Transcript generated from the episode’s audio. Speaker names are identified from the context of the conversation rather than from recorded speaker data, and automatic transcription may misspell names and terminology. Please refer to the video for the authoritative version.

David Raubach: I want to thank you all for joining us on today’s episode of the Cancer Project podcast. We’re really privileged to be joined by Mark Malin, the US president of RaySearch Laboratories, which is one of the most important companies in the world of radiation oncology, and we’re going to talk about why that is here, and then we’re also going to talk about all things treatment planning. Mark is a dosimetrist by training, but he’s also very good at translating what is a very complicated topic into a way to understand it for the average patient. And so that’s what we’re going to do today. So Mark, thank you so much for joining us.

Mark Malin: Thanks for inviting me. I’m glad to be here.

David Raubach: Yeah, so just to kick off, tell us about RaySearch since we’re sitting there. You’re sitting there at the RaySearch Laboratories headquarters in the Empire State Building there in New York City. What is it? What is RaySearch? What do they do? Talk a little bit about the history of the company.

Mark Malin: Yeah, sure. So RaySearch Laboratories is actually based in Stockholm, Sweden, right? So that’s where the development for our software is done. And they were formed, we were formed in 2000 as a company. And then in 2011, we opened a US branch called RaySearch Americas. That’s the organization I’m the president of, and that’s based in New York, and we also have an office in California. So RaySearch Laboratories is primarily a company that creates software for radiation therapy planning. And there’s a couple of different products that that we do. Both oncology information systems and treatment planning, which I’m sure we’ll get into here. And there’s about 450 employees total, have an organization here in the US of about 40, probably going up to about 50 people this year. So, it’s been a great run and it’s a great company to work for.

David Raubach: And talk about the scale of the services that they provide, or their customer base, both here in the US and worldwide.

Mark Malin: Right. So, we have about, I’d say, 1,300 facilities around the world that provide cancer treatment. And most of those are photon treatments, right? Which is your conventional linear accelerator that you find in many hospitals around the world. On the proton side, which of course you guys are doing protons, and I assume that a lot of the patients that’ll be watching this are under treatment for protons as well, we have really most of the centers around the world. We have a very very powerful product that, just for, you know, example, in the United States, there’s I guess 47 or so operating proton centers, and there’s others that are in development. And we have, RayStation is in all of those centers except, you know, three. And we’re talking to those folks as well.

Mark Malin: And there’s various reasons for that, but it’s a, the product is a relatively new product. It was, you know, released in the United States in 2011, and protons in 2014. And it’s just got a lot of great features, and it was really, it introduced a lot of algorithms that really make it safer and better for patients to be treated with.

David Raubach: So, talk about… Yeah, go ahead, Mark.

Mark Malin: I was just going to say we also have an oncology information system, which is maybe of less interest to the, you know, to patients, but it’s the software that is connected to the treatment machine and the radiation therapy plans that were created in our other software called RayStation. That goes over to that controlling system, and that’s how we keep track of the dose that you’re getting every day and the prescriptions that the physician writes and so forth, just to make sure that everything is right between the time that the planning is done and the time your delivery is executed.

David Raubach: So talk about your background, and I’d actually love to start with your growing up, because you’re from New York. You had a little bit of a challenging upbringing. So talk a little bit about just growing up in the Bronx, and then ultimately that path that led you to becoming a dosimetrist.

Mark Malin: Yeah. So it’s a fun story, but I’ll keep it simple. So I did grow up in the Bronx. My father died when I was quite young, about 7 years old. My mother was disabled. You know, one of those life stories that could kind of go any which way, so to speak, and, you know, ultimately I made the right life choices. I started taking martial arts. You know, as a kid in the Bronx, I had to survive. Went to the right schools with help of my grandparents, and then eventually made the choice to go to University at Stony Brook in Long Island. So, you know, it wasn’t that far from the Bronx, but it felt very far. So it’s, you know, that’s really how that happened, and I wanted to be a physician. Actually, my original intention was to become a medical doctor.

Mark Malin: And when I went to college, I just, you know, learned about myself as a leader. I was the president of an ambulance company. I was a resident assistant. I, you know, I did all the things that leaders kind of do, and I just had a great time. And then I started doing research in medical physics, which is what brought me into radiation oncology, because to become a physician you need to have some sort of background in research. It helps you with your application. But I just loved radiation oncology. It was a mix of medicine, of computers, of dealing with patients, and it’s was just a great place to be. And that was in 1989, to show my age. So, that was in 1989, and things were quite different then. But, I just stayed in radiation oncology, and I trained, became a medical dosimetrist.

Mark Malin: I was certified in 1994. And for those folks that don’t know what a CMD, or medical dosimetrist, is, the person that actually operates the computers and the software that do the dose calculations and helps the physicians figure out what your treatment is going to be. So, that’s what I did for quite a long time until, I guess, from well, until 1997, when I was hired by a company to work as an application specialist.

David Raubach: And so, that company, ADAC, and I think, as the story goes, you were working on a requesting service from ADAC, and they were a little bit slow to respond to the service, and you said, “What’s the problem?” And they said, “Well, we need more service people.” And then within a few days, you’d been hired by that company. And so, talk a little bit about ADAC, because they were really one of the early pioneers in treatment planning, I believe, founded in Cupertino in 1970, initially within the world of nuclear medicine, nuclear imaging, but then got into treatment planning. So, just talk about the legacy of that company and what they were doing, and the impact that they’ve had on on the field of radiation oncology.

Mark Malin: Yeah, it’s so strange how, you know, there’s certain times within the development of, clears throat, software and medicine that really make a difference. And about the 1997 time frame, a new algorithm sort of came out. It was called the superposition convolution algorithm, and it was just a way to calculate the radiation dose in a much more correct way than had ever been done before. I mean, not not that things were wrong, but, you know, just everybody has a body shape, right? And the original dose calculations assumed that everyone was a square box of water. And so, that’s just one example of how things were different back then. And ADAC purchased a company called CMS Tricks. And there was actually, you know, quite a few famous names that were part of that development. And it it just was a great product. It was called Pinnacle.

Mark Malin: And at the time it was a terrific product. Pin, ADAC was then purchased by Philips in 2000. But Philips really didn’t buy ADAC for radiation therapy. They bought them for nuclear medicine. And so, I was with Philips from 1997 until 2007. And And your story is exactly right. I was a, I was working in a hospital. I needed some help. And I called them up. Took them a while. And I said, “What’s going on?” And they said, “Well, we’re looking for people.” And I said, “What kind of people are you looking for?” And they said, “People like you.” And literally 48 hours later I was in California. And it just, I realized then I loved working with patients. I mean, I just want to say that when I was a dosimetrist and I worked with patients all the time.

