Hi, so in my first lecture, I talked about lung cancer screening. And one of the things I alluded to was that one of the downsides of lung cancer screening is that you're going to find a lot of positives. And those false positives usually occur as lung nodules. And fortunately for us, this is not a new problem. Lung nodules are extraordinarily common. Even if nobody ever gets lung cancer screening, this is not a problem that's going to go away. In fact, the vast majority of lung nodules will be discovered incidentally because we do, so many more CAT scans now a days for so many more reasons. And, we do CAT scans with far greater detail than we did even 10, 20 years ago. The CAT scanners give us more information with less radiation. And for a lot of reasons that's good, but we also have to learn to deal with the down side of these very sensitive tests. And most of the time that means lung nodules. There are going to be all sorts of incidental findings on CAT scans ordered for one reason that then disclose a problem somewhere else. In this case, we're going to focus just on lung nodules. And of course, if you're a patient and somebody says that you have a lung nodule, most patients will leap to the incorrect conclusion that they have lung cancer. And we will learn in a moment here that most lung nodules are not cancer. So one of the first objectives is to understand how you can assess the probability of malignancy in a given lung nodule very quickly by just some simple features. And we'll talk about the features of nodules that predict the higher likelihood of malignancy. And some of the features of the patients in which the nodules are found. So those are the major objectives of this brief lecture on how to recognize signs of lung cancer in a lung nodule. And for the purposes of this lecture, I'm going to refer to all lung nodules as if they were either found on purpose, with lung cancer screening or if they were found by accident what I like to call incidentalomas. So, let's start with a question. You're confronted by a patient who ask you what is the proportion of lung nodules detected on CT scans that turn out to be lung cancer? And you have to give them an answer, which is the following you can give your patient. Is it A, the probability of malignancy in a pulmonary nodule is 20%? B, the probability of malignancy in a pulmonary nodule is zero if you never smoked? C, the probability of malignancy in a pulmonary nodule is 10%? Or D, The probability of malignancy in a pulmonary nodule is less than 4%. So we'll go on, and learn about these. The first thing I'm going to do is we're going to go through some images, examples, and practice recognizing signs of lung cancer. And then, we have models we can use if we want to calculate the probability that allow us to determine from clinical criteria, that is, questions you can answer sitting in the exam room with your patient. What is the probability of cancer? And more importantly, what do you do with this information? So, I'm going to start with an exercise. And in each of the next few slides, two lung nodules that are found on CT scans, and you'll see some similarities and some differences between these. And simply think to yourself, A or B, which one of these is more likely to be cancer? And when you think of that, ask yourself, why you chose that? So, we're going to go through this exercise, two modules, one is more likely, one is less likely, and ask yourself, why you chose the one that you chose? So, example first one, module on the left A or the module on the right B. Which of these two modules, and I'll point them out for you here, And here, which are more likely to be cancer and, more importantly, why did you choose that? Another example, here is a nodule, here, and here. And think to yourself, which of those is more likely to be cancer and, more importantly, why did you choose that? The next example, two very similar appearing nodules. This one just above the diaphragm in this right lung here and this one here. And they look the same, but the difference is one is in a 65 year old man, the other is in a 32 year old man. Which of those is more likely lung cancer and why did you choose that? And lastly, again, two two similar looking nagles. About the same size in the left upper lobe here. About the same size, kind of odd shaped. One is in a 65 year old heavy smoker. The other is in a 64 year old non-smoker. Which of these two is more likely to be cancer? And more importantly, why did you choose that one? So think about what you did for those last four examples. Which features did you use to guess which one is more likely to be cancer? Now, it doesn't matter whether you got it right or not, but most of the time, you probably hung yourself thinking about the things like well, how big is it? Indeed size does predict the probability cancer very effectively, regardless of how old you are, regardless of your smoking history. The size of a nodule is a very good factor in predicting the probability of malignancy. And you may have seen two nodules that were very similar but one had kind of fuzzy spiculated edges, whereas the other comparison nodule was relatively smooth. Edge characteristics: spiculation, lobulation, as compared to something that's nice and smooth and round are very, very strong predictors of malignancy. Lung nodules that are very smooth and round are very unlikely to be cancer, whereas nodules that you have a hard time picking out the edge because they're speculated or perhaps infiltrating the tumor. Rather the tumor's infiltrating the lung around them cause it to be very difficult to trace the edge of that module. These are characteristics more likely to be found in a cancer. None of these are 100%, but what we're doing here, is we're building a story in our head about the probability of cancer. And you can think of this, and I'll show you a picture in a minute. As a pendulum swinging towards one side of very unlikely to be malignancy, into the other side of very likely to be malignancy. And then I