You can see the areas
• 11:00that are, there are more
• 11:02involved in terms of
• 11:04metabolism.
• 11:06And then you can see
• 11:07from,
• 11:07the FET, the subset of
• 11:10that tumor,
• 11:11there is the more aggressive
• 11:12component.
• 11:14And that, you know, can
• 11:15be one way to look
• 11:16at image guided
• 11:18radiotherapy
• 11:19based on the biology as
• 11:20opposed to, a hunch.
• 11:23And you can see on
• 11:24the on the right side
• 11:25the the signature of these,
• 11:26which are, on the MRSI,
• 11:28which are different.
• 11:29This is all done with,
• 11:31this is work done by
• 11:32Chao Mang, and a grant
• 11:33he just started, with, Proton.
• 11:37And now we can do
• 11:38also,
• 11:39deuteron. This is the work
• 11:40of, Hank Fader and, Robin
• 11:42de Graaf here at Yale.
• 11:43We're, now we're looking at
• 11:45the deuterium metabolic imaging. So
• 11:47we're not looking at the
• 11:48h one now. We're looking
• 11:49at the h two here.
• 11:51Just that number changes, but
• 11:52a lot of things go
• 11:53with that. And we can
• 11:54look now at a three
• 11:55d map of the glucose
• 11:57deuterium metabolic imaging, the glutamate,
• 11:59glutamine,
• 12:01all of those in
• 12:03in a human four t
• 12:04scanner.
• 12:05This is again,
• 12:07a this is now a
• 12:08little larger
• 12:09voxel. Now we're talking about
• 12:11a two centimeter isotropic,
• 12:13in a thirty minute. But
• 12:14remember, this is now
• 12:16a deuterium that we're imaging,
• 12:17not pro, proton
• 12:21water.
• 12:22So signal is definitely less.
• 12:24The the way we do
• 12:25this is no different than
• 12:26what you're used to with,
• 12:27glucose,
• 12:28FPG. You would,
• 12:30you know, instead of having
• 12:31an IV injection, you would
• 12:32drink some,
• 12:34drink some glucose,
• 12:35wait for seventy five minutes,
• 12:37and then, your image for
• 12:38forty five minutes.
• 12:40Here's some of the typical
• 12:41image you'd see. You would
• 12:42see this is one of
• 12:43series of twenty three patients
• 12:45with brain tumors that have
• 12:46been,
• 12:47imaged now by,
• 12:49by Hank,
• 12:51where, you could interleave your
• 12:53MR with your, deuterium metabolic
• 12:56imaging. So you'd have both
• 12:57about the same time.
• 12:59It's a forty five minute
• 13:00protocol. So it's still a
• 13:02little long, but it's not,
• 13:04you know, impossible to do.
• 13:06And I'd like to draw
• 13:06your attention to the to
• 13:08the bottom where not only
• 13:09you can see the glutamine,
• 13:10glutamine, lactate, but the ratio
• 13:11of lactate to glutamine is
• 13:13actually an indicator of the
• 13:14Warburg effect,
• 13:16and that is indicative of
• 13:17the aggressiveness of the primary
• 13:19tumor. So we are getting
• 13:21now more of a window
• 13:22into the functionality of that
• 13:24tumor as opposed to only
• 13:25the appearance that we have
• 13:26from the t two.
• 13:28Last slide on MRSI is
• 13:30to show you that we
• 13:31can also look at the,
• 13:32choline metabolism in these brain
• 13:34tumors.
• 13:35As you know, choline is
• 13:37a precursor to acetylcholine
• 13:38neurotransmitter in the brain, but
• 13:40it's also a key component
• 13:41of the bio membrane.
• 13:43And, the choline transport is
• 13:46and the metabolism is regulated.
• 13:48It's upregulated in many cancers,
• 13:49so,
• 13:50especially brain tumors.
• 13:52So the idea here is,
• 13:54that by, you know, you
• 13:56can have it,
• 13:58either IV or, you can
• 13:59drink it. And in both
• 14:01cases,
• 14:02you can see that,
• 14:05seventy five minutes later, you
• 14:06you have a signal
• 14:08that is now,
• 14:10the area of,
• 14:11choline metabolism in in the
• 14:13brain. So, and this is
• 14:15now without an amino acid
• 14:17PET injection. So you see
• 14:18that there's there's a lot
• 14:19of, duality here in what
• 14:21we're doing, and doing one
• 14:22or the other allows you
• 14:23to see more.
• 14:25Now I hope you've noticed
• 14:26that the images I've shown
• 14:27you of the brain were
• 14:28very poor quality. If you
• 14:30didn't, you're very polite. But
• 14:32but these are the kind
• 14:33of images that we're all
• 14:35used to seeing in PET.
• 14:37Those are images at a
• 14:38resolution of about, four millimeters,
• 14:40five millimeters. So for a
• 14:42volume, that would be a
• 14:43hundred and twenty five millimeter
• 14:45cubed.
• 14:46What I'm gonna show you
• 14:47next are images now at
• 14:49two millimeters or one point
• 14:50five millimeters. So,
• 14:52you know, something around six
• 14:54millimeter cubed. So about
• 14:56twenty five times a better
• 14:57spatial resolution.
• 14:58This is,
• 15:00a new brain system, a
• 15:01neuro explorer that has just
• 15:02been installed at Yale,
• 15:04funded by a u o
• 15:05one led by Rich Carson
• 15:07at Yale and United Imaging,
• 15:10health in Houston.
• 15:12And the idea here is
• 15:13to go with a very
• 15:14small crystal
• 15:16with a very large,
• 15:18coverage of the brain,
• 15:20very unusual to what we
• 15:21do today. This is about
• 15:22fifty centimeters of axial coverage.
• 15:25And the reason is
• 15:27we would like to get
• 15:28the highest sensitivity possible,
• 15:30and I'll show you some
• 15:31clinical implications or benefits of
• 15:33that.
• 15:35You can think of that
• 15:36both in terms of, well,
• 15:36you could inject a lot
• 15:38less,
• 15:38but also in terms of
• 15:40you can see signal in
• 15:41the marginal lesion detectability, what
• 15:43we call marginal lesion detectability.
• 15:45Those tumors, they are the
• 15:46the hardest to see because
• 15:47the contrast to background is
• 15:48the the lowest.
• 15:50And now you can start
• 15:51seeing things we're we're not
• 15:52used to seeing. And I'll
• 15:53show you some examples of
• 15:54both.
• 15:54So I'm gonna start with,
• 15:56like, maybe the second slide
• 15:57of a normal,
• 15:59no cancer,
• 16:00but to drive the message
• 16:02of what high resolution and
• 16:04sensitivity buys you.
• 16:06So for those who are,
• 16:07fans of astronomy, think of
• 16:09the HRT, which has been
• 16:10the best system we've had
• 16:12as the Hubble Telescope.
• 16:13And that is still much
• 16:14better than a regular, brain
• 16:16scanner. Those images actually are
• 16:17better than the ones you
• 16:18see in the clinic.