Mark Malin: But then, when a company said, “Hey, look, you could come here. You can make a much bigger difference. It’s not just the patients in your center that you’re helping. Now, by making the product better and by by helping hospitals use the product, now you’re helping, you know, an exponential number of patients. Not just a, the 10 or 20, whatever it was, on treatment.” So, I’m, I was really happy to make the move. And I knew it was the right thing. So, ADAC was great. And we had, at its high point, when I left in 2007, we had 1,400 centers just in the United States.

David Raubach: Wow.

Mark Malin: So, it was an amazing experience. I built an organization of support. I was in charge of the physics training. And yeah, so it was very hands-on and very involved.

David Raubach: And so, I’ve read that the, there was a, was there a partnership then between, I, I’ll use Pinnacle, the name of the planning system, and RaySearch, and they were working on IMRT, or intensity-modulated radiation therapy planning?

Mark Malin: Right.

David Raubach: How did that… Talk a little bit about that relationship.

Mark Malin: Clears throat. So, there was a gentleman named Johan Löf, and he’s the founder and CEO of RaySearch Laboratories at the time. RaySearch created algorithms for other companies. So, they didn’t, RaySearch didn’t have its own treatment planning system, didn’t have the products that it has today. They were primarily a laboratory, so to speak, that created algorithms and then sold it to companies like Philips, actually Varian. There was IBA, there was a few projects that were going on at the time, and that’s how I knew Johan and and Björn Hårdemark, who’s the deputy CEO, and a whole team of people used to come over, and and their algorithms were incorporated into the Pinnacle treatment planning system to help with a a new technique at the time called IMRT, which is intentional intensity-modulated radiation therapy.

Mark Malin: And just in 60 seconds, what that is, or 60 seconds or less, in the old days, when I was a a young buck, we used to, you know, aim at a tumor with pretty much a square field, a rectangular field, and put lead blocks to protect healthy tissues. So, if, let’s say you had a tumor in the neck, you would want to put a block that would block the cords that you weren’t, you know, treated there, or the eye, or something like that, just to make sure there was no damage. And then, with the advent of what’s called multi-leaf collimators, these are basically, it’s almost like little blocks, but they’re they’re leaves that interdigitate, and you had a lot more control over what area of the body you would expose to the radiation.

Mark Malin: And by sort of taking a whole bunch of these little leaf motions, you could build the perfect dose distributions, that you would no longer needed the blocks, and you were treating just the tumor and not the healthy tissue. And RaySearch Laboratories was just key to that whole algorithmic development. And, that’s one of the benefits and one of the realities of why Pinnacle was such a great treatment planning system.

David Raubach: And you were a block cutter.

Mark Malin: Yeah, so in nine, well, so in 1989, I started in medical physics research. And then in like 90-91, I started training in dosimetry. And one of my roles, one of my jobs, was to actually, you know, cut the blocks. And the doctor would draw the shape on on the x-ray film. And then, you know, I would use a, it’s a piece of Styrofoam with a hot wire. And you cut the block out. And then you pour lead into it. And then you attach that to a tray. It was a whole physical process that was, looking back, it was pretty crazy. But it was the best that we could do at the time. And so yes, there was a lot of history and knowing of where we came from. And just it’s amazing to see where the technologies have gone. And now protons and IMPT, intensity modulated proton therapy, it’s just an amazing time that we live in.

David Raubach: So, and just to kind of tie the ribbon on this. So the blocks are external devices. So you’re actually making those in a laboratory. And then those get slid in in front of the beam, attached to the delivery snout.

Mark Malin: Right.

David Raubach: But then these multi-leaf collimators are actually built into the machine themselves. And so they can be adjusted almost real time as you’re delivering the radiation. So, big step forward.

Mark Malin: Big step forward. And in many different, it was photons. Protons weren’t even really much of a thing at that time. Actually, in the early days of protons, it was like that. It was compensators, right? So compensators are like blocks, just shaped to, you know, to shape the radiation. That’s a whole ‘nother conversation, but it’s similar, but and then when IMPT came around, the compensators went away, and now you had these, you know, this way of delivering spots to deliver the dose, and I’m sure we’ll get into that a little bit.

David Raubach: Yeah, and we have, I mean, here at the Oklahoma Proton Center, so we were one of the first proton centers in the country, we still have a machine shop, and some of our rooms still require these external apertures, which are the brass devices that create the two-dimensional field that the protons can travel through, and then the compensators that help control the depth or energy of the protons. So, we’re still doing that…

Mark Malin: Right.

David Raubach: …for some patients. Fortunately, we do have a room that has intensity-modulated proton therapy, so that process is built into the snout. So, talk about, cuz I’ve, these are terms that we hear thrown around, 2D planning, 3D planning, or IMRT, or inverse planning. So, walk us through that progression and what each of those mean.

Mark Malin: Right. Sure. So, I’m going to go back in my memory a little bit. So, 2D planning, so as I mentioned before, the original assumption was that we were blocks of water. That’s mostly true. When we talk about 2D, it just means that one single plane. So, let’s say someone was being treated for prostate cancer. We would actually do a tracing of their external contour, their shape, and basically on a piece of paper, imagine the person’s head into the paper and their feet sticking out at you, and you would have a shape of a person, and then we would use a computer to calculate what the radiation dose would be within that drawing of a person. But it didn’t take into account, you know, curvatures that were further up. I mean, a really good example is breast, right?

Mark Malin: So, in the early days, we would also take a tracing of a breast patient right through the middle of the breast, but the breast is conical tissue, right? So, you would, you know, above that middle part of the breast there’s less tissue, below it there’s, you know, less tissue, and you have a different shape. And radiation, without getting too much into the physics, when radiation enters the body, it scatters around, right? And when it scatters around, those interactions of photons and electrons and so forth, they all add up and they, there’s a lot going on. It’s not just a single simple calculation. And that’s what made Pinnacle so great, and the algorithms from research, that these dose calculations were now really correct. And so, but from a 2D perspective, again, that was all it was. It was just a simple contour. CAT scans were done.

