Optical coherence tomography (OCT) and Photoacoustic microscopy (PAM) are two noninvasive, high-resolution, three-dimensional, biomedical imaging modalities based on different contrast mechanisms. OCT detects the light backscattered from a biological sample either in the time or spectral domain using an interferometer to form an image. PAM is sensitive to optical absorption by detecting the light-induced acoustic waves to form an image. Due to their complementary contrast mechanisms, OCT and PAM are suitable for being combined to achieve multimodal imaging. In this dissertation, an optical coherence photoacoustic microscopy (OC-PAM) system was developed for in vivo multimodal retinal imaging with a pulsed broadband NIR light source. To test the capabilities of the system on multimodal ophthalmic imaging, the retina of pigmented rats was imaged. The OCT images showed the retinal structures with quality similar to conventional OCT, while the PAM images revealed the distribution of melanin in the retina since the NIR PAM signals are generated mainly from melanin in the posterior segment of the eye. By using the pulsed broadband light source, the OCT image quality highly depends on the pulse-to-pulse stability of the light source without averaging. In addition, laser safety is always a concern for in vivo applications, especially for eye imaging with a pulsed light source. Therefore, a continuous wave (CW) light source is desired for OC-PAM applications. An OC-PAM system using an intensity-modulated CW superluminescent diode was then developed. The system was tested for multimodal imaging the vasculature of a mouse ear in vivo by using Gold Nanorods (GNRs) as contrast agent for PAM, as well as excised porcine eyes ex vivo. Since the quantitative information of the optical properties extracted from the proposed NIR OC-PAM system is potentially able to provide a unique technique to evaluate the existence of melanin and lipofuscin specifically, a phantom study has been conducted and the relationship between image intensity of OCT and PAM was interpreted to represent the relationship between the optical scattering property and optical absorption property. It will be strong evidence for practical application of the proposed NIR OC-PAM system.

For most of the patients with brain tumors and/or epilepsy, surgical resection of brain lesions, when applicable, remains one of the optimal treatment options. The success of the surgery hinges on accurate demarcation of neoplastic and epileptogenic brain tissue. The primary goal of this PhD dissertation is to demonstrate the feasibility of using various optical techniques in conjunction with sophisticated signal processing algorithms to differentiate brain tumor and epileptogenic cortex from normal brain tissue intraoperatively. In this dissertation, a new tissue differentiation algorithm was developed to detect brain tumors in vivo using a probe-based diffuse reflectance spectroscopy system. The system as well as the algorithm were validated experimentally on 20 pediatric patients undergoing brain tumor surgery at Nicklaus Children’s Hospital. Based on the three indicative parameters, which reflect hemodynamic and structural characteristics, the new algorithm was able to differentiate brain tumors from the normal brain with a very high accuracy. The main drawbacks of the probe-based system were its high susceptibility to artifacts induced by hand motion and its interference to the surgical procedure. Therefore, a new optical measurement scheme and its companion spectral interpretation algorithm were devised. The new measurement scheme was evaluated both theoretically with Monte Carlo simulation and experimentally using optical phantoms, which confirms the system is capable of consistently acquiring total diffuse reflectance spectra and accurately converting them to the ratio of reduced scattering coefficient to absorption coefficient (µs’(λ)/µa(λ)). The spectral interpretation algorithm for µs’(λ)/µa(λ) was also validated based on Monte Carlo simulation. In addition, it has been demonstrated that the new measurement scheme and the spectral interpretation algorithm together are capable of detecting significant hemodynamic and scattering variations from the Wistar rats’ somatosensory cortex under forepaw stimulation. Finally, the feasibility of using dynamic intrinsic optical imaging to distinguish epileptogenic and normal cortex was validated in an in vivo study involving 11 pediatric patients with intractable epilepsy. Novel data analysis methods were devised and applied to the data from the study; identification of the epileptogenic cortex was achieved with a high accuracy.