• 16:19And this is the neuro
• 16:20explorer, which think of it
• 16:21as maybe the Webb telescope.
• 16:23And, here you have a
• 16:24twenty five
• 16:26fold better image resolution and,
• 16:29twenty fold,
• 16:30sensitivity.
• 16:31So now we're starting to
• 16:32see cortical ribbon. We're starting
• 16:33to see central,
• 16:35brain structures. We're seeing the
• 16:36horn of the chordate nucleus,
• 16:37the basal ganglia, things that
• 16:39until now we we know
• 16:40about in neuroanatomy, but in
• 16:41PET, we don't usually see.
• 16:43So what does that do
• 16:44to us in oncology? So
• 16:46here's an example of,
• 16:49another brain tumor that,
• 16:51is again
• 16:53well well characterized on FLAIR.
• 16:55But what I would like
• 16:56to show you is the
• 16:57FDG scan of that patient,
• 16:59both on a clinical
• 17:01scanner
• 17:02and on the neuro explorer.
• 17:03And I do hope
• 17:05yes. I can see it.
• 17:06I hope you see it
• 17:07over there. Can you see
• 17:09my cursor when I'm moving
• 17:10over there? You can. Oh,
• 17:11good. Because usually by the
• 17:13end of the talk is
• 17:13when the speaker asks, can
• 17:14you see my cursor? So
• 17:16at least at least I
• 17:17asked only twenty one slides
• 17:19into my seven hundred slides.
• 17:21So I hope you can
• 17:22see the lesion here.
• 17:24And unless you're,
• 17:27really really good, I don't
• 17:28think you can see it
• 17:28here.
• 17:30That's a good example of
• 17:31what a gain in sensitivity
• 17:33buys you,
• 17:34when, imaging with PET.
• 17:38Alright.
• 17:39So we're gonna move to
• 17:40sarcomas.
• 17:41And,
• 17:42here I'm gonna try to
• 17:44show you some examples,
• 17:46of what PET and a
• 17:47Marsh Petrosky can do together.
• 17:49You Starting to see a
• 17:50theme. This started with, a
• 17:52grant we were in our
• 17:53own, we're working on where,
• 17:55basically, we had asked a
• 17:56question for many of the
• 17:57sarcomas,
• 17:59who,
• 17:59for many of the patients
• 18:00who refuse to have surgery.
• 18:02We we do have about
• 18:04thirty percent of patients who
• 18:05say, no. I wanna forego
• 18:06surgery because I wanna go
• 18:07back to work,
• 18:08less than a year later.
• 18:10There is a risk of
• 18:11recurrence. And so there are
• 18:12two questions. The first one,
• 18:14well,
• 18:15can we tell if we've
• 18:16treated everything or not? And
• 18:17two, if there is recurrence,
• 18:19are you able to tell,
• 18:21early enough?
• 18:22And the answer to two
• 18:23of the those two is
• 18:25yes. I hope to I
• 18:26hope I'll be able to
• 18:26convince you of that.
• 18:28Just know that from the
• 18:29radiation oncology side, and there's
• 18:31no critique by no
• 18:33mean, the current consensus is
• 18:35quite crude. Basically, it's, you
• 18:36know, you take a three
• 18:37and a half centimeter
• 18:38longitudinal, one and a half
• 18:39centimeter radial, blast that, and
• 18:41you're good.
• 18:43And the question is, well,
• 18:44is that really necessary?
• 18:46And again, this is not
• 18:47at all we we work
• 18:48very, very closely with many
• 18:50of our radiation oncologists. This
• 18:51is not at all by
• 18:51any mean, a criticism, but
• 18:53these are, what we call
• 18:55gross target volume. So that's
• 18:56what we've decided is the
• 18:58tumor,
• 18:59that was delineated by multiple,
• 19:01radiation oncologists and okay. And
• 19:03maybe a couple of residents.
• 19:04And the message we're trying
• 19:06to convey here is that,
• 19:09depending on who's doing
• 19:12what at what time of
• 19:12the day, your contour will
• 19:14vary.
• 19:16So don't hope for a
• 19:17very reproducible
• 19:19treatment that you'd have the
• 19:20same way if two physicians
• 19:22did the same.
• 19:23And the message from that
• 19:24is not, oh, you shouldn't
• 19:25do it. The message of
• 19:26that is, is there a
• 19:27way we could reduce that
• 19:28variability? And I'll show you,
• 19:30that yes. We can. Alright.
• 19:31So let's start with the
• 19:32first question. So here's one
• 19:33example.
• 19:34This is a six year
• 19:35old female with a soft
• 19:37tissue circum of the right
• 19:38leg.
• 19:40This is your t two,
• 19:42enhanced MR. So based on
• 19:43that, all of this would
• 19:44be treated because some of
• 19:45it is tumor, some of
• 19:46it is edema. We don't
• 19:47know what is what.
• 19:48This is your pet signature.
• 19:50We see that it's mainly
• 19:51this area that is actually,
• 19:53active and the rest is
• 19:54not.
• 19:57Oh, somebody's trying to do
• 19:58something else while listening.
• 20:01And,
• 20:02of course, on pathology that
• 20:04is confirmed, this is the
• 20:05area that is, the the
• 20:06tumor and on, on a
• 20:08pathology, it's, that's confirmed. Now
• 20:10don't take my word for
• 20:11it. If this was my
• 20:12my grandmother, I would say
• 20:13no treat the whole thing.
• 20:15But,
• 20:16but doing this enough times,
• 20:18now we've seen that, you
• 20:19know, every time every time
• 20:21what you see on FDG
• 20:22is what you see on
• 20:22pathology.
• 20:23So, yes, you could, you
• 20:25know, use PET to guide
• 20:26your treatment.
• 20:27And the second question was,
• 20:28well, after treatment now, can
• 20:30can pet help me with
• 20:31determining if determining if there
• 20:33is any remaining? And the
• 20:34answer is no.
• 20:35Because, yes, in this case,
• 20:37for example, you see there
• 20:38is signal here,
• 20:40but we don't know if
• 20:41this is tumor or if
• 20:43this is simply
• 20:45inflammation post treatment.
• 20:47MR spectroscopy, on the other
• 20:48hand, can help you. So
• 20:50here's, an example, that that
• 20:52same example where
• 20:54this is the healthy contralateral
• 20:56leg where you see the
• 20:57choline protein ratio is normal.
• 21:00This is the,
• 21:01tumor where you see that
• 21:02the choline protein ratio is
• 21:04overtly abnormal.
• 21:05And in that area, you
• 21:06didn't know what to do
• 21:07with PET. Well, the ratio
• 21:09is normal and sure enough,
• 21:10a month later that has
• 21:11resolved.
• 21:12So you see that using
• 21:14both, has a value because,
• 21:17the pet can guide you,
• 21:18but I can't tell you
• 21:19in this case whether it's
• 21:20a remaining tumor,
• 21:21or not, and, a Mars
• 21:23spectroscopy can.
