Week 5: Rollin'

Finally back to a regular full week's schedule, unobstructed by the national holidays nor other commitments! The last two weeks have been shortened one way or another, so it's great to be immersed for a full week again!

I spent most of the time bouncing around between Floors 0, 2, and 4 of the Starr Building this week, and reinforcing what I have learned about cardiology and different kinds of imaging so far in the program. Got to ask the fellows, nurses, and techs in each department tons of questions, as well as getting a lot more interesting references and resources to read. It was also great to see the end of the tunnel for my immersion project, for which I now have a realistic timeline to complete the study and possibly a paper or an abstract.

This week, I'll write a little bit more about the software that's used in my project, the LVMetric Segmentor, which was developed at WCMC to speed up the segmentation process of cardiac images. Image segmentation provides a lot of important information, such as the chamber volume, blood mass, etc. which can be used as an indicator for certain diseases. In the past, doctors spend an awfully long time on each image case to segment myocardium from the chambers, while taking into account the papillary muscle mass, etc. For each patient's image, it can take anywhere from 4 to 10 minutes for an experienced doctor like Jonathan to segment the image profiles at the systolic and diastolic cardiac phases. LVMetric, on the other hand is very efficient, as it automates this segmentation process using some nifty image transforms and segmentation algorithms, and does it for all 25 or so different cardiac phases; in a matter of few seconds!

In addition to speeding up the process for doctors, the software can get data point at almost every cardiac phase; this allows us to study the temporal aspects of the chamber volume, etc. at each moment in the cardiac phase. We've recently added a new function to the program, so that it can output a decent amount of data from different cases that we examine. The remainder of my project starting Monday will be to organize, process, and analyze the volume curve for a number of these cases (Jonathan said it would be ~20 or so).

From this study, we are hoping to identify a quantitative indicator of certain physiological defects by analyzing quantitative data that I will work with. So it will be time to hit my Statistics textbooks hiding somewhere in my room next week (where are they?!). I'm really looking forward to wrapping up my project.

Finally, I got to follow Dr. Frayer on the rounds in the NICU this morning; I really must resonate Shawn and everybody else's earlier comments: man those babies are cute!