Our MR-based attenuation correction method offers similar correction accuracy as offered by segmented CT. According to the specialists involved in the blind study, these differences do not affect the diagnostic value of the PET images.

Compton Cameras emerged as an alternative for real-time dose monitoring techniques for Particle Therapy (PT), based on the detection of prompt-gammas. As a consequence of the Compton scattering process, the gamma origin point can be restricted onto the surface of a cone (Compton cone). Through image reconstruction techniques, the distribution of the gamma emitters can be estimated, using cone-surfaces backprojections of the Compton cones through the image space, along with more sophisticated statistical methods to improve the image quality. To calculate the Compton cone required for image reconstruction, either two interactions, the last being photoelectric absorption, or three scatter interactions are needed. Because of the high energy of the photons in PT the first option might not be adequate, as the photon is not absorbed in general. However, the second option is less efficient. That is the reason to resort to spectral reconstructions, where the incoming γ energy is considered as a variable in the reconstruction inverse problem. Jointly with prompt gamma, secondary neutrons and scattered photons, not strongly correlated with the dose map, can also reach the imaging detector and produce false events. These events deteriorate the image quality. Also, high intensity beams can produce particle accumulation in the camera, which lead to an increase of random coincidences, meaning events which gather measurements from different incoming particles. The noise scenario is expected to be different if double or triple events are used, and consequently, the reconstructed images can be affected differently by spurious data. The aim of the present work is to study the effect of false events in the reconstructed image, evaluating their impact in the determination of the beam particle ranges. A simulation study that includes misidentified events (neutrons and random coincidences) in the final image of a Compton Telescope for PT monitoring is presented. The complete chain of detection, from the beam particle entering a phantom to the event classification, is simulated using FLUKA. The range determination is later estimated from the reconstructed image obtained from a two and three-event algorithm based on Maximum Likelihood Expectation Maximization. The neutron background and random coincidences due to a therapeutic-like time structure are analyzed for mono-energetic proton beams. The time structure of the beam is included in the simulations, which will affect the rate of particles entering the detector.

In order to exploit the advantages of ion-beam therapy in a clinical setting, delivery verification techniques are necessary to detect deviations from the planned treatment. Efforts are currently oriented towards the development of devices for real-time range monitoring. Among the different detector concepts proposed, Compton cameras are employed to detect prompt gammas and represent a valid candidate for real-time range verification. We present the first on-beam test of MACACO, a Compton telescope (multi-layer Compton camera) based on lanthanum bromide crystals and silicon photo-multipliers. The Compton telescope was first characterized through measurements and Monte Carlo simulations. The detector linearity was measured employing (22)Na and Am-Be sources, obtaining about 10% deviation from linearity at 3.44 MeV. A spectral image reconstruction algorithm was tested on synthetic data. Point-like sources emitting gamma rays with energy between 2 and 7 MeV were reconstructed with 3-5 mm resolution. The two-layer Compton telescope was employed to measure radiation emitted from a beam of 150 MeV protons impinging on a cylindrical PMMA target. Bragg-peak shifts were achieved via adjustment of the PMMA target location and the resulting measurements used during image reconstruction. Reconstructed Bragg peak profiles proved sufficient to observe peak-location differences within 10 mm demonstrating the potential of the MACACO Compton Telescope as a monitoring device for ion-beam therapy.

We propose in this study a novel PET detector concept as insert for simultaneous PET/MR imaging, using arrays of Silicon Photomultipliers (SiPMs) as photodetectors, read out by a data acquisition system based on sampling ADCs. A 2 × 2 LSO-SiPM detector array and four single channel LYSO-SiPM detectors have been evaluated and compared to a LSO-APD detector. A 17.9% energy resolution and a 1.4 ns time resolution have been measured. No degradation of these values could be detected when simultaneous MR acquisitions were performed. The nonlinear detector behaviour due to the limited dynamic range and recovery time effects has been studied. In addition, the contribution of dark counts and optical crosstalk for PET applications was also addressed. The feasibility for position localization of the incident light to a SiPM array using Anger logic has been investigated.