• 21:24Now this was,
• 21:26easier said than done. What
• 21:27we actually did, this is
• 21:29the ugly part of it,
• 21:30is in order to map
• 21:32absolutely
• 21:33and be absolutely sure what
• 21:34is where,
• 21:35I showed you all look
• 21:36this the path and pathology
• 21:38agrees. What we did really
• 21:40was,
• 21:41we did an MR. We
• 21:42did a three d printing
• 21:43of the tumor
• 21:44and of its surrounding.
• 21:45When the tumor was excised,
• 21:48it was taken in
• 21:50and frozen in this mold,
• 21:52then it was sliced.
• 21:54We had to pay a
• 21:55lot of chocolate and champagne
• 21:57and drinks for the pathologist
• 21:59who agreed to do not
• 22:00two slides, but forty slides
• 22:02out of one slice.
• 22:04And now you have your
• 22:07pathology and your pet absolutely
• 22:09in the same reference.
• 22:11And and now you have
• 22:12a validation slide by slide.
• 22:14This is very important because
• 22:15if we're gonna do any
• 22:16deep learning, we need that.
• 22:18And I'll show you some
• 22:19of what we've done with
• 22:20this. It is very hard,
• 22:22very lengthy, but there is
• 22:23no shortcuts if you really
• 22:25wanna do this, the right
• 22:26way.
• 22:28Remember I showed you a
• 22:29slide of big variability in
• 22:30the GTV.
• 22:32We have been working on
• 22:33this
• 22:34not to replace the radiation
• 22:36oncologist,
• 22:37but to provide the radiation
• 22:38oncologist with a starting point
• 22:40so they save time.
• 22:41In the US, you know,
• 22:42we have radiation oncologist who
• 22:44are specialized in head and
• 22:45neck, in sarcomas, in
• 22:47CNS.
• 22:48In many parts of the
• 22:49world and,
• 22:50including Germany, France, China, many
• 22:52other countries,
• 22:53they do all parts, all
• 22:55body parts.
• 22:56So when you're starting, it's
• 22:57really nice to have something
• 22:58that can be a a
• 22:59place you can start from
• 23:00and adjust. It saves you
• 23:02time. It increases your
• 23:04productivity,
• 23:05and it's a good,
• 23:07training tool. So the idea
• 23:08here was,
• 23:10not to learn from what
• 23:11one radiation oncologist can draw
• 23:13in terms of gross target
• 23:14volume or clinical target volume,
• 23:16but to have many of
• 23:17them do the same thing
• 23:19and have the neural network
• 23:21learn from all of those
• 23:23as opposed to learning from
• 23:25one contour.
• 23:26This is a lot harder
• 23:27because now you don't have
• 23:28a truth. You have more
• 23:30of a level of confidence
• 23:31based on where they agree.
• 23:33It takes a lot longer
• 23:34to learn. You need more
• 23:35data. And you're not gonna
• 23:37be as accurate
• 23:38as if you had one
• 23:40traditional colleges because what you're
• 23:41learning is the variability.
• 23:44However,
• 23:45that will allow you to
• 23:45be a lot more robust.
• 23:47Meaning,
• 23:48if you go to a
• 23:49different hospital,
• 23:50if you go to a
• 23:51different setting, you'll still be
• 23:52fine because what you've learned
• 23:54is a confidence level as
• 23:55opposed to a black and
• 23:56white. So instead of having
• 23:57one contour, what you will
• 23:58have at the end, what
• 23:59I'm showing you here is
• 24:00a confidence level. So let
• 24:02me show you some results
• 24:03of how well we do
• 24:04with this.
• 24:05These are
• 24:07patients that were never presented
• 24:08to the network until validation
• 24:10where you can see,
• 24:11that there's a very good
• 24:13agreement between what the consensus
• 24:16between,
• 24:16the radiation oncologist is, or
• 24:19I should say therapeutic radiologist,
• 24:21at Yale. And, what the
• 24:23level of confidence you have
• 24:25from the network. The hotter
• 24:26the yellower, the hotter. And,
• 24:29and the orangier,
• 24:30the less. I should have
• 24:31picked different colors, I guess.
• 24:33And you see that the,
• 24:34accuracy is not, you know,
• 24:35very good. It's in the
• 24:36eighty six percent, which is
• 24:37where we expected. It's not
• 24:39ninety nine percent. And, frankly,
• 24:40I don't believe in network
• 24:41that does ninety nine percent
• 24:42because you take it to
• 24:43a different location, it won't
• 24:45do as well. However,
• 24:47we are capturing very well
• 24:48the inter observer variability
• 24:50and, from the CT, the
• 24:51clinical target volume, we're doing
• 24:53also very well,
• 24:54with the compared to what
• 24:55was predicted.
• 24:57This is an example showing
• 24:58you now that if you
• 24:59did that instead of doing
• 25:00it only on CT, if
• 25:01you did with PET,
• 25:02you reduce your variability, you
• 25:04increase your reproducibility, which is
• 25:06what you would expect.
• 25:07And this is showing you
• 25:09that,
• 25:09you know, we can do
• 25:10this now in a more
• 25:12sophisticated way with diffusion networks,
• 25:15but the resolution,
• 25:16is about the same. We're
• 25:17still in the eighty eight
• 25:18percent. It's just that we're
• 25:19now more resilient to, to
• 25:21noise.
• 25:23Alright. This has shown you
• 25:24that we can do this
• 25:25also for the clinical target
• 25:26volume, not just for the
• 25:27gross target volume.
• 25:29I'd like to move now
• 25:30to head and neck. We're
• 25:31excited that we're starting a
• 25:33new, project now looking at
• 25:35this in head and neck
• 25:36as opposed to sarcomas,
• 25:38where we're looking again, how
• 25:39is the contribution from PETCT
• 25:41or taken together, and how
• 25:43well can we do?
• 25:45I hope you can see
• 25:46here that we can delineate
• 25:47very accurately the, the tumor.
• 25:50And, more importantly, I wanna
• 25:52show you what you can
• 25:53do now if you have
• 25:55a much better sensitivity with
• 25:56your PET scan, again, compared
• 25:58to what we're used to.
• 26:00So those are the same,
• 26:01Webb Telescope images.
• 26:03Now this is the work
• 26:04of, the creator Inaga in
• 26:06our group who is looking
• 26:07at,
• 26:08head and neck cancer within
• 26:09our explorer. So much higher
• 26:11sensitivity,
• 26:12much higher resolution,
• 26:14same patients scanned on our
• 26:16clinical
• 26:17vision
• 26:18and our,
• 26:20research for now, NeuroExplorer, which
• 26:22is FDA approved by the
• 26:23way. Some of those are
• 26:24very obvious. You see the
• 26:26lesion very well in both.
• 26:27What I would like you
• 26:28to notice is, one, that
• 26:30the lesion delineation is clearer
• 26:33and the contrast is higher.
• 26:34That is not a higher,
• 26:36glycolytic rate of the tumor.
• 26:38It's exactly the same tumor.
• 26:39It's just that we have
• 26:40less partial volume effect. That's
• 26:42all.
• 26:43These are lymph nodes in
• 26:44the left neck where you
• 26:45see,
• 26:46same story.