did show you some examples where the nodules looked identical, but one was in an elderly person, or a more elderly than the other one, and of course age is a big predictor. If you're an older person with a given size nodule, it's much more likely to be cancer than if you are a much younger person with the exact same nodule. And finally, tobacco history. We know that lung cancer is a disease largely caused by tobacco use, not exclusively but almost exclusively. And so a given person who's a smoker is much more likely to have cancer in that nodule than a person with an identical-appearing nodule who's a non-smoker. We're talking here about probability. Not diagnostic characteristics, but probability. Now, as it turns out, there are a number of models out there, some of which were developed many years ago. And really, even with time and with technology, we haven't improved much upon this one, which was published. Almost 20 years ago now. And this was largely done on nodules found on chest X-rays, but it really still holds quite well today. This is what we call the Swensen model, it was developed by some investigators from Mayo Clinic. Steve Swensen was the lead investigator on this. And they found that age, smoking history, size of the nodule and edge characteristics were great predictors of malignancy. And there are two further characteristics that aren't quite as obvious, but if you have a prior history of cancer, what that tells us is that your genetics are capable of resulting in the development of cancer. And if you have a prior history of cancer, then any given nodule found on a chest X-ray or CAT scan imaging, is more likely to be lung cancer. Not because it spread there from other cancers, but because individuals who can make one cancer are capable of making another. And finally, the location of the nodule in the upper versus the lower middle lobe. It turns out that more cancers appear in the upper lobes than the lower lobes and each of these appears in what we call the Swensen model. Three characteristics of the nodule itself three characteristics of the patient, each of which independently predict the probability of malignancy to various degrees. These are the four that we identified by the exercise that we just completed. These last two are a little less intuitive but clearly strong predictors both in the Swensen model and more recent models that were updated to include additional information that you can really only get from a CAT scan. This model applies to people with chest X-rays or CAT scans and ideally you can use any one of them. The point is that we start out with every patient and when we find a nodule with this pendulum that sits somewhere in the middle. And a younger patient with the small nodule that is smooth borders. That pendulum starts to swing towards this side of the scale. Towards what we ultimately want to get which is its definitely benign. Now, none of these features can get us to the extremes of this arrow. But all the things that we just talked about, age, size, the border of the nodule. The smoking history, the location of the nodule, and finally what we haven't talked about yet, which is another radiographic test called the PET scan. It's actually a nuclear medicine study, is very effective in helping swing this pendulum Towards or away from one end or the other of this scale. So, why do I use this scale? Well, in my mind I've got three large zones that I'm trying to ultimately get the patient into, because in each of these zones we have a separate strategy for how to deal with the nodule. One of the things I always tell my patients is that if you've got a nodule my job is to prove it's not cancer and I really only have two tools that can prove it's not cancer. One is take it out and that involves having you go to a surgeon and having a part of your lung removed and the pathologist then looks at the nodule under a microscope. For some people that's the appropriate test but the other is time. Obviously, these are two very different strategies: lung surgery and time. Time involves doing multiple scans over a period years to prove the nodule doesn't behave like a cancer. Watching the behavior or removing the nodule are the only two tools that I have in my kit to prove that a nodule isn't cancer. In the end, if those two strategies are so different, I have to have clinical tools that point us in the right direction and these are the clinical tools. So at this very low probability end, if I can swing that probability down here with just clinical features, all I do is tell the patient. I'm going to reassure them, we're going to prove it isn't cancer and we're going to do it by showing this thing doesn't behave in a sinister way. On the other hand, is I evaluate the patient and the pendulum moves up here. I'm going to be much more interested in getting aggressive, perhaps referring the patient to surgery or doing other tests to find out whether this is cancer. So it's easier to prove something is a cancer than to prove it isn't but we start out with this clinical picture in our head. What's the pretest probability? What do we do with this probability? Big deal, we've done all our history taking and we've reviewed the scan with the patient. We've reviewed it with our radiologist, and there the pendulum sits in one of these three zones. What do we do? Well, this is where it actually gets, I think, easier. The hard part, is getting to this step. When I get to this point, where I have that probability, to the very low, very high, and everything else in between, then we can talk about where this cutoffs are, but that's less important than the general ideas in our head. At this low end when we have a low probability I refer to this as the Fleischner Zone. And the term Fleischner comes from the Fleischner society which years ago came out with recommendations on how to help us deal with all of the long nodules we were finding. All the incident along we were finding with a more sane approach. In other words, rather than doing scans every three