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Register a new userComparative Study of Simulated Nebulized and Spray Particle Deposition in Chronic Rhinosinusitis Patients
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Introduction: Topical intranasal drugs are widely prescribed for Chronic Rhinosinusitis (CRS), although delivery can vary with device type and droplet size. The study objective was to compare nebulized and sprayed droplet deposition in the paranasal sinuses and ostiomeatal complex (OMC) across multiple droplet sizes in CRS patients using computational fluid dynamics (CFD). Methods: Three-dimensional models of sinonasal cavities were constructed from computed tomography (CT) scans of three subjects with CRS refractory to medical therapy using imaging software. Assuming steady-state inspiratory airflow at resting rate, CFD was used to simulate 1-120 {mu}m sprayed droplet deposition in the left and right sinuses and OMC with spray nozzle positioning as in current nasal spray use instructions. Zero-velocity nebulization simulations were performed for 1-30 {mu}m droplet sizes, maximal sinus and OMC deposition fractions (MSDF) were obtained, and sizes that achieved at least 50% of MSDF were identified. Nebulized MSDF was compared to sprayed droplet deposition. We also validated CFD framework through in vitro experiments. Results: Among nebulized droplet sizes, 11-14 {mu}m droplets achieved at least 50% of MSDF in all six sinonasal cavities. Five of six sinonasal cavities had greater sinus and OMC deposition with nebulized droplets than with sprayed droplets at optimal sizes. Conclusions: Nebulized droplets may target the sinuses and OMC more effectively than sprayed particles at sizes achieving best deposition. Further studies are needed to confirm our preliminary findings. Several commercial nasal nebulizers have average particle sizes outside the optimal nebulized droplet size range found here, suggesting potential for product enhancement.
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Objective: Minimal literature exists investigating changes in inflammation with respect to the main nasal cavity (MNC) and paranasal sinuses (PS) before and after maximal medical therapy (MMT) for chronic rhinosinusitis (CRS). We hypothesized that MMT produces a differential level of change in the volume of air space in the MNC and PS, and that resolution of mucosal disease associated with the osteomeatal complex (OMC) influences clinical response to MMT. Study Design: Retrospective study of 12 pre- and post-MMT sinus-CT scans from 6 subjects with CRS, of which three succeeded and three failed therapy. Methods: Mimics was used to create 3D-models of the MNC and PS, and then analysis of the models was performed. Results: Mean differences in the sinonasal volume were 7866.5+/-4339.9 mm3 and 17869.10+/-19472.70 mm3, amongst the failures and successes, respectively. There is wide variability in the contribution of PS and MNC airspace volume change to the overall change in the sinonasal volume. In two subjects, the direction of volume change in the MNC and PS diverged with respect to the overall change in volume. Line-of-sight analysis demonstrated that successful responders to MMT had more patent MNC with direct access to the OMC. Conclusions: There is a differential contribution to sinonasal, airspace volume change after MMT, when comparing the MNC and PS. Response to MMT may not be solely attributable to PS change and may include a function of MNC change. Line-of-sight models suggest that direct access to the OMC may impact response to MMT.
A patient-specific fluid-structure interaction (FSI) model of a phase-contrast magnetic resonance angiography (PC-MRA) imaged arteriovenous fistula is presented. The numerical model is developed and simulated using a commercial multiphysics simulation package where a semi-implicit FSI coupling scheme combines a finite volume method blood flow model and a finite element method vessel wall model. A pulsatile mass-flow boundary condition is prescribed at the artery inlet of the model, and a three-element Windkessel model at the artery and vein outlets. The FSI model is freely available for analysis and extension. This work shows the effectiveness of combining a number of stabilisation techniques to simultaneously overcome the added-mass effect and optimise the efficiency of the overall model. The PC-MRA data, fluid model, and FSI model results show almost identical flow features in the fistula; this applies in particular to a flow recirculation region in the vein that could potentially lead to fistula failure.
Objective: A numerical 3D model of the human trunk was developed to study the biomechanical effects of lumbar belts used to treat low back pain. Methods: This model was taken from trunk radiographies of a person and simplified so as to make a parametric study by varying morphological parameters of the patient, characteristic parameters of the lumbar belt and mechanical parameters of body and finally to determine the parameters influencing the effects of low back pain when of wearing the lumbar belt. The loading of lumbar belt is modelled by Laplaces law. These results were compared with clinical study. Results: All the results of this parametric study showed that the choice of belt is very important depending on the patients morphology. Surprisingly, the therapeutic treatment is not influenced by the mechanical characteristics of the body structures except the mechanical properties of intervertebral discs. Discussion: The numerical model can serve as a basis for more in-depth studies concerning the analysis of efficiency of lumbar belts in low back pain. In order to study the impact of the belts architecture, the pressure applied to the trunk modelled by Laplaces law could be improved. This model could also be used as the basis for a study of the impact of the belt over a period of wearing time. Indeed, the clinical study shows that movement has an important impact on the distribution of pressure applied by the belt.
We study the energy deposition by light and heavy nuclei in tissue-like media as used for cancer therapy. The depth-dose distributions for protons, $^{3}$He, $^{12}$C, $^{20}$Ne, and $^{58}$Ni nuclei are calculated within a Monte Carlo model based on the GEANT4 toolkit. These distributions are compared with each other and with available experimental data. It is demonstrated that nuclear fragmentation reactions essentially reduce the peak-to-plateau ratio of the dose profiles for deeply penetrating energetic ions heavier than $^{3}$He. On the other hand, all projectiles up to $^{20}$Ne were found equally suitable for therapeutic use at low penetration depths.
Purpose: To develop an automated machine-learning-based method for the discovery of rapid and quantitative chemical exchange saturation transfer (CEST) MR fingerprinting acquisition and reconstruction protocols. Methods: An MR physics governed AI system was trained to generate optimized acquisition schedules and the corresponding quantitative reconstruction neural-network. The system (termed AutoCEST) is composed of a CEST saturation block, a spin dynamics module, and a deep reconstruction network, all differentiable and jointly connected. The method was validated using a variety of chemical exchange phantoms and an in-vivo mouse brain at 9.4T. Results: The acquisition times for AutoCEST optimized schedules ranged from 35-71s, with a quantitative image reconstruction time of only 29 ms. The resulting exchangeable proton concentration maps for the phantoms were in good agreement with the known solute concentrations for AutoCEST sequences (mean absolute error = 2.42 mM; Pearsons r=0.992 , p$<$0.0001), but not for an unoptimized sequence (mean absolute error = 65.19 mM; Pearsons r=-0.161, p=0.522). Similarly, improved exchange rate agreement was observed between AutoCEST and quantification of exchange using saturation power (QUESP) methods (mean absolute error: 35.8 Hz, Pearsons r=0.971, p$<$0.0001) compared to an unoptimized schedule and QUESP (mean absolute error = 58.2 Hz; Pearsons r=0.959, p$<$0.0001). The AutoCEST in-vivo mouse brain semi-solid proton volume-fractions were lower in the cortex (12.21$pm$1.37%) compared to the white-matter (19.73 $pm$ 3.30%), as expected, and the amide proton volume-fraction and exchange rates agreed with previous reports. Conclusion: AutoCEST can automatically generate optimized CEST/MT acquisition protocols that can be rapidly reconstructed into quantitative exchange parameter maps.
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