Development of a Prototype AWSM-PET System for Augmented Whole-body PET Imaging

Positron Emission Tomography (PET) is a critical imaging modality for medical diagnostics, yet its accuracy is often limited by spatial resolution and sensitivity constraints. This dissertation presents the development of Augmented Whole-body Scan via Magnifying PET (AWSM-PET), a novel technique integrating high-resolution auxiliary detectors with a clinical PET scanner to enhance sensitivity and resolution while remaining fully compatible with standard clinical protocols. The study encompasses hardware development, image reconstruction methods, and performance evaluation through imaging studies, including human trials. High-resolution outsert panel detectors were designed, mounted on a mobile cart, and integrated with a Biograph Vision PET/CT scanner. Firmware and software modifications enabled simultaneous data acquisition under clinical protocols. The outsert detectors achieved an energy resolution of 11% full width at half maximum (FWHM) at 511 keV and a coincidence resolving time (CRT) of 183 ps FWHM. Sensitivity improved by up to 18.4%, depending on source location. A data-driven geometric alignment method was developed using point source measurements, achieving sub-millimeter precision without requiring special landmarks or repetitive measurements. This approach optimized the outsert detector positioning to minimize angular discrepancies in detected lines of response (LORs) via an iterative optimization method. Monte Carlo simulations confirmed that the deviation between the ground truth and estimated geometry remained well below 1 mm. Experimental validation demonstrated that point source images using the estimated geometry aligned well with those from the Biograph Vision scanner, with centroid deviations below 1 mm and angular deviations of line source images under 1 degree across the field of view. To support image reconstruction, a Maximum Likelihood Expecation Maximization (MLEM) listmode image reconstruction technique was developed for continuous-bed-motion (CBM) reconstruction in AWSM-PET. To balance reconstruction speed and accuracy, a single-ring approximation and grouped crystal approximation were introduced to accelerate sensitivity image calculation. Scatter and random corrections were implemented to achieve quantitative images, incorporating approximations to optimize computational efficiency. Additionally, a spatially variant point spread function (PSF) model was compared with a spatially invariant model. Rather than enhancing spatial resolution, the PSF model primarily contributes to improving contrast recovery and noise control. AWSM-PET was evaluated through NEMA-IQ, and mini-Derenzo phantoms, as well as human imaging studies. Compared to the Biograph Vision scanner, the mini-Derenzo phantom study demonstrated improved spatial resolution for spherical lesions ≤6 mm in diameter, and the NEMA-IQ study confirmed higher contrast recovery coefficients (CRC) for the smallest lesion (4.88 mm Ø). Initial human imaging validated clinical compatibility, showing enhanced resolution in high-count regions (e.g., brain) but increased noise in low-count regions (e.g., abdomen), highlighting areas for further refinement.