6517-MARESCAUX-Palazzini.mp4

Good afternoon, everybody, and first of all, thanks a lot.

You asked me to speak about innovation and development in cancer surgery

that we have done in Irkart since the creation of Irkart in 1994.

I just want to say as an introduction, first of all, where is Irkart? In Strasbourg.

And you know, Strasbourg in France is a little city of less than 400,000 inhabitants, but it is in the top 100 worldwide universities in the world, in the ranking of Shanghai.

And that is certainly a reason why we can attract so many researchers and industrial partners.

and you imagine that in 1991 he explains the next step of surgery especially saying that the

it will be the strength of internet that was 1991 internet arrived in 1992 the strength of

robotic surgery virtual reality augmented reality applied to surgery and oncological

physiological surgery, and also artificial intelligence. So I came back, I discussed with

my co-workers, and we decided to create IRCAD. That means an institute totally dedicated to

research in new technology and training in this new technology. Since the beginning, we work on

the concept of augmented surgery. And if we want really to understand what is augmented surgery,

just have to ask the question to a surgeon the first answer is to improve my surgery i want to

improve my eyes i want to see more than what i can see normally and especially i want to see in

transparency so that is the first answer the second answer is i want to do more with my hand

that is augmented hand and that is robotic surgery and finally i want to have a better strategy

before the operation, during and after the operation, and that is the role of augmented

brain. That means artificial intelligence. So if we start by augmented eye, what is augmented eye?

We have a CT scan in 2D. Here is the example of a cholangiocarcinoma. Very difficult to understand

where is the tumor. You see that all the experts say the tumor is on the right side. That was

during an advanced course of hepatobiliary surgery. And when we have the opportunity to

reconstruct in 3D, you are going to see very easily because we can remove the external part

of the liver. So we have all the branches, we want to remove the biliary tracts, the arteries,

and immediately when you have just the veins, you see that the tumor is absolutely not in the right

part of the liver, but because we have not a median vein, it is in the left part. And when

When we apply a virtual clip, you see that we see exactly the vascularization.

And when we do that on the left part, you see that we remove absolutely the left part of the liver.

So that is to explain how important is 3D reconstruction.

The same for this amartoma, young baby, two months old.

You see this big amartoma.

It's very difficult to know where the vascularization starts.

So we can navigate inside, and you will see that very easily, we see that we are going to see the hepatic artery.

So we see the hepatic artery here, and we see the two branches going to the tumor.

So immediately, for the pediatric surgeon, it was so easy to start the operation by this control, and after that, in 45 minutes, the operation was done.

another example is this double nephroblastome and you see that with a 3d reconstruction it is the

only way to be possible to to be able to do a conservative surgery bilateral conservative

surgery and that was what has been done by the surgical team in paris you know that is the first

steps the first step is the planning the second step is the simulation so you see here three

metastases of the liver we know that for the left one it's possible to do a trisegmentectomy

and for the right one we want to do an ablation and because we have this possibility of interactivity

we can take any instruments so we take for example the needle here we are just looking what is the

the best way to be in the center of the tumor and you see that that is a real simulation

of the radiofrequency ablation we plan to do for the patient. We can take also the virtual

optic and the virtual camera and you see that on the window on the left we see exactly what we are

going to see the day of the operation. So you imagine that with the increasing of the power

of the computer it will be more and more realistic to do the simulation of the operation the day

before and certainly one day it will be totally mandatory to prove that we have simulate the

operation before making the real operation finally after the planning the simulation is

the fusion of both that is augmented reality you have the 3d image you have the normal image

you lose a fusion of both image and you have the concept of augmented reality we

start this concept by tumors of the adrenal gland and you see that we

publish the result in JAMA that was nearly 20 years ago and why because it

was possible to reconstruct in 3d so it is a first step that is the planning the

planification of the operation we see two main vein and not only one and you

you will see that when we dissect the external part of the vena cava we just ask the computer

scientist to do the superimposition and we see in transparency the exact position of the main veins

and when we start to dissect the renal vein we see in transparency the polar superior

kidney artery that so we need absolutely to preserve so that is a concept of augmented

reality that we can apply also for some pancreatic tumors like insulinoma that you see here

we have the transparency we know exactly the position of the tumor the localization the

landmark with the main duct so that is the concept of vision in transparency but it is not simple

because, you know, we have a lot of challenge for this kind of augmented reality.