A major source of error in quantitative PET/CT scans of lung cancer tumors is respiratory motion. Regarding the variability of PET texture features (TF), the impact of respiratory motion has not been properly studied with experimental phantoms. The primary aim of this work was to evaluate the current use of PET texture analysis for heterogeneity characterization in lesions affected by respiratory motion. Twenty-eight heterogeneous lesions were simulated by a mixture of alginate and F-fluoro-2-deoxy-D-glucose (FDG). Sixteen respiratory patterns were applied. Firstly, the TF response for different heterogeneous phantoms and its robustness with respect to the segmentation method were calculated. Secondly, the variability for TF derived from PET image with (gated, G-) and without (ungated, U-) motion compensation was analyzed. Finally, TF complementarity was assessed. In the comparison of TF derived from the ideal contour with respect to TF derived from 40%-threshold and adaptive-threshold PET contours, 7/8 TF showed strong linear correlation (LC) (p< 0.001, r > 0.75), despite a significant volume underestimation. Independence of lesion movement (LC in 100% of the combined pairs of movements, p < 0.05) was obtained for 1/8 TF with U-image (width of the volume-activity histogram, WH) and 4/8 TF with G-image (WH and energy (ENG), local-homogeneity (LH) and entropy (ENT), derived from the co-ocurrence matrix). Their variability in terms of the coefficient of variance ([Formula: see text]) resulted in [Formula: see text](WH)  =  0.18 on the U-image and [Formula: see text](WH)  =  0.24, [Formula: see text](ENG)  =  0.15, [Formula: see text](LH)  =  0.07 and [Formula: see text](ENT)  =  0.06 on the G-image. Apart from WH (r > 0.9, p < 0.001), not one of these TF has shown LC with C . Complementarity was observed for the TF pairs: ENG-LH, CONT (contrast)-ENT and LH-ENT. In conclusion, the effect of respiratory motion should be taken into account when the heterogeneity of lung cancer is quantified on PET/CT images. Despite inaccurate volume delineation, TF derived from 40% and COA contours could be reliable for their prognostic use. The TF that exhibited simultaneous added value and independence of lesion movement were ENG and ENT computed from the G-image. Their use is therefore recommended for heterogeneity quantification of lesions affected by respiratory motion.

MADPET-II is a small animal PET tomograph that features individual Lutetium Oxyorthosilicate (LSO) crystal readout from Avalanche PhotoDiodes (APDs). The detector signals are preamplified by 16-channel fully integrated ASICs which are placed as close as possible to the detector in order to avoid attenuation of the signal or unwanted stray capacitance. However, the power consumption of the preamplifier (30 mW per channel) can cause heat transfer and, consequently, gain drift to temperature sensitive detectors. Temperature measurements on the front-end electronics of MADPET-II have shown a maximum increase of approximately 30 C in the area around the preamplifier and 10 C in the area around the APD-LSO detector with respect to room temperature. In the presence of this temperature gradient, energy spectra have been acquired from which a significant drift of the photopeak (3.4% per C) and a small increase of the mean energy resolution (3% over the whole temperature range studied) with increasing temperature has been observed. The effect of temperature on the time resolution is small in comparison to the effect of walk and jitter introduced by the analog processing electronics. The behavior of two 4 8 LSO-APD front-end detector arrays in coincidence at temperatures below ambient and at various values of the APD bias voltage in terms of energy and time resolution has also been studied. The total current drawn by the APDs (leakage current and photocurrent) has been monitored at various temperatures T and APD bias and was modelled and fitted by a theoretical function demonstrating a T and 1 dependence. No significant improvement on time resolution with decreasing temperature has been observed. For temperature stabilization and monitoring, thermoelectric cooling is considered appropriate for mounting in the limited free space of a PET scanner, especially when this is inside an MR scanner for simultaneous PET/MR imaging.

In lung cancer, quantification by positron emission tomography/computed tomography (PET/CT) imaging presents challenges due to respiratory movement. Our primary aim was to study the impact of motion compensation implied by retrospectively gated (4D)-PET/CT on the variability of PET quantitative parameters. Its significance was evaluated by comparison with the variability due to (i) the voxel size in image reconstruction and (ii) the voxel size in image post-resampling. The method employed for feature extraction was chosen based on the analysis of (i) the effect of discretization of the standardized uptake value (SUV) on complementarity between texture features (TF) and conventional indices, (ii) the impact of the segmentation method on the variability of image features, and (iii) the variability of image features across the time-frame of 4D-PET. Thirty-one PET-features were involved. Three SUV discretization methods were applied: a constant width (SUV resolution) of the resampling bin (method RW), a constant number of bins (method RN) and RN on the image obtained after histogram equalization (method EqRN). The segmentation approaches evaluated were 40[Formula: see text] of SUV and the contrast oriented algorithm (COA). Parameters derived from 4D-PET images were compared with values derived from the PET image obtained for (i) the static protocol used in our clinical routine (3D) and (ii) the 3D image post-resampled to the voxel size of the 4D image and PET image derived after modifying the reconstruction of the 3D image to comprise the voxel size of the 4D image. Results showed that TF complementarity with conventional indices was sensitive to the SUV discretization method. In the comparison of COA and 40[Formula: see text] contours, despite the values not being interchangeable, all image features showed strong linear correlations (r > 0.91, [Formula: see text]). Across the time-frames of 4D-PET, all image features followed a normal distribution in most patients. For our patient cohort, the compensation of tumor motion did not have a significant impact on the quantitative PET parameters. The variability of PET parameters due to voxel size in image reconstruction was more significant than variability due to voxel size in image post-resampling. In conclusion, most of the parameters (apart from the contrast of neighborhood matrix) were robust to the motion compensation implied by 4D-PET/CT. The impact on parameter variability due to the voxel size in image reconstruction and in image post-resampling could not be assumed to be equivalent.

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