Okay.
Okay, it's 2 minutes past so I.
Can you see my slide.
Yes. Okay. Dr. Nordstrom please go ahead.
They want a, I will let you begin. Okay, thank you. Thank you. Both on behalf of the center for medical imaging. Any probiotics.
I'm sorry, my problem is probiotics and information technology.
It's my pleasure to join the call with my colleague Dr Nordstrom from the cancer programs.
And as the site's is a, this is a slightly new approach to the webinars really closer collaboration across the 2 programs offering interesting and cutting edge topics and speakers.
Such as today's today, Michigan, Michigan community so we're looking forward to collaborating with our colleagues in the cancer program.
Thank you. Bye right and I can't think of a better person in with calen, uh, to be doing this with you and I spent.
Many years working together, so I'm looking forward to.
Continuing our relationship in this particular environment.
I guess the best thing for me to do is just to say that a.
We're looking to to bring both imaging and Informatics together.
In a stronger way, than it has been done in the past. And I think with the 2 of these people with 2 of us together, I think we'll have a good opportunity to do that.
Let me begin by introducing our speaker today and I.
Certainly hope that you all had the opportunity to read the brief resume that was put on the wiki page talk or even Rosenthal is a professor of both auto oncology and radiology at Stanford.
He currently serves as the John and and or medical director at Stanford cancer center and I could go on with a lot of other very interesting and exciting things about him. But on a personal note, I want to say that even has been a very good friend.
Of, and has been instrumental in supporting certain workshops on image, guidance surgery for us.
He's conducted bench to bedside, the development of obstacle contrast agents.
To identify cancer in the operating room and early phase, clinical trials under his leadership.
Using fluorescently labeled antibodies have demonstrated that this technique.
Can, in fact, visualize microscopic cancer in the operating room environment.
That may significantly even improved clinical outcomes. Of course.
He's a prolific rider having published well, over a 160 peer reviewed scientific articles.
He's authored many book chapters and in fact, published the book entitle optical imaging of cancer by Springer. So, without further ado, please join with me in welcoming Dr Rosenthal to today's meeting.
Even Thank you very much. Dr, Nordstrom and.
All right, Eva is a real pleasure to be here. And thank you the work that you guys do to fund.
These kind of initiatives is critical for us to be able to move forward at various academic centers.
So, I'm going to share my slides here and.
Can you please confirm that? You can see them okay.
Okay, great.
The patient mode? Yeah. Okay. Okay. I can change that.
How's that? There we go. Okay. Fantastic. So, again, thank you very much for having me. I see a lot of colleagues on the phone and.
I'm going to try to talk for about 40 minutes on. Now, what in general, I think that the field is doing in some common mistakes that we've made over the past 50 years that we've been doing it.
And then I'm going to talk about some variety of clinical trials going on in the field currently.
Uh, specifically head neck, I have some consulting relationships, which are listed here. They're not going to be what I'm going to talk about today.
And I also have, of course, some information that, regarding all of these are mostly funded.
Grants and funded these trials so, as you know.
Cancer is a surgical disease fundamentally if you look at the light shading in these circles.
With the exception of lung cancer, the vast majority of these cancer types solid tumors get surgery is part of their treatment. So improving outcomes in surgery requires us to better.
Uh, uh, evaluate cancer in the operating room. So that's sort of the, the main thing. And then if you.
The main purpose of the, the work and then if you look at.
Actual margin positivity rates.
They remain and changed for the past 20 years. You can see.
These are flat curves for, for prostate oral cavity. Lung thyroid can either all flat and so changing. This will require changing what we're doing and not doing the same thing.
So, the proposed solution is to develop a contrast agent.
That allow surgeons to detect very small fragments.
During surgery, but before we talk about what this looks like, it's important to understand the ground rules for.
Uh, flourescence imaging. Okay. And this is just my opinion, but these are 4 lessons that I've learned over the last.
Many years, and the 1st is, is that the surface margin?
That is the mucosal margin or a skin margin is not usually the.
Can you see my pointer here?
So, if you, if you look at panel a, that is the surface area, usually surgeons can palpate that and can identify the lesion.
However, it's the biggest area of concern is the deep area because that's the majority of the in other words, the.
95% of the area that is likely to be missed.
Is that deep surface, which can be seen in the lower right hand? Panel?
Demonstrating the large piece of muscles, so it's the deep surface. That is the problem when evaluating these agents, not the surface area.
And this was actually shown in a very recent trial where.
Catherine Poe and Canada has done a lot of really great work showing that auto fluorescence.
Can map the surface of tumors.
And she 1st, published this in clinical cancer research in 2006, demonstrating a really nice.
Margin can be identified with auto flourescence.
Or follow up study from a large clinical trial conducted in Canada.
Found that there was no difference when mapping the surface lesion.
In the overall survival of these patients does that mean that fuller essence is not a valuable tool or that auto fluorescence is not a valuable tool. I don't.
I don't know, but I imagine that the problem is not.
The surface lesion the problem is the deep part, which.
Article lessons does not assess. So this is really clear evidence that the focus should be.
If you want to find a difference in outcome, it should be on the.
The 2nd concept.
In evaluation and is that positive margin?
Is a variable it is, it is a linear variable and not that common spirit.
And that's not always true for every cancer type, but it's important to think about.
In the bottom panels, you can see a negative margin and head and neck. Cancer is actually 5 millimeters.
A normal tissue away from the tumor.
If you a close margin is 1 to 5.
And a cut through margin is what some people call a positive margin, but it's actually leaving tissue behind.
And you can last audio.
Yes, we did.
I sent Dr Rosenthal it is. There we go here is.
I'm sorry guys. Good. Did you hear back? I was sorry about that. I didn't know. I went off. I was just talking away.
Can you hear me? Yeah, we got we got you your cut through margin.
Okay, you got the country margins, so that's the.
That's essentially the.
