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So welcome to the third section

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and this is where magic happens.

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We are going to be looking at reading of the PSMA PET scan

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and I'm gonna be taking you through how I set up my images,

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some tips and tricks that I use,

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and then working through some um, normal study.

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We're working through a normal study

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and then a very straightforward case

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before in the upcoming sections we work into some more

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challenging cases with more widespread disease.

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But the first thing to consider here is

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how does your institution look at nuclear medicine images

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and what we will find here as we work through.

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So I've taken some screenshots of my viewer.

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I use MIM seven and my workplace.

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Um, we also have another client which

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we can use fusion images.

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And what I've uploaded into the live cases

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that we'll be working on through the arm reviewer, um,

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is some fused stacks

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but also what we call the functional data as well

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as the low dose ct.

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And ideally if you're working through these,

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you want a software which does the fusion,

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which you can adjust the intensity of the PET data

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or the functional data to help you know with your viewing.

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And we'll see why that's important

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in some upcoming sections.

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So we need to think about the intensity of the uptake.

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We need to think about how the fusions work

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and how you can manipulate them

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as you work through the images.

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Um, and also how you display dynamic data.

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We don't have any more dynamic cases, um,

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as we saw in the end of the last module,

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but if you do have um, dynamic PSMA pet, it's important

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to think about how you will display them.

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So we think about the information that we have.

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Um, so we have the PET or functional data

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and then the low dose ct.

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And then how do we bring in comparison imaging?

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So here is um, a screenshot from my workstation.

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So we have our low dose CT data here,

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which then takes in PET SWB is our

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attenuation correction PET data.

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You'll see that there's uncorrected data in there as well,

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which is non attenuation correction.

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Um, I use that to troubleshoot sometimes,

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but it's not part of my standard read.

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I pick my pet CT viewer

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and then this is just how I go through and load it up.

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And then we get a display of the pictures.

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So I think about how I like to display my pictures.

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I sometimes create my own workstations so,

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or my own work displays.

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And here you can see that I'm thinking about bringing in

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the functional data.

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So across the top and then I'll bring in a

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rotating MIP as well.

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And then I will bring that through and then create that.

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And then I also wanna have a comparison image

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for looking at the pet data on its own

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and then also the fsed data and then the low dose ct.

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And I'll bring in a sagittal reconstruction as well

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as the axial.

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Um, but if I'm looking at this in my standard workstation,

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which is often on two screens, um,

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I'll have the coronal data

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as we can see there on that first workflow.

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So I can tab between these

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and this will really help me with reading.

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Um, I think don't be afraid to look at different planes

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of your imaging as well.

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A great pearl that I got was not to ever forget

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that humans are three dimensional structures.

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Um, so we are not just trans axial.

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So I will constantly be moving in between the axial

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Which is here, um, sagittal, um, coronal,

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and then also really relying quite heavily on the rotating

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MIP to get a bit of an overview of my patient.

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So you heard me mention on an earlier stage

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that we're thinking about SUVs.

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So that's our standardized uptake value.

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And this is a semi-quantitative measure

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of the tracer uptake in a specific tissue

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or specific region of the body.

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And so we, that's why we

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weigh the patients when they arrive.

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We also take their height so we get a bit of a sense of, um,

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the size of the patient

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and the amount of tracer that we are injecting.

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'cause we know exactly how much in megal that

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or milli curie that we've injected.

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And then the scanning equipment will adjust this

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for the delay and then give us a semi quantitative

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standardized uptake value.

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So it is essentially a surrogate measure for the amount

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of PSMA expression in tissue.

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And this is goes across all PET scans.

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So if you were doing an FDG pet,

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it would give a surrogate marker

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for the glucose metabolism in a tissue.

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If you're doing dotatate pet,

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it would give you a surrogate marker for the amount

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of somatostatin receptor expression in a tissue.

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Um, and in this case we're looking at PSMA

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and one thing to kind of consider is

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that this SUV range similar to CT windows is adjustable.

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So I'll show you a range.

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So if we look at SUV max as our viewing window, zero

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to five, um, the liver and spleen and the bowel

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and the kidneys look quite black

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and then zero to seven, which I typically read on zero

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to seven, but that's a little warmer

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or a little bit more toasty than some

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other my colleagues do.

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They'll read on zero to 10 or sometimes even zero to 15.

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And I will actually move

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through these ranges depending on what tissue I'm looking at.

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So my standard look through is usually zero to seven,

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and then I'll turn it down to zero to 10

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or zero to 15 to look through the liver

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and kidneys, um, and spleen.

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Um, as you can see there, they're less, um,

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black on those higher images.

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And here we go. Here's another one at zero to 20 as well.

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So you can see that making those adjustments,

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you can really highlight the difference in tissues exactly

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as we would with a CT window.

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And here's a few examples of color displays.

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I typically read on warm metal.

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I used to read on hot body and it just depends on the site

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and what you are used to using.

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And Pet rainbow I do use as well, I tend

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to use pet rainbows for brains.

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Um, but one of the sites I trained at,

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I'll use Pet Rainbow for all their pets.

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Um, so it really just depends on

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where you feel most comfortable.

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But one thing I will say is don't

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forget the black and white data.

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There are so many more shades of gray, um,

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and derivatives of gray than colors.

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And so you get a lot of range of data in a single image.

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Um, and I actually find, especially when I'm looking

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for small nodes or you know, punctate, foci of uptake

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or small lung lesions, the black

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and white data, going through that

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and scrolling through that can actually be really useful in

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terms of sensitivity for detection of lesions.