Statistical LOR estimation for a high-resolution dMiCE PET detector

Abstract

We develop a statistical line of response (LOR) estimator of the three-dimensional interaction positions of a pair of annihilation photons in a PET detector module with depth of interaction capability. The three-dimensional points of interaction of a coincidence pair of photons within the detector module are estimated by calculation of an expectation of the points of interaction conditioned on the signals measured by the photosensors. This conditional expectation is computed from estimates of the probability density function of the light collection process and a model of the kinetics of photon interactions in the detector module. Our algorithm is capable of handling coincidences where each annihilation photon interacts any number of times within the detector module before being completely absorbed or escaping. In the case of multiple interactions, our algorithm estimates the position of the first interaction for each of the coincidence photons. This LOR estimation algorithm is developed for a high-resolution PET detector capable of providing depth-of-interaction information. Depth of interaction is measured by tailoring the light shared between two adjacent detector elements. These light-sharing crystal pairs are referred to as dMiCE and are being developed in our lab. Each detector element in the prototype system has a 2 × 2 mm2 cross section and is directly coupled to a micro-pixel avalanche photodiode (MAPD). In this set-up, the distribution of the ratio of light shared between two adjacent detector elements can be expressed as a function of the depth of interaction. Monte Carlo experiments are performed using our LOR estimation algorithm and compared with Anger logic. We show that our LOR estimation algorithm provides a significant improvement over Anger logic under a variety of parameters.

Effects of multiple‐interaction photon events in a high‐resolution PET system that uses 3‐D positioning detectors

“…A number of studies have quantified the effects of MIPEs on system photon sensitivity and the quality of highresolution PET images, [7][8][9][10][11][12] based on either crystal configurations with the ability to record only a MIPE's center-of-mass coordinates in 2-D, 7 systems that can record individual MIPE interactions, but using crystal elements larger 1 mmϫ 1 mmϫ 1 mm, or systems with limited ability to process MIPEs for image reconstruction. [8][9][10][11][12] Different approaches have been studied in Refs.…”

“…[8][9][10][11][12] Different approaches have been studied in Refs. 7-12 for identifying the first interaction in MIPEs, these include positioning MIPEs ͑i͒ at the energy-weighted spatial mean, ͑ii͒ at the interaction with the highest or second highest energy, ͑iii͒ at the interaction closest or farthest from the scintillator-photodetector interface, ͑iv͒ at the interaction most likely to be the first according to Compton kinematics or Klein-Nishina differential cross section ͑as well as hybrids thereof͒, and ͑v͒ using a maximum likelihood Bayesian estimator based on photon interaction kinematics.…”

Accelerating Statistical LOR Estimation for a High-Resolution PET Scanner Using FPGA Devices and a High Level Synthesis Tool

“…e k is the computed estimated energy of a photon after the k-th interaction at position a k , and e 0 is assumed to be 511 keV. The detail of computing the probability for an interaction sequence could be found in [3].…”

“…In order to estimate the first interaction positions of photons, a statistical LOR estimation method is proposed in [3]. It uses a Bayesian estimator for determining a LOR by estimating three-dimensional interaction positions of a pair of annihilation photons.…”

A Building Block for Nuclear Medicine Imaging Systems Data Acquisition

“…As we developed our dMiCE and cMiCE detector concepts [1,2], we found that our existing electronics was inadequate to the task and launched a design effort we have termed our Phase II electronics [3]. Here we report on the implementation and evolution of the Phase II system as a basic building block for a wide variety of data acquisition tasks.…”