• 26:48And in the base of
• 26:49the tongue, same story again,
• 26:50where you have a much
• 26:51better deniation of the anatomy
• 26:53and of the tumor.
• 26:56This is a lymph node
• 26:57in the left neck, and
• 26:58I think I have one.
• 26:59Yeah. This one I like.
• 27:00And this is, again,
• 27:02lymph node left neck, but
• 27:04what I draw what I
• 27:04would draw your attention is
• 27:06to this component of the
• 27:07tumor, which is barely visible
• 27:09and clearly visible on,
• 27:12on the nurse core.
• 27:15Okay.
• 27:16I think you've seen enough
• 27:17good pictures. Let's move to
• 27:18the next, some basic science.
• 27:20Now we're gonna move to,
• 27:22more basic science in terms
• 27:24of,
• 27:26a new radio
• 27:27a a new a new
• 27:29target.
• 27:29What we're looking here at
• 27:31is measuring the membrane potential.
• 27:33And you can think of
• 27:34the membrane potential as the
• 27:35battery,
• 27:36of life for the cell
• 27:37because that's the that's what
• 27:38the mitochondria uses,
• 27:41in its role as an
• 27:42energy plant,
• 27:43so as a power plant.
• 27:45So that's what we use
• 27:46to convert our, ADP to
• 27:48ATP,
• 27:49and
• 27:50this is the canary in
• 27:51the mine. It is affected
• 27:53very early on,
• 27:55anytime there is a change
• 27:57in the reactive oxygen species.
• 27:59So you'll see this affected
• 28:01long before
• 28:02other more,
• 28:04anatomical
• 28:05or functional. I'll show you
• 28:06some examples.
• 28:09Parameters we measure usually are
• 28:11are affected.
• 28:12Okay. So
• 28:14let let's, let's dig into
• 28:15this. This has been known
• 28:17for for a long time,
• 28:18as something you can measure
• 28:20with treated compounds
• 28:22in dead in
• 28:24in in cells but in
• 28:24dead people.
• 28:25The idea here was to
• 28:26do this in vivo in
• 28:28living humans. So
• 28:29we labeled,
• 28:31the tryphalan phosphonium with f
• 28:32eighteen, and then,
• 28:34we set out to measure
• 28:36that membrane potential, which would
• 28:37be basically if you had
• 28:38a
• 28:39nano electrode inside the cell
• 28:41and one outside the cell,
• 28:42that would be the voltage
• 28:43difference you would see.
• 28:45That's what we're trying to
• 28:46measure.
• 28:47I'll spare you the kinetic
• 28:49modeling, which is what a
• 28:50lot of us spend our
• 28:51time doing.
• 28:52But I wanna I wanna
• 28:53just point out that what
• 28:54you're measuring here is the,
• 28:57voltage in millivolts,
• 28:59not arbitrary units.
• 29:02That was published in twenty
• 29:03twenty, and here's some of
• 29:04the applications. The one I'll
• 29:05show you obviously is the
• 29:07one that has to do
• 29:07with cancer.
• 29:09So,
• 29:09what we look at is
• 29:11cardiotoxicity,
• 29:12but before we go there,
• 29:13I would like to show
• 29:14you this graph to show
• 29:15you that
• 29:16the membrane potential measurement is
• 29:18incredibly
• 29:19well preserved in humans.
• 29:21And rightfully so because it's,
• 29:23as I told you, the
• 29:23canary in the mind. So
• 29:25this is very valuable because
• 29:26that means that when we're
• 29:27gonna set out to imaging
• 29:29that in patients versus healthy
• 29:31controls,
• 29:32the difference will be due
• 29:33to the disease, not to
• 29:34variability in the patients. Because
• 29:36this is many, many patients
• 29:37that were scanned, and you
• 29:38can see that they're plotted
• 29:39here and they're all about
• 29:41the same.
• 29:43Alright. So cardiotoxicity,
• 29:44why are we doing this?
• 29:46As you know,
• 29:47patients who receive doxorubicin
• 29:49in breast cancer, for example,
• 29:52they,
• 29:52they have serious side effects
• 29:54that not all not always
• 29:56manifest immediately. Sometimes it's
• 30:00months and years later. And
• 30:02these can be very healthy
• 30:03otherwise patients. So there's
• 30:05very little in terms of
• 30:06predictive,
• 30:08prediction of who's gonna
• 30:10go for,
• 30:12cell death and heart failure
• 30:13other doctor Rubinstein versus who's
• 30:14not going to.
• 30:16One of the measurements we
• 30:17do is the left ventricle
• 30:18ejection fraction,
• 30:20but that's a little bit
• 30:22late. By the time you
• 30:24see the ejection fraction changing,
• 30:26a lot of the harm
• 30:27has been done. And I'll
• 30:28show you in the experimental
• 30:29model that
• 30:30that's the case. So the
• 30:32idea here is, is there
• 30:34a way we could predict
• 30:36long before ejection fraction has,
• 30:39started to telling us there's
• 30:40something wrong,
• 30:41that, you know,
• 30:43it's too late?
• 30:44Alright. And that's where
• 30:45we would like to,
• 30:47intervene with,
• 30:49membrane potential PET imaging.
• 30:51Alright.
• 30:53Let's see. First, I'm gonna
• 30:54show you some acute,
• 30:55examples because,
• 30:57in physiology, you always have
• 30:59to show
• 31:00effect in in real time
• 31:01before we go to more,
• 31:03more long term, and I'll
• 31:04then I'll show you the,
• 31:06chronic care model. So in
• 31:07the acute model,
• 31:08these are pigs that are,
• 31:10I'm showing here results in
• 31:11eight pigs. They're you know,
• 31:12we have an intervention. We
• 31:13go into the LAD. We
• 31:14inject,
• 31:16acutely
• 31:17docservicin in the LAD, and
• 31:18we expect to see
• 31:20a drop in the membrane
• 31:21potential transiently
• 31:24in the anterolateral wall, you
• 31:25know, insert in the anterior
• 31:26wall and septal wall, but
• 31:28not in the inferior wall
• 31:29because we didn't inject anything
• 31:31in the right circumflex. So
• 31:32the right circumflex serves as
• 31:34the,
• 31:35control in each in each
• 31:36animal and you should see
• 31:38in this area a drop
• 31:39the membrane potential in millivolts
• 31:41and this area no drop
• 31:42and that's exactly what you
• 31:44see. Alright. That's the chronic
• 31:46model. And when we form
• 31:47the images of these, again,
• 31:49these units here are in
• 31:50millivolts. You see minus one
• 31:51twenty millivolts and in the
• 31:53anterior and septal, there is
• 31:54a drop, but in the
• 31:55inferior wall, there's none.
• 31:57Then we move to the
• 31:58chronic setting. That's the more
• 31:59complicated study. Now we're treating
• 32:01pigs as, patients who have
• 32:03a breast cancer,
• 32:05over, several months.
• 32:07And
• 32:08the figure I would like
• 32:09you to leave, if there's
• 32:10one figure to leave for
• 32:11doc cardiotoxicity with is this.