months what the Fleischner Society really succeeded in doing is showing us how to prove a nodule was benign with fewer CAT scans. And that's good. Patients don't want the radiation. Their insurers don't want the cost. And we don't want to have to put patients through unnecessary testing. So the Fleischner zone simply tells us that we can follow these lung nodules with pre specified intervals of follow. Look at the cat scan and show that the behaviour of the nodule is not that of a malignant process, in other words it's not growing. For the vast majority of nodules, and here's where this number comes in. Most of the nodules that are discovered nowadays far more than 95% of them are not cancer, that's even true in smokers. Now on the other hand, you've got this middle zone and this is what I call the PET scan zone. The PET scan is a test I referred to earlier, but other than taking a history, it is the one test that is the most effective at pushing that pendulum towards one end of the extreme or the other. Now, the PET scan is one of the most useful tests in our armamentarium. It's also one of the most misused tests and so I think it's important to understand that you cannot diagnose cancer with a PET scan. And you cannot exclude cancer with a PET scan, it simply moves the pendulum in the right direction. So now, we've got what we do with the people in the low end of the probability. We've got the large group of people in the middle. What about these people that have a nodule that looks really, really concerning for cancer. This is also PET scan zone. But why I am I doing the same test here? Why do I have two zones? The difference is that in this high probability zone, I have already made the decision that I think this is cancer. And in this case, I am using the PET scan for it's other purpose which is to stage the cancer. A PET scan is two tests in one and because it is two tests in one, it has two sets of performance characteristics. One test that you get when you order a PET scan Is simply, what is the probability of cancer in this indeterminate pulmonary nodule? The other test that the PET scan provides you is, if this is cancer, what's the possibility that is spread to the lymph nodes, or to the liver, or the adrenal, or the bones, or some other part of the body? There, it's a staging test, so you really get two tests in one when you order a PET scan. They're expensive, they're hard to get, they take time to do, but they're very useful if you know how to use it or, more importantly, if you know how not to use it. So, each of these zones has a strategy, the Fleischner Zone for low probability nodules PET scans for staging high probability nodules. And PET scans for intermediate probability, to move that pendulum towards one end of the extreme or the other. So, after all this talk about a PET scan and a few moments about what it really is, you take fluorodeoxyglucose, which Is taken up in metabolically active lesions in the body. So infections can be metabolically active and light up on a PET scan. Granulomas can be highly metabolically active but tumors and the utility of the PET scan is that tumors use a lot of sugar. They take up that sugar and they emit these positrons and the positron detector localizes the uptake of the sugar. And combines that with the radiographic information, so you get anatomic metabolic correlates of where the tumor may actually be. And here you see, an unexpected tumor in the neck of this individual with a history of cancer. And the PET scan here disclosed unexpected metastatic disease that was not detectable in routine routine imaging, and not detectable by physical exam. So again, the PET scan is 95% sensitive for detecting many times of malignancy. Not all of them, but it has a very high false positive rate, particularly with enlarged mediastinal lymph nodes. False negatives, very common, and what we call ground glass lesions in the lung. They're also common in small legions. The smaller you get, the less useful the PET scan is. So when a nodule in the lung is less than ten mm in size, the utility of the PET scan starts to fall off. There are also other features, such as where in the lung the nodule is localized. In the upper lobe, it tends to be very good, because the upper lobe doesn't move as much. It takes about 45 minutes to record the data on a PET scan. The lower lobes, because of the diaphragm, are moving so much, that they can, if you will, wash out. The activity on the pet scan can give you a falsely reassuring appearance. So a good experienced nuclear medicine doctor will take these things into account. When they read their PET scan and you should to take these things into account as you are interpreting these results of the PET scan. So the take home points from this lecture, is that features that one can take about the nodule, from the CAT scan, as well as clinical features about the patient, can be combined. And used to estimate the probability of malignancy in any pulmonary nodule and this probability helps you to determine the next step. So very low probability nodules should be followed up long term. We can reassure our patients of the low probability. The PET scan is useful for intermediate probability nodules at segregating that nodule into high versus low probability. And again, for very high probability nodules we're talking about staging what seems to be very likely to be lung cancer. And in that case, the PET scan is a staging test. The PET is a very useful test with a high negative predictive value for nodules that are generally over 8 mm, depending on where they're located in the lung. So back to our original question. The patient asks you, what proportion of lung nodules detected on CT scan turn out to be cancer? What is the correct answer? Is it 20%? Is it zero, if you've never smoked? Is it 10% or is it less than 4%? And as you've heard during our lecture, the correct answer that even in heavy smokers the probability in malignancy is somewhere less than 4%. Use this information to reassure your patients.