The first one is that we have mobilization of the organ due to the bracing of the patient.

That has been solved by the computer scientists

because they have some landmark on the sternum

and predictive algorithms concerning the mobilization of the liver, for example.

The second challenge is the position of the patient,

which is not always the same during the operation

and during the CT scan which has been performed some days before and here again this challenge

is solved and they have some algorithm to do the exact fusion if the patient has a new position

but the more difficult one is that the first thing we do in surgery in visceral surgery in

digestive surgery or urology or thoracic surgery is to put a retractor and so we have immediately

a new volume a new localization of the organ and that is very difficult because we need the machine

needs to understand where is now the final localization of the organ and the volume of the

organ and to do that we have created in 2018 another institute just in front of IRGAD which

which is the Institute of Image-Guided Surgery,

where we tried with our partner Siemens

to imagine an operating room

with all the different systems of imaging technologies.

That means we have the CT scan in the operating room,

we have the MRI, we have the robot-sized CT scan,

which is the zygote or the pheno,

we have the last generation of ultrasonography.

and that was the end of this construction just in front of IRCAD and that is a concept that

means for a complex hepatic surgery we can have the intraoperative CT scan for arterial phase

or venous phase but we know that we need also to see the biliary tract and for that we need

absolutely the MRI so we have the MRI in the operating room and after that during the operation

we can see absolutely in 3D with Ziggo the different images

and we have a fusion of different images.

So you understand that the most important step is 3D reconstruction.

For that we have created a spin-off of IRCAD which is visible patient

And you see that we can, in 3D, reconstruct all the different organs.

The problem was that it was long, because for one reconstruction of all the details of the liver, the lung, or the kidney, it was more than between three and four hours.

But during the COVID, you see, that is really magic, because you see that for the lung, and that is applied to lung cancer,

in 2019 it was four hours of reconstruction and it was semi-automatic and at the end of the COVID

because a visible patient has to reconstruct thousands of cases of lung you see that it was

nine minutes fully automatic by artificial intelligence using two algorithms patented

in Europe and in United States so you see in in one year the fantastic power of artificial

intelligence to decrease the time of reconstruction and now visible patient

is an exclusive license with Johnson & Johnson for open laparoscopic surgery

and especially for the development of the new robot verb. Second challenge

after the vision is augmented hands that is that is robotics and robotics how we

we can integrate the image in the robot of the future generation.

And here you see the robot da Vinci.

You see like a GPS in a car,

the 3D modeling, which is integrated on an iPad.

And when the surgeon is looking inside the master part of the robot,

you see that he has a vision of the camera,

but he has also the vision of the 3D reconstruction,

which is like a landmark to know exactly the details of the anatomy the second thing that we

have developed in in surgery and i think it's very important for cancer for oncologic surgery

is a long distance surgery to have a team which can which is able to support another team and

And you remember that in 21, we described the operation whose name was Lindbergh operation

between New York and Strasbourg.

That was a total operation, very simple one.

It was a cholecystectomy.

But just to prove that today with the technology, we can do without any problem, a total long

distance remote surgery.

And that was published in high priority in Nature.

But something is very important is that today, since last year, you have a lot of publication, Chinese publication, trying to use the 5G for remote surgery.

But today it is only preclinical trials, never more than 3,000 kilometers with a latency time of 264 milliseconds.

And you imagine that 20 years ago, it was clinical on a patient.

it was 14 000 kilometers and a time of latency of 155 millisecond which was totally unique

performed by two young engineers of france telecom a word about alimentary tract cancer

and you know the evolution of what we call endoluminal surgery using flexible endoscopy

and certainly in the future robotics flexible endoscope.

Why?

Because I was absolutely impressed by a conference of Professor Tanigawa

that was seven years ago.

And seven years ago in Japan,

they have operated more gastric cancer by endoluminal way

with flexible endoscope than by conventional and laparoscopic surgery.

And they say certainly in the next 15 years, 80% or more of alimentary tract cancer, if you have early detection, will be operated by flexible endoscope.

But what we have seen is a lack of triangulation.

And you know that to operate, it's difficult to operate with a normal, conventional, flexible endoscope because we need a triangulation.

So we developed with Karchtos on the scope this system whose name was Anubis.

And you see that we have a triangulation.

We have a mobilization of two instruments.

And we can do a lot of manipulation, even a suture, an endoluminal suture.

But it was difficult to manipulate.