Mark Malin: So, CAT scans are still a great way to calculate dose. And the reason for that is cuz a CAT scan carries density information. So, if you’ve ever looked at a CAT scan, it’s got, you know, gray, grayscale, there’s, you know, dark areas which are mostly air, then you have light areas which are tissue or fluid. And the, you can use that information to calculate the dose even more correctly. But again, even in the early days, it was only a single slice, or, you know, two slices, or three, maybe. Snorts. Uh, so, that’s 2D planning. 3D planning was where now we took a CAT scan of the whole patient, or at least the area that was being treated. And now the treatment planning systems were able to calculate dose much more correctly.

Mark Malin: So, and it makes a big difference, you know, when when you’re trying to treat a tumor, you’re trying to kill the tumor, but you’re trying to protect everything that’s healthy around it, all the organs at risk. And so, you know, in the early days, we you just couldn’t go that high of a dose, couldn’t, you know, treat that high, because you were so concerned about what you would do to the other healthy tissue that was around it. But once three-dimensional treatment planning systems came out, you were able to have a much better idea what, what was going on. So, that was sort of 3D. Now, again, as I mentioned before, you used to have these single fields with blocks, and you could have lots of fields.

Mark Malin: You could have anywhere from two to say seven fields was typical, where the the gantry would rotate around the person, and the the dose would be delivered from all these different angles, and it’s the addition of all these angles that would give you the highest dose in the tumor, and spread that dose around so you weren’t, you know, hurting anything that was healthy. And that was 3D treatment planning. But then IMRT happened, and with the MLCs and so forth, now you had intensity modulation, and you could have still anywhere from, say, five to nine beams, well, on average, but in each of those cases, you created that perfect dose distribution because the MLC leaves were able to move, and really, you know, come up with it, just an amazing plan that was going to be good for the patient’s specific problem.

Mark Malin: And so, that’s IMRT, and translating to protons, IMPT, intensity modulated proton therapy, and although some systems use MLCs, another way is just to shoot these little directional small beams, almost like spots, and then you could build the perfect dose distribution through this optimization. And that’s where the computers are so important, and that’s where RaySearch, that’s our strength, is the optimization and dose calculations.

David Raubach: And so, what do you mean by intensity modulation?

Mark Malin: Yeah.

David Raubach: Like literally, what is what’s practically happening when we say intensity modulation?

Mark Malin: Right. So, in, first, let’s talk about photons, right? So, you have this MLC. I’m going to use my little flesh MLC here. So, you know, let’s say you have like a little spot that’s, so my fingers are lead, or, you know, alloys that are blocking the radiation, and then you have this open little spot. Well, if I give dose there, I can give a little bit, or I can give a lot. I can, you know, leave the machine on so that it’s delivering more dose at that little spot. But then I could move it, and now I’ve got a different area that’s open or closed, and I can deliver dose there, right? So now what I’m doing is is I’m giving a different intensity.

Mark Malin: I’m modulating the intensity to each of these open areas of the MLC, and when you add all that up, you end up with that wonderful dose distribution that’s better for the patient. So intensity modulation means I’m changing how much dose is going to each of these open areas. In the case of protons, it’s primarily, as I mentioned before, that the proton beams are delivered in spots. So you basically have this delivery where I’m giving a certain amount of dose, and, you know, I, snorts, don’t know if we want to get into the the physics of proton, I think maybe watching a Dr. Schrader’s…

David Raubach: Yeah. Right, right. What happens with a proton when it goes in the body is all done.

Mark Malin: But protons are a little bit different. They have a different way of reacting in the body. But basically it’s very similar, that you’re putting in a certain amount of dose into each of these little areas, and when you build up all those areas from the multiple angles, you end up with the perfect dose distribution. So that’s really what intensity modulation is. And it’s much harder to calculate. You know, in the old days you could calculate by hand with a calculator and a table, and you know, now no one really does that. They use the computers, and then they use second computers to check what the first computer did. So that’s how they…

David Raubach: Well, there’s, so there was engineering barriers, and then there’s computing power barriers. I remember when I first started at the proton center here in 2010, there were plans that we would run, and it would literally take days to put the plan together, cuz you’re just sitting and waiting for the computer to run cal, iterative calculations.

Mark Malin: And then these are things that happen, I don’t want to say instantaneously, but minutes today.

David Raubach: So, things that took hours or days now take minutes.

Mark Malin: And seconds to calculate. I mean, so Monte Carlo is a, is, so, I mentioned superposition convolution before, which is sort of a, it’s a great calculation method, but it’s, it’s an, an approximation. It’s not exact. Monte Carlo is a, basically, a simulation, but it’s using first principles. So, it’s using the science of particle interactions. And I mean, we do a single, a calculation of a patient in 5 seconds now. Now, that’s different from the optimization, where, you know, you’re trying to come up with that plan. That could take, as you mentioned, minutes to hours depending on the complexity. But GPUs, that, you know, the graphic cards that are used for computer games, they are great at calculating things. And so, now with the use of GPUs, and you know, that’s why things are just so much faster. And the dose calculations are better.

David Raubach: Which, by the way, especially for protons, is super important, because when you talk about protons, they’re very sensitive to density.

Mark Malin: So, they behave, the protons behave very differently in my lung than they would in my breast tissue, right? So, it’s really important that the dose calculations that are used, especially, you know, if you’re being treated in the head and neck or in the lung area, are so important that the dose calculations are right.

David Raubach: And so, maybe talk about that, because part of the information that we gather is this, this term, or this thing that we call Hounsfield units…

Mark Malin: Mhm.

David Raubach: …off of the CAT scan. So, talk about all of the information that’s being gathered at that initial initial treatment planning CAT scan. So, that’s like this really important part of the process. What is everything that happens there that’s so important for a dosimetrist to be able to do their job?

Mark Malin: Right. So, to, before I explain that, let’s talk about treatment planning, right, in general. So, what is treatment planning, when, you know, you hear that that’s being done? So, essentially, RayStation, which is our treatment planning system, is basically a computer that takes in your CAT scan. So, you go to the hospital, you get a CAT scan, and now I’ve got, I guess the term that medicine uses these days is a digital twin, right? I’ve got, okay, I’ve got a patient that’s now a three-dimensional model in my system. I could do whatever I want to that model. And what has to happen is is that, number one, we have to sort of decide where we’re going to treat.

Mark Malin: The physician does that, and the dosimetrist works with the physician to figure out what’s healthy, what’s not healthy, what are we going to do, what kind of disease is this. And the Hounsfield unit is is basically a a unit of of density, so to speak, that comes with the CAT scan. So, as I mentioned before, in dark areas, which is typically air, that’s very low density. In areas where it’s, you know, lighter color, could be bone, it could be tissue, whatever it is. And the treatment planning system will use those Hounsfield numbers and some, you know, predetermined measurements to figure out what is the density within the patient. For photons, they’re they’re sensitive to density, and you need to know what the density is.