And I just and then I just use an example of that in breast cancer. It's 1 millimeter.
And is actually checking the cavity.
Which is a very effective way to allow surgeons to identify the positive margin, residual tumor. So, the point is, is that some tumor to every tumor talk to is different.
Every tumor type is different, and there's different definitions of a positive margin.
And different definitions of what surrounding tissue is.
Finally, number 4 fuller essence is always relative.
There is no absolute. For essence.
A positive fluorescent signal simply means greater than something adjacent. So it's not that you can set a difference between patients. You can only set it within patients.
And here, you can see that if patient 1 has high flourescence, medium, fluorescence and low fluorescence.
You can only evaluate that relative scale within the same patient, but you cannot judge 1 patient to the other.
And I'll show you a really great example of that coming up. So, summary of the talk is workflow of our clinical trial.
How to leverage fluorescence in surgery some of the key ways to do that.
You're doing it evaluation of lymph nodes and then other technology and clinical trials in head and neck.
Our approach was labeling an antibody.
Which is already approved and has now and toxicity profile.
As a result, the labeling is a minimum change, we infuse it. Systemically. And then take the patient to the operating room 1 to 3 days later.
Our workflow as 2 separate settings.
The 1st setting is the inter operative setting where reuse the camera.
As Dennis in the photo with the surge and evaluating the screen.
As the wound is image, that's the inter operative. 1st.
The specimen mapping or vivo portion.
Is performed in a separate device that is on loan from, like, or.
That allows us to map the device in in multiple dimensions.
So, what everybody knows that fuller essence, the penetration of light depends on the wavelength.
800 nanometers goes farther than blue light. That's why we chose near and correct.
But there's also a limit to the extent to which.
The will travel, it simply will not travel through more than 5 or 6 millimeters.
And as a result, you can't see fluorescence if it's too deep, just like, you can't see a laser point, or on your finger, but you can see it on. Excuse me? You can see it on your finger, but not on your palm.
So, what that means is, is that if the if the tumor is far enough away.
From the cut surface, you won't see it.
But you will see hotspots associated with tumor. You can see that. There's an area in the center of high fluorescence, meaning red.
That does not me.
That the tumor is present at the margin. It simply means that that's the closest place.
Here you can see that if we took that same specimen and measured the histology.
The closest area is actually.
That 1 area that has the highest for us and so again, everything is relative.
It's relative within the specimen, we can't compare it. We can't say that anything is positive or negative. We can simply say that relative to other tissue in this specimen. That's the hottest spot. That's most likely to be positive.
So, what that means when you're doing surgery is, is that as you're removing this specimen, you look at the under surface.
And you might see flourescence, which means that it's closer than 5 millimeters or you might actually have a residual margin. And I'm going to show you examples of each of these.
Here's an example of a patient who's having a Congress section.
This is the deep surface of the tongue it's being reflected back.
This is the cut edge of the mandible and you can see that. This is the same sample with different for us and settings. And you can see that. There's a hotspot.
If the surgeon marks with a, um.
With a needle in order to demonstrate that we don't know if that's positive or not but we can we think that that and we've shown that that will be the closest.
So, if that margin is negative, the chances are all the margins will be.
So that's why we're calling it a sentinel margin and you can identify that.
With fluorescence, it's not quantitative. It's simply qualitative.
Here's an example where the margin is negative.
Here's a tumor in the in the panel on your left, you can see a a tumor.
We've cut down the deep surface of it and we're, we're reflecting it.
Laterally and you can see the under surface is negative.
And that's demonstrated that the tumor is 5 millimeters or more away from the cut surface, such that you don't see fluorescence.
So, that implies that you are clear so that's a confirm deep margins or negative during the surgery.
Here's an example of a patient with a speculated highly invasive neck node that is invading the deep neck musculature.
And this is an example where tumor was left residual within that area.
And you can see this in the following pictures here is the white light image in the upper left.
You can see the internal jugular vein. The nerve crossing over is the 11st nerve and you can see this.
For us an area that's adjacent that is deep and and base it.
Doing the lessons we can measure of both the gross disease, and also you can see here a very small area in a lower right. Hand panel. It's very clear fluorescent that turned out to be positive.
And again, it's all relative because the tissue to the right and the lower right hand panel is it doesn't mean that that's positive. It means that that's closer to the image.
The surgeon uses their ability to to understand tissue using all of the inputs not just the fluorescence.
So that's intro operative surgery. Now we're going to talk about specimen mapping.
And that's been mapping is when you evaluate, this is what we do as surgeons to map out the margins.
And this is the mucosal margin, but again, the most important margin is actually the deep March.
So, how we do that is using a device on loan to us and develop, like, or.
We developed a a.
A mapping device that allows us to map the deep.
Peripheral inside surfaces of the lesion, and we simply have this in the, or we put it in.
And it allows us to more quantitatively and map the tumor. It's a more it's a device that's more fixed and we're able to better study the information.
So, how do we use this information? You can see that.
If we do a cross sectional analysis of the specimen.
We can see areas of rightful for us and correlate that directly to for us in positive. And the difference between.
Ah, the tumor and the cut surface in E already and panel of the left side.
And then if we map that we can see that fluorescent positive.
Is almost always less than 5 millimeters distance from the cut surface whereas for us is negative.
Is almost always greater, so, in this setting and head neck cancer, you can use this.
Approach in order to separate out potentially positive.
Central margins from clearly negative margins, which can save time in the operating room and help direct.
In real time decision making, and if you want to get very kind of technical about how you can do this.
We're, we're using a device, you can generate peaks from the deep surface.
The most intense is the 1st intensity peek on the right hand graph.
It is always the closest margin you can see it's always the closest margin. It doesn't mean that.
It's a certain distance, but it's always the closest margin. The 2nd.
In the middle is always the next closest and so on.
What that means is, is that if you're negative at the 1st intensity, you don't have to do any more frozen. Your margin is going to be 20.
