Charged-particle emission tomography

Abstract

Purpose: Conventional charged-particle imaging techniques -such as autoradiography -provide only two-dimensional (2D) black ex vivo images of thin tissue slices. In order to get volumetric information, images of multiple thin slices are stacked. This process is time consuming and prone to distortions, as registration of 2D images is required. We propose a direct three-dimensional (3D) autoradiography technique, which we call charged-particle emission tomography (CPET). This 3D imaging technique enables imaging of thick tissue sections, thus increasing laboratory throughput and eliminating distortions due to registration. CPET also has the potential to enable in vivo chargedparticle imaging with a window chamber or an endoscope. Methods: Our approach to charged-particle emission tomography uses particle-processing detectors (PPDs) to estimate attributes of each detected particle. The attributes we estimate include location, direction of propagation, and/or the energy deposited in the detector. Estimated attributes are then fed into a reconstruction algorithm to reconstruct the 3D distribution of charged-particle-emitting radionuclides. Several setups to realize PPDs are designed. Reconstruction algorithms for CPET are developed. Results: Reconstruction results from simulated data showed that a PPD enables CPET if the PPD measures more attributes than just the position from each detected particle. Experiments showed that a two-foil charged-particle detector is able to measure the position and direction of incident alpha particles. Conclusions: We proposed a new volumetric imaging technique for charged-particle-emitting radionuclides, which we have called charged-particle emission tomography (CPET). We also proposed a new class of charged-particle detectors, which we have called particle-processing detectors (PPDs). When a PPD is used to measure the direction and/or energy attributes along with the position attributes, CPET is feasible. (C) 2017 The Authors. Medical