Mark Malin: But for protons, it’s it’s exceedingly important to calculate that the right way, because they are so sensitive to what’s going on. And And again, without getting too much into the physics, the protons kind of have, I’m going to call the Bragg peak a sweet spot. And I know that’s a, it’s a horrible simplification, but…

David Raubach: Yeah.

Mark Malin: You shoot protons in, and there’s a certain distance that the proton goes, and there’s a a sweet spot where the dose deposited is at its highest. And if you’re shooting that into the lung versus into bone, that location is completely different. So, that’s why the treatment planning system has to know all that. So, a treatment plan is essentially a three-dimensional model of you, where the physician and the dosimetrist and the physicist work together to come up with a simulation. So, we shoot the beam into your picture on the, in the computer and calculate the dose set, you know, we figure out all the problems that that we’re going to have to overcome before you get on the table, right? So, there’s a lot of work that’s done to make sure that what we’re doing is completely correct.

Mark Malin: We’re not, we’re not taking pictures of you when you come in for your first day of treatment and figuring it out then. We’re doing that all behind the scenes before you get there.

David Raubach: And so, one of the terms that I’ve heard used that’s associated with the data that’s gathered with this treatment planning CAT scan is organs at risk, or OAR, and not to be confused with Over Revolution, which is a fantastic band. So, we also have OAR, or OARs, with treatment planning. So, talk about what that means and what the dosimetrist is doing with organs at risk, or these OARs.

Mark Malin: Sure. So, let’s say you’re being treated for prostate cancer. The target, what the physician wants to treat, let’s keep it simple, is your prostate, right? And what he or she doesn’t want to over treat is rectum and bladder, and maybe if you have an artificial hip, we have to take that into account. So, all of those structures, even though they’re, we see them on the CAT scan, the treatment planning system has to know what those things are, right? So, basically, the dosimetrist, with the use of the software, could be AI, it could be manual, maybe we’ll get, talk about that a little bit more, but basically all that stuff is outlined, right? So, I draw the bladder, I draw the rectum, and I’m doing that not just at one level, but throughout the entire patient.

Mark Malin: So, the bladder, you know, looks like, you know, I I can actually imagine what that thing looks like in three-dimensional space. And that’s considered an organ at risk. And then when we do the intensity modulation that I’ve explained, you now have a way to explain to the computer what you don’t want to do. So, the bladder doesn’t want to be treated, right? So, what I say to the computer is, “All right, computer, I want you to treat the prostate to whatever the target dose is, 7,000 centigray, whatever it is, but I don’t want you to go higher than some number to a certain amount of the bladder,” and, you know, and here’s where the physician comes in, right? So, it’s not all up to me to figure this out.

Mark Malin: The experience of the physician, the research that’s gone on in radiation oncology, you know, we know what the, what’s known as the TD5/5, which is the, you know, the the dose that, you know, you can give without causing damage. We know what a lot of these numbers are. And that’s where the science always is, that we’re always pushing to eradicate the tumor and to not hurt. And that’s called the therapeutic ratio, where we’re giving the right amount of dose that’s going to help cure a patient, but is not going to cause harm. So, organs at risk are purely, you know, the parts of the body that we want to avoid, and the target is the disease. And And by the way, it’s not just tumor.

Mark Malin: In a lot of cases, it’s other areas, which would be called a clinical target volume, where the physician says, “Okay, well, here’s where the tumor is, but I know that there’s lymph nodes, or I know there’s other things around the tumor that need to get the radiation as well, because if they don’t, the cancer cells may still survive that, and even though you may have solved the problem in just one area, those cancer cells, if they’re still left, they could metastasize, go, you know, and cause trouble in the future.””

David Raubach: So, it’s a, so, you, good rule set. And so, you bring up a good point. So, the next phrase I was going to use was target volume. So, the target volume is this area that the physician says, “I want you to treat.” And there could be the primary two tumor volume. And then there’s this clinical target volume that may be a little bit of a bigger area. But either way, there’s an area that we’re trying to treat. So, talk about then the next step being this idea of beam arrangement.

Mark Malin: Yeah. So, you know, so now I’ve got the target. I know what the physician wants to treat. I know what I’m, I can’t treat or what I shouldn’t treat. And sometimes you don’t have a choice, right? I mean, and, clears throat, a lot of times the tumor’s in a really bad location. I mean, a good example for that would be, you know, parotid treatments are, in the head and neck region, where a tumor is close, and, you know, that’s why a lot of folks have a hard time with, clears throat, head and neck cancer, because there’s just so many important things, whether it’s the the spinal cord or the parotid glands, you know, parotid glands obviously, you know, help you to generate saliva so that you can eat and be more comfortable.

Mark Malin: The muc, the mucosal linings of the head and neck are very sensitive to radiation. So much to, you know, so much to take into account. So, as a dosimetrist, and with the treatment planning system, we then decide, “Okay, how are we going to treat this?” And I’ll use a simple example of a prostate where someone has an artificial hip. You want to avoid the artificial hip because of the density is going to hold, is going to mess up the radiation, right? And it, when I treat through that, it’s not the same as treating from the other, from the bone on the other side. So, I might do an arrangement of beams that avoids that hip, so that I don’t have to worry about the weirdness of the radiation. Another example might be someone with a pacemaker.

Mark Malin: I don’t want to treat through the pacemaker cuz it could cause damage. And then there’s other the organs at risk that we’ve talked about, that in some cases I may want to avoid them if I can. So, sometimes in, I’d say in most cases, there’s standard arrangements, like, you know, if someone has prostate cancer, we pretty much know whether it’s going to be what we call arcs, which means that the radiation’s on while the gantry is moving around the patient. But basically the dosimetrist and the computer is going to come up with the proper angles to insert the radiation at, so that you’re not causing damage. And that’s that’s what that is. And a a very common treatment is arcs, like I mentioned before, very common in photons, brand new to protons. Right?

Mark Malin: So, proton arcs, meaning that the proton is that the protons are being delivered while the machine is moving. That’s a new sort of technique in protons, and I think it’ll be more used in the future.

