3D in‐system calibration method for PET detectors

Abstract

BackgroundLight‐sharing detector designs for positron emission tomography (PET) systems have sparked interest in the scientific community. Particularly, (semi‐)monoliths show generally good performance characteristics regarding 2D positioning, energy‐, and timing resolution, as well as readout area. This is combined with intrinsic depth‐of‐interaction (DOI) capability to ensure a homogeneous spatial resolution across the entire field of view (FoV). However, complex positioning calibration processes limit their use in PET systems, especially in large‐scale clinical systems.PurposeThis work proposes a new 3D positioning in‐system calibration method for fast and convenient (re‐)calibration and quality control of assembled PET scanners. The method targets all kinds of PET detectors that achieve the best performance with individual calibration, including complex segmented detector designs. The in‐system calibration method is evaluated and empirically compared to a state‐of‐the‐art fan‐beam calibration for a small‐diameter proof of concept (PoC) scanner. A simulation study evaluates the method's applicability to different scanner geometries.MethodsA PoC scanner geometry of 120 mm inner diameter and 150 mm axial extent was set up consisting of five identical finely segmented slab detectors (one detector under test and four collimation detectors). A 22Na point source was moved in a circular path inside the FoV. Utilizing virtual collimation and by selecting gamma rays incident approximately perpendicular to the detector normal of the detector under test, training data was created for the training of a 2D positioning model with the machine‐learning technique gradient tree boosting (GTB). Data with oblique ray angles was acquired in the same measurement for subsequent angular DOI calibration. For this, a 2D position estimate in the detector under test was calculated first. On this basis, the DOI label was calculated geometrically from the ray path within the detector to finally establish up to 3D training data.ResultsWith a mean absolute error (MAE) of 0.8 and 1.19 mm full‐width at half maximum (FWHM) along the planar‐monolithic slab dimension, the in‐system methods performed similarly within 1% to the fan‐beam collimator results. The DOI performance was at ∼90% with 1.13 mm MAE and 2.47 mm FWHM to the fan‐beam collimator. Analytical calculations suggest an improved performance for larger scanner geometries.ConclusionThe functionality of the 3D in‐system positioning calibration method was successfully demonstrated with the measurements within a PoC scanner configuration with similar positioning performance as the bench‐top fan‐beam setup. The in‐system calibration method can be used to calibrate and test fully assembled PET systems to enable more complex light‐sharing detector architectures in, for example, large PET systems with many detectors. The acquired data can further be used for more complex energy and time calibrations.