• 32:13This is the membrane potential
• 32:16of those pigs over time,
• 32:17and you can see that
• 32:18this was before treatment.
• 32:20You see how it drops
• 32:23very quickly?
• 32:24Whereas the left ventricle ejection
• 32:26fraction stays on for a
• 32:27while
• 32:28before it drops.
• 32:30What is interesting is that
• 32:31when we start treatment,
• 32:34you know, the
• 32:36the ventricle ejection fraction drug
• 32:37goes up again very quickly.
• 32:39Whereas with the,
• 32:41sorry, the membrane pressure goes
• 32:43up quickly whereas the ejection
• 32:44fraction doesn't. So this is
• 32:46a canary in the mind
• 32:47that allows you, in this
• 32:49case, after six cycles, to
• 32:50determine where you are in
• 32:51terms of,
• 32:53in terms of,
• 32:55viability of the tissue. And
• 32:57this is a study that
• 32:58we will be starting here
• 32:59at Yale,
• 33:00next month.
• 33:02Alright. Last part of my
• 33:03talk, I would like to
• 33:04cover some of the,
• 33:06again, more exploratory in, imaging
• 33:08immune response with PET. And
• 33:10we're gonna start with Feraheme,
• 33:11which is an MR contrast
• 33:12agent. That's fermoxetil. It's an
• 33:14iron particle that is actually
• 33:15FDA approved for, anemia.
• 33:18Because, over, over time the,
• 33:21the bioavailable iron, the nano
• 33:24particle core dissolves and the
• 33:25bioavailable iron becomes exposed and
• 33:27that's a treatment for anemia
• 33:28that is approved. But it
• 33:29started as an MR contrast,
• 33:31and there have been several
• 33:32clinical trials done in that
• 33:34space because,
• 33:35you know, it it will
• 33:36track lymph nodes and you
• 33:37can see lymph node involvement.
• 33:39The only problem is because
• 33:41it's an MR contrast, you
• 33:42have a few minutes to
• 33:43see it. And after ten,
• 33:44fifteen minutes, the signal is
• 33:45gone. So the idea was,
• 33:46well, if we label this,
• 33:47and in this case, I'll
• 33:48spare you the radiochemistry, but
• 33:49it's basically a chelation where
• 33:51you heat,
• 33:52the core and then, the
• 33:53the zirconium
• 33:55eighty nine goes into the
• 33:56core
• 33:57of the, fermoxetal
• 33:58and stays there forever.
• 34:00If we label that, we
• 34:01could follow then for a
• 34:02long time,
• 34:04that,
• 34:05that, compound as it,
• 34:08distributes in the body.
• 34:10And, this is where we
• 34:11were very very surprised.
• 34:13This is an example in
• 34:14an animal that had,
• 34:16a skin lesion.
• 34:18This is a nonhuman primate
• 34:19where, now you see the
• 34:21time is two hundred hours.
• 34:22We're following for a long
• 34:23time because zirconium eighty nine
• 34:24allows you, to follow the
• 34:26enemy.
• 34:27You can see that the
• 34:28uptake in the ipsilateral lymph
• 34:30nodes was going up over
• 34:31time,
• 34:32but there is no circulating
• 34:34activity anymore. You know, the
• 34:35activity after a few minutes
• 34:37has distributed, and that's it.
• 34:39So this is not circulating
• 34:40activity. This is
• 34:42active trafficking of monocytes.
• 34:45And that was our first,
• 34:46discovery in this, the totally
• 34:48scientifically because we we didn't
• 34:49expect to see that over
• 34:50time.
• 34:52So I'll show you now
• 34:53another example of,
• 34:55what we can do with
• 34:56this.
• 34:57Those of you old enough
• 34:58to know white blood cell
• 34:59imaging, Indian white blood cell,
• 35:01remember how we draw bloods
• 35:02and then he labeled Indian
• 35:03and,
• 35:04well, this is a spin
• 35:05on that. No pun intended.
• 35:07But now we're,
• 35:09we draw the blood and
• 35:10then we isolate by, you
• 35:12know, by facts the t
• 35:13cells and the b cells.
• 35:14And we can isolate the
• 35:16monocytes also,
• 35:17by buffy coat extraction.
• 35:19And then you label those
• 35:21b cells or t cells
• 35:22with the zirconium for a
• 35:23hem, then you reinject them.
• 35:25And now what you see
• 35:26is, this is an EAE
• 35:27model, where we're labeling the
• 35:29b cells. And you can
• 35:30see that,
• 35:31when, you have EAE induction,
• 35:33you do see,
• 35:34uptake in the, area of
• 35:36lesion. Whereas when, you don't
• 35:38have,
• 35:40the EAE model, when you
• 35:42when you have a sham
• 35:43induction without labeling of the
• 35:44b cells, you don't see,
• 35:46uptake in that area. And
• 35:47the same with the immunomodulator
• 35:49with the t cells. You
• 35:50see that, with the immunomodulator,
• 35:52you have a drop when
• 35:54you're doing the t cells.
• 35:55Whereas when you're doing the
• 35:56sham or n p injection,
• 35:58you don't see that drop.
• 35:59So this is to peak
• 36:01your curiosity about what you
• 36:03could do now,
• 36:04imaging t cells and b
• 36:05cells in the body,
• 36:07as opposed to and you
• 36:08can see if they're going
• 36:09to the spleen, well, nothing's
• 36:10happening or they're going to
• 36:11the tumor. Well, that's a
• 36:12real, immune
• 36:15recruitment.
• 36:16This is a compound that
• 36:17we hope to bring to
• 36:18man here at Yale.
• 36:20It is part of,
• 36:21a large study where we've
• 36:23done now the dosimetry. It
• 36:24is, all very promising.
• 36:26Really chemistry,
• 36:28purity is also very good.
• 36:30And we're hoping that, you
• 36:31know, within a year from
• 36:32now, this will be in
• 36:33humans here, with an IND.
• 36:36Alright. I'd like to close.
• 36:37I have still a few
• 36:38minutes. I'd like to close
• 36:39with,
• 36:40the piece de resistance, which
• 36:42is
• 36:43the rhinostics and the role
• 36:44of pet inspect in there.
• 36:46So for those of you
• 36:47who,
• 36:48you know, don't know the
• 36:49rhinostics,
• 36:51the idea is
• 36:52that said in words, you
• 36:54could see what you treat
• 36:55and you could treat what
• 36:56you see.
• 36:57It is something that we
• 36:58don't often have the luxury
• 37:00of with chemotherapy
• 37:02where
• 37:03you don't see what you're
• 37:04treating. You you treat and
• 37:05then you're treating blind. So
• 37:06the idea basically is that
• 37:09we would use a PET
• 37:10agent, and we'll talk in
• 37:11a minute about agents, but
• 37:13that is going specifically to
• 37:14a tumor to see if
• 37:15you have enough signal
• 37:16to justify treatment,
• 37:18through a radiopharmaceutical
• 37:19treatment.
