Detection of novel PPP1R1B::STARD3 fusion transcript in acute myeloid leukemia: a case report.

BACKGROUND: Acute myeloid leukemia (AML) is the second most common type of leukemia in children. Although prognostic and diagnostic tests of AML patients have improved, there is still a great demand for new reliable clinical biomarkers for AML. Read-through fusion transcripts (RTFTs) are complex transcripts of adjacent genes whose molecular mechanisms are poorly understood. This is the first report of the presence of the PPP1R1B::STARD3 fusion transcript in an AML patient. Here, we investigated the presence of PPP1R1B::STARD3 RTFT in a case of AML using paired-end RNA sequencing (RNA-seq). CASE PRESENTATION: A Persian 12-year-old male was admitted to Dr. Sheikh Hospital of Mashhad, Iran, in September 2019 with the following symptoms, including fever, convulsions, hemorrhage, and bone pain. The patient was diagnosed with AML (non-M3-FAB subtype) based on cell morphologies and immunophenotypical features. Chromosomal analysis using the G-banding technique revealed t (9;22) (q34;q13). CONCLUSIONS: Single-cell RNA sequencing (scRNA-seq) analysis suggested that the PPP1R1B promoter may be responsible for the PPP1R1B::STARD3 expression. Alterations in the level of lipid metabolites implicate cancer development, and this fusion can play a crucial role in the cholesterol movement in cancer cells. PPP1R1B::STARD3 may be considered a candidate for targeted therapies of the cholesterol metabolic and the PI3K/AKT signaling pathways involved in cancer development and progression.

Estimation of kinetic parameters in dynamic FDG PET imaging based on shortened protocols: a virtual clinical study.

This study investigated the estimation of kinetic parameters and production of related parametric Ki images in FDG PET imaging using the proposed shortened protocol (three 3-min/bed routine static images) by means of the simulated annealing (SA) algorithm. Six realistic heterogeneous tumors and various levels of [18F] FDG uptake were simulated by the XCAT phantom. An irreversible two-tissue compartment model (2TCM) using population-based input function was employed. By keeping two routine clinical scans fixed (60-min and 90-min post injection), the effect of the early scan time on optimizing the estimation of the pharmacokinetic parameters was investigated. The SA optimization algorithm was applied to estimate micro- and macro-parameters (K1, k2, k3, Ki). The minimum bias for most parameters was observed at a scan time of 20-min, which was < 10%. A highly significant correlation (> 0.9) as well as limited bias (< 10%) were observed between kinetic parameters generated from two methods [two-tissue compartment full dynamic scan (2TCM-full) and two-tissue compartment by SA algorithm (2TCM-SA)]. The analysis showed a strong correlation (> 0.8) between (2TCM-SA) Ki and SUV images. In addition, the tumor-to-background ratio (TBR) metric in the parametric (2TCM-SA) Ki images was significantly higher than SUV, although the SUV images provide better Contrast-to-noise ratio relative to parametric (2TCM-SA) Ki images. The proposed shortened protocol by the SA algorithm can estimate the kinetic parameters in FDG PET scan with high accuracy and robustness. It was also concluded that the parametric Ki images obtained from the 2TCM-SA as a complementary image of the SUV possess more quantification information than SUV images and can be used by the nuclear medicine specialist. This method has the potential to be an alternative to a full dynamic PET scan.

Development and validation of an optimal GATE model for proton pencil-beam scanning delivery.

OBJECTIVE: To develop and validate a versatile Monte Carlo (MC)-based dose calculation engine to support MC-based dose verification of treatment planning systems (TPSs) and quality assurance (QA) workflows in proton therapy. METHODS: The GATE MC toolkit was used to simulate a fixed horizontal active scan-based proton beam delivery (SIEMENS IONTRIS). Within the nozzle, two primary and secondary dose monitors have been designed to enable the comparison of the accuracy of dose estimation from MC simulations with respect to physical QA measurements. The developed beam model was validated against a series of commissioning measurements using pinpoint chambers and 2D array ionization chambers (IC) in terms of lateral profiles and depth dose distributions. Furthermore, beam delivery module and treatment planning has been validated against the literature deploying various clinical test cases of the AAPM TG-119 (c-shape phantom) and a prostate patient. RESULTS: MC simulations showed excellent agreement with measurements in the lateral depth-dose parameters and spread-out Bragg peak (SOBP) characteristics within a maximum relative error of 0.95 mm in range, 1.83% in entrance to peak ratio, 0.27% in mean point-to-point dose difference, and 0.32% in peak location. The mean relative absolute difference between MC simulations and measurements in terms of absorbed dose in the SOBP region was 0.93% ±â€¯0.88%. Clinical phantom studies showed a good agreement compared to research TPS (relative error for TG-119 planning target volume PTV-D95 ∼ 1.8%; and for prostate PTV-D95 ∼ -0.6%). CONCLUSION: We successfully developed a MC model for the pencil beam scanning system, which appears reliable for dose verification of the TPS in combination with QA information, prior to patient treatment.

Sensitivity analysis of the efficiency of Compton camera to the detector parameters using the GEANT4 computer code.

