An unusual case of a triple suicide pact at the time of the COVID-19 pandemic.

In December 2020, the World Health Organization (WHO) declared SARS-CoV2 a global pandemic. Home confinement, low social contacts, and fear of virus transmission played a major role as risk factors for suicides during the following period. Suicide pacts, in particular, showed a different pattern. A rare case of a triple suicide pact among members of the same family nucleus is presented. The victims were an elderly, severely ill woman and her adult children (a son and daughter), linked by a morbid relationship. The last time the family was seen alive was 40 days before the discovery. All corpses presented decompositional changes. After a full autopsy, the cause of death was determined to be a lethal intake of morphine for the mother and acute blood loss due to self-stabbing at the neck for the siblings. The younger woman was under the effects of a large amount of heparin. Toxicological analysis was positive for opioids and alcohol in both siblings. Suicide pacts have rarely been described during the COVID-19 pandemic. In the few cases reported, the victims were more often relatives than people in a romantic relationship. The involvement of three people is unusual, as is the use of different suicide methods among the victims. In the presented case, the elderly mother's imminent death from terminal cancer, her concern over dying in a nondomestic environment, and the siblings' fear of being alone likely led to the conception of the suicide pact. Social isolation and economic difficulties also played a contributing role.

PET iterative reconstruction incorporating an efficient positron range correction method.

Positron range is one of the main physical effects limiting the spatial resolution of positron emission tomography (PET) images. If positrons travel inside a magnetic field, for instance inside a nuclear magnetic resonance (MR) tomograph, the mean range will be smaller but still significant. In this investigation we examined a method to correct for the positron range effect in iterative image reconstruction by including tissue-specific kernels in the forward projection operation. The correction method was implemented within STIR library (Software for Tomographic Image Reconstruction). In order to obtain the positron annihilation distribution of various radioactive isotopes in water and lung tissue, simulations were performed with the Monte Carlo package GATE [Jan et al. 2004 [1]] simulating different magnetic field intensities (0 T, 3 T, 9.5 T and 11 T) along the axial scanner direction. The positron range kernels were obtained for (68)Ga in water and lung tissue for 0 T and 3 T magnetic field voxellizing the annihilation coordinates into a three-dimensional matrix. The proposed method was evaluated using simulations of material-variant and material-invariant positron range corrections for the HYPERImage preclinical PET-MR scanner. The use of the correction resulted in sharper active region boundary definition, albeit with noise enhancement, and in the recovery of the true activity mean value of the hot regions. Moreover, in the case where a magnetic field is present, the correction accounts for the non-isotropy of the positron range effect, resulting in the recovery of resolution along the axial plane.

Accurate and efficient modeling of the detector response in small animal multi-head PET systems.

In fully three-dimensional PET imaging, iterative image reconstruction techniques usually outperform analytical algorithms in terms of image quality provided that an appropriate system model is used. In this study we concentrate on the calculation of an accurate system model for the YAP-(S)PET II small animal scanner, with the aim to obtain fully resolution- and contrast-recovered images at low levels of image roughness. For this purpose we calculate the system model by decomposing it into a product of five matrices: (1) a detector response component obtained via Monte Carlo simulations, (2) a geometric component which describes the scanner geometry and which is calculated via a multi-ray method, (3) a detector normalization component derived from the acquisition of a planar source, (4) a photon attenuation component calculated from x-ray computed tomography data, and finally, (5) a positron range component is formally included. This system model factorization allows the optimization of each component in terms of computation time, storage requirements and accuracy. The main contribution of this work is a new, efficient way to calculate the detector response component for rotating, planar detectors, that consists of a GEANT4 based simulation of a subset of lines of flight (LOFs) for a single detector head whereas the missing LOFs are obtained by using intrinsic detector symmetries. Additionally, we introduce and analyze a probability threshold for matrix elements of the detector component to optimize the trade-off between the matrix size in terms of non-zero elements and the resulting quality of the reconstructed images. In order to evaluate our proposed system model we reconstructed various images of objects, acquired according to the NEMA NU 4-2008 standard, and we compared them to the images reconstructed with two other system models: a model that does not include any detector response component and a model that approximates analytically the depth of interaction as detector response component. The comparisons confirm previous research results, showing that the usage of an accurate system model with a realistic detector response leads to reconstructed images with better resolution and contrast recovery at low levels of image roughness.