Prism-PET: A TOF-DOI-Compton PET detector technology for total-body PET imaging

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Abstract The relatively small axial field-of-view (FOV) in almost all PET scanners has severely limited their sensitivity and resulted in significant tradeoffs between image signal-to-noise ratio (SNR), acquisition time, and delivered dose. The solution is to improve geometric coverage using large axial FOV for total-body imaging which has the potential to improve sensitivity by about 40 times compared to existing commercial whole-body PET scanners. The construction of the world's first total-body PET/CT scan-ner, called EXPLORER, with 194-cm axial FOV has recently been completed. However, it has a poor time-of-flight (TOF) resolution of 430 ps, compared to the state-of-the-art whole-body PET scanner with 200 ps timing resolution (Siemens Biograph Vision). In addition, axial detector penetration of obliquely incident gamma photons detected within this wide acceptance angle will introduce significant depth-of-interaction (DOI) parallax error, leading to degraded spatial resolution. These two major defi-ciencies of the EXPLORER scanner offset its effective sensitivity gain, specially for imaging single organs such as the human brain when compared to the Biograph Vision PET scanner. For this research, we propose to build cost-effective block detectors with combined highest spatial resolution (2 mm), highest TOF resolution (<120 ps and potentially 100 ps), best DOI localization (1.85 mm), and highest inter- crystal Compton scatter recovery capabilities (88%) using single-ended readout and machine learning post-processing engines. Our novel detector module, called Prism-PET, enables these capabilities by mimicking very closely the behavior of dual-ended readout with enhanced and controlled light sharing using a segmented array of right angle prism-mirror light guides. Given our promising preliminary ex-perimental results, we aim to accomplish the following tasks: (1) model a prototype TOF-DOI PET scanner using GATE Monte Carlo simulations and use its list-mode data to develop our TOF-DOI image recontruction; (2) build Prism-PET detector modules and characterize coincidence detector blocks for DOI-corrected spatial resolution, energy resolution, and timing resolution and use machine learning to recover inter-crystal Compton scattered events to reach the 2-mm intrinsic spatial resolution without sacrificing sensitivity; (3) Build a one-ring prototype Prism-PET scanner; (4) perform normalization scan, optimize our image reconstruction using experimental coincidence events and validate the optimal imaging performance using Hot Spot phantoms. Our proposed TOF-DOI-Compton detector and system technologies maximize the sensitivity benefits of improved geometric coverage in total-body PET scanners across the entire FOV.