Dosimetry of gamma chamber blood irradiator using PAGAT gel dosimeter and Monte Carlo simulations.

Currently, the use of blood irradiation for inactivating pathogenic microbes in infected blood products and preventing graft-versus-host disease (GVHD) in immune suppressed patients is greater than ever before. In these systems, dose distribution and uniformity are two important concepts that should be checked. In this study, dosimetry of the gamma chamber blood irradiator model Gammacell 3000 Elan was performed by several dosimeter methods including thermoluminescence dosimeters (TLD), PAGAT gel dosimetry, and Monte Carlo simulations using MCNP4C code. The gel dosimeter was put inside a glass phantom and the TL dosimeters were placed on its surface, and the phantom was then irradiated for 5 min and 27 sec. The dose values at each point inside the vials were obtained from the magnetic resonance imaging of the phantom. For Monte Carlo simulations, all components of the irradiator were simulated and the dose values in a fine cubical lattice were calculated using tally F6. This study shows that PAGAT gel dosimetry results are in close agreement with the results of TL dosimetry, Monte Carlo simulations, and the results given by the vendor, and the percentage difference between the different methods is less than 4% at different points inside the phantom. According to the results obtained in this study, PAGAT gel dosimetry is a reliable method for dosimetry of the blood irradiator. The major advantage of this kind of dosimetry is that it is capable of 3D dose calculation.

Deep-learning survival analysis for patients with calcific aortic valve disease undergoing valve replacement.

Calcification of the aortic valve (CAVDS) is a major cause of aortic stenosis (AS) leading to loss of valve function which requires the substitution by surgical aortic valve replacement (SAVR) or transcatheter aortic valve intervention (TAVI). These procedures are associated with high post-intervention mortality, then the corresponding risk assessment is relevant from a clinical standpoint. This study compares the traditional Cox Proportional Hazard (CPH) against Machine Learning (ML) based methods, such as Deep Learning Survival (DeepSurv) and Random Survival Forest (RSF), to identify variables able to estimate the risk of death one year after the intervention, in patients undergoing either to SAVR or TAVI. We found that with all three approaches the combination of six variables, named albumin, age, BMI, glucose, hypertension, and clonal hemopoiesis of indeterminate potential (CHIP), allows for predicting mortality with a c-index of approximately 80 % . Importantly, we found that the ML models have a better prediction capability, making them as effective for statistical analysis in medicine as most state-of-the-art approaches, with the additional advantage that they may expose non-linear relationships. This study aims to improve the early identification of patients at higher risk of death, who could then benefit from a more appropriate therapeutic intervention.

Modelling physiology of haemodynamic adaptation in short-term microgravity exposure and orthostatic stress on Earth.

Cardiovascular haemodynamics alters during posture changes and exposure to microgravity. Vascular auto-remodelling observed in subjects living in space environment causes them orthostatic intolerance when they return on Earth. In this study we modelled the human haemodynamics with focus on head and neck exposed to different hydrostatic pressures in supine, upright (head-up tilt), head-down tilt position, and microgravity environment by using a well-developed 1D-0D haemodynamic model. The model consists of two parts that simulates the arterial (1D) and brain-venous (0D) vascular tree. The cardiovascular system is built as a network of hydraulic resistances and capacitances to properly model physiological parameters like total peripheral resistance, and to calculate vascular pressure and the related flow rate at any branch of the tree. The model calculated 30.0 mmHg (30%), 7.1 mmHg (78%), 1.7 mmHg (38%) reduction in mean blood pressure, intracranial pressure and central venous pressure after posture change from supine to upright, respectively. The modelled brain drainage outflow percentage from internal jugular veins is 67% and 26% for supine and upright posture, while for head-down tilt and microgravity is 65% and 72%, respectively. The model confirmed the role of peripheral veins in regional blood redistribution during posture change from supine to upright and microgravity environment as hypothesized in literature. The model is able to reproduce the known haemodynamic effects of hydraulic pressure change and weightlessness. It also provides a virtual laboratory to examine the consequence of a wide range of orthostatic stresses on human haemodynamics.

Paediatric haemodynamic modelling: development and experimental validation using quantitative flow MRI.

BACKGROUND: Congenital vascular disease is one of the leading causes of death in paediatric age. Despite the importance of paediatric haemodynamics, large investigations have been devoted to the evaluation of circulation in adults. The novelty of this study consists in the development of a well calibrated mathematical model of cardiovascular circulation in paediatric subjects. To reach the purpose, a model for adult circulation was modified and recalibrated with experimental data and literature from children to be able to calculate the flow rates and pressures in the brain and neck. METHODS: The haemodynamic model simulates the 76 main arteries, together with the main veins in brain and neck. A proper magnetic resonance imaging (MRI) dataset of 29 volunteers aged 12 ± 5 years (mean ± standard deviation) was used to extract age-dependent physiological and clinical parameters such as heart rate, flow rate, vessel cross section area, and blood pressure. The computational model was calibrated using such experimental data. The paediatric and adult model results were compared. RESULTS: Increase of the vessels stiffness due to aging contributes to a flow rate decrease while blood pressure increases. In accordance, our simulation results show about 16% decrease in mean pressure of internal jugular vein in paediatric rather than adult subjects. The model outcomes indicated about 88% correlation with MRI data. CONCLUSIONS: The mathematical model simulates the paediatric head and neck blood circulation. The model provides detailed information of human haemodynamics including arterial and venous network to study both paediatric and adult blood circulation.

Calculation of dose distribution in compressible breast tissues using finite element modeling, Monte Carlo simulation and thermoluminescence dosimeters.

Compression is a technique to immobilize the target or improve the dose distribution within the treatment volume during different irradiation techniques such as AccuBoost(®) brachytherapy. However, there is no systematic method for determination of dose distribution for uncompressed tissue after irradiation under compression. In this study, the mechanical behavior of breast tissue between compressed and uncompressed states was investigated. With that, a novel method was developed to determine the dose distribution in uncompressed tissue after irradiation of compressed breast tissue. Dosimetry was performed using two different methods, namely, Monte Carlo simulations using the MCNP5 code and measurements using thermoluminescent dosimeters (TLD). The displacement of the breast elements was simulated using a finite element model and calculated using ABAQUS software. From these results, the 3D dose distribution in uncompressed tissue was determined. The geometry of the model was constructed from magnetic resonance images of six different women volunteers. The mechanical properties were modeled by using the Mooney-Rivlin hyperelastic material model. Experimental dosimetry was performed by placing the TLD chips into the polyvinyl alcohol breast equivalent phantom. The results determined that the nodal displacements, due to the gravitational force and the 60 Newton compression forces (with 43% contraction in the loading direction and 37% expansion in the orthogonal direction) were determined. Finally, a comparison of the experimental data and the simulated data showed agreement within 11.5% ± 5.9%.