Charged-particle emission tomography

Abstract

PurposeConventional 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 charged-particle imaging with a window chamber or an endoscope.MethodsOur 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.ResultsReconstruction 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.ConclusionsWe 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.

Computational Methods for Photon-Counting and Photon- Processing Detectors

“…and bias voltage V bias applied across the semiconductor. Some recent results for the Medipix2 sensor have been reported in [1,7]. When a highly energetic particle enters the detector, a large number of charges will be collected at its electrodes.…”

“…in which A denotes the mean of the image intensifier amplification (gain) A . The variance, σ 2 m , of g m is related to p m and the statistics of A as follows [7]:…”

“…A is the variance of the amplification A and σ 2 read denotes the variance of the sensor's readout noise. If the blur introduced by the image intensifier and optics located between the image intensifier and the CCD sensor is smaller than the size of a sensor pixel, then output g m is independent on g m 0 for any m 0 6 ¼ m. If we further assume that the amplification A and the readout noise also obey Gaussian statistics, we can write [1,7]:…”

“…An example of a particle-processing detector for beta particles is shown in Figure 6. This detector includes two layers of ultrathin phosphor foils separated by an air gap, an image intensifier, a high numerical aperture lens system and a light sensor [1,7].…”

“…A portion of this chapter has been adapted from Y. Ding, "Charged-Particle Emission Tomography" [1].…”