Imaging and Response Measurement
Lung Cancer Imaging, Debate and New Issues
An interesting article from Japan was published out in the Journal of Thoracic Oncology that asks how long a duration of follow-up imaging of a ground-glass opacity (GGO) is really needed to be confident it’s going to remain stable and not grow. It’s very common to see small lung nodules that are ambiguous in their significance, for which follow-up scans are typically recommended rather than diving into a biopsy, and non-solid, hazy GGOs are another form of lung lesion that might possibly represent a lung cancer but are also the way a little inflammation or small infection would appear. Even when they turn out to be something technically called cancer based on its appearance under the microscope, it’s often a non-invasive adenocarcinoma (sometimes termed bronchioloalveolar carcinoma, or BAC, but shifting in terminology to adenocarcinoma in situ, or AIS) or minimally invasive adenocarcinoma (MIA), in which the invasive component is less than 5 mm in diameter. Even when they grow, it can be at an extremely slow pace.
I’m completing a chapter in a key lung cancer textbook on managing multi-focal bronchioloalveolar carcinoma, a clinical entity that is in the process of being re-labeled lepidic predominant adenocarcinoma (LPA) (lepidic meaning scale-like, which is the classic way that the cells are defined as spreading when looked at under a microscope). I suspect that it will continue to be called multifocal or advanced BAC for a long time (after all, the formal staging of small cell lung cancer goes from stages 1 to 4, but nobody ever uses that, classifying it as just limited or extensive stage).
When asked to write this chapter, I faced the challenge of there being very little actual hard data on managing multifocal BAC. Though many experts have a very similar approach, this is actually based on expertise, good judgment, and clinical experience more than data we can point to, and I don’t think this approach has ever been articulated in a scientific paper or book chapter, so I’m hoping this will be a valuable addition to the literature.
As I reviewed the papers out there, what struck me most are two things:
1) There is incredible variability in the appearance and clinical behavior of what is called advanced BAC in the clinical world — some of it is aggressive and imminently threatening, and much of it is very slow growing and among the least threatening cases ever labeled as lung cancer.
2) People with a very slow growth rate are likely to do very, very well no matter what treatments they get, as much despite as because of those treatments. In many cases, interventions are pursued on patients who are destined to do very well, and then when their short term survival is good, the people who did that intervention write a paper saying how their approach is feasible and attractive because the patients did well — not recognizing, or at least glossing over the idea, that they were going to do very well anyway.
I would say that in no other area of lung cancer care is it more important to distinguish between what can be done and what should be done. And the real experts know when to not intervene.
So here is the algorithm I developed, which isn’t beautiful, but you can see that it focuses on seeing what is actually changing rather than treating reflexively based on a label on a pathology report or single a scan finding. Essentially, it says to try to avoid intervening at all unless or until you see clinically significant change (which I would consider as something that is readily apparent as progression on scans done 6 months apart or less), and then if you see progression, clarify whether it’s limited to one lesion or progressing more diffusely in multiple areas.
Malignant pleural mesothelioma (MPM) is a challenging cancer to treat for many reasons, one of which being the difficulty in assessing whether there has been any meaningful change in the volume of a cancer that doesn’t tend to appear as a discrete mass, but most commonly as thickening of the pleura, the lining around the lung that is normally a thin, onion skin, but can thicken to be more like an orange rind or even thicker. We can often see this pattern in some people with lung cancer who happen to have a form of the disease that also primarily appears as pleural-based deposits of cancer.
Here’s a post I did for another site about this issue of imaging to assess response in MPM. I hope it’s helpful to those of you with pleural-based disease.
As a second part of a recent video I did that introduces the concept of a mixed response in lung cancer (or many other cancers) and how we might manage that situation, I wanted to cover the biology of what is presumably occurring. Here’s a video that covers this issue, as well as the implication that we can learn more about this by doing multiple biopsies, more than is considered as the typical standard now.
The question of whether and how to use blood tests, and particularly serum tumor markers, to monitor the status of a lung cancer has come up often here. There are a few places where we’ve covered this in text, but for those of you who would prefer a video format for your information gathering, here’s a podcast I just did on that subject for Swedish Medical Center.
Here are the 5 presentations at ASCO in stage I-III NSCLC and small cell lung cancer that I think are most interesting and relevant. You’ll note that several are “negative” trials — blockbusters are hard to come by here — but even trials that tell us what not to do are important. And there are some hints of new approaches that could improve outcomes for patients.
We know that there is a big difference between a lung (or pulmonary) nodule and having cancer. Formal screening studies or just random CT scans done for other reasons will often show nodules that are of questionable significance, leading us to recommend either follow-up imaging or an immediate biopsy, depending on the level of suspicion. Often, the biopsy gives us an explanation for the nodule: perhaps cancer, but otherwise, perhaps just inflammatory or scar tissue, or else infection. That answer is usually the right answer, but not always. There is a chance that a result that comes back as “not cancer” is actually a false negative result: this happens there is actually cancer, but the correct answer wasn’t detected. What are the features that suggest a greater probability that we can’t necessarily be as confident of a biopsy result that comes back as something other than cancer?
We can get some insight about this question from the published experience from the radiology groups at Cornell University and Mt. Sinai Medical Centers in New York City, who just published on their results of the clinical and imaging features of their false negative CT-guided biopsy results over a three-year period from the beginning of 2002 to the end of 2004 (Dr. Yankelevitz, who has great experience as an expert in CT screening and biopsies and who did a terrific webinar for us on detecting and evaluating lung nodules last year, is the senior author of this paper). To do this, they reviewed the results from 170 patients in that interval who had an initial biopsy that was reported as negative initially who were then either found to: