Week 4: Analysis of MRI Images

I spent much of this week performing analysis of the MRI data we collected last week from loaded and unloaded porcine patellar tendon. This included using preexisting software as well as code developed by the MRI Lab. Often, the first step in medical image processing is segmentation. In this case, we were interested in only looking at T2* relaxation times in the tendon. Using a software called ITK-SNAP I was able to outline the tendon in every slice where it appeared in the MR image stack. Next a MATLAB code that calculates the decrease in T2* signal intensity over time was used to determine T2* relaxation times over the segmented region. For each pixel, the code fits a curve to the signal intensity vs. time. This can be a time consuming process, so part of my job this week was try different curve fitting algorithms for determining these values.

On Friday I had the opportunity to see a hip revision surgery. The patient volunteered to be part of a study collecting MR images, tissue biopsy, and implant mechanics data and correlating with implant performance and reasons for implant failure. We first had to consent the patient which involved explaining the study and asking them to filling out a questionnaire. During the surgery a sample was collected in an area that appeared to have adverse local tissue reaction in the MRI. Blood samples were also collected to detect any cobalt or chromium from the implant in the patient's blood. It was very informative to see the additional steps taken in research involving human subjects.

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