Penta-Modal Imaging Platform with OCT- Guided Dynamic Focusing for Simultaneous Multimodal Imaging

Authors

Arash DadkhahFollow

Document Type

Dissertation

Degree

Doctor of Philosophy (PhD)

Major/Program

Biomedical Engineering

First Advisor's Name

Shuliang Jiao

First Advisor's Committee Title

Committee Chair

Second Advisor's Name

Wei-Chiang Lin

Second Advisor's Committee Title

Committee Member

Third Advisor's Name

Jessica Ramella-Roman

Third Advisor's Committee Title

Committee Member

Fourth Advisor's Name

Rong Wen

Fourth Advisor's Committee Title

Committee member

Fifth Advisor's Name

Jin He

Fifth Advisor's Committee Title

Committee Member

Keywords

Optical imaging, Photoacoustic microscopy, Optical Coherence Tomography, Optical Doppler Coherence Tomography, Confocal Fluorescence Microscopy

Date of Defense

3-16-2021

Abstract

Complex diseases, such as Alzheimer’s disease, are associated with sequences of changes in multiple disease-specific biomarkers. These biomarkers may show dynamic changes at specific stages of disease progression. Thus, testing/monitoring each biomarker may provide insight into specific disease-related processes, which can result in early diagnosis or even development of preventive measures. Obtaining a comprehensive information of biological tissues requires imaging of multiple optical contrasts, which is not typically offered by a single imaging modality. Thus, combining different contrast mechanisms to achieve simultaneous multimodal imaging is desirable. However, this process is highly challenging due to specific optical and hardware requirements for each optical imaging system. The objective of this dissertation is to develop a novel Penta-modal optical imaging system integrating photoacoustic microscopy (PAM), optical coherence tomography (OCT), optical Doppler tomography (ODT), OCT angiography (OCTA) and confocal fluorescence microscopy (CFM) in one platform providing comprehensive structural, functional, and molecular information of living biological tissues. The system can simultaneously image different biomarkers with a large field-of-view (FOV) and high-speed imaging. The large FOV and the high imaging speed is achieved by combining optical and mechanical scanning mechanisms. To compensate for an uneven surface of biological samples, which result in images with non-uniform resolution and low signal to noise ratio (SNR), we further develop a novel OCT-guided surface contour scanning methodology, a technique for adjusting objective lens focus to follow the contour of the sample surface, to provide a uniform spatial resolution and SNR across the region of interest (ROI). The imaging system was tested by imaging phantoms, ex vivo biological samples, and in vivo. The OCT-guided surface contour scanning methodology was utilized for imaging a leaf of purple queen plant, which resulted in a significant contrast improvement of 41% and 38% across a large imaging area for CFM and PAM, respectively. The nuclei and cells walls were also clearly observed in both images. In an in vivo imaging of the Swiss Webster mouse ear, our multimodal imaging system was able to provide images with uniform resolution in an FOV of 10 mm x 10 mm with an imaging time of around 5 minutes. In addition to measuring the blood flow in the mouse ear, the system also successfully imaged mouse ear blood vessels, sebaceous glands, as well as several tissue structures. We further conducted a comparative study of OCTA for rodent retinal imaging by evaluating the performance of three OCTA algorithms, namely the phase variance (PV), improved speckle contrast (ISC), and optical microangiography (OMAG). It was concluded that the OMAG algorithm provided statistically significant higher mean values of BVD and VPI compared to the ISC algorithm (0.27±0.07 vs. 0.24±0.05 for BVD; 0.09±0.04 and 0.08±0.04 for VPI), while no statistically significant difference was observed for VDI and VCI among the algorithms. Results showed that both the ISC and OMAG algorithms are more robust than PV, and they can reveal similar vasculature features. Lastly, we utilized the proposed imaging system to monitor, for the first time, the invasion process of malaria parasites in the mosquito midgut. The system shows a promising potential to detect parasite motion as well as structural changes inside the mosquito midgut. The multimodal imaging system outlined in this dissertation can be useful in a variety of applications thanks to the specific optical contrast offered by each employed modality, including retinal and brain imaging.

Identifier

FIDC009578

Comments

Please note that as included in the "Authorship Attribution Statement " section in the dissertation, the majority of the content of the dissertation is directly from my 4 peer-reviewed publications: Chapter 3, Chapter 4, Chapter 5, and Parts of Chapter 2 & 8

Previously Published In

Authorship Attribution Statement

This dissertation contains material from 4 published papers in the following peer- reviewed journals.

The content of chapter 3 is published in Biomedical Optics Express as Arash Dadkhah, Jun Zhou, Nusrat Yeasmin, and Shuliang Jiao,” Integrated multimodal photoacoustic microscopy with OCT- guided dynamic focusing”.

The content of chapter 4 is published in the Journal of Biomedical Optics, as Arash Dadkhah and Shuliang Jiao,” Optical coherence tomography-guided dynamic focusing for combined optical and mechanical scanning multimodal photoacoustic microscopy”.

The content of chapter 5 is published in Journal of Experimental Biology and Medicine, as Arash Dadkhah and Shuliang Jiao,” Integrating Photoacoustic Microscopy, Optical Coherence Tomography, OCT Angiography, and Fluorescence Microscopy for Multimodal Imaging”.

Parts of the content of chapter 2 and chapter 8 are published in Journal of Experimental Biology and Medicine, as Arash Dadkhah and Shuliang Jiao,” Integrating Photoacoustic Microscopy with Other Imaging Technologies for Multimodal Imaging”.

Recommended Citation

Dadkhah, Arash, "Penta-Modal Imaging Platform with OCT- Guided Dynamic Focusing for Simultaneous Multimodal Imaging" (2021). FIU Electronic Theses and Dissertations. 4672.
https://digitalcommons.fiu.edu/etd/4672