And we showed this in this paper and a couple others.
So that's specimen mapping that's inter, operative removal and how surgeons I think.
Can use this technology in the operating room for head neck and I think it has applications for other tumor types as well.
But let's talk about lymph nodes so we believe that the floor essence imaging agent goes into the tumor and then goes to the central.
So suppose that you wanted to do central node map and what that is is today.
A fluorescent and a technician agent are both used in order to identify.
The sentinel, the gamma counter, and flourescence imaging are used in the operating room and it's a common technique that's done in every operating room every day around.
The limitation of it is that you have to be able to inject the tumor directly.
With a, with a needle, so that's why we only do it in breast melanoma and padded knack.
Because you have to be able to reach you with a needle, but suppose that.
You could use a fluorescent plus a radio nucleotide agent and inject that and perform the same.
Same study, so that's kind of a very critical part of being able to detect.
Sentinel and positive notes.
So, essentially what we don't know is whether or not.
It goes to the systemic agent goes directly to the lymph node where it's positive.
Or it goes to the primary tumor and then drains non specifically to the central. No, we don't actually know, but we think it's both.
Here's an example of what a knack looks like after systemic injection of the fluorescent agent you can see here is the neck.
And it looks like a bunch of meat, but when you get the fluorescence imaging, you can see that the lymph nodes stand out.
Now, as you know, if you take all those lymph nodes out.
They all are going to flourish, depending on the threshold that you sat.
But what we can specifically show is that the positive nodes demonstrated by the red.
Are always going to be the highest fluorescent for that patient.
It's not necessarily going to be the highest for.
Uh, flourescence across the cohorts.
The different patient, but it's always the most positive. So, what we found is, is that.
If you take the top 3, lymph nodes.
The top 3 for us and lymph nodes of any of these patients.
You're going to be able to completely stage the patient because it almost always goes in.
1st, to the positive note into the central.
And you can see all flourescence is relative. Remember. So, it, the, the.
The benign lymph node, it's always less for us in the same patient. The positive.
And that's true across the board so it's not an absolute fluorescence. It's relative to a negative note.
So, that's obviously obviously challenging, but, you know, the majority of lymph nodes are always going to be negative. So there is, you can sort of map the floor essence, intensity and lymph nodes and then identify that 1. that's the most.
We actually did this study and you comparing it directly to to direct injection.
Okay, so the 1st, a, is an example of a patient that got injected technician.
And then they got the injected systemic antibiotic.
The central node was benign.
The sentinel node was benign. The central node was benign.
And we found an additional fluorescent central node that was benign, using the systemic techniques.
But even more interesting, and we've only done 2 cases like this.
The non sentinel load in other words, not identified by spec.
Was actually positive, and the sentinel node as identified by SPECT was actually a negative.
So that is this technique may even be better.
Then the conventional map, it.
And there were 2, actually, 2 central nodes.
Identified by the floors and techniques, so.
So, this, this implies that it goes to positive and Central notes, and we've got more data on that, which is available on the paper. I just shared before in nature communications.
All right, so I, I wanted to sort of talk a little bit about some of the other technologies that are out there and this is Justin head and neck and obviously the field is expanding broadly, but.
I'm not going to show images for a couple of these, but it's worth mentioning that alone.
Is a company that is started by just looking at nerve imaging and specifically have a.
For us and peptide that is being systemically injected and used to image. We're doing the Stamper. We're doing the trial at Stanford.
Other folks are doing the trial as well and that's a very exciting trial. I think there will be many more of these nerve agents.
Uh, coming on board, I don't have any relationship, you know, any personal financial relationship with any of these companies.
Nano is a also in phase 2 trials. Very exciting agent.
Max, which is is using syntax map, which we've used in the past 2, and they've shown really good data with that. We obviously are using it to map.
And then there are other techniques that all or other agents that I'd like to mention.
So 1 is, is the pH, sensitive the advantage of this is that.
It has these myself that essentially will release.
A quenched floor for upon entering a pH environment that's very, very to a specific pH.
The advantage of this is that you could essentially.
To the pH, to any to many different tumor types, and it can be used in a pan tumor type approach.
Which is which has real advantages to other more targeted approaches.
They have shown that it to be very effective and using this pH approach approach they've shown it.
In multiple tumor types here is an example of head and neck cancer where they did a dose escalation study and they found really nice of around 3 and you can see the imaging and the near infrared range is very
small.
So this is an example of going into phase 2 trials aka Nano is a company out of southwestern,
and an agent created by Ron simmer and Jimmy gal who are really leaders in the field of developing sensitive probes.
The other really interesting agent is, um.
Is a small molecule inhibitor very different than a period sensitive and this is basically.
This a small molecule that is linked to a, to a fluorescent agent.
And it's, it's, it's an anti cancer agent that binds intracellular.
Uh, and therefore is picked up by.
Cancer and they have it a couple different ways of using it right now they have a.
A topical study where they're looking at the mucosal surface, or for a screening.
So here's an example of a patient who has a suspected lesion.
They washed with the agent and then they rinse with the agent.
And then they're able to see the lesion because it binds specifically to those tumor types, but not to normally themselves. So they're interested in using it.
For detection of these or monitoring benign disease and this is.
How Patel and Tom Weiner who are at and really some, some really great work on this.
And it also allows you to do this high high, magnification confocal imaging insight to.
Of the tumor and be able to map this, and they have a phase 1 and are advancing into phase 2, which is actually the roles closed looking at the African see this as the sensitivity and specificity compared to.
So, I think we'll hear a lot more of this aging as well.
Finally, there's a different a completely different non.
A contrast agent dependent, or which is, which has actually been used for many years in dermatology offices and evaluating it for other lesions as well.
And this looks at sort of an insight to histology group miles at Mt. Sinai is doing this.
And you can see that as you as you move the floor essence across the specimen that has ultrasound,
John,
it you can see very clearly that,
that there is changes in histology that can be used.
