Reconstruction of multi-animal PET acquisitions with anisotropically variant PSF.

Among other factors such as random, attenuation and scatter corrections, uniform spatial resolution is key to performing accurate quantitative studies in Positron emission tomography (PET). Particularly in preclinical PET studies involving simultaneous acquisition of multiple animals, the degradation of image resolution due to the depth of interaction (DOI) effect far from the center of the Field of View (FOV) becomes a significant concern. In this work, we incorporated a spatially-variant resolution model into a real time iterative reconstruction code to obtain accurate images of multi-animal acquisition. We estimated the spatially variant point spread function (SV-PSF) across the FOV using measurements and Monte Carlo (MC) simulations. The SV-PSF obtained was implemented in a GPU-based Ordered subset expectation maximization (OSEM) reconstruction code, which includes scatter, attenuation and random corrections. The method was evaluated with acquisitions from two preclinical PET/CT scanners of the SEDECAL Argus family: a Derenzo phantom placed 2 cm off center in the 4R-SuperArgus, and a multi-animal study with 4 mice in the 6R-SuperArgus. The SV-PSF reconstructions showed uniform spatial resolution without significant increase in reconstruction time, with superior image quality compared to the uniform PSF model.

Dictionary-based software for proton dose reconstruction and submilimetric range verification.

Objective.This paper presents a new method for fast reconstruction (compatible with in-beam use) of deposited dose during proton therapy using data acquired from a PET scanner. The most innovative feature of this novel method is the production of noiseless reconstructed dose distributions from which proton range can be derived with high precision.Approach.A new MLEM & simulated annealing (MSA) algorithm, developed especially in this work, reconstructs the deposited dose distribution from a realistic pre-calculated activity-dose dictionary. This dictionary contains the contribution of each beam in the plan to the 3D activity and dose maps, as calculated by a Monte Carlo simulation. The MSA algorithm, usinga prioriinformation of the treatment plan, seeks for the linear combination of activities of the precomputed beams that best fits the observed PET data, obtaining at the same time the deposited dose.Main results.the method has been tested using simulated data to determine its performance under 4 different test cases: (1) dependency of range detection accuracy with delivered dose, (2) in-beam versus offline verification, (3) ability to detect anatomical changes and (4) reconstruction of a realistic spread-out Bragg peak. The results show the ability of the method to accurately reconstruct doses from PET data corresponding to 1 Gy irradiations, both in intra-fraction and inter-fraction verification scenarios. For this dose level (1 Gy) the method was able to spot range variations as small as 0.6 mm.Significance.out method is able to reconstruct dose maps with remarkable accuracy from clinically relevant dose levels down to 1 Gy. Furthermore, due to the noiseless nature of reconstructed dose maps, an accuracy better than one millimeter was obtained in proton range estimates. These features make of this method a realistic option for range verification in proton therapy.