David Raubach: Yeah, so that’s a good point. So, you can either have these individual fields, or beam angles, where you deliver the beam and then you rotate the gantry, and then you deliver another beam, rotate the gantry, or you can just deliver continuous beam as the gantry is rotating, which has been fairly commonly used in photon treatment for many years now. TomoTherapy was, that was a machine that kind of pioneered this technique. So, talk about the number of fields, because, so, I’m a patient, and my radiation therapist is saying, I’m, this is probably more applicable to protons, well, you’re getting two fields. But then my buddy that I’m sitting next to in the lobby every day is like, “Well, I’m getting three fields.” And then this lady down at the other end of the hall is saying, “Well, I’m getting one field.” So, why, why are we getting different numbers of fields?

Mark Malin: Right. It really, it depends on the disease, and, you know, where the tumor is, what’s around it, how big you are. You know, there’s energies of the radiation to consider, right? So, higher energy goes deeper. Protons are really interesting, right? Because now you have this delivery of the spots, as we’ve talked about, and, and there’s also, you know, different energies that you can do with the intensity-modulated proton therapy. So, it’s mostly about the same concepts that we sort of have on the photon side, is that based on where the tumor is, and what’s the best way to treat the tumor without, you know, impacting healthy tissue, that’s really the determinant.

Mark Malin: And, you know, there are some common techniques, but, you know, in general, I think people are, the dosimetrist is a good dosimetrist, going to sit there and try and think out of the box, right? I’ve got a patient, I’ve got it, it always bothered me, I’ll be honest with you. It always bothered me that when I was a dosimetrist and I sat in front of, you know, a patient’s images on the screen, it, it was like it was the first time I’d ever done it before, right? And that’s really where AI is going to help out, and not not the scary kind of AI that you hear about in the news, but…

David Raubach: Right.

Mark Malin: …but training the planning system to do things that we know were successful in that facility with that physician and that, you know, environment, and at least as a starting point, so that the dosimetrist and the physicist could say, “Okay, all right, this is what the computer says we could do. How could we adjust that?” I I just will say, maybe I’m jumping to a later part of the discussion, but…

David Raubach: No, let’s go ahead.

Mark Malin: The future of AI is very different. The future of AI is going to take everything into account, and it’s going to take into account, you know, your blood tests, it’s going to take into account, you know, your medical history, it’s going to take into account the medications that you’re on, your family, you know, how were they treated before and whether it was successful. There’s so many variables that impact whether or not your treatment is going to be super successful. And we just don’t know all of those, right? So, when we sit in front of the computer, we want to make 100% of the radiation get to your tumor and as little as possible get to your healthy tissue. But there’s a lot more to that story, you know? And I think that current AI is very simple.

Mark Malin: It’s just, “Hey, how do I get the right dose to the pancreas?” Or, “How do I get the right dose? How do I avoid the prostate as much as possible?” But, there’s, I think the future is super bright. We’ll talk about online adaptive, which is now, but from an AI perspective, I think that’s much later, because we need information from all different areas, and the world of medicine isn’t quite there yet.

David Raubach: So, online adaptive, what, what does that mean?

Mark Malin: So, you know, when a patient comes in for treatment, and I’m going to, so, I’m going to go back in time…

David Raubach: Okay.

Mark Malin: …you know, to the ’90s, and when a patient came in for treatment, they would lay on the table, you would get tattoos, you know, you would line up the patient exactly in the room. There’s lasers in the room so that, you know, you’re in the same place every day with respect to the machine. And then they would take an image, you know, it could be a simple film, like an X-ray, or it could be something better, like, or, that’s, I shouldn’t say better, but more informational, such as a cone beam CT, which is basically like a simplified CAT scan when you’re in the room ready for treatment. And you would, the doctor and the therapist and surgeon would look at it and say, “Are we in the right place?” “Yeah, yeah, we’re in the right place.”

Mark Malin: Or, “No, move the patient a half a centimeter, or move the patient a centimeter, and I think we’re good.” But the reality is is that the original treatment plan that was done 3 weeks ago, which was, you know, when you first went in for your simulation, that tumor may not be in exactly the same place anymore. I mean, it’s, there’s a lot of assumptions, and we always knew in radiation therapy that, you know, things could move. Things could happen.

Mark Malin: And in the perfect world, speaking about limitations of computers and time and everything else that I talked about on dose calculations, if you think about it, the perfect scenario is that the person lays down on the couch, we know exactly where the tumor is that day, and we treat exactly the tumor, and that the system will calculate the differences, saying, “Okay, they went to Taco Bell last night, they have a lot of gas in their bowels, and, you know, things are different now.” And the computer should really should be able to calculate that, so that we’re treating exactly the tumor. And we are finally getting there. We, I, we’re, I think that the world is super close to that. The speed of the dose calculations, the imaging in the room, a lot of things had to come together for this to be a reality.

Mark Malin: And so, with our products, you know, with the RayStation as the treatment planning, RayCare as our oncology information system, and then of course, whether you’re talking about a, a Varian delivery system, or an IBA, or Mevion delivery system, you really want to be able to get the images, figure out where everything is, send it to the treatment planning system, recalculate, figure out what to do that day, then the oncology information system sends it back to the treatment machine and says, “Okay, today Mrs. Jones is going to get this treatment, because this is where the tumor is.” That is, I, I don’t want to say the holy grail, cuz I think we could do even better than that, but I think that’s it’s a great, it’s a great time in technology, where we can do that.

David Raubach: Yeah, so for decades, just to kind of summarize that. So, for decades, we’ve tried to reproduce where the tumor was in relationship to the beam and the table and the patient every single day when the patient came in. So, in reference back to their original treatment planning CAT scan. So, however that patient was set up, however full their bladder was, however they were laying, however they were breathing, everything about that original treatment planning CAT scan, we say we have to replicate that every single day in order to get the beam where we want it to go. But, what you’re saying is, in the future, we don’t have to do that anymore, or even now we’re starting to experiment with this, with some machines and some disease sites, we’ll actually just do a new treatment plan each day.

David Raubach: So, we don’t have to completely reproduce what that patient looked like and how they were set up the day before. We’ll just plan that day on the table.

Mark Malin: Right. Now, there’s, there’s things that make that complicated, in the sense that, you know, when you start changing things up every day, you have to keep track of what that means over 20 fractions, over 20 days or 30, whatever the number of days are. So, the computer now has to say, “Okay, here’s what that CT scan looked like on day one. Here’s what the cone beam CT scan looks like from the machine on day eight. Compare the two, overlay the two, add the doses together, and let’s make sure that, you know, as we go out to the prescription, the total prescription of the physician, that we’re going to do what we thought we were going to do.”