Sense that this is more there's more interpretation required sometimes, but all of these require a level of.
Interpretation and and understanding.
I do want to mention so we have I've focused very much on head and neck. Cancer head and neck. Cancer is a.
A focus of mind, but we've also conducted trials and long headed neck, skin, brain and pancreas tumors. I'm going to show the pancreas and brain tumors here.
Just to give you an idea that the application is broader, although the definition of a positive margin may be different.
So, here we're looking at data that was generated by twins out and.
In my lab that shows specifically that, um.
Neurosurgeon that we work with currently is able to map these tumors and remove it as we go. So you can see.
That, um, the low dose.
In the high dose, both have good fluorescence.
But the high dose is better. So we've chosen to go with the high. Does.
And along the bottom here, you can see the comparison with 5 L. A.
Which is sort of a little bit the gold standard and that's an L, the blue 400 imaging.
You can see that. There is very high level of specificity within the cavity and at the perimeter.
Associated with the the urine for 800 agent.
Here in the far right hand panel M, as compared to the blue in 400 part of that is simply because the specificity the agent is so much higher.
Pancreas also presents a real challenge not just also for lymph nodes, and also for the primary tumor.
We have shown that parent Neal match very small parent. Neal mats can be identified and very.
And positive lymph nodes can be identified as demonstrated in the lower set of panels. Golan. Lou did this work and it's published in in the Lancet gastroenterology Journal, and we showed an a dose escalating cohort that.
Uh, 50 to 75 milligrams was appropriate agent and this was able to detect primary tumors as well as policy margins. And again, each margin is different in how it's used in each surgery is not the same in each clinical trial devised for.
A specific tumor type, I will need to be changed according to.
Basically work like this is done from a huge team. Obviously the.
Uh, the, the, the laboratory folks who include bill on Lou.
Nick, Marissa Stan, a lot of the work with from stamp, and it's in the Netherlands now, doing a residency.
And, of course, my colleagues in in at Stanford who perform many of these surgeries with me.
And probably 1 of the key elements is having a medical oncologist that's willing to infuse these patients and monitor them. And Dimitri believe this has been.
An outstanding collaborator, so, and the work was done at Stanford as well as where I was prior and I want to thank you very much for your.
Time and attention. Wonderful Thank you. Very much. Even.
Do we have any, any questions.
While they're waiting to come up with a, with a question or 2 uh, let me ask you.
What exactly is the current status of FDA approval on some of these agents.
Where do we what do we stand on that? Well, I think everybody's racing to get there.
I think that the.
You know what, the, as, as you mentioned, there is a number of.
Guidance that we receive from the about.
The specific need to have to show clinical benefits specifically that margins are going to that. It's going to change what surgeons do.
Huh.
But, yeah, if everybody has a slightly different, you know, different.
Approach, but essentially, I would bet you that in a couple of years, there's going to be an agent to approve.
Do you feel that the field is being held back because of that? Or do you think things are moving forward at a steady page? Anyway?
I think the biggest issue, I don't think I think the has been really great about mutually educating us about how to design the trials and us educating them about these agents and surgery and.
They kind of get stalled nature of surgery or or.
Kind of interpretation that surgeons with all information, not just anything for us and we're just going to cut out.
But I think that education process is actually work as well. I think the biggest the biggest challenge is that.
Problem with diagnostics, not having the same reimbursement is therapeutic.
Huh.
Any anything else from the audience.
Yeah, 1st of all. Thank you. Wonderful talk. I'm Dr Ralph Costa I met the principal Margaret cancer center in Toronto, Canada. Our land has a much like many of the colleagues on this call.
I've been looking at margin assessment using flourescence technologies.
We've been working with the FDA quite intimately 1 of the things.
And this is my question 1 of the things the team has asked us to do towards a phase 3 randomized control trial is to pay much closer attention to. And I think you mentioned this in your previous comment.
Uh, pay much closer attention to false positives and false negatives. In other words.
You know, what does a search and do if they see something fluorescent.
Uh, and there really isn't disease there and usually, for example, in the brain.
I don't think we may have lost Eva. Maybe my question was too long.
Shall we wait to reestablish the connection? I think so.
Back yeah, I'm sorry about that. I'm sorry. Dr cost. I, I just didn't hear the last part of that. I heard that you were working and you're.
Have a specific question about trial design. Well, in particular the, a, and I'll be great. The FDA does work.
I think you're right, it does want these technologies to get approved if there's value and if they're safe, what would you say in terms of the focus more recently?
In the last I would say, maybe last 3 to 4 years.
With groups, like sciences, et cetera.
On the idea of false positives and false negatives.
Uh, you know, if you see something fluorescent that there's maybe no disease there.
How do you, um, how does that reconcile with the standard of care and the, and the thought process the decision making process interoperatively when we have patients who could benefit from this technology. So.
Uh, what's your experience in terms of the requirement for demonstrating clinical safety?
And utility yeah, so that's a really good question. I.
You know, I think the main question is is how can you manage.
False positive and in general,
when evaluating this technology,
the biggest fear is false negatives rather than false positives because so so I would say that when we design our studies or evaluate the different agents of different settings,
we would always.
Err on the side of of not having false negative knowing that today uh, we, we are unable to.
Really see cancer on the deep surface, particularly at all. And the best we can do is palpation, which is, which is our best.
So, I think trying to go back to the standard of care that we have today, would would be the most effective way to argue that.
Yes, we have false positives but what is our standard? And can we compare for that?
And design, that's easy to say, but I know the trial itself is more complicated and can be somewhat surgeon institution specific. Yes. Thank you. I understand that.
Yes, please I have a question.
Okay, thank you very much for a great of different imaging work and for an update on logical imaging from margins.
Uh, I work at Memorial with Dr Patel and on imaging and vocal imaging. I hope I represented your work. Well, thank you very much. Thank you very much.