A novel biocompatible and biodegradable polymer, termed poly(Glycerol malate co-dodecanedioate) (PGMD), was prepared by thermal condensation method and used for fabrication of nanoparticles (NPs). PGMD NPs were prepared using the single oil emulsion technique and loaded with an imaging/hyperthermia agent (IR820) and a chemotherapeutic agent (doxorubicin, DOX). The size of the void PGMD NPs, IR820-PGMD NPs and DOX-IR820-PGMD NPs were approximately 90 nm, 110 nm, and 125 nm respectively. An acidic environment (pH=5.0) induced higher DOX and IR820 release compared to pH=7.4. DOX release was also enhanced by exposure to laser, which increased the temperature to 42°C. Cytotoxicity of DOX-IR820-PGMD NPs was comparable in MES-SA but was higher in Dx5 cells compared to free DOX plus IR820 (pIn vivomouse studies showed that NP formulation significantly improved the plasma half-life of IR820 after tail vein injection. Significant lower IR820 content was observed in kidney in DOX-IR820-PGMD NP treatment as compared to free IR820 treatment in our biodistribution studies (p

Breast cancer is the No.1 prevalent new cancer in female cancer now. Compared to mastectomy (removing the entire breast), breast-conserving surgery (only removing cancerous tissue), has become the preferred treatment for its better cosmetic outcome and patient healthcare. However, it is challenging for surgeons to accurately locate the tumor and completely remove it during the surgery. Consequently, it leads to prolonged surgical time and inadequate tumor margins, which requires a second operation. Currently, the reoperation rate in the U.S. is as high as 25%. This is due to the lack of intraoperative tumor margin assessment and accurate breast tumor localization tools inside the operating room (OR), making current lumpectomy far from precise. My thesis work aims to achieve precision lumpectomy through development of photo- and thermo-acoustic imaging and sensing techniques. To fulfill the first unmet need of high-speed intraoperative assessment of breast tumor margins, we developed a compact multimodal ultrasound and bond-selective photoacoustic imaging system to image the entire excised tissue in just 10 minutes. The system was validated at hospitals with fresh lumpectomy specimens from 66 patients, and it achieved a sensitivity of 85.5% and specificity of 90%, showing its potential for high-speed and accurate intraoperative assessment of breast tumor margins. Next, we addressed the second unmet need of fast and accurate breast tumor localization in the OR through development of a fiber optoacoustic guide (FOG). It resembles the current metal guide wire but broadcasts MHz ultrasound omnidirectional via photoacoustic effect and can achieve sub-mm tumor localization. With an augmented reality system, the obtained tumor location was projected as an intuitive visual guidance to minimize the interference to surgical workflow and achieve optimal surgical planning. A surgeon successfully deployed the FOG to excise a “pseudo tumor” in a female human cadaver. Lastly, to improve the patient flow and logistics in clinics with a wireless breast tumor localization tool, we developed a resonant ring antenna that converts microwave into ultrasound to realize a wireless acoustic beacon. As a proof-of-concept, the ring antenna demonstrated over 3 orders of improvement in conversion efficiency than a common contrast agent for thermo-acoustic imaging. / 2021-08-30T00:00:00Z

Fluorescence microscopy has revolutionized medicine and biological science with its ability to study the behavior and chemical expressions of living cells. Fluorescent probes can label cell components or cells of a particular type. Clinically the impact of fluorescence imaging can be seen in the diagnosis of cancers, AIDS, and other blood related disorders. Although fluorescence imaging devices have been established as a vital tool in medicine, the size, cost, and complexity of fluorescence microscopes limits their use to central laboratories. The work described in this thesis overcomes these limitations by developing a low cost integrated fluorescence microscope so single use fluorescence microscopy assays can be developed. These assays will enable at-home testing, diagnostics in resource limited settings, and improved emergency medicine.

Two batches of CdSe QDs with different sizes were synthesized for immobilizing in polyisoprene (PI), polymethylmethacrylate (PMMA), and low-density polyethylene (LDPE). The combinations of QDs and polymer substrates were evaluated for their analytical fit-for-use in applicable immunoassays. Hydrogen peroxide standards were injected into the flow injection analyzer (FIA) constructed to simulate enzyme-generated hydrogen peroxide reacting with bis-(2,4,6-trichlorophenyl) oxalate. Linear correlations between hydrogen peroxide and chemilumenscent intensities yielded regression values greater than 0.9750 for hydrogen peroxide concentrations between 1.0 x 10-4 M and 1.0 x 10-1 M. The developed technique’s LOD was approximately 10 ppm. Variability of the prepared QD-polymer products was as low as 3.2% throughout all preparations.Stability of the preparations was tested during a 30-day period that displayed up to a four-fold increase in the first 10 days. The preparations were decently robust to the FIA system demonstrating up to a 15.20% intensity loss after twenty repetitive injections.

