When people ask me what kind of research I did during my PhD (and indeed what kind I do now), I tell them I did MRI methods research. But what I do is very different to the image that comes up in people’s minds when I tell them this. I don’t build radiofrequency coils for MRI scanners, nor do I write MR sequences or even develop new analysis methods. I spent the majority of my PhD making small, incremental changes to the way MRI data is acquired and analyzed, and then testing how these changes affect how we measure certain things in the brain.
This type of research exists within what I consider a spectrum of phases of clinical research (NB: this has nothing to do with the phases of clinical trials of interventions – it’s only “clinical” in the sense that the research is being done on humans):
1. New methods are developed
2. They are validated by testing how well they perform in certain settings and improvements are made accordingly (followed by more validation).
3. Then, when they’re good and ready (this can take years), they’re used to answer clinical or biological questions.
People often neglect the second phase – the validation, improvement, and re-validation. It’s sometimes completely overlooked, but arguably the bigger problem is that it’s often conflated with the latter stage – the testing of clinical or biological hypotheses. The line between these phases is often blurred and when, as a researcher, you try to emphasize the separation of the two, it’s considered pedantic and dull.
Several types of scenarios exist – for example, you can have a method that measures a phenomenon X in a different way to an established method or you can have an operationalized measurement of phenomenon X (i.e. an indirect measurement, almost like a surrogate marker). The key question has to be: am I measuring what I think I’m measuring? This can be done by directly comparing the performance of the new method to a more established method, or by testing to see if that method gives you the results you would expect in a biological or clinical situation that has been previously well studied and described.
For the record, I think the second option, although indirect, is completely valid – taking a method that’s under development and testing if it reflects a well-established biological phenomenon (if that’s what it’s meant to reflect) – that still counts as validation (I’ve done this myself on several occasions – e.g. here, here, and here). But the key thing is that it has to be well-established. Expecting a method you’re still trying to comprehensively understand to tell you something completely – or even mostly – new makes no sense.
Unfortunately, that’s often what’s expected of this kind of research. It’s expected from the researchers doing the work themselves, from their colleagues and/or supervisors, from manuscript reviewers, as well as from funding agencies. The reason is simple (albeit deeply misguided), and it confronts researchers working on improving and validating methods in clinical research very often: people want you tell them something new about biology or pathophysiology. They very often don’t want to hear that you’re trying to reproduce something established, even if it is with a new method that might be better for very practical reasons (applicability, interpretability, etc). This has presented itself to me over the years in many ways – reviewers bemoaning that my studies “provide no new biological insights” or well-meaning colleagues discouraging me from writing my PhD dissertation in a way that makes it sound “purely methodological” (“you need to tell the reader something new, something previously unknown”).
The irony is that, in the years I’ve spent doing (and reading) imaging research, I’ve become fairly convinced that the majority of clinical imaging studies should fall into the second category mentioned above. However, it’s often mixed up with, and presented as though it belongs to, the third category. Researchers use new method Y to test a “novel” hypothesis, and interpret the results assuming (without proper evidence) that method Y is indeed measuring what it’s supposed to be. I notice this when I read papers – the introduction talks about the study as if its aim is to test and validate method Y, and the discussion ends up focusing on all the wonderful new insights we’ve learned from the study.
To be clear, I’m in no way saying that the ultimate goal of a new method shouldn’t be to be taken to studies of the third category. Validate, improve, validate, then apply with the hope of learning something new – that’s should clearly be the goal of any new method meant for clinical use. But we shouldn’t expect both to be done simultaneously. Instead, we need to acknowledge the clear separation between the types of clinical research and their respective goals, and to recognize that not all research is new and exciting in terms of what it tells us about biology or pathophysiology.