And so the question I have given that you've been doing a lot of work with microscopy and demography, and then the ultrasound goes deeper.
What was the use of ultrasound imaging for deep margins and you see a role where 1 might combine optical imaging with ultrasound.
Or have been done already. Yeah. So so, 2 things 1 is, I do think ultrasound has been used to measure depth.
Both the depth of the tumor as well as the,
the distance between the tumor and the normal and Mark virus has done a lot of really good work on that that you can do interoperatively without a contract at all in terms of your mapping on the mucosal surface yes,
that that works.
I, I think Catherine posed paper showed I don't know whether or not I don't know if you were there for the beginning of the talk.
Whether or not mucosal surface mapping, provides the surge in that extra information that died faster was bringing up.
Or whether or not, it's simply going to be no difference and that's obviously a large trial. We want to avoid that. And because the more failures they're on it just the less interest there are.
So your question about ultrasound using contrast agents I do think that.
Photo acoustics, although kind of early and the technology today.
Is sub optimal we've published a paper on it. We've been using the visual Sonics device. I think it's gonna work really well, it's the technology developed, but I think so that's where you could you could manage the.
Margin using opt to acoustic agents.
Where you would get some penetration and you'd be able to use ultrasound and that would provide.
Additional information that article on.
So, that knowledge matures I think it'd be a great up.
Get a great option. Great. Good to hear. Thank you.
Yes, yes, we had we have 1 question in the chat and James who unfortunately didn't give his last name, had a question and.
Doctor pharaoh.
What already want to take them and maybe the check question. 1st and I can read it.
Okay, so, for the lymph node imaging with systemic administration of imaging agents.
How many lymph nodes to you reject to determine? Positivity how long does it take? And do you determine positivity?
Sequentially and I hope I read this correctly. Yeah so.
So, I think if if if we are going to use.
Imaging to identify lymph nodes to do it in the same way that we do with a current standard of care, which is we do not rely on optical imaging alone.
We rely on the combination of the radio label agent plus.
The the sign in green, so that means that if we are going to successfully identify with and how to resect, to determine positivity, we're going to need to use.
And assess in the in a trial.
The use of a label so that it can work with the current operating room equipment.
As well, as a fluorescent label, just like we do today in the operating room for no mapping and to answer your question specifically.
How many lymph nodes do you resect if we had the gamma counter in addition to the lessons we could remove that sort of the top 3 or 4 hot nodes,
which we show should stage the cancer effectively and then if those are positive and the end 0T neck that is the neck that does not have known disease based on conventional imaging.
We can go back and resect the rest of the notes. So how long would it take? It would take the same it would be conducted. Exactly. Like.
A conventional central node, you would have the gamma counter and you would make a small incision.
In order to assess it. So that's that's, you know, that's really the hope is, is, is that you can.
Go through the same process as the direct injection.
It's just that it's a systemic injection with both the fluorescent in the radio label so that you are able to map nodes in any tumor type, whether it's pancreas or long.
Or or any of those, not just those that are amendable to injection, like melanoma and.
Does that answer your question? I guess.
Yeah, hi, Evan. Good to see you.
Nice to hear the talk and all the updates. I had.
one point i wanted you to explain but just following this lymph node data .
Isn't it, do you think there's a possibility of.
Of doing an injection of a dye for a seminal lymph nodes.
But also looking for your own agency, that's targeted to the cancer. In other words, sort of, right away knowing if the setting a lymph node has.
flourescence from the cancer and it could you do a 2 level imaging there?
I don't think so and it's a great idea actually but the main problem is that you're.
Systemic injection needs to be performed the day before or 2 days before surgery.
So, you wouldn't have that feedback, but we did do the study where we injected the dye.
And the re, you know, systemically and the radio label, we injected.
The day of and we could map and show that our method was actually more specific for identifying positive nodes.
Come here the conventional method? Yeah. That's really cool. The question that I wanted to ask I put my hand up for.
In the very beginning you talked about making sure.
You know, if, if your brightest section at a clear margin.
Then all your other margins would be clear too and my concern with that is.
Is your brightest coin since it's subjective in the way that it's being done?
Can really has to be understood.
In terms of where the imaging camera is located.
Towards that so, have you been able to take that into account? Do you do a lot of different areas to make sure that how does that work.
Physically, and that's a really great question. So, there are 2. there are 2 ways. We're getting that data 1 way.
Is during the surgery, when I showed the reflected tissue looking at it, that is completely susceptible to that to the distance. The angle.
And all of that, and that's but that's real time information, which it has real value, but it is very hard to measure that. And I completely agree that that.
And that is the underlying problem with that, you know, interrupt true. Inter, operative in vivo imaging is that it is so.
Pattern recognition subjective. The data I showed on the clinical cancer research paper.
Was done in the device in the small animal imager converted to specimen imager that that I've been working with with, like, or.
And that device is pretty solid, like, right. So, um, so so that device has fixed distance very, very high resolution.
and when we look back at our specimens very consistently do we see that pattern of first second third .
So, I cannot speak to the which provides good information, but not.
The same kind of scientific information, and then more by virtue of the number of cases we've done, we can.
You know, feel very comfortable that the peak mapping in that device is very effective.
Is that their core 3 D imager the prototype? Or are you using an odyssey?
We're using a 3 D, but you can use an odyssey too. They're very equivalent.
Okay, thanks, man. I just been a pearl, but but but the small not not the scanner.
Right now, for a couple more.
Yes, good. Good.
Hi, I'm Horner from myself. Uh, I don't have a question. I, I just have a comment, uh, going back to what Eva was saying about MTA.
So, we've been working with FDA for quite some time now, obviously, on on the signing all our clinical trials, and the clinical development of, of, of the of our combination product. We have the drug. We have the device.
We have both and 1 thing that I want to say is that they draw these time while they sign that we've worked with FDA there more than willing to work with you on the sign in your study.
Uh, and I think i2nd what Evan said is, it's mutually a learning process. They learn from us, we learn from them. And and what I wanna say is that they, they're, they're open for.
For these conversations,
and and discussing the the right endpoints for that specific clinical trial,
what you really want to try and,
and,
you know,
a good sensitivity and specificity for or an acceptable sensitivity specificity for brain,
for example,
might not be acceptable for purpose or otherwise,
you know,
I mean,
impressed you may accept some,
a bigger number of false positive because,
you know,
you have there's a,
you can spare some of that tissue.
We last effect and say taking normal brain tissue.
So, I think you, when you approach as yeah, you have to think about.
What the application is what what the,
what the risks are for the patients when you have a false positive or false negative,
and having these questions with the FDA and they're more than willing more than willing to to have these conversations with you and and work out something that it's a 3 civil that you can,
that you don't have to power your study for 10000 patients that are open for that.
So I just wanted to share some our experience and I think I can approach it. Mta just, uh, uh, just be open and tell, you know, see, this is these are the challenges they need to understand what your challenges are. So they can give you feedback.
And that's what we've done. We've spent quite a bit of time telling them talking about our challenges. So I just wanted to share that with the team. And cause I know a lot of you are going through these we do have to share your challenges that they will listen. And that will really try to help you.
Thank you I appreciate that. I have a quick question. Yeah, I got a shopper send proposal and I'm a scientist. Are they doing research and clinical research?
Great talk but the question that they have in terms of sensitivity.
How sensitive do you need to be? I mean, I'm not a physician. I know. I mean, even if you leave 100 behind.
That can cause that occurrence. I mean, can you.
Ever get that you really need to get that kind of sensitivity.
Well, I think, I mean, it's a scale you can you can scale yourself to 100%.
Sensitivity and then your specificity will drop.
As a result and so that's a number.
You know, and we showed a couple of curves, you know, to kind of demonstrate that. So I think that the principle of.
Using it last to specifically identify cancer and is part of it, but it's also.
devin's showing you an area to tests to be suspicious. For. In other words, you're not trying to say everything that's fluorescent is cancer.
But that there's a, I should look at this area more carefully. I can send it for frozen. There's 6 different ways to.
Evaluate that usually the surgeon has other information for brain. For example, they can review it on the, they can compare the floor essence.
But in general, the sensitive we get, we get pretty good sensitivity. We get a sensitivity of about 90 high ninety's to 100, but we, but our specificity.
Will be in the AIDS, so we're going to miss.
You know, we're going to take some additional tissues, so we don't miss cancer.
I think is the idea, but I think the point made every tumor type is different.
Is it's really important brain you're never going to get a complete resection.
So so managing that, I did.
At the end of the day, of course, you are concerned about a false negative.
I mean, it's the best way to test. It is do a randomized trial showing that.
The image guide is actually gives us better outcome. Is that not the real.
Elephant in the room, if you wish the said that you need to.
You know, that, that the, that the trial design needs to show benefit.
And benefit does not need to be survival benefit can be, uh.
Demonstrating pot close margins are positive margins, because that's a known entity. That correlates with survival. So, in brain that's maximal. Reception is associated with improved survival, over partial, partial section.
So if you can demonstrate that you after, you do your standard care. You add the for essence. And you remove more tumor, positive areas, then you have a brain it's easier to do survival because of the dismal outcome.
But you still can do positive margins because it's known to correlate and most cancers with.
Hello Dr Costa has 1 more follow up question and then I think we should move on to the other. I have a question.
Okay,
Eva,
it's Ralph here in Toronto,
uh,
just a quick question,
because,
you know,
obviously all of the folks on this call,
including your own excellent work are looking at using optical technologies whether it's or photo acoustics or infrared.
Or a, for that matter, what are your thoughts or your observations in terms of what you're hearing from your.
Uh, from from the surgeons who actually are going to hopefully use these technologies to improve above and beyond standard care, as it relates to image interpretation how important do you think is image of interpretation?
Because obviously.
You know, rigorous training on how to interpret these often unfamiliar types of imaging.
It's very important. Have you been thinking about this? And if so to what degree? That's a great question because when we went into this, the initial few patients, we did.
We thought it was gonna be such a flash, because it was going to be used 1 way, but that was all wrong. And, and I've been doing cancer surgery, my whole life. So it's it's not what I thought. It's completely different.
So, what I, what I gave you today was my interpretation for head neck cancer.
For 10 years of doing clinical trials and so, and a lot of that has been a result of working with my colleagues in my laboratory to talk about how it should be used.
And in particular with lymph nodes, so.
I totally think that for each tumor type, you've got to work with the and figure out what the floor essence is telling you and and how to design the trial in a way that it'll be effective. But.
How you think it's going to be used is not necessarily how it's going to be used,
which I've had the pleasure to do because I was using an age grants and an academic setting,
and not under the gun of of industrial funding,
which creates a lot of Hanks,
so so,
I mean,
I think it's a real process and finding for different tumor types of different agents how it's best to use.
It's really important. I think your point of working with the surgeons is really important and I did put in there, check my email. I'm happy to answer additional questions by email if those come up.
Thank you you said, you had another question.
Yes, but I like evan's comment. I'm not sure if I should email him that but let me just ask, uh, thank you have. And this was great presentation.
I'm going to ask an imaging and Informatics related question.
Are the image archived.
And do you see value in making those as well as Pre and post op images publicly available for, you know, to.
Encourage machine learning or other types of research in, in this area.
But I think to the point that was made earlier about the inter, operative images, the relative value of those is really, really challenging in other words, the angle, all those things.
But I do think that standard images obtain from, like, the, like, word devices or any, any small animal imaging device will give the standard that you're able to do that. So, yes, for those images less.
So, for the the real time images that are challenging to kind of understand, and of course, pathology would be really important to correlate with that as well. But, yeah, that's a great idea.
And I think you're probably the best person to do it.