Mark Malin: So, it can’t be, you know, it, I want to make sure that patients realize that there’s a lot that goes on behind the scenes to make sure that the total dose that they receive to the tumors and the organs at risk and everything else are exactly right. So, that’s why it’s taken so long to get here, David. It’s, you know, the computers just needed to be able to do all this stuff. And now we’re, it’s now we’re there.

David Raubach: So, one of the things that also is a challenge, so there’s this reproducibility of, of treatment each day, or reproducibility of the setup. But I’m, I’m a person, and I, I breathe every day, and even when I’m laying on the table getting treatment, I’m breathing. And so I try to hold still. But it’s possible that my tumor is moving a little bit inside my body.

Mark Malin: Right.

David Raubach: So, there’s this concept of motion management.

Mark Malin: Yeah.

David Raubach: And I know when you were working in, as a dosimetrist, and even now when you’re looking at treatment plans, you know, you might get a CAT scan, and it’s a 4D CAT scan where it’s showing motion over time, and you’re looking at it and you’re like, “Wow, that tumor’s moving a lot.”

Mark Malin: Right.

David Raubach: So, then what are you doing as a dosimetrist to account for that, to ensure that you’re still getting as much radiation to the tumor as possible and as little to healthy tissue as possible?

Mark Malin: Sure. And that’s another whole conversation in science, really. So, I also, for 3 years, I worked for a company called Civco, in hardware, which is patient positioning, and, you know, so, the thermoplastics that hold, you know, the someone down for a head and neck treatment, or, you know, a board that that someone’s laying on to stabilize them. So, I was involved in a lot of development on those things, especially for SBRT, which was stereotactic body radiation therapy, which is delivery of high amounts of dose over just a few fractions.

David Raubach: Mhm.

Mark Malin: And that’s very common, even in protons as well. We won’t even talk about flash, which is the future, of 1 second of radiation. But, and maybe I should say that flash in the future, if we can deliver radiation in a second, then we have to worry less about that motion, right? It’s about motion over a period of time that, that’s a challenge. So, there’s a few things to say. In protons, we use something called robustness. And a robustness in planning means that when we identify the target, what is the tumor, we look at what kind of motion is expected there. And then what we do is we we tell the system, “Hey, you know, this thing might move by a half a centimeter or a centimeter, and we’re not exactly sure that the density is going to be exactly right every day.

Mark Malin: So, when you do a plan, do a plan that if the tumor does move, that, you know, in this expected amount, that it’s still going to be treated okay.” And let’s let’s watch the other, you know, structures as well, like the organs at risk that we talked about. So, there’s a computer component that handles that. But then from a dosimetry perspective, from a dosimetrist’s perspective, and a therapist’s perspective, there’s a lot of interaction between the patient, between the immobilization equipment. You know, sometimes we just start and we’re like, you know, this is not going to work, because, you know, so we may have to remake a mask, especially if you gain or lose weight, and, you know, the, the immobilization equipment is no longer effective.

Mark Malin: So, that’s why, as a patient, you might, you know, hear a lot of discussion about, “Hey, we’re going to make a new mask.” Or, you know, “Let’s, you know, we have too much motion.” Or, sometimes there’s breath, breathing holds that we ask patients to do if they are able to do that. And then when we do the planning, the plans take into account that, “Okay, we’re going to look, only look at images when you’re holding your breath, and that’s what the plans are going to be done on.” And so, there’s a lot that goes into it, depending on where your tumor is.

David Raubach: And I’ll mention too, cuz this is a device that we have here at the proton center, we have a surface imaging camera, a 4D surface imaging camera, in the treatment room, and that is tracking the patient’s motion over time. And if gets, and if it gets out of a certain tolerance, then we can shut the beam off and get the patient set back up. So that’s another mechanism. And then I’ve also seen where you might actually put some type of belt or strap over a patient’s chest. So even though they are breathing, their chest isn’t moving as much. Like if you’re trying to treat a lung tumor, they would have a lot of motion. So I think the point with that is that you as a dosimetrist and then the radiation therapist are really working together to figure out the best way to deal with any tumor motion.

Mark Malin: And utilize all of those technologies, right? In some cases, the surface guidance works really well. In other cases, it’s more about the imaging, right? Because there’s no no absolute guarantee that the surface and the internal, you know, structures are in the same place. But if you use all of that information together, then all of a sudden you’ve got a good way to try and make sure that you’re always treating the the tumor, right? And as imaging gets better in the rooms, I, you know, and also even while the beam is on, you know, where, if the patient moves while the beam is on, that the patient, that the beam could be interrupted and say, “No, you know, stop. Let’s give the rest when the patient’s back in the right place.” These are all technologies that are, they’re, still developing. They’re not used all the time, but I think that’s where we’re definitely headed for sure.

David Raubach: So, another question I have, and this is, I’ll put you on the spot a little bit, because this may be a question that the equipment vendors would have to help answer as well. But one of the questions that we get is, how do we know that the right amount of radiation is getting to the tumor? And you’ve talked a little bit about calculating that dose, but that’s a concern. I’m a patient. I don’t see anything. I don’t feel anything. I don’t hear anything. How do I know that the right amount of radiation is getting to the right spot?

Mark Malin: Right. So that starts, you know, way at the beginning, right? So, the, when a treatment planning system, let’s say RayStation, is going to be implemented in a hospital, the physicists do a great job at measuring all the radiation in phantoms, which are then put into the treatment planning system. And there’s tons of research that’s done, you know, papers proving that all the treatment planning systems that are out there are safe, that the dose calculations are right. And then when you’ve got that all modeled up, then you start doing tests to prove that, there’s phantoms that, you know, you get from, you know, the, if you’re on a protocol, there’s, you know, labs out of MD Anderson that will send you a phantom, and then you expose that phantom to prove that the dose calculations were right.

Mark Malin: There’s the, the dosimetry programs, again from MD Anderson, there’s a couple different labs there where they send out these little crystals that, you know, are exposed on a regular basis, maybe annually, to prove that the amount of radiation that your machine, that you think is coming out of your machine, is coming out of your machine. So, there’s an ongoing daily, monthly, quarterly, annual quality assurance that goes into that component. When it comes to delivery, there’s always a step of secondary dose calculations, where, you know, RayStation says, “Okay, give this amount of dose.”

