Positron range in PET imaging: non-conventional isotopes.

In addition to conventional short-lived radionuclides, longer-lived isotopes are becoming increasingly important to positron emission tomography (PET). The longer half-life both allows for circumvention of the in-house production of radionuclides, and expands the spectrum of physiological processes amenable to PET imaging, including processes with prohibitively slow kinetics for investigation with short-lived radiotracers. However, many of these radionuclides emit 'high-energy' positrons and gamma rays which affect the spatial resolution and quantitative accuracy of PET images. The objective of the present work is to investigate the positron range distribution for some of these long-lived isotopes. Based on existing Monte Carlo simulations of positron interactions in water, the probability distribution of the line of response displacement have been empirically described by means of analytic displacement functions. Relevant distributions have been derived for the isotopes (22)Na, (52)Mn, (89)Zr, (45)Ti, (51)Mn, (94 m)Tc, (52 m)Mn, (38)K, (64)Cu, (86)Y, (124)I, and (120)I. It was found that the distribution functions previously found for a series of conventional isotopes (Jødal et al 2012 Phys. Med. Bio. 57 3931-43), were also applicable to these non-conventional isotopes, except that for (120)I, (124)I, (89)Zr, (52)Mn, and (64)Cu, parameters in the formulae were less well predicted by mean positron energy alone. Both conventional and non-conventional range distributions can be described by relatively simple analytic expressions. The results will be applicable to image-reconstruction software to improve the resolution.

Denoising techniques combined to Monte Carlo simulations for the prediction of high-resolution portal images in radiotherapy treatment verification.

This work investigates the possibility of combining Monte Carlo (MC) simulations to a denoising algorithm for the accurate prediction of images acquired using amorphous silicon (a-Si) electronic portal imaging devices (EPIDs). An accurate MC model of the Siemens OptiVue1000 EPID was first developed using the penelope code, integrating a non-uniform backscatter modelling. Two already existing denoising algorithms were then applied on simulated portal images, namely the iterative reduction of noise (IRON) method and the locally adaptive Savitzky-Golay (LASG) method. A third denoising method, based on a nonparametric Bayesian framework and called DPGLM (for Dirichlet process generalized linear model) was also developed. Performances of the IRON, LASG and DPGLM methods, in terms of smoothing capabilities and computation time, were compared for portal images computed for different values of the RMS pixel noise (up to 10%) in three different configurations, a heterogeneous phantom irradiated by a non-conformal 15 × 15 cm(2) field, a conformal beam from a pelvis treatment plan, and an IMRT beam from a prostate treatment plan. For all configurations, DPGLM outperforms both IRON and LASG by providing better smoothing performances and demonstrating a better robustness with respect to noise. Additionally, no parameter tuning is required by DPGLM, which makes the denoising step very generic and easy to handle for any portal image. Concerning the computation time, the denoising of 1024 × 1024 images takes about 1 h 30 min, 2 h and 5 min using DPGLM, IRON, and LASG, respectively. This paper shows the feasibility to predict within a few hours and with the same resolution as real images accurate portal images, combining MC simulations with the DPGLM denoising algorithm.

Positron range in PET imaging: an alternative approach for assessing and correcting the blurring.

Positron range impairs resolution in PET imaging, especially for high-energy emitters and for small-animal PET. De-blurring in image reconstruction is possible if the blurring distribution is known. Furthermore, the percentage of annihilation events within a given distance from the point of positron emission is relevant for assessing statistical noise. This paper aims to determine the positron range distribution relevant for blurring for seven medically relevant PET isotopes, (18)F, (11)C, (13)N, (15)O, (68)Ga, (62)Cu and (82)Rb, and derive empirical formulas for the distributions. This paper focuses on allowed-decay isotopes. It is argued that blurring at the detection level should not be described by the positron range r, but instead the 2D projected distance δ (equal to the closest distance between decay and line of response). To determine these 2D distributions, results from a dedicated positron track-structure Monte Carlo code, Electron and POsitron TRANsport (EPOTRAN), were used. Materials other than water were studied with PENELOPE. The radial cumulative probability distribution G(2D)(δ) and the radial probability density distribution g(2D)(δ) were determined. G(2D)(δ) could be approximated by the empirical function 1 - exp(-Aδ(2) - Bδ), where A = 0.0266 (E(mean))(-1.716) and B = 0.1119 (E(mean))(-1.934), with E(mean) being the mean positron energy in MeV and δ in mm. The radial density distribution g(2D)(δ) could be approximated by differentiation of G(2D)(δ). Distributions in other media were very similar to water. The positron range is important for improved resolution in PET imaging. Relevant distributions for the positron range have been derived for seven isotopes. Distributions for other allowed-decay isotopes may be estimated with the above formulas.

Positron follow-up in liquid water: II. Spatial and energetic study for the most important radioisotopes used in PET.

With the increasing development of positron emission tomography (PET), beta(+)-emitters are more and more regularly used in nuclear medicine. Therefore, today it is of prime importance to have a reliable description of their behavior in living matter in order to quantify the full spectra of the molecular damages potentially radio-induced and then to access a cellular dosimetry. In this work, we present a detailed inter-comparison of the main isotopes commonly used in PET: (18)F, (11)C, (13)N, (15)O, (68)Ga and (82)Rb. We have used an event-by-event Monte Carlo code recently developed for positron tracking in water (Champion and Le Loirec 2006 Phys. Med. Biol. 51 1707-23) which consists in simulating step-by-step, interaction after interaction, the history of each ionizing particle created during the irradiation of the biological matter. This simulation has been finally adapted for describing the decays of medically important positron emitters. Quantitative information about positron penetrations, Positronium formation, annihilation event distributions, energy deposit patterns and dose profiles is then accessible and compared to published measurements and/or calculations.

Positron follow-up in liquid water: I. A new Monte Carlo track-structure code.

When biological matter is irradiated by charged particles, a wide variety of interactions occur, which lead to a deep modification of the cellular environment. To understand the fine structure of the microscopic distribution of energy deposits, Monte Carlo event-by-event simulations are particularly suitable. However, the development of these track-structure codes needs accurate interaction cross sections for all the electronic processes: ionization, excitation, positronium formation and even elastic scattering. Under these conditions, we have recently developed a Monte Carlo code for positrons in water, the latter being commonly used to simulate the biological medium. All the processes are studied in detail via theoretical differential and total cross-section calculations performed by using partial wave methods. Comparisons with existing theoretical and experimental data in terms of stopping powers, mean energy transfers and ranges show very good agreements. Moreover, thanks to the theoretical description of positronium formation, we have access, for the first time, to the complete kinematics of the electron capture process. Then, the present Monte Carlo code is able to describe the detailed positronium history, which will provide useful information for medical imaging (like positron emission tomography) where improvements are needed to define with the best accuracy the tumoural volumes.