So, sorry, I've just got 1 last question. I believe it to a Canadian to go over time. That's why I personally just I'm thrilled to be part of this conversation and it was just a terrific talking to them.
Thank you so much for going into such detail. Is there an opportunity through that? We can all start talking about how to.
You know, we can to the extent possible as a community.
Engage a little bit more to share experiences to figure out what what we've learned. Even you spent the last decade.
In the, or with these technologies, we've got an equally like like the program in Toronto.
I'm just wondering, is there such an opportunity early or somebody who had those NCI workshops and was was instrumental in those with the FDA and 1 with CMS and.
So, I think I organized the last few and then, I mean, I just got, it's a lot to do, but I'd be happy to participate in 1 of those and.
If if Dr Nordstrom or or other folks, the NCI Vance athletes, and it becomes a.
A, very stable non suspect environment to to do so yeah, that's interesting.
i agree with that workshops are the first first thought but if we want to come up with something that's a little more regular we'll have to put our thoughts to that and see what it would come up with .
Excellent Thank you.
Thank you everybody very much is wonderful to be able to share my work and I appreciate everybody who gave me slides to allow me to present their work.
Well, I think so do you.
Thank you very much.
Haven't I say, I really, really.
We're not quite done yet for those who are interested. Dr John is going to give a brief update on the cancer imaging archive. And this will be followed by a brief update on the imaging data comments.
And I hope this is of interest to you John. If you want to take it away from here, please.
Thank you, Willie and yes, this will just be 5 or 10 minutes. Very brief.
We do this regularly on this call and that is to provide an update on the latest news and data sets available on the cancer imaging archive, cave on question.
Just a 2nd, the last 1 question question on this call was a really nice segue in terms of data sharing. My name's John. Simon I'm the Frederick National Lab lead on helping the cancer imaging program on Informatics, and our.
Flagship activity is a cancer imaging archive and so what we did regularly on this call is provide a 5 minute update, but I wanted to start with just a quick.
A quick introduction to cancer imaging for those who aren't familiar with it. It'll just take a couple of minutes.
So, cancer and archive cancer imaging archive dot net is a website, but primarily is a service to help sharing of data to promote reproducibility and validation of research.
So, this is a place where we provide a, an interface that anyone in the public can access data. That's been generated through research programs, or an age programs.
The primary focuses on providing the application and submissions support because we saw that as a major barrier to sharing of data and group science. So that's fully provided. And I want to encourage anyone on the call to.
To propose a contribution of data, if you like, it's very simple process. We meet once a month to prioritize new collections that come on for.
For sharing,
we also provide data object,
identifiers and data citation support,
because we want to see data shared as much as literature is shared and provide the same kind of credits to researchers provide data that they get from sharing analysis results.
The data comes in from large age projects. The cancer genome Atlas was 1 of the main.
The primary 1st, very large collection of imaging data we worked and proteomics data.
Collections we also support.
The sharing of national clinical trials, network imaging data, but we also importantly get data from community proposals either their data generated by grants or just data that's being using in large challenges or data that needs to be shared.
So that publication can be.
Accepted by a major journal and oftentimes now there are insisting that the, the baseline data for analysis and publications are.
Shared as a result over the last.
Decade or so we have now over 130 collections that are all very highly curated and focused on particular.
Research questions, but they could be used in any way that researchers secret to use them.
Researchers are sharing there and then also results making this data set, much richer. The data has wide covers wide variety of cancers and phantoms, including head and neck.
We're leading the way, and trying to come up with new ways of dictation, head and neck images. This is becoming more and more a priority, but we providing that support because we know that's a challenge there and the data sharing, that type of data.
But we also link it to lots of different data types so it's not just imaging or Histopathology imaging. Also we link out to the.
Linked demographics, clinical genomics, proteomics and other types of data.
It's got multiple features. There's a lot of fun to go in and browse different types of collections.
You can search and all sorts of different dotcom tags and other types of metadata and you visualize either the radiology or the Histopathology images and,
as I mentioned,
link out to all sorts of other resources that are related to those carts that we host.
And then this has really been a model that.
Paid a lot of great benefits, I think, to the research community there's been over a 100.
Publications sorry i1000 publications.
Generated based on data that's been shared to so we're really hoping that this will continue to.
To simulate research once again, the data is all.
Almost all of it is completely available. You don't even need to put in to.
Uh, to provide a research objective, so.
Please, if any of you all would like to access the data, or certainly share your data sets, please get in touch with us. There's cancer imaging archive, dot net.
And this data will also ultimately be shared on the imaging data comments, which I think we will discuss for cloud based analysis. So.
That's my quick introduction to cancer imaging. Our guide for the latest developments of the month. We just wanted to call everyone's attention that we've been very active in sort of redirecting some of the resources of.
Cancer imaging to the covert 19 imaging over this pass.
Well, I guess almost 12 months now, since the.
Of a virus became a major issue and so that you could find now on that.
For large collections.
Of imaging and their linked in some cases to the genetics and other, which.
Just this month, though, we were collaborating with the new metric, medical imaging and data risk per center.
Project, which is a collaboration between university, Chicago, Chicago, and others. We have 2 new data sets now that they've provided that also be showing up on their repository when it's ready.
Um, you can find these data sets on the cancer imaging archive.
I will.
Share we have a covered 19 section. We have 4 data sets 1, a rural data set from Arkansas, the data set of 600 cases from.
From the clinical center, and that is ultimately.
Source from China and then these other.
Metric related data sets and we have 1 more large data sets.
Coming out on shortly.
From the New York area, another announcement we are going to make was we have a new.
Collection TCI collaborates with the, the integrated canine data Commons, which is another note on the cancer research. You had comments at NCR.
Uh, supports, so this is 9 data.
Imaging this this particular data set was a glioma.
0, 1 study, you can access the imaging Stripe from tca and you can get the related.