Compton imaging is an imaging technique in which Compton scattering is used to produce images from a gamma-ray source. Compton imaging systems are also known as Compton camera. The basic design of Compton imaging systems consists of two-position detectors that are sensitive to the position and energy scattered from gamma rays. Compton camera efficiency is defined as the fraction of photons entering the scatterer (disperse) detector that undergoes only one Compton scattering and is then photoelectrically absorbed in the absorber detector. In the present study, the efficiency of a Compton camera was investigated based on semiconductor detectors using the GEANT4 simulation toolkit. In this study, the sensitivity of the efficiency of the Compton imaging systems to the distance between the source and the scatterer detector, the distance between the two detectors, dimensions, and thickness of the absorber and scatterer detectors, number of scatterer detectors with different thicknesses, the energy of radioisotope of the source, and semiconductor's type in the scatterer and absorber detectors were performed. To this end, the Compton camera was modeled using the GEANT4 simulation toolkit. In addition, the code was developed in C++ to get the correct events of efficiency in the Compton camera. The simulation model includes the details of the detector geometry, detector segmentation, and energy discrimination levels of the scatterer and absorber. According to the results, 11C has the maximum efficiency as a radioactive source."GaAs" and "Ge" as the scatterer detector and "CdTe" and "HgI2" as the absorber detector are the best choices. According to the results, the shorter the distance between the source and the two detectors, the higher the efficiency of the Compton camera. Of course, this distance must be selected according to the application used. According to the results in the research, with increasing the dimensions of the scatterer detector plate, the amount of efficiency increases up to the dimensions of the absorber detector plate, but a size larger than the absorber detector, it reaches a degree of saturation. Also, by increasing the thickness of the scatterer detector, the efficiency first increases and then reaches the maximum value and then decreases, and increasing the thickness of the absorber detector increases efficiency. The results of the simulation in the present paper have an acceptable agreement with the experimental several types of research in the world. The results of this simulation can be considered for the design of Compton cameras.

Malignant Melanoma Metastasis to the Appendix as the First Presentation of Lentigo Maligna Melanoma.

Malignant melanoma is a malignant neoplasm of the skin and mucosal tissues, and its behavior is not predictable. Thus, it could metastasize via mysterious routes. Here, we report a rare case of acute abdomen and acute appendicitis which involved metastatic malignant melanoma in a 63-year-old man without a history of previously treated malignant melanoma.

Determining of the optimized dimensions of the Marinelli beaker containing source with inhomogeneous emission rate by using genetic algorithm coupled with MCNP and determining distribution type by neural networks.

In order to determine the activity of C137s in soil resulting from nuclear accidents or fallouts, the best choice is to use HPGe detectors due to their best energy resolutions. In this regard, in order to enhance the detection efficiency, the Marinelli beakers have been used to increase the radiation interaction with the sensitive volume of the detector. In previous works, to optimize the dimension of Marinelli beakers, the assumption was that the emission rate of the source is homogeneous in beaker volume. In the present study, to investigate the effect of the inhomogeneous emission rate of the source on the optimum dimensions of the beaker, in a simple case, the beaker was divided into two sections (upper and lower) containing different C137s emission rates. A code based on MCNPX2.6 coupled with genetic algorithm was developed and used to investigate the effects of different emission rates of C137s at the upper and lower section of the beaker on optimum dimensions of the Marinelli with different volumes (300-1500 cm3). The results showed that the inhomogeneity in the emission rate greatly affects the optimal dimensions of the beaker. By using the C137s spectra simulated for a conventional beaker at different emission probabilities in the upper and lower section in training a neural network, the emission probabilities of a beaker containing C137s was estimated.

Evaluation of a new neutron energy spectrum unfolding code based on an Adaptive Neuro-Fuzzy Inference System (ANFIS).

The purpose of the present study was to reconstruct the energy spectrum of a poly-energetic neutron source using an algorithm developed based on an Adaptive Neuro-Fuzzy Inference System (ANFIS). ANFIS is a kind of artificial neural network based on the Takagi-Sugeno fuzzy inference system. The ANFIS algorithm uses the advantages of both fuzzy inference systems and artificial neural networks to improve the effectiveness of algorithms in various applications such as modeling, control and classification. The neutron pulse height distributions used as input data in the training procedure for the ANFIS algorithm were obtained from the simulations performed by MCNPX-ESUT computational code (MCNPX-Energy engineering of Sharif University of Technology). Taking into account the normalization condition of each energy spectrum, 4300 neutron energy spectra were generated randomly. (The value in each bin was generated randomly, and finally a normalization of each generated energy spectrum was performed). The randomly generated neutron energy spectra were considered as output data of the developed ANFIS computational code in the training step. To calculate the neutron energy spectrum using conventional methods, an inverse problem with an approximately singular response matrix (with the determinant of the matrix close to zero) should be solved. The solution of the inverse problem using the conventional methods unfold neutron energy spectrum with low accuracy. Application of the iterative algorithms in the solution of such a problem, or utilizing the intelligent algorithms (in which there is no need to solve the problem), is usually preferred for unfolding of the energy spectrum. Therefore, the main reason for development of intelligent algorithms like ANFIS for unfolding of neutron energy spectra is to avoid solving the inverse problem. In the present study, the unfolded neutron energy spectra of 252Cf and 241Am-9Be neutron sources using the developed computational code were found to have excellent agreement with the reference data. Also, the unfolded energy spectra of the neutron sources as obtained using ANFIS were more accurate than the results reported from calculations performed using artificial neural networks in previously published papers.

Optimization of the marinelli beaker dimensions using genetic algorithm.

A computational code, based on the genetic algorithm and MCNPX version 2.6 code was developed and used to investigate the effects of some important parameters of HPGe detector (such as Al cap thickness, dead-layer thickness and Ge hole size) on optimum dimensions of marinelli beaker. In addition, the effects of detector material on optimal beaker dimensions were also investigated. Finally, the optimized beaker dimensions at various beaker volumes (300, 500, 700, 1000 and 1500 cm3) were determined for some conventional Ge detectors with different crystal sizes (16 sizes). These sets of data then were used to drive mathematical formulas (obtained by best fitting to data sets). The results showed that, there is no meaningful correlation between the optimum dimensions of the beaker and each of the dead-layer thickness, Al cap thickness and the Ge-crystal hole size. On the other hand, the optimum beaker radius increases with decreasing the density of the detector material while the beaker height decreases.