Mark Malin: And, but then there’s other products that are out there from other companies that will take that information, whether it’s the whole plan or just parts of the plan, calculate it outside of the treatment planning system, and then say, “Yeah, that’s, that’s right for, for these, for this setup, for this configuration, that’s the right amount of dose.” And then finally, on the delivery side, there’s a combination of things. There is something called EPID-based dosimetry, where you actually, you know, look at the dose that exits from the patient, and then you do an analysis to see if that’s what you expect. There are log files that are always recorded on all of these systems that say exactly what happened and when. In some cases, they’re calculated after the fact to prove that, you know, you did the right thing.

Mark Malin: But in general, you know, that that was a problem of the ’90s. It’s definitely not a problem these days. I think that the dose delivery, and even if the machine stops, if let’s say there’s a problem, a power surge or something that happens, all of these systems are checked, so that, you know, to prove that if the power goes out, that both the treatment planning system and the delivery system can recover when the power comes back on. So, you’re always going to get the right amount of dose. So, it’s it’s pretty good these days.

David Raubach: Yeah, with protons, you know, it’s like measuring water coming out of the water faucet. And we have, there’s even devices built into the actual delivery snout, these ion chambers that are, if you really want to dumb it down, it’s literally counting the number of protons that are coming out of the snout going into the patient. And so, talk a little bit more about dose, because you mentioned the term earlier in the conversation, you said 70 centigray.

Mark Malin: Mhm.

David Raubach: And so, when you say dose, or prescriptive dose, or centigray, what do all these words mean?

Mark Malin: Right. So, you have to have a a sort of a standard for what dose is, right? So, if a physician is going to write a prescription for a certain amount of radiation, there’s got to be a common language that, you know, that, that we’re using. And so, in medical physics, there are definitions, you know, gray, centigray. A centigray is a hundredth of a gray, which is a measurement, you know, which is a, I’m sorry, it’s a quantity of of dose. And then if I just go to the machine, I could say, let’s talk about photons, I could say, in, with this shape field, with the MLCs a certain way, if I give a certain amount of time where the machine is on, which we call monitor units, then I know in that configuration how much dose that is, in centigray or gray.

Mark Malin: And so, for each of these fields, I’ve got a way to know exactly how much dose is being delivered to the patient, and then it’s all of this, you know, beam time on, whether you’re talking about spots and protons, or whether you’re talking about monitor units and photons, where I can sum everything up and be able to report really correctly and carefully what is the dose that I’ve delivered to that amount of tissue that I’m targeting to treat. So, and that’s why the quality assurance and the modeling and everything’s got to be so correct, for the medical physicists, the dosimetrists, I mean, everyone’s involved in making sure that those those measurements are right. And I’ll mention, with that, that different patients get different dose amounts. And so, depending on the the type of tumor, where it is, the histology, how aggressive the tumor is, how responsive it is to radiation, you might get more gray, you might get less gray.

David Raubach: Now, I do have to ask you, protons are particles, and photons are a form of electromagnetic wave energy. So, they’re very different.

Mark Malin: Right.

David Raubach: How do we relate the two? I think there’s a, maybe a term called RBE, so…

Mark Malin: Yeah, so that’s another whole conversation, but, so, radiobiological effectiveness, right? So, and that’s the science. That’s a, that’s actually, you know, and then when you start talking about different particles, like carbon and helium, and so, it’s, you know, basically what happens is is that, you know, when you have a particle and it sort of comes into contact with tissue, in some cases, it may hit the DNA in a cancer cell and it may cause damage, or it may not, right? And depending on how big that, I’m going to simpli, I’m oh, oversimplified, depending on how big that particle is, it may have more or less of an effect, and it’s also going to bounce around, you know, within the body in a different way.

Mark Malin: So, it is, it’s a science that’s developing, and there’s biological models that are still being developed and being discussed, and how should we measure this? I mean, there’s even discussion now about, you know, maybe we should move away from these measurements or these these definitions of dose and go towards what’s their effect on DNA, you know, like, how, you know, when, and then it gets really weirder because, you know, if you think about, at least from a, as you were talking about, from patient to patient, certain cancers are more or less sensitive, so they’re more or less sensitive to the radiation dose for various reasons. It could be because there’s more or less blood flow to them. I mean, there’s so many reasons why the amount of dose delivered is going to, as you mentioned before, some patients have one field, two fields, three fields.

Mark Malin: Some will have much more dose because they’re, you know, the, the tumor requires it, and, you know, because maybe it’s a little bit farther away from healthy tissue. So, radiobiological effectiveness is really, it’s a function of the type of particle that’s being put into the body. And again, right now we use a a simple value of 1.1, but I think it’s going to change over time and be specific to tissue types. So, that’s a developing field as well.

David Raubach: So, you’ve touched on this before, and I think this is a good way to kind of tie everything together. AI. So, AI is very important. How are, how is that going to change, or maybe how specifically with RaySearch and your planning system, how is that going to change just everything about radiation oncology and the way it’s delivered and the way we think about treating patients going forward.

Mark Malin: Yeah. So, as I mentioned, you know, online adaptive is such, clears throat, a, an important thing, and it’s super important for us. So, AI, online adaptive, you know, developing some of these biological models that we’ve talked about, and and, all this imaging, and, you know, handling that, research is really focused. We have so many research projects that are related to this, you know, we don’t create hardware. So, our entire company is focused on software development. That’s really, you know, from a corporate perspective, if you say what makes RaySearch special, it’s the passion and dedication to, you know, patients and and doing the right thing, but it’s, we don’t, we’re not thinking about hardware. We only think about these algorithms, and we have something like 260 or 300, you know, engineers that are working on this, you know, every day that do an amazing job.

Mark Malin: But I think that it’s the combination. So, AI is going to enable much faster response to things, right? So, when it comes time to look at that day, where is the tumor that day, rather than a person sitting there and going, “Okay, well, yeah, that kind of looks like it,” or, “Let’s circle that,” and AI is going to take care of a lot of that. And then the physicist and dosimetrist are going to be less concerned about the little menial tasks that a computer can handle, and they’re going to be more involved in the case management and the deciding what’s the right way to treat the patient with the physician. Whereas AI is just going to optimize these these treatments.

Mark Malin: And then in the future, when we have other information, like, as you mentioned, histology, medications that they’re on, all of these variables, I can’t wait for the day when AI is just going to take all that stuff, so all the information in our oncology information system, and feed, and now we have a feedback loop that is going to make every treatment better, and every next patient’s treatment better. And that’s really where AI is going to take us.