On the cancer on the the canine data comments, and here's the screen of the integrated candidate cancer data Commons and.
You can just go in there and find the data for this glioma study.
Which is linked directly to the, the imaging data on. We're very careful to make sure that the, the identifiers for each case are are mapped appropriately. Another announcement was that we wanted to share that.
In terms of advancing the science of the identification of imaging of clinical imaging, the TCM and effort this year to provide a pseudo com data collection, which they're sharing.
To the community to advance the science of getting rid of the potential Chi and clinical imaging without removing the research value of that data set. So that's available.
We also work closely with the clinical proteomics tumor analysis consortium and as that project releases.
Discovery data sets with very, very rich.
Proteomics and genomic information for each 1 of those tissue samples we also share the Histopathology imaging.
For each of those, and we also shared the scans, we independently work with the sites.
Radiology departments and collect the the.
Either.
Scans for those patients as well. We just released recently released the.
Be set for the pancreatic customer.
Uh, data set that they've just released there are some new software features on now you can do some things more efficiently.
Um, and and in addition getting a full inventory of.
The data set, when you download, I said you'll get a full detailed inventory of.
Of that data that you downloaded that you can use.
And then there's just a number of other items where we've seen people in the community using.
Using the data that's on this all this information is released every month in a newsletter and I'll ask Michelle technology to please put her.
Email in the chat, if you're not receiving this newsletter and you'd like to please just.
Email Michelle, and she'll be sure to get you on the list. We also.
Announce as in real time, these kind of new daily releases and news items on.
Twitter Facebook and other social media, so thanks very much. And I'll turn it back to you.
Thank you, John. John would you be so kind to put the U. R. L. to the cancer imaging archive in the chat?
Just for those folks who may not have had a chance to look at it.
I'm going to share, uh, I would like to give a brief update on the imaging data comments.
The imaging data comments is part of the moon should moonshot initiated and funded.
And see, I cancer research data comments, and it builds a cloud based data science infrastructure, which can then be used for analyzing these large data sets of, for visualizing them.
The cancer research data comments consists of multiple components. John mentioned already some, uh, in his talk.
So there are data repositories like the genomic data comments, the proteomics data comments, the integrated canine data comments, and as of late the imaging data comments.
In addition to those data repositories, the cancer research data comments also has analysis platforms.
And these repositories and the analysis platforms, they are all tied together.
By infrastructure components that will allow users to query across all the data repositories and then hand the data they selected over to the analysis platforms.
As for the imaging data comments, it's a new project. So the minimal viable product was released in October of 2020 and minimal viable product means it has the structure.
It has the bones, but we still need to put a little bit of meat on it.
And that's what the team is currently focusing on. There's a lot of development work, going on on the user interface on how data come in. And as John mentioned, uh, initially we are going to import.
Uh, the public tca data sets.
So, they become available to cloud processing.
And the imaging data Commons is also working on more cloud specific works. So, how do we give users access? How do we transfer the data to the analysis centers and things like this?
Uh, the the team has also been working on versioning strategies as you can imagine tca and Jess data on a regular basis.
So,
the imaging data comments aims to have these data also available for cloud processing processing,
which means we need to take care of versioning and the imaging data comments team is in constant communication with other imaging and teams.
We hope to have a production release of the imaging data comments in the fall of 2020, but you can already access. Uh, what's they're currently.
The I posted the, I'm showing the Ella here on the slide it's portal dot imaging data comments that canceled out cough and I will also put it in the chat.
And if you are looking for more information about the cancer research data comments, and everything, it has to offer, please point your browser at data, common, start, cancel.
Are there any questions for John or myself?
Comments as well as the credits.
Okay.
Okay, I think this brings us to the last point.
Um, the.
As was stated in the beginning, we're reworking the webinar at the moment a little bit.
So,
as of now,
invitations have gone out would be a Google group and the link is here,
but we are making use of the services offered by both communications team teams and at the exhibit.
And we will continue sending out.
The invitations to both email lists as well as to the information via the Google group.
Information can usually also be found on the imaging and Informatics community Vicki, and I should have updated this and that's the L. and I will also post the recordings on this page.
So, if you want to go back, or if you want to recommend a specific talk to somebody who might be interested in it, please point them to the wiki page.
Our next calls are scheduled for April 5th, and may 3rd, and will send out information about the upcoming speaker speakers and topics.
I have some information if you'd like to have it now. Yeah. Next month we're going to hear from Dr sob Josh from the University of Pennsylvania. I've gotten him to come to us.
He's, he's a radiologist and does the things that radiologist do, but he has also got a strong interest in artificial intelligence, which I think is interesting. He's a very provocative writer.
He's written on such things as the economics of automation or the radiologist and over diagnosis.
And he's even written something called stop planning with zebras in Texas. So he's very interesting person to, to to listen to he's going to speak to us about artificial intelligence next month.
But with a fairly interesting twist, title of his talk is going to be the legal element of who is going to be sued if it screws up.
So, I think it's going to be rather interesting opportunity for us to think about artificial intelligence in a, from a different perspective.
Thank you Dr Nordstrom.
Okay, I think that's, uh, talk to Nordstrom if you are on a, if you want to close out the call I think we are about there.
I'm just, I'll just say that Thank you all for being a part of this today. Dr Rosenthal I thought was very was very stimulating and I thought a lot of good questions came from it came on. Do you want to say anything?
I think this was a great.
Women are a, the speakers presentation was very enlightening and we had a really, I think record.
Attendance by a broad range of, you know, uh, institutes and folks from different.
Expertise area, so this.
It's been encouraged with webinar and good start for our joint collaboration.
If anybody has suggestions for what they'd like to hear, please don't hesitate to.
To talk to either 1 of us will be glad to.
See, what we can do about putting something like that on the schedule yes. Thank you.
Okay, okay Thank you so much. Thank you. Everybody. Bye have a nice day.
You too. Bye. Bye. Bye.