And it is the reason why we have developed a specific robot with the team of the University of Strasbourg.

and it is very interesting here to see how esd is possible on the left it is a south korean

gastroenterologist with an experience of more than 1000 esd and on the right it is a surgeon

without any experience of esd but with a robot and when you compare the image on left with a

gastroenterologist with a huge experience and on the right with a robot and no experience

immediately you see that on the right it is a real operation so certainly the future will be

robotic and flexible endoscope i want to finish by augmented brain which is artificial intelligence

just to remember that it is not new you know in all the newspapers since five years we see a lot

of papers concerning artificial intelligence as it was something totally new now the first

machine learning was elaborated in 1957 by Frank Rosenblatt. 1957. But nobody believed in the

project. And you all know that in 2014, because a machine was a winner against the world champion

of a Go game in Korea, that was the beginning of an explosion of money support for artificial

intelligence what we have done is in the last five years elaborate what we call a condor project

which is a control tower in the operating room it didn't exist but it is possible today because we

can storage with absolutely a low cost all the pretty image the external image of the operations

laparoscopic image all the physiological signals and we can follow the patient until he returned

to work so that is an application the other one very interesting certainly in the future for

cancer surgery is how the machine is going to be able to to to send an alarm to the surgeon if

the protocol is not the exact protocol here we start with cholecystectomy we send a hundred of

case of cholecystectomy and the machine understand different step and you know that the only way

to preserve from a complication like biliary tract the common biliary tract

section is to have a perfect dissection of what we call the triangle of safety

so if the machine see that the triangle of safety is not very well dissected

immediately she can send an alarm to the surgeon or if it is a robotic surgery

stop the effectors of the robot i want just to to say something very important especially for cancer

is that we speak about a rolls-royce or a ferrari with 3d med robotics etc and when you look at the

report of the who in 2021 we see that five billions of the world population don't have

have access to any medical imaging you imagine so we change and we say okay it's good to work

with Rolls-Royce but we need also to imagine how we can detect little tumors for this population

and how we can treat this tumor because in one of the last article in the Lancet we see that more

than two billion people in the world population has no access to a very simple safe operation

operation. So it's the reason we have developed this project, which is very nice. The first one

is how artificial intelligence can do a screening of little tumors with a low-cost ultrasonogram

that is possible. Second step, how we can imagine to have a 3D image with ultrasonography

and a system you see like a target. We can immediately know where we have to put the

needle for ablation and the third part of this project is to imagine a protocol with a low-cost

robot to have the exact positioning of the probe and the positioning of the needle for the ablation

so that is a fantastic project that we developed not only with our team which is in strasbourg but

also with a team in taiwan and a team in rwanda because in kigali they have a very very important

university for computer science I want to finish by the training why because

when we develop new technology especially against cancer tumors we know

that the training for the operation is very important so we develop a lot of

courses where we are emerged with the best experts in the world for example we

want to train gastric cancer operation we are connected in South Korea because

because each department, they have more than 1,000 cases,

and we have between 20 and 50.

So they can explain how to do that by laparoscopy,

how we have to do that with the robot.

We train also in the lab.

That is done on simulators, on pigs, on cadavers.

And you see that the surgeons are totally immersed

in the atmosphere of a normal operating room.

We train flexible endoscopy,

because you know that it is so important for the future and percutaneous surgery but also robotics

and here we have you know the unique platform in Europe with 13 da Vinci robot but because we

we want to be an academic center we also created an extension of IRCAD to have also the robot of

of Medtronic, but also the robot of Cambridge Medical that we have.

And we know that it is so important to have a different, various robot

and the different training are organized.

WebSearch is a unique virtual university on the Internet

for all these minimally invasive approaches for different specialties,

free of charge, translated in seven different languages,

with today more than 430,000 active members.

Finally, the globalization, because if we want to develop education,

especially for cancer, we cannot train everybody.

So you see that we start by IRCAD France in 1994,

and after that we have one in Taiwan, two in Brazil,

Sao Paulo State, and Rio de Janeiro.

One in Beirut, two projects.

One in Rwanda is going to be finished in six months.

China finished in the end of 2022.

And recently, we signed an agreement in the United States

to have also an IRCAD in the United States.

So thank you very much for your attention.

That was a quick summary of all the different technologies

that we have developed in IRCAD since 20 years

because we believe that computer science image

is going to transform the way we have to operate our patients.

Thank you so much.