What to think about when choosing a topic for a technical PhD in cardiac imaging
by Martin Ugander, MD, PhD
Originally published October 11, 2010, revised October 20, 2010

I was recently approached via e-mail for advice on what to think about when choosing a subject for a technical PhD within cardiac imaging. My research interest is in cardiac imaging, in particular MRI, but also SPECT and CT. If I were embarking upon technical PhD studies within cardiac imaging today, I would focus on the following things.

1. Go out of your way to find a problem of high clinical relevance.

Most importantly, I would go out of my way to insure that I am working on trying to solve a problem with high clinical relevance. I would read the literature and, in particular, discuss with medical doctors regarding particular unsolved problems in their current practice. In my experience, there is unfortunately a strong tendency for researchers in the field of technical development within medicine to focus on working on problems of high technical interest, but with little or no medical or clinical relevance.

2. If you can, choose MRI.

There will always be interesting problems in all fields. However, from my experience, I am convinced that cardiac MRI is the subfield within cardiac imaging which has the greatest level of complexity, and which has the greatest potential for improvement. If I were starting a PhD in Medical Physics with a focus on cardiac imaging, I would focus on learning MRI pulse programming. Insights into the basics of image formation are critical to quantitative image analysis.

Furthermore, I foresee that MRI will be the imaging modality which will have the greatest impact on diagnosis and treatment within cardiology in the future. I base this assumption on the observation that MRI does not require ionizing radiation, and that the inherent tissue qualities and quantification possibilities with MRI are unsurpassed by other imaging modalities. The installation base of MRI machines continues to increase, and the major driver of costs in imaging is not the cost of purchasing the machine as such, but rather on the staffing costs, which are, by comparison, roughly similar across the modalities. From this perspective, MRI is certainly the technology of the future.

3. Choose your supervisor wisely.

Choose a supervisor/mentor who has a good track record, and with whom you get along with when it comes to communication. I do not know of a PhD student who has run into trouble because of scientific shortcomings, rather, communication and relations with their supervisor is the key component to success, and the largest potential potential pitfall when it comes to successfully obtaining a PhD.

4. Go open source

If your work is in image analysis, I would highly recommend that the software which you develop is implemented in an open source format. For example, Segment is a cardiac image analysis software platform is largely open source. More people will use and cite it if it is open source. Conveniently, Segment allows you to do this within the Segment platform. That said, Segment is not the only way to do this, but it may be a successful way to share your results in an open source fashion.

For more general tips on PhD studies, I recommend the writings of Matt Might:
The illustrated guide to a PhD
10 ways to fail a PhD

Originally published October 11, 2010, revised October 20, 2010