• 37:20If you do, then you
• 37:21have your radiopharmaceutical
• 37:22treatment, and Pam is doing
• 37:24a lot of this in
• 37:25NET.
• 37:26And then, at the end,
• 37:27you could even image and
• 37:28see how well have you
• 37:29done.
• 37:30That's the general idea.
• 37:32What we're interested in doing,
• 37:33and we're very excited, that's
• 37:34another project that we'll be
• 37:36starting,
• 37:37is that what you could
• 37:38do is not just
• 37:40do your
• 37:41pretreatment,
• 37:42in this case, Lutetium,
• 37:44and then Pam told me
• 37:45we've just done our first
• 37:46alpha last week.
• 37:48But for both of them,
• 37:49it's the same idea. You
• 37:50don't do your
• 37:52pretreatment imaging. You say, yes.
• 37:53There's enough uptake. Well
• 37:55and then we do our
• 37:56post treatment.
• 37:57We've done well. What we
• 37:59would like to do is
• 38:00after every treatment,
• 38:02image the patient to define
• 38:05how our targets are responding,
• 38:07what is our pharmacokinetics,
• 38:09and what is our effective
• 38:10dose. Because
• 38:11there are some patients where
• 38:12we will need to treat
• 38:13more. And there are some
• 38:15patients where
• 38:16we don't need at all
• 38:17the dose we're doing. We
• 38:18can go a lot lower
• 38:19and we still have the
• 38:20same effect.
• 38:21We have an opportunity to
• 38:22do what we've done always
• 38:23in iodine, for example, month
• 38:24thirty one, to do a
• 38:26a dosimetry
• 38:27on the fly as the
• 38:28patients are being,
• 38:30given their two hundred milli
• 38:32curiae of Lutetium.
• 38:33And there's no cost to
• 38:34it other than the imaging
• 38:35piece because they are having
• 38:37their Lutetium anyway. So that's
• 38:39the idea with, NET with
• 38:41the neuroendocrine tumors. You can
• 38:42do the same, and and
• 38:44you can define the refine
• 38:45this at every treatment. So
• 38:46So you can see cycle
• 38:47one, cycle two, and then
• 38:49you decide, well, you know,
• 38:50we we can stop now.
• 38:52Or, no, we're gonna have
• 38:52to go one more cycle
• 38:54as opposed to six cycles
• 38:55of two hundred manicures.
• 38:57You can do the same
• 38:58in, prostate with the prostate
• 39:00specific membrane antigen that we
• 39:01can image. We can do
• 39:03a gallium pre, and then
• 39:04we can look at those
• 39:06targets. What's the effective dose?
• 39:08Do we need to go
• 39:08up or down? And do
• 39:10that one, two cycles and
• 39:11then,
• 39:13and then stop.
• 39:14We can even go further.
• 39:17What we can do, actually,
• 39:18and this is the project
• 39:19that I said we're excited
• 39:20we're starting,
• 39:21is we could do pre
• 39:22imaging therapy
• 39:24and only have one or
• 39:25two of those scans, and
• 39:26that is enough to predict,
• 39:29you know,
• 39:30whether you should act,
• 39:34increase or decrease your dose
• 39:36and and predict your outcome
• 39:37from very few of those
• 39:39studies. You don't need the
• 39:40whole
• 39:41study to predict that. So
• 39:42the idea is gonna be
• 39:43to looking at the very
• 39:44early frames to very early
• 39:46treatments to predict that because
• 39:48more often than not, it
• 39:49it is something you can
• 39:50predict. It is challenging. It's
• 39:52not simple, but I think
• 39:52it's very valuable because,
• 39:55you know, when we talk
• 39:56about personalized medicine,
• 39:58this is
• 39:59personalized medicine by excellence. This
• 40:01is like, you know, you
• 40:01can't go more personalized than
• 40:02that. It is your scan
• 40:04that is defining your dose.
• 40:06I would like to leave
• 40:07you with two last slides
• 40:08on something that is a
• 40:09lot more, you know, also
• 40:11coming, down. This is work
• 40:13from Jason Kai who's looking
• 40:15at a similar approach for,
• 40:18prognostics
• 40:19but for gliomas. And this
• 40:20is looking at PARP.
• 40:23Those of you who work
• 40:23in PARP, you probably know
• 40:24that PARP one inhibitors
• 40:26are approved as treatment drugs
• 40:28in many cancers, breast, pancreatic,
• 40:30but also in brain. And
• 40:31the idea here is to
• 40:32label the PARP
• 40:33and
• 40:34see,
• 40:36and see if we can
• 40:37then use it for treatment.
• 40:39What Jason has done is
• 40:40the very first PARP
• 40:42brain penetrant tracer. There has
• 40:43been some that were not
• 40:44brain penetrant.
• 40:46Why that is important? Because
• 40:47if it's not brain penetrant,
• 40:48then you can't cross the
• 40:49blood brain barrier and the
• 40:50only time you see the
• 40:51tumor is when there's breakage.
• 40:52In this case, he has
• 40:53shown that in the intact
• 40:54brain barrier, you can image
• 40:56that,
• 40:57and see the tumor. And
• 40:58the idea, of course, is
• 40:59now well, he's done that
• 41:01first with c eleven because
• 41:02that's the easiest. Now we're
• 41:03doing it with f eighteen,
• 41:04and his plan is to
• 41:05do that with,
• 41:06acetylene,
• 41:07because then you can, do
• 41:09the same story. We we
• 41:10talked about with neuroendocrine
• 41:12and with
• 41:15prostate. Now you can do
• 41:16that in in the brain.
• 41:17So that would be
• 41:19a first.
• 41:20And, it's, optimistic, but he's
• 41:22hoping that in a year
• 41:24or two from now, his
• 41:24ID will be up and
• 41:25running.
• 41:26Alright. So,
• 41:27I was asked to finish
• 41:29with enough time for questions.
• 41:30I hope this gave you
• 41:32a good sense of what
• 41:33can PedamR do PedamR do
• 41:35for you.
• 41:37I do hope, you know,
• 41:38it gives you
• 41:40some appetite for for some
• 41:41of the imaging. I do
• 41:43believe that imaging is not
• 41:44meant to be just, you
• 41:45know, show and tell, but
• 41:46it has to guide the
• 41:47treatment. If imaging doesn't guide
• 41:49treatment,
• 41:50for me, it's, you know,
• 41:52a very,
• 41:53you know, frustrating.
• 41:55It's a nice exercise, but,
• 41:57when we can guide treatment,
• 41:58that's when we have a
• 41:59role, that is meaningful. So
• 42:00with that, I'd like to
• 42:01thank you for the kind
• 42:02invite to be here. And,
• 42:03if you have any questions,
• 42:04happy to take them.
• 42:13Questions from the room. And
• 42:15yes. Go ahead.
• 42:17Yeah. That's a thought. You
• 42:19talked about a lot of
• 42:19things. I was curious. What
• 42:22of of the things you
• 42:23talked about, where do you
• 42:24think you kinda where's the
• 42:25lowest hanging fruit? What do
• 42:26you think of this as
• 42:27the kind of most immediate
• 42:28potential to impact cancer care?
