Radonc/BME Medical Image and
Computational Analysis Laboratory
Siri Ravuri
Statistics and Biology
expected graduation Spring 2021


email link
My linkedIn page

Honors and Awards
      -- 2019-2020 UF Health Cancer Center University Scholar Award Recipient
      -- 2020-2021 UF Health College of Medicine University Scholar Award Recipient

Research Overview

Using Three-Dimensional Modeling to Analyze and Quantify Lung Vascular Structures

Background and Significance
Clinical manifestation of disease in the lungs are visible through CT scans only when the disease progresses to an aggressive state. The ability to better visualize, analyze, and quantify the progression of vascular changes is hoped to improve early diagnosis and improve treatment and outcomes for patients with vascular diseases. This research has the potential to identify early markers of vascular injury and further understand the vascular changes and vascular damage that occurs with the induction of pulmonary arterial hypertension and the growth of lung tumors.

Aims
      1. Model and Quantify Vascular Structures in Pulmonary Arterial Hypertension Induced Experimental Rat Lungs.
Pulmonary arterial hypertension (PAH) often occurs in idiopathic forms and is commonly associated with disease including cirrhosis, congenital health malformation, and scleroderma. A clinical manifestation of chronic PAH is the progressive pruning of pulmonary blood vessels which often leads to death from heart failure. The ability to better quantify the progression of vascular changes is hoped to improve outcomes for patients and accelerate the translation of future PAH-correction agents to the clinic.

      2. Use Three-Dimensional Modeling to Quantify the Vascular System around Lung Tumors.
Lung cancer is typically diagnosed once lung tumors are visible through CT scans, and generally becomes more difficult to treat as the tumor growth progresses. This portion is aimed at using three-dimensional modeling techniques to characterize changes in the vascular tree structures of patients with lung tumors, including ratio of parent-child branch radii, vessel tortuosity and bifurcation angles.

Methods
This investigation will use sequential CT scans of the right middle lobe of the right hemi-lung of Sprague Dawley rats and CT scans of patients who have growing lung tumors. The patient CT scans will be gathered from patients enrolled in an on-going IRB approved study. The chest CT scans will be pre-processed and analyzed using software developed in our lab and built upon the NIH ImageJ platform. Skeletonizing and thresholding will be applied to facilitate traversing and charactering the tree structure. Various vascular characteristics will be analyzed including vessel count, parent-child branch radii ratios, bifurcation angles, vessel tortuosity and area ratio.

Immediate Research Objectives
I plan to study 6-8 more patient CT scans, along with approximately 20 Rat CT scans under the supervision of Dr. O’Dell. The process of studying the final sets of CT scans will involve identifying clear images, code improvements to optimize quantification, and data analysis to identify significant changes due to vascular damage. I have chosen this project due to the fact that modeling vascular damage could optimize the diagnosis of vascular disease and further understand the human lungs and their response to growing tumors and infections. It will also allow me to expand upon my academic research interests in biological and computational tools for addressing patient care.

  • National Presentations
    Ravuri S, Siva Kumar O’Dell WG.
          Using three-dimensional modeling to analyze vascular changes around primary lung tumors.
          Biomedical Engineering Society Annual Meeting. (virtual)
          Oct. 17, 2020.

    Ravuri S, Siva Kumar S, White RJ, Haight D, O’Dell WG.
          Modeling and quantifying vascular structures in experimental rat lungs.
          Biomedical Engineering Society Annual Meeting. Philadelphia, PA:
          Oct. 16, 2019.

  • Related MIACALab projects
          Lung vessel segmentation

  • Close Research Collaborators
    1. W. O'Dell (Radiation Oncology Research)
    2. R. Jim White, MD, PhD, Dept. of Pulmonology, University of Rochester