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[Music]

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Welcome to our next interview in medical

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physics. In this interview we are going

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to meet Amit. He is a postdoctoral

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researcher here at the German Cancer

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Research Center in the Division of

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Medical Physics in Radiation Oncology. As

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you can see here we are on the second

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floor of the building Imaging in

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Radiation Oncology of the German cancer

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Research Center and on this floor mainly

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the researchers and students are located

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and have their offices.

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Let's go and pick up Amit. 

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[Music]

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Let's see if he is here. 

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Hi Amit. Hey. Nice to see you. Thanks

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for your time. Absolutely. I have just mentioned

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that you are a postdoctoral research in

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our division, maybe you could just

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introduce yourself briefly. 

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Hi, my name is Amit, I'm a

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postdoctoral researcher within the

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radiotherapy optimization group and

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we work on generating treatment plans

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for 

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radiotherapy. Okay, I think we

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start our discussion in more detail in

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our open seminar room in order not to

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disturb the rest of the group. So let's go. 

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Why did you choose the

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DKFZ for your uh PhD? 

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So firstly, it was a very interesting

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topic that I had gotten for my PhD

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and the radiotherapy optimization group

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over here at the DKFZ had this

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combination of specialities in so

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many different topics like biology,

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radiobiology,optimization, mathematics,

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and all of this played a part for this

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subject and for this PhD topic.

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So it was not really a

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big question as to saying yes or no. 

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We have prepared here this so-called

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radiotherapy chain in order to locate

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your research on this workflow. You will

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talk about your research in a

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second but to start with: where

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would you locate your research on this

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chain? Okay, the radiotherapy

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treatment planning process is one

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important ring of this chain already

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and this happens when the patient comes in,

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they've been imaged and doctors have

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already delineated the organs that are

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important for the treatment. And now

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comes the question of how do we deliver

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radiation, so what is the machine

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parameters, what are other technical

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challenges that might be there in

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delivering this treatment, and this is

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modeled in a computer and you can

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optimize this system, you can

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already analyze different options but

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all of this falls under treatment planing. 

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Okay then I think you mentioned you work

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with a computer let's go to your laptop

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to see more details. 

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Could you just walk us through

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the topic of treatment planning and

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optimization. Absolutely, so what

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I've put up over here on screen, on

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my laptop screen what you can see here

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is the matRad system. It's an open-

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source treatment planning system that

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our radiotherapy optimization group

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here manages and

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maintains and this is open for

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researchers or students to explore and

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use and what you see here is a liver

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patient case. This is a volunteer.

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We've taken a CT and the doctors's gone

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ahead and identified the liver for us.

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That's what you see in the blue contour

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here. Now we've designed a hypothetical

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tumor that we want to treat. That's the

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blue case

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here

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and we want to

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deposit a rather high amount of

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radiation dose within this target volume

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while reducing the amount of dose to the

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surrounding healthy tissues, right. That

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is the aim of radiotherapy.

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And

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in this toolkit of radiotherapy

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we have photons for example. So, these are

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high energy x-rays and they would look

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like this: an individual beam of photons

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would look like this passing through the

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body and as it's passing through the

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body like when you get an x-ray of your

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arm for example it's depositing dose as

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it goes through, right. Now in order to

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cover the whole region we could use a

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combination of such individual pencil

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beams

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right and that's what you see

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here. But if you notice what happens is

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you have a high dose where the beams

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coming in and as it's going through it's

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depositing less and less dose, so it's

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sloping downwards and if we want to give

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a high amount of dose here we have to

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give really high amount of dose to

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the healthy tissue at the start.

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So, in order to avoid this what we can do

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is then include multiple beams, right. 

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In this situation I've calculated a

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plan with five

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beams right, and

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they add up and over here what you see

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is that the red region is where you have

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the high dose and the blue region which

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is closer to the other healthy organs is

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where you have the lower dose, right.

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But in the clinic for example this plan

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might not necessarily be acceptable

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because over here if you see there's

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this one beam. The structure you see

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here is the spinal cord. 

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That's a very sensitive

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organ and a very important organ. So, you

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want to deposit as low dose there as you

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possibly can and in order to do that

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what you could do is for example you

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could shift or use a different beam

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angle or you could reduce the intensity

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to reduce the amount of dose delivered

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by this beam, right, and all of these

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little tradeoffs and exchanges that you

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can do is what our optimization

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algorithm takes care of and how it knows

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to do this is we create a mathematical

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objective function, so this is

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converting the requests of the clinic as

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to how much dose should this organ get.

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You convert that into a mathematical

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function and in optimizing that we get a

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dose distribution something like this.

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So we understand your research

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but why do we need your research from a

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patient perspective? Why is it so

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important what you are working on?

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When we're giving radiation we need to

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know it is the best possible thing

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because one is: it is going to affect

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healthy tissue that is passing through.

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So, we need to find a way to deposit as

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low dose to the healthy tissue as

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possible

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and in order to do that we need to

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understand what are the limits and what

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are the constraints that we're working

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with and doing this in an optimization

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framework assures us or guarantees us that

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it is mathematically at least the best

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deliverable plan for this patient

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Thanks for your information

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about your topic and about treatment

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planning. But what are

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other parts of medical physics, what are

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the most fascinating

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parts for you?

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I think for me in my topic especially

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with treatment

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planning the interesting parts is that

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there's an overlap of so many different

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topics and

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subjects. There is physics you know,

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there is mathematics in terms of

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optimization

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algorithms, there is biology in terms of

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understanding

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how you know tissue reacts to

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radiation, and so kind of having all

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of these moving parts in this complex

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system and really understanding and

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exploring it and trying to figure out

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solutions that would help people you

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know that is, I think, that is a

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really rewarding job I think. 

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[Music]