Interactive Transcript
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In this lecture, I will talk about how
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coronary stents are imaged, particularly
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the nuances, uh, for imaging stents.
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Now, coronary stents are controversial,
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but for the purposes of images, that's
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not so important to, um, understand.
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What is important to understand is that, uh, though
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they come in all shapes and sizes, uh, two things.
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Firstly, size is important.
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If the stent is less than three millimeters,
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it becomes very difficult imaging it.
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If the stent is greater than three millimeters,
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our chances of imaging it are greater.
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Stents have different types of material,
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some of which can barely be seen on CT.
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So clearly, if that's the case,
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then that makes life easier.
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But I'm talking about stents that have
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a great deal of metallic component.
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And here are some examples.
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I know examples of the quality.
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You can see that three very different stents over here.
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The one on the left, A.
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The quality is good, you can see inside the stent,
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the one in B, you can kind of see inside the stent,
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but the one in C, you know, all bets are off.
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So the marker of stent imaging is being able to
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see through that stent strut, inside the stent.
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And when done properly, you can have an image as
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nice as this, which carries multiple stents and
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you can see the opacification, it doesn't change
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very much prior to the stent and going into the
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stent, and you can see with great confidence.
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The stent is patent.
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In other scenarios, you have a situation where though
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the image quality isn't great, you could still say
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with some degree of confidence, as in this case where
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inside the stent you really see a very low attenuation
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area, which is, uh, suggestive of stent occlusion.
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But stents have problems and the three
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problems with the stents all arise
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with the fact that the stent has metal.
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And because the stent has
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metal, it creates an artifact.
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The metal, what it does, it reduces the
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transmission of X-rays so that only those X
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rays that are really strong can go through
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the metal, and that's called beam hardening.
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And beam hardening means that only the strongest
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of the X-ray beams can get through the metal.
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And once the strongest of the X-ray
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beams goes through the metal, it gives
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a false sense of a lower attenuation.
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Metal can bloom, meaning that it can look larger than
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it actually is, and the net effect of all of this is
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that the stenosis gets inflated, which means that our
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specificity for detecting critical stenosis is reduced.
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So how do we reduce the artifact?
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Any consideration of stent imaging, you have to think
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very much about the nuance of the stent imaging.
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Well, first and foremost, every good
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practice for cardiac imaging must
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be adhered to when there's a stent.
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So we must control the heart rate to preferably
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less than 70, particularly if there's a stent,
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because whatever suboptimality that occurs
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in a normal CT will just get exaggerated
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when there's a stent.
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So first and foremost, you want to have good contrast
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dynamics, make sure that you have heart rate control.
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Other things that one needs to
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think about, one is raising the KVP.
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KVP is often set as a default in many places.
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And that default may be 100 KVP, which
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is the default for vascular imaging.
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So you have to raise that to 120 KVP.
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We obviously need to use thin sections.
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This is for
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metallic stuff anywhere.
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However, for coronary imaging, we are
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going about as thin as we can, and I don't
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think that's going to go much thinner.
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So that leaves two methods.
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One is using a sharper kernel, and the
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other one is iterative reconstruction.
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So that's within your control, the sharper kernel.
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The iterative reconstruction actually
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depends on the, um, CT platform.
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So before the acquisition has been made,
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be careful to make sure the KVP is 120.
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After the images have been acquired, then
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ensure that you're using the appropriate kernel.
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So what is a sharp and what is a medium kernel?
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A kernel is a kind of reconstruction algorithm that
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is a trade-off between two types of resolution.
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One is the soft tissue resolution, the ability
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to tell different tissues apart, different
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tissues of similar attenuation apart.
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And the second thing is spatial
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resolution, particularly edge definition.
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And it would seem that in coronary imaging, soft tissue
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resolution is more important, and it is, but it comes
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at a penalty that you don't get the edge definition.
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And as these things are almost always
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opposing forces, sometimes you get too much
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soft tissue contrast without enough edge.
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So here are three images.
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Image A shows you a reconstruction with
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a soft tissue kernel, image B shows you a
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reconstruction with a sharp kernel, you can
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instantly see the difference between the two.
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It's very important seeing the edge of the stent,
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because if you don't see the edge of the stent,
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how will you know where the lumen begins and ends?
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And if you don't know where the lumen begins and
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ends, how do we know what's stenosis, what's not?
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So a sharp kernel instantly
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gives you that edge definition.
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Image C is actually a sharp kernel
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bolstered by iterative reconstruction.
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That bolstering has made a little bit of
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an effect, but I'd say that the biggest
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effect came from going from A to B.
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Another set of images.
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Again, the purpose here is to show you
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the incremental gains going from soft
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tissue, which is A, to sharp, which is C.
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D is sharp plus iterative
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reconstruction, which is the best.
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And in D you really can see through the stent.
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You can see through the stent in C as well.
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You can do a soft tissue plus iterative
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reconstruction, which is B, but that's not going
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to give you as much as the sharp is.
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So two methods.
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Used concurrently, are more powerful than used singly.
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But of them, the sharp reconstruction
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is the most important one.
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And, um, often you can get a sense
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that there is a high-grade stenosis.
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If you look at A, you'll see that the top half where
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the arrows are pointing is of a lower attenuation.
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The bottom of B, by virtue of simply that you can
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infer that there is a, because there's
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a gradient, there's an attenuation
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gradient that there's a high-grade stenosis.
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But it's made much clearer in C and
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confirmed by a catheter angiogram.
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Thank you.
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