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UBC Theses and Dissertations

Photoacoustic tomography for prostate imaging by transurethral illumination Ai, Min

Abstract

Photoacoustic tomography (PAT) is a hybrid imaging modality that combines optical excitation and acoustic detection and overcomes the optical diffusion limit in tissue. Taking the advantages of deep penetration and high resolution, PAT is widely applied in biosciences. In prostate imaging, several PAT systems have been demonstrated to be capable of showing distinct photoacoustic (PA) contrast from malignant tissue or angiogenesis-related to prostate cancer. In this thesis, I explore the potential of applying PAT with transurethral illumination for prostate imaging. Challenges in translating PAT system to clinical imaging for prostate include the lack of sufficient local fluence for deep tissue penetration, risk of over irradiation near the laser-tissue contact surface and limited image reconstruction quality caused by the limited detection view and noisy PA signal. In this thesis, systematic design, optimization, and application of a PAT system with transurethral illumination are conducted. A fiber coupling scheme with a beam homogenizer is demonstrated for coupling high energy pulses in a single multimode fiber, achieved by using a cross cylindrical lens array. The peak power on the fiber tip surface is reduced and thus enhances the coupling performance. Recorded high pulse energy is achieved with high coupling efficiency as well. The high pulse energy can enable deep imaging depth in tissue. With high-energy pulses delivered by the multimode fiber, a transurethral illumination probe is designed, which can illuminate the prostate from the urethra. A parabolic cylindrical mirror reflects the light emitted from the diffusing fiber to achieve a parallel side illumination with doubled fluence. This design is optimized for both high energy pulse illumination and maintaining the laser fluence below the safety limit in tissue. As the detection view for prostate imaging is limited, a variance-reduced stochastic gradient descent (VR-SGD) algorithm is developed to improve the image reconstruction. The algorithm is verified by simulation and experiment of 2D imaging. VR-SGD algorithm demonstrates its capability to reduce the noise level and artifacts generated in the limited-view detection by linear array transducers. Through this study, the PAT system with transurethral illumination is shown to be capable and feasible for prostate imaging.

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Attribution-NonCommercial-NoDerivatives 4.0 International