Volumetric optical microscopy has the advantages of quantitative and global measurement of three-dimensional (3D) biological specimens with high spatial resolution and minimum invasion. However, current volumetric imaging technologies based on light transmission, scattering or fluorescence cannot reveal specimen’s chemical distribution that brings insights to study the chemical events in organisms and their metabolism, functionality, and development. Stimulated Raman scattering (SRS) microscopy allowing visualization of chemical contents based on their intrinsic molecular vibrations is an emerging imaging technology to provide rapid label-free volumetric chemical imaging. This dissertation describes three methodologies for developing advanced volumetric SRS imaging technologies to address the challenges of imaging in vivo samples, imaging speed, and axial resolution. In the first methodology, SRS volumetric imaging is enabled by axially scanning the laser foci for sectioning different depth layers. In Chapter 2, we utilize a piezo objective positioner to drive the objective. Combining with the tissue clearance technique, we realize volumetric SRS imaging up to 500 µm depth in brain tissues showing the potential for 3D staining-free histology. The limitations of piezo scanning are slow speed and disturbance to in vivo samples while rapidly scanning the objective. To tackle the limitations, in Chapter 3, we develop a remote-focusing volumetric SRS microscope based on a deformable mirror and adaptive optics optimization, allowing focal scanning without physically moving the objective or sample. We demonstrate in vivo monitoring of chemical penetration in human sweat pores. In the second methodology, instead of axially scanning the laser foci, the SRS volumetric imaging is enabled by projection imaging with extended depth-of-focus (DOF) beams such as Bessel beams and low numerical-aperture beams. The extended DOF beams integrate SRS signals along the propagation direction to form projection images; thus, a single lateral scan obtains the volumetric chemical information, significantly increasing the volumetric imaging speed for measuring chemical content over a large volume. In Chapter 4, we describe a stimulated Raman projection microscope for fast quantitation of chemicals in a 3D volume. However, projection imaging intrinsically loses axial resolution. We addressed the limitation by developing SRS projection tomography. Mimicking computed tomography, the axial information is reconstructed by angle-dependent projection images obtained by sequentially rotating the sample in a capillary glass tube within the SRS focus. Nevertheless, sample rotation is complicated and not compatible with in vivo samples. To address the difficulty, in Chapter 5, we develop tilted-angle-illuminated stimulated Raman projection tomography which utilizes tilted-angle beams with a tilted angle respected to the optical axis of the objective to obtain angle-dependent projections. This scheme is free of sample rotation and enables fast projection scanning for pushing the imaging speed. The calibration approach and vector-field back-projection algorithm are developed for the multi-view tomographic reconstruction. In the third methodology, we improve the spatial resolution in miniature volumetric SRS imaging via the innovation of metasurface photonics. In developing an SRS endoscope for volumetric chemical imaging inside the human body, the axial resolution deteriorates due to chromatic and monochromatic aberrations induced by poorly made miniature objective lenses. In Chapter 6, we develop a silicon metasurface tailored for compensating the phase errors between the pump and Stokes wavelengths of a singlet refractive lens. Integrating the metasurface with the refractive lens, the hybrid achromatic metalens is compact and provides nearly diffraction-limit resolution, demonstrating a way for developing high resolution chemical imaging endoscopy.

The kinetics of milk coagulation are complex and still not well understood. A deeper understanding of coagulation and the impact of the relevant factors would aid in both cheese manufacturing and also in determining the nutritional benefits of dairy products. A method using confocal microscopy was developed to follow the movement of milk fat globules and the formation of a milk protein network during the enzyme-induced coagulation of milk. Image processing methods were then used to quantify the rate of coagulation. It was found that the texture of the protein network is an indicator of the current status of the milk gelation, and hence can be used to monitor the coagulation process. The imaging experiment was performed on milk gels with different concentrations of the coagulation enzyme, chymosin. Rheological measurements were taken using free oscillation rheometry to validate the imaging results. Both methods showed an inverse relationship between rennet concentration and the coagulation time. The results from the imaging study were used to create a computational model, which created simulated images of coagulating milk. The simulated images were then analyzed using the same image analysis algorithm. The temporal protein network texture behavior in the simulated images followed the same pattern as the protein texture in the confocal imaging data. The model was developed with temperature and rennet concentration as user inputs so that it could be implemented as a predictive tool for milk coagulation.