• 42:31When it comes back. What
• 42:32are you most excited about?
• 42:33I hate this question because
• 42:35each of those is one
• 42:35of my kids, and whichever
• 42:37I'm gonna say, a lot
• 42:38of others are gonna be
• 42:39upset. But,
• 42:43I do think that in
• 42:44the diagnostic space, there's a
• 42:46lot of room.
• 42:49I don't wanna sound pessimistic.
• 42:51We are behind
• 42:52we are behind the eyeball
• 42:53here.
• 42:55Most sites have already now,
• 42:58very active diagnostic sites,
• 43:00centers that are treating regularly
• 43:03hundreds of patients. That's one
• 43:04area of there's clear opportunity.
• 43:07I understand some of the
• 43:08caution of, well, you know,
• 43:09a lot of these patients
• 43:10recur, and that's right.
• 43:12But it is the
• 43:16you saw that example where,
• 43:17you know, we learned by
• 43:18by doing something, we realized,
• 43:20oh my god. There's monocytes
• 43:21being trafficked.
• 43:23You're not gonna do the
• 43:24alpha
• 43:25treatments. You're not gonna do
• 43:26the second generation
• 43:27if you don't have a
• 43:28site where you're doing a
• 43:29lot of those patients.
• 43:30So,
• 43:32it is one area clearly
• 43:33where there is
• 43:34a huge impact,
• 43:35for our patients. I understand
• 43:37for now it's only two
• 43:38cancers, not every cancer. But,
• 43:40again, if you don't have
• 43:41it for two, you're not
• 43:42gonna have it for ten.
• 43:43The other area I would
• 43:44say is the spectroscopy part
• 43:46because that is now very,
• 43:48mature.
• 43:49And, for the longest time,
• 43:50we didn't do it because
• 43:51it was too prohibitive in
• 43:52terms of imaging. If you
• 43:53need, you know, thirty minutes
• 43:54to scan in addition to
• 43:55everything you're doing in MR,
• 43:57nobody's gonna agree to it
• 43:58because spots are what they
• 44:00are. But eight minutes is
• 44:01feasible, and I think there's
• 44:02there's a role there.
• 44:04And I would say guiding
• 44:05the treatment is something that
• 44:07is very important because,
• 44:10you know, it it in
• 44:11in in no way it
• 44:12is meant to be, oh,
• 44:13well, no. You got it
• 44:15wrong. It is that a
• 44:16lot of times we don't
• 44:16see on the on the
• 44:17images
• 44:18as much as we should
• 44:19be. So I think the
• 44:21treatment guidance is one area
• 44:22that is promising.
• 44:40Good.
• 45:15That's right. So
• 45:16we do know that they
• 45:17are affected, actually,
• 45:19because, you know, if it's,
• 45:22if it's if if it's
• 45:23Farheem,
• 45:24you know,
• 45:25once it breaks down, it
• 45:27will be taken out in
• 45:28in anemia.
• 45:29But,
• 45:31but that core is not
• 45:33in the case of Fahraheem,
• 45:34that core is not broken
• 45:36for,
• 45:37over four hundred hours.
• 45:39So
• 45:41as long as we're imaging
• 45:42within the area,
• 45:44the time that we have
• 45:45validated our radio tracer,
• 45:47we are safe.
• 45:49What you can't assume and
• 45:50and to be clear, what
• 45:52you're injecting is picomolar.
• 45:54So from a physiological point
• 45:55of view, you're not gonna
• 45:56see any effect. It's just
• 45:57that your image after a
• 45:59while will not represent,
• 46:01the membrane potential or the,
• 46:04or the monocyte trafficking. It's
• 46:05just taken up,
• 46:07wherever there's iron,
• 46:08iron need. It's just over
• 46:10two hundred and fifty hours
• 46:11later. So you're that's where
• 46:13we would worry about it,
• 46:15but not in the not
• 46:16within the imaging time.
• 46:27Right. So we have there
• 46:29what we have done. And
• 46:30and for the member potential
• 46:31compound, I think I showed
• 46:32you some human studies. We
• 46:33have an IND. We've done
• 46:34first in human. We've done
• 46:35over thirty of them now.
• 46:36We have done
• 46:38the test retest in multiple
• 46:40patients on different days.
• 46:42And that's the curve I
• 46:44showed you, and I
• 46:45thank you, Harriet, for pointing
• 46:47this out. That's the curve
• 46:48I showed you where I
• 46:49said it's very constant.
• 46:52This was surprising for us
• 46:53because, you know, there is
• 46:54big variability when we do
• 46:55humans on different days.
• 46:57It is just that this
• 46:58is such a
• 46:59tightly regulated,
• 47:02physiological parameter that there was
• 47:04very little change. So we've
• 47:05we've tested that in but
• 47:07I mean, it's indirectly, obviously,
• 47:08but we've done that in
• 47:09test retest. And even when
• 47:10we did patients
• 47:12well, for now, the chronic
• 47:14is in pigs. When we
• 47:15did pigs over time, I
• 47:16showed you eight of those
• 47:17that have gone for six
• 47:18month,
• 47:19the areas that were not,
• 47:24when we did when we
• 47:25first did the
• 47:27the acute, the errors that
• 47:28were not affected on multiple
• 47:29times, that was the same.
• 47:31So that was that was
• 47:32reliable.
• 47:33The obviously, when we did
• 47:34the chronic, then the whole
• 47:35the whole heart, then myocardium
• 47:37was affected because this is
• 47:38somatic IV injection.
• 48:10Yes.
• 48:17I would say yes. So
• 48:19thank you. That's not good.
• 48:20Another nice plug in. So
• 48:22we have a Panama coming
• 48:23in.
• 48:26Let me I did mine.
• 48:28We have a Panama coming
• 48:30in
• 48:31in
• 48:33q three
• 48:34twenty twenty six
• 48:36on the so
• 48:38I know it sounds long
• 48:39from now, but I'm told,
• 48:41you know, in the old
• 48:41timelines, that's very fast.
• 48:44I've been here eleven months,
• 48:45so I've I've learned enough
• 48:47now. It's
• 48:48so this is a research
• 48:50scanner
• 48:51that we are working hard
• 48:53on
• 48:54making one day available
• 48:56for clinical work.
• 48:58The same way we have
• 48:59a seven Tesla coming in.
• 49:00We're there. We have now
• 49:02the agreement that two days
• 49:03a week will be available
• 49:04for
• 49:05clinical. I'm very keen on
• 49:07on sharing these because
• 49:10the seven Tesla would be
• 49:11two days for clinical.
• 49:13So I hope we'll be
• 49:15able to do the same
• 49:16on the Panama side
• 49:18because I'm I'm putting my
• 49:19money where my mouth is.
• 49:20I mean, what's the point
• 49:21of doing all this if
• 49:22you can't see it? The
• 49:23idea being that, you know,
• 49:24if we do one day
• 49:25a week and we see
• 49:26a huge value, like you're
• 49:27saying, well, then that would
• 49:28justify that would give us
• 49:29the argument for having more
• 49:31of those installed clinically.
