Laasya Devi Annepureddy

School: The Illinois Institute of Technology

Major: Biomedical Engineering

DOI: https://doi.org/10.21985/n2-ryw3-8m94

Biography:

Laasya is a third-year Biomedical Engineering student specializing in cell and tissue engineering, at Illinois Tech. Her research interests include mathematical modeling of diseases and detection of Diabetic Retinopathy (DR). She is currently working on the application of a kinetic model to enhance the imaging protocol for better detection of DR. After under-graduation, Laasya wants to pursue a MS-PhD program. Besides pursuing research, Laasya likes to tutor students at the Academic Resource Centre where she has been a Peer tutor for the past three years. In her free time, Laasya enjoys trying different food cultures, spending time with friends and traveling with an intention to explore the values of the place.

Application of a Dynamic Tracer Kinetic Model to Optimize the Frame Rate for Improved Detection of Diabetic Retinopathy in Humans

Abstract

Diabetic Retinopathy (DR) is a common ophthalmological condition that is caused as a side effect of Diabetes. DR does not show early onset of symptoms; however, if left untreated, it can lead to permanent loss of vision. Early detection of the preclinical signs of the disease can be critical in identifying patients that will most likely progress into DR and prevent vision impairment. Volumetric blood flow (VBF) and vascular permeability (VP) have been associated with early signs of Diabetic Retinopathy and can be used as biomarkers that can help detect healthy patients and patients suffering from DR. This study will employ a dynamic tracer kinetic model to better quantify the parameters VBF and VP and optimize imaging parameters for applications in the retina. In this study, human retinal scan data will be analyzed, and simulations will be created using MATLAB to provide a better imaging protocol for enhanced detection of diabetic retinopathy. Computer simulations of the data will be used to apply the kinetic model and optimize the number of frames required to produce a high-quality image that can accurately quantify volumetric blood flow. A simulation study will be performed at various numbers of frames and image processing tools will be applied to estimate blood flow. An optimized frame rate will allow for a rapid retinal scan for patients with increased comfort and safety. Furthermore, quantifiable hemodynamic parameters can be sensitive biomarkers which can be used as an early indicator of the disease and develop preventive therapies.

What is your research topic, in a nutshell?

In a nutshell, the project aims to optimize the number of frames required to produce high quality FVA images that will allow for accurate estimation of the biomarker, volumetric blood flow, to better detect Diabetic Retinopathy (DR). This is a simulation-based study carried out in MATLAB with noise added model curves.

How did you come to your research topic?

Diabetic Retinopathy is a common side effect of diabetes that often goes unnoticed until permanent vision impairment. Hence, a kinetic model was developed that can better quantify the biomarkers or preclinical signs related to the disease that will allow for early detection. However, for the model to be applied to the retina and FVA imaging modality, several parameters have to be optimized, one such parameter is the frame rate.

Where do you see the future direction of this work leading (how might future researchers build on your work or what is left to discover in this field)?

Recent research has suggested that the extraction fraction may be a better indicator for separating healthy patients from those suffering from DR than volumetric blood flow. Using a five-parameter model instead of three (the one used in this project) and estimating extraction fraction can lead to interesting results and potentially new discoveries in detection of DR.

Where are you heading to after graduation?

After graduation, I plan to pursue graduate studies through a MS/PhD program.