Positron emission tomography (PET) is a tool for metabolic imaging that has been utilized since the earliest days of nuclear medicine. A key component of such imaging systems is the detector modules—an area of research and development with a long, rich history. Development of detectors for PET has often seen the migration of technologies, originally developed for high energy physics experiments, into prototype PET detectors. Of the many areas explored, some detector designs go on to be incorporated into prototype scanner systems and a few of these may go on to be seen in commercial scanners. There has been a steady, often very diverse development of prototype detectors, and the pace has accelerated with the increased use of PET in clinical studies (currently driven by PET/CT scanners) and the rapid proliferation of pre-clinical PET scanners for academic and commercial research applications. Most of these efforts are focused on scintillator-based detectors, although various alternatives continue to be considered. For example, wire chambers have been investigated many times over the years and more recently various solid-state devices have appeared in PET detector designs for very high spatial resolution applications. But even with scintillators, there have been a wide variety of designs and solutions investigated as developers search for solutions that offer very high spatial resolution, fast timing, high sensitivity and are yet cost effective. In this review, we will explore some of the recent developments in the quest for better PET detector technology.

We present a clustering method to extract the depth of interaction (DOI) information from an 8 mm thick crystal version of our continuous miniature crystal element (cMiCE) small animal PET detector. This clustering method, based on the maximum-likelihood (ML) method, can effectively build look-up tables (LUT) for different DOI regions. Combined with our statistics-based positioning (SBP) method, which uses a LUT searching algorithm based on the ML method and two-dimensional mean-variance LUTs of light responses from each photomultiplier channel with respect to different gamma ray interaction positions, the position of interaction and DOI can be estimated simultaneously. Data simulated using DETECT2000 were used to help validate our approach. An experiment using our cMiCE detector was designed to evaluate the performance. Two and four DOI region clustering were applied to the simulated data. Two DOI regions were used for the experimental data. The misclassification rate for simulated data is about 3.5% for two DOI regions and 10.2% for four DOI regions. For the experimental data, the rate is estimated to be approximately 25%. By using multi-DOI LUTs, we also observed improvement of the detector spatial resolution, especially for the corner region of the crystal. These results show that our ML clustering method is a consistent and reliable way to characterize DOI in a continuous crystal detector without requiring any modifications to the crystal or detector front end electronics. The ability to characterize the depth-dependent light response function from measured data is a major step forward in developing practical detectors with DOI positioning capability.

Abstract-Appropriate application of spatially variant system models can correct for degraded resolution response and mispositioning errors. This paper explores the detector blurring component of the system model for a whole body positron emission tomography (PET) system and extends this factor into a more general system response function to account for other system effects including the influence of Fourier rebinning (FORE). We model the system response function as a three-dimensional

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Here we demonstrate a parametric positioning method on a continuous crystal detector. Three different models for the light distribution were tested. Diagnosis of the residues showed that the parametric model fits the experimental data better than Gaussian and Cauchy models in our particular experimental setup. Based on the correlation between the spread and the peak value of the light distribution model with the depth of interaction (DOI), we were able to estimate the three-dimensional position of a scintillation event. On our continuous miniature crystal element (cMiCE) detector module with 8 mm thick LYSO crystal, the intrinsic spatial resolution is 1.06 mm at the center and 1.27 mm at the corner using a maximum-likelihood estimation (MLE) method and the parametric model. The DOI resolution (full width at half maximum) is estimated to be approximately 3.24 mm. The positioning method using the parametric model outperformed the Gaussian and Cauchy models, in both MLE and weighted least-squares (WLS) fitting methods. The key feature of this technique is that it requires very little calibration of the detector, but still retains high resolution and high sensitivity.