• 49:33That's how we've done at
• 49:34Pest General before. We we
• 49:35started with a research one,
• 49:36and then at one point,
• 49:38surgeons refused to go in
• 49:39unless they had the PET
• 49:40and the MR. And it
• 49:41was like, okay. Well, now
• 49:42we're gonna have one clinical.
• 49:43Can I ask the question?
• 49:45Of course.
• 49:47So a a question as
• 49:48it relates to quantitative imaging
• 49:50for clinical trials.
• 49:51So I think as we're
• 49:53getting better and better resolution,
• 49:54especially with the sort of
• 49:56PET MR, we're really stuck
• 49:58as it relates to quantitative
• 50:00imaging, especially as it relates
• 50:01to even our new diagnostic
• 50:02trials where we're we have
• 50:04to use RECIST, which is
• 50:05based just on
• 50:07cross sectional imaging. Do you
• 50:08have any thoughts on sort
• 50:10of the evolution of that
• 50:11field and where we should
• 50:12be going?
• 50:14Yes. I think resist is
• 50:15a heresy in the age
• 50:17of the diagnostics because
• 50:19what you're measuring is
• 50:21if you think ejection fraction
• 50:24is too late compared to
• 50:25membrane potential for the canary
• 50:26in the mine,
• 50:28This is you know, that
• 50:29that tumor is not gonna
• 50:31shrink for months before I
• 50:32mean, this is not at
• 50:33all useful.
• 50:35What I showed in the
• 50:36case of the,
• 50:38NET and and prostate
• 50:40is a full model, a
• 50:41full dosimetry. We can do
• 50:43that now.
• 50:44The challenge is that currently,
• 50:46if we were to do
• 50:46this I mean, Larry would
• 50:48love to do this every
• 50:49day. But on his spec
• 50:50scanning, it would take him
• 50:51an hour and a half,
• 50:52an hour to do that
• 50:54full survey.
• 50:56But there are scanners available
• 50:57today that are
• 50:59full ring spec systems where
• 51:00you can do in ten
• 51:01minutes what you do in
• 51:02an hour and a half.
• 51:04And,
• 51:05we also are planning on
• 51:06installing one, and we're hoping
• 51:07that will be one also
• 51:08on the clinical side. And
• 51:10there, what you do is
• 51:11just a simple survey,
• 51:12a ten, twenty minute, but
• 51:14every time.
• 51:15And as you do that,
• 51:16then you can see your
• 51:17residency time of your tracer.
• 51:19You can quantify your effective
• 51:21dose, which is a lot
• 51:22more I mean, that's what
• 51:24people have been doing for
• 51:25ages in in I one
• 51:26thirty one when they needed
• 51:27to quantify,
• 51:29how much can you give
• 51:30somebody who's coming back after
• 51:32recurrence.
• 51:32This is
• 51:34there's nothing there. I wish
• 51:35I could say, oh, this
• 51:36is groundbreaking and very novel.
• 51:38This is standard,
• 51:40and we can do it
• 51:40tomorrow if we had,
• 51:43We just need a clinical
• 51:44trial to catch up. Correct.
• 51:45Oh, absolutely. So this is
• 51:45available well well, you know,
• 51:46well I mean, it's
• 51:49there's
• 51:50nothing
• 51:51there that is
• 51:55very novel. It is just
• 51:57that for most trials, we
• 51:58we just cut corners and
• 51:59say, yeah. Let's look at
• 52:00resist, but it's there. It's
• 52:01available. And we can do
• 52:02it. And in the past
• 52:03center, we can do that
• 52:04for any of those trials.
• 52:06Question about AI, which you
• 52:08talked a little bit about.
• 52:10In lung cancer, for example,
• 52:11there's a civil, which is
• 52:13a way of using AI
• 52:14to look at,
• 52:16low dose screening, and and
• 52:18sometimes it's more effective than
• 52:20than, our current methods. So
• 52:22and you talked a little
• 52:23bit about, you know, standardizing
• 52:25and the the inter
• 52:27you know, different
• 52:29Inter observer availability. Yes.
• 52:33I think it's gonna go.
• 52:34Is this something where AI
• 52:36is gonna help
• 52:37be more accurate, be more
• 52:38better? Is it gonna actually
• 52:41be able to replace some
• 52:42of those radiologists
• 52:44so that you can get
• 52:45to,
• 52:46you know, different places in
• 52:47rural communities?
• 52:48Where do you think AI
• 52:49is is, is gonna
• 52:52I was recently at a
• 52:53talk in surgery. Don't ask
• 52:54why, but it's surgery talk
• 52:56for a surgeon who only
• 52:58does surgery in the middle
• 52:59of this the toxic and
• 53:00here's my slide for AI
• 53:01because you have to have
• 53:02one. And I was like,
• 53:04wow.
• 53:04If surgery is now in,
• 53:06then we're good.
• 53:07I think it's not a
• 53:08question of if. It's a
• 53:09question of when. It's happening.
• 53:11It is AI is taking
• 53:12over a lot of what
• 53:13we're doing.
• 53:14The reason why you notice
• 53:15I'm very careful in what
• 53:16I'm showing
• 53:18is because we are doing
• 53:19a lot of deep learning,
• 53:20and there are
• 53:21what we call case of
• 53:22hallucination where
• 53:24every now and then you
• 53:25get a case that doesn't
• 53:26make any sense.
• 53:28And our biggest worry is
• 53:29that and this is why
• 53:31I was very careful saying
• 53:33this is an aid
• 53:34as somebody's starting to use.
• 53:37The big worry from many
• 53:39of the ethicists right now
• 53:40is that as the physician
• 53:42relies more and more on
• 53:43the on the tool, they
• 53:45become more and more different
• 53:47to the tool. And when
• 53:48sometimes they feel like, oh,
• 53:49I'm not sure, but, oh,
• 53:50but think that I'm it
• 53:52must be true. And and
• 53:54you're still liable.
• 53:55You're still responsible. So I
• 53:57would have a word of
• 53:58caution that,
• 53:59yes, it is happening, but
• 54:00I I don't see it
• 54:03as the the panacea because
• 54:06until we have such volumes
• 54:08of data, which we don't
• 54:09have today,
• 54:10that any case we're gonna
• 54:12see has been seen before.
• 54:17I'm I'm sorry. I'm not
• 54:18as enthusiastic as I was
• 54:20about everything else I talked
• 54:21about, but that's because we
• 54:22do a lot of deep
• 54:23learning in our we do
• 54:24a lot of it, and
• 54:26we see limitations.
• 54:27So because of the limited
• 54:28data we have, we don't
• 54:30have
• 54:31the data that Facebook has.
• 54:32We don't have a billion
• 54:34paths.
• 54:35I mean, we don't have
• 54:36a billion CTs, let alone
• 54:37a billion paths.
• 54:40We we probably need to
• 54:41end if others have questions,
• 54:43maybe come up afterwards, but
• 54:44we're at time that