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Radonc/BME     Medical Image and
Computational Analysis Laboratory
Matt Wilhelm
BS Biology, pre-Med
2014-15 College of Medicine University Scholar
Graduation: Spring 2015
Currently: 2nd year graduate medical student: Nova Southestern College of Osteopathic Medicine

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  1. Resume (pdf)
  2. Research Overview

    Quantifying Lung Vascular Response to Radiation


    Background and Significance
    The lungs are highly sensitive to radiation due to a large density of vessels and high oxygen concentration. Following radiation, acute endothelial cell damage and inflammatory response leads to blockage of the arterial lumen starting with the small arterioles. This subsequent increase in pulmonary arterial pressure further damages vascular endothelium, leading to progressive occlusion of ever larger arterioles creating an unfavorable positive feedback scenario.

    Hypothesis
    My hypothesis is that radiation damage to pulmonary vascular tissue can be quantified over time as pruning of the vascular tree that scales with regional radiation dose.
    Figure 1. Time course of vascular changes following whole-lung RT. The image on the left is a CT slice through the patient’s chest with the treatment radiation dose overlaid in color, with white representing the highest dose. The plot on the right illustrates the number of branches (on a Log10 scale) for each of 4 branch radius size ranges. Plotted for each range are data from 6 time points, from pre-treatment to 17 months post-RT. An initial decrease in the number of small vessels is apparent at 3 months and progresses through 7 months post-RT. A partial recovery after 10 months is then seen. All CT images were acquired without contrast and with similar imaging parameters (slice thickness; in-plane pixel size).
    Methods
    I will receive 3D radiation dose distributions and x-ray computed tomography (CT) chest scans acquired pre and post-radiation exposure in patients. Our lab has developed methods to quantify changes in pulmonary vascular structure from 3D CT scans that we have applied successfully to human and animal models. For my research, I will employ these same tools to quantify progressive pruning of small branches, as evident in radii histograms. I will be responsible for accumulating and compiling the data into visual aids for further interpretation in cooperation with my research mentor, Dr. Walter O'Dell, and his team for presentations and publications. The number of subjects to be analyzed was chosen for feasibility. There is no available data upon which a clinical research hypothesis can be powered. However, data collected under this award will be invaluable toward that end.

    Figure 2. The time course of the branch radii histogram of the left hemi-lung in an RT patient with 2 left-lung tumors and 5 follow-up CT scans. [A] shows an RT-planning CT slice through the center of one of the targeted tumors. The color-overlay represents the prescribed dose, where white is the highest doss (~60Gy). [B] shows an analogous slice through the 2nd target in this patient. [C] shows the radii histogram. A decrease in the number of small vessels through 9 months is followed by a partial recovery. All CT images were acquired without contrast and with similar imaging parameters.

    Immediate Objectives
    For the following semester, I aim to complete 3-4 full patients' CT scans per week, including follow-ups. For each patient with their follow-ups, approximately one and a half hours will be needed. I will present my updates every month to the lab group and Dr. O'Dell. I will be overseen by Dr. O'Dell and UF medical student Dustin Begosh-Mayne throughout the entirety of the semester.

  3. National Presentations
    Wilhelm M., Begosh-Mayne D., O'Dell W.
          Pulmonary vascular pruning in response to radiation
          Radiation Research Society 60th Annual Meeting, Las Vegas, NV, Sept. 2014

    O’Dell, W.G, Govindarajan, S.T., Salgia, A., Hegde, S., Prabhakaran, S., Finol, E.A., White, R.J.
          Traversing and labeling interconnected vascular tree structures from 3D medical images
          In S. Ourselin & M. A. Styner (Eds.), Proceedings of SPIE Medical Imaging 2014; (p. 90343C).
          doi:10.1117/12.2044140
  4. Related MIACALab projects
    1. Vessel Segmentation
    2. Lung radiation dose response

  5. Close Research Collaborators
    1. W. O'Dell (Radiation Oncology Research)
    2. Dustin Begosh-Mayne
    3. Blake Boudreaux