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Aleef, Tajwar Abrar

University of British Columbia

Prostate cancer (PCa) represents a substantial health concern for men, and this thesis focuses on improving its diagnosis and treatment. The first contribution introduces a registration framework that localizes transperineal template-guided mapping biopsy (TTMB) cores in volumetric ultrasound (US) using only standard TTMB information. With an average target registration error of 1.2 mm and ≈97 s of registration time, this framework provides fast and accurate TTMB core localization. The pathology of these registered cores can serve as ground truth for training US-based PCa classifiers. To improve diagnosis, three US systems are developed to perform Shear Wave Absolute Vibro-Elastography (S-WAVE), a technique for quantitative tissue stiffness assessment. The first system, compatible with TTMB, employs multi-frequency transperineal excitation for the first time and correlates with magnetic resonance elastography (MRE) imaging at 96%. Clinical studies revealed a positive correlation between its measurements and PCa detected from histopathology. A PCa classifier, trained using clinical S-WAVE data taken with this system, achieved an AUC of 0.87±0.12. The second system is the first hand-operated 3D S-WAVE system with a transducer-mounted exciter designed for targeting systematic biopsies. When compared to MRE, it achieves a cross-correlation of 99% and 94% on quality assurance phantoms and in vivo human livers, respectively. In the third system, both S-WAVE and strain elastography are implemented for the first time in a commercial microUS system thus enabling the possibility of multi-parametric microUS imaging. For localized PCa, low-dose-rate prostate brachytherapy (LDR-PB) is an effective treatment where small radioactive seeds are permanently implanted within the prostate. The arrangement of these seeds is pre-planned manually, which is an iterative and time-consuming process. To automate this, two new methods based on conditional generative adversarial networks are proposed. Comparable results to the high-quality manual plans were achieved, demonstrating 98.9% coverage of the clinical target volume (CTV) receiving the minimum prescribed dose. Planning times are significantly reduced, with the proposed methods running approximately 7 and 400 times faster.

Text

2023-12-18

Attribution-NonCommercial-ShareAlike 4.0 International

http://hdl.handle.net/2429/86967

Biomedical Engineering

University of British Columbia

UBCV

http://creativecommons.org/licenses/by-nc-sa/4.0/