Attention Deficit Hyperactivity Disorder (ADHD) affects 5-10% of children worldwide. Its effects are mainly behavioral, manifesting in symptoms such as inattention, hyperactivity, and impulsivity. If not monitored and treated, ADHD may adversely affect a child's health, education, and social life. Furthermore, the neurological disorder is currently diagnosed through interviews and opinions of teachers, parents, and physicians. Because this is a subjective method of identifying ADHD, it is easily prone to error and misdiagnosis. Therefore, there is a clear need to develop an objective diagnostic method for ADHD. The focus of this study is to explore the use of machine language classifiers on information from the brain MRI and fMRI of both ADHD and non-ADHD subjects. The imaging data are preprocessed to remove any intra-subject and inter-subject variation. For both MRI and fMRI, similar preprocessing stages are performed, including normalization, skull stripping, realignment, smoothing, and co-registration. The next step is to extract features from the data. For MRI, anatomical features such as cortical thickness, surface area, volume, and intensity are obtained. For fMRI, region of interest (ROI) correlation coefficients between 116 cortical structures are determined. A large number of image features are collected, yet many of them may include redundant and useless information. Therefore, the features used for training and testing the classifiers are selected in two separate ways, feature ranking and stability selection, and their results are compared. Once the best features from MRI and fMRI are determined, the following classifiers are trained and tested through leave-one-out cross validation, experimenting with varying feature numbers, for each imaging modality and feature selection method: support vector machine, support vector regression, random forest, and elastic net. Thus, there are four experiments (MRI-rank, MRI-stability, fMRI-rank, fMRI-stability) with four classifiers in each for a total of 16 classifiers trained per each feature count attempted. The results of each classifier are the decisions of each subject, ADHD or non-ADHD. Finally, a classifier decision ensemble is created through the combination of the outputs of the best classifiers in a majority voting method that includes results of both the MRI and fMRI classifiers and keeps both feature selection results independent. The results suggest that ADHD is more easily identified through fMRI because the classification accuracies are a lot higher using fMRI data rather than MRI data. Furthermore, significant activity correlation differences exist between the brain's frontal lobe and cerebellum and also the left and right hemispheres among ADHD and non-ADHD subjects. When including MRI decisions with fMRI in the classifier ensemble, performance is boosted to a high ADHD detection accuracy of 96.2%, suggesting that MRI information assists in validating fMRI classification decisions. This study is an important step towards the development of an automatic and objective method for ADHD diagnosis. While more work is needed to externally validate and improve the classification accuracy, new applications of current methods with promising results are introduced here.

The purpose of this study is to develop a test method to non-invasively measure the development of subclinical atherosclerosis through acoustic sound wave analysis. This test method involves the manufacturing and use of silicone arteries with varying relative roughness values in their inner diameters to mimic arterial plaque buildup, a flow model, and a physiological microphone. A flow model that can generate both steady and oscillatory flow to mimic the pulsatile flow of a heartbeat was developed to successfully test and analyze fluid flow through the varying arteries. The first finding in this study was that confocal microscopy is an effective method is quantifying the surface roughness of the inner diameter the silicone artery phantoms. Results of this study found that the surface roughness of the arteries reflects the increase of surface roughness hypothesized when manufacturing the artery molds. The gravitational flow model experimental design proved to be effective in collecting steady flow data that was used to verify the experimental relative roughness and friction factor values. Additionally, the results indicated that pressure drop and friction factor (both experimental and theoretical) increased as the surface roughness of the artery increased. Furthermore, the pulsatile flow model was unsuccessful in generating a consistent frequency that was greater than 2.0 Hz. Because of this, many of the Womersley’s numbers remained undefined or frequency dependent. No concrete conclusions can be drawn regarding the relationship between Womersley’s number and surface roughness during pulsatile flow. A key finding in this study was that the signal power of an FFT of the audio data vs. relative roughness for both steady and pulsatile flow conditions experienced a slightly positive linear association. Meaning that there could be a relationship between the increase of surface roughness and the increase of signal power in an FFT of the audio data. Based on the findings in this study, this demonstrates that there could be a method to correlate the values of signal power to a specific relative roughness value.