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Radonc/BME     Medical Image and
Computational Analysis Laboratory
Sneh Parekh
BS Biology, pre-Med
2016-17 College of Medicine University Scholar
expected graduation: Spring 2018

email link
  1. Resume (pdf)
  2. Research Overview

    Anatomic Modeling and visualization of the major vessels in the kidney

    Background and Significance
    Kidney cancer patients who have tumors along the kidney in the form of renal cell carcinoma (RCC)/renal cell adenocarcinoma often undergo radiation therapy in an attempt to eradicate residual cancer tissue. Sometimes, these tumors are very large, that they require a combination of this radiation therapy along with cancer surgery to remove the tumors. Although physicians when performing the surgery in an attempt to minimize and eradicate the amount of cancerous tissue use extreme care, surrounding tissues and organs are frequently hit and damaged. There is a large possibility of damaging the surrounding tissues, as physicians are unable to distinguish among the cancerous and surrounding blood vessels and non-cancerous tissue, invariably leading to serious situations during surgery.

    The purpose of the research project I am working on, with the help of Dr. Walter O’Dell, is to create an accurate three-dimensional (3D) model of the kidney and major vessels and ureters using kidney cancer patient MRI and CT images. The vessels and major collecting ducts are segmented and modeled using software created in our lab for lung vessel analysis (project link here) and tailored for the kidney environment. The segmentation and modeling of the kidney are performed using methods developed to model the geometry of the heart (project link here). The high quality MRI and CT images will first enable us to detect the location of tumors with respect to the kidney, and other blood vessels in its vicinity. My hypothesis is that the 3D models that I generate will enable our clinical collaborators to obtain a better picture of surrounding tissues and organs, reducing the risk of complications such as bleeding out, and thus improving overall survival rate.

    Figure 1. Initial segmentation of the kidneys and surrounding anatomy using the lab's version of the NIH ImageJ software toolkit.
    A number of image processing steps are needed to go from a series of kidney MR and CT images to a 3D model of the kidney. Using Dr. O’Dell’s in-house software tools, the tumor and surrounding blood vessels are semi-automatically traced. Our program then employs an algorithm to create a three-dimensional model of the kidney and surrounding areas. The ultimate goal is to aid clinicians in studying, diagnosing and treating patients with renal cell carcinoma (kidney cancer). Similarly, the model would provide information to clinicians of the relative locations of tumors and blood vessels, thus aiding them in performing more successful, lowered risk surgeries.

    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. Publications
    Parekh S., Su L.M., O’Dell W.G.,
          Anatomic Modeling And Visualization Of The Kidney And Its Associated Major Vessels In Patients With Kidney Cancer
          UF Journal of Undergraduate Research, December, 2017
  4. Local Presentations
    Parekh S., Su L.M., O’Dell W.G.,
          Anatomic Modeling And Visualization Of The Kidney And Its Associated Major Vessels In Patients With Kidney Cancer
          UF Health Cancer Center Research Day Symposium. November, 2016
  5. Related MIACALab projects
    1. Vessel Segmentation
    2. Lung radiation dose response

  6. Close Research Collaborators
    1. W. O'Dell (Radiation Oncology Research)
    2. Dr. Li-Ming Su