David Raubach: Yeah, each person is like their own little large language model, in the sense that there’s like all these inputs. You mentioned what drugs are they on, that can impact how radiation interacts with the cells in the body. What other comorbidities maybe do they have? Have they had prior radiation? How old are they? What’s the genetic, do they have specific genetic mutations? There’s just so much data that goes in, and you have to have incredibly powerful, very well-trained software systems to process all of that, and then spit out a practical output that says, “Okay, well yeah, we have all this data, but this is what we can do with it for this specific patient.” And the harder it gets…

Mark Malin: And right now, you know, the physicians are the natural intelligence, right? Not the artificial intelligence. The physician, she’s the one that is, you know, using her experience based on what she knows, what she’s studied, you know, her previous patients. She’s the model of the decision-making on how to treat that patient. In the future, it’s going to be taking in a lot more variables, and then she and AI are going to make those decisions together. And I think that’s just going to be really the great way, because it’s, it’s very difficult to take all of these variables into account and draw conclusions from the thousand patients that I’ve treated, okay, how should I treat this patient? Why not take all that experience, especially the good experience, and then use that to train the systems to to do that again. And I think that’s where the future is for sure. And RaySearch is dedicated to that.

David Raubach: And that’ll give patients, or that’ll give physicians more time to just interact with patients, because that’s, that’s what a computer can’t do, is that relational element. And that frees up the physician to actually, to spend more time in the room with the patient.

Mark Malin: You know, it’s, it’s kind of a shame, you know, I think people are afraid of AI, you know, dosimetrists in particular.

David Raubach: Yeah.

Mark Malin: You know, oh my god, the computer’s going to do all this stuff, and I’m going to lose my job. Clears throat. But, you know, I was with Philips in 2000 when, you know, IMRT was being introduced. The arguments were the same back then. They were like, “You’re going to have automated optimization? Well, what am I going to do?”

David Raubach: Yeah.

Mark Malin: And what we learned was the, our jobs became more difficult. I mean, it was, you know, now you had to teach the computer how to do things, and it, our the work that went into it was amazing. So, I think in the future, everyone’s job is unfortunately still safe, and they’re going to be needed to, you know, come up with the plans and work with the patients and work with the medical experts on, you know, what’s the right approach, and, and, because we’re all still learning, right? I mean, we, now we’re getting new research that says, as an example, that head and neck treatments are effective, and you have all these things. So, there’s going to be new developments about what treatment techniques are are going to be needed, and you’re still going to need humans to implement those.

David Raubach: Well, this has been really good. I think this is going to be extremely helpful for patients. I can’t wait to get this out on our website and out for patients across the country to watch. I do have one last question for you. So, you’re the president of RaySearch America. You’re also the unofficial president of the Radiation Oncology Karaoke Association.

Mark Malin: Ah.

David Raubach: And I’m very curious about how that came about. So, I know that you’re the person that puts the karaoke sessions together at the national conferences. It’s, and sometimes we have 30, 40 people show up for it.

Mark Malin: So, I look at karaoke as it’s the ultimate, clears throat, human, snorts, exposure of weakness, right? None of us are expert, you know, musicians, or at least some of them, most of us aren’t. And there’s a real human side. I mean, one thing I really love about RaySearch, and I love about working with, you know, people like you, David, and, you know, people that are that take care of patients, you know, all, all of our, our academic partners, all of our hospital partners, is everyone really cares for their patients. And I think that the relationship between companies and clinicians should be strong. And so, you know, I, when there’s a problem, you know, you can call me up and say, “Hey Mark, you know, I know we sang Bohemian Rhapsody last night, but you have to help me with my problem today.”

Mark Malin: So, it just became a thing where we have to keep the human side going. And I really think that some of my favorite relationships were, are based on singing in front of each other and feeling comfortable doing that. I talked with our VP of finance here at the facility who went to NAPT in Nashville a couple weeks ago, and it was her first time going to this conference, and I said, “Oh, I’m doing a podcast later with Mark Malin.” And she kind of was like, you know, she’s still learning everybody’s names and who they are, and I I said, “Oh, well, he’s the president of RaySearch.” And she was kind of like, “Oh,” thinking about it, and then she was like, “Oh, he’s the karaoke guy.” And by the way, that was the biggest scary thing, right?

Mark Malin: Because when we went to Nashville, there’s so much great music. No one really wants to hear me sing, right? But we went to a nice place, and we sang in front of a crowd of people. It was tons of fun, you know?

David Raubach: And, uh, no, that was super fun. So, if you had to sing a song today, right now, you left today, what’s your go-to song?

Mark Malin: You know, I’m a big Billy Joel guy. I’m a big Billy Joel guy, and you know, I think all of his love songs and all of his, you know, if you watch, you know, he’s got this great way of looking at life in so many different ways, and he’s so human. So, I would say any of the Billy Joel songs. I would sing for you.

David Raubach: Is that, is that the next segment we’re doing? Is it going to, I’m going to sing a song? It’s live.

Mark Malin: Yeah, I know.

David Raubach: Yeah, we’re going to do it, but we’re going to live stream it. So, that way we’ll send out the invite for everybody. And then everybody can get continuing education credits for it, too.

Mark Malin: Yeah, I think I’m going with Blink 182 next time, because they, their melody doesn’t move up and down very much, and there’s plenty of guitar solos. So.

Mark Malin: No, you’re a good singer, David. Just remember that. It’s, it’s, if you’re willing to get on stage and have fun, that’s the most important thing, right? So, with karaoke.

David Raubach: Well, thank you so much, Mark. I really appreciate it, and thank you for everything that RaySearch continues to do, and for us at the Proton Center and for the industry, and I really appreciate your time.

Mark Malin: Now, I appreciate the opportunity, and I love sharing knowledge, and by all means, if there’s anything in the future that, you know, we can help us help educate patients, we’re always there for them.

David Raubach: All right, thank you so much, Mark.

Mark Malin: All right, thanks.

David Raubach: The Cancer Project podcast is made possible by the Oklahoma Proton Center, a state-of-the-art cancer center where precision in treatment meets real compassion in care. We’re grateful for their support and for you for spending this time with us. If you’d like to learn more about the Oklahoma Proton Center, you can visit their website at the link below. And if something you heard today resonated, we’d love for you to stick with us. You can subscribe to the podcast and follow along on our socials link below for more conversations like this, honest stories, thoughtful perspectives, and the kind of support people don’t always know where to find, but do truly need. At the end of the day, this podcast isn’t just about cancer. It’s about what it means to be human inside of it and how we keep living, connecting, and moving forward together.

David Raubach: We hope you leave each episode feeling a a bit more informed, a little bit more supported, and a lot less alone.