RESEARCH ARTICLE


Numerical Computational Study of Photoacoustic Signals from Eye Models to Detect Diabetic Retinopathy



Sherif H. ElGohary1, *, Shaimaa A. Azab1, Mohamed K. Metwally2, Noha S. Hassan1
1 Biomedical Engineering and Systems Department, Cairo University, Giza12613, Egypt
2 Radiology Department, Medical Center, Leiden University, Leiden, Netherlands


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Creative Commons License
© 2020 ElGohary et al.

open-access license: This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International Public License (CC-BY 4.0), a copy of which is available at: https://creativecommons.org/licenses/by/4.0/legalcode. This license permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

* Address correspondence to this author at the Biomedical Engineering and Systems Department, Cairo University, Giza12613, Egypt; E-mail: sh.elgohary@eng1.cu.edu.eg


Abstract

Introduction:

Detection of Diabetic Retinopathy (DR) is essential in clinical ophthalmology as it may prevent sight degradation. In this paper, a complete Photoacoustic (PA) analysis is implemented to detect DR in three different eye models representing a healthy eye as well as two abnormal eyes exhibiting Non-Proliferative Retinopathy (NPDR), and Proliferative Retinopathy (PDR)

Methods & Materials:

Monte Carlo method was used to simulate the interaction of a 0.8 ns duration laser pulse with eye tissues at 750 nm wavelength. Thermal, structural and acoustical analyses were performed using the Finite Element Method (FEM).

Results:

The results showed that there is a significant change in the amplitude of the detected PA signal for abnormal eye tissues in the retina (P < 0.05) as compared to healthy eye tissues. The maximum amplitude of the received PA signal in the NPDR and the PDR eye models is 5% and 33%, respectively, which are greater than those observed in the healthy eye.

Conclusion:

These results may provide insights into using PA imaging to detect DR.

Keywords: Diabetic Retinopathy (DR), Photoacoustic (PA) Analysis, Non-Proliferative Retinopathy (NPDR), Photoacoustic signals, Monte carlo method, Acoustical analyses.