田中 学

In this study, a moving boundary deformation model based on four-dimensional computed tomography angiography (4D-CTA) with high temporal resolution is constructed, and blood flow dynamics of cerebral aneurysms are investigated by numerical simulation. A realistic moving boundary deformation model of a cerebral aneurysm was constructed based on 4D-CTA in each phase. Four hemodynamic factors (wall shear stress [WSS], wall shear stress divergence [WSSD], oscillatory shear index [OSI], and residual residence time [RRT]) were obtained from numerical simulations, and these factors were evaluated in basilar artery aneurysms. Comparison of the rigid body condition and the moving boundary condition investigating the relationship between wall displacement and hemodynamic factors clarified that the spatial-averaged WSS and maximum WSSD considering only the aneurysmal dome has a large difference between conditions during the peak systole, and there were also significant differences in OSI and RRT.

The study of lung mechanics is important to futureproof resilience against potential novel threats to lung health. Medical imaging provides insight to lung function. High-resolution, high-speed synchrotron radiation micro-CT imaging at SPring-8 (Japan) and in situ mechanics were used to characterize healthy and diseased airways. Synchrotron radiation was important to maximize speed and spatial resolution to map the lung architecture clearly. Links between global lung mechanical measurements (pressure-volume) and regional tissue strains were made. Tissue strains were computed from a sequence of tomograms during a respiratory cycle, demonstrating clear differences for the surfactant-free lungs compared to the controls. Poorly ventilated areas were identified within three-dimensional strain maps computed via digital volume correlation. Occluded pathways at low pressures were seen to be opened at higher pressures, augmenting the deformation pathways. The results will aid correlations between microscale and macroscale measurements and the potential impact on patient management guidelines for mechanical ventilation.

The global spread of COVID-19 in 2020 had a significant impact on the population. Healthcare workers who have unpreventable contact with infected individuals are at high risk of infection. We therefore proposed “infection control methods in high-risk environments” and demonstrated that appropriate placement of suction devices in otorhinolaryngology examination rooms is effective for aerosol control [Takada M, Fukushima T, Ozawa S, Matsubara S, Suzuki T, Fukumoto I, Hanazawa T, Nagashima T, Uruma R, Otsuka M, Tanaka G: Sci Rep. 12(1), 18230, 2022]. As a further study of the previous research, this study analyzed the specific environmental factors that contribute to reducing the risk of infection by optimizing the manner in which suction devices are set up. The models of a patient and doctor were placed in an examination room. A steady flow of 2.5 m/s was applied to the patient’s mouth as exhalation. Aerosol diffusion was analyzed using computational fluid dynamics. The optimization parameters were the position and angle of suction inlet, and suction speed. The objective evaluation was the “maximum number of particles aspirated from the suction inlet”. A total of 150 designs were tested, and the search for the optimal positions was performed in the examination room. The optimization results showed that the maximum particle removal rate was 98.6%. There were six cases in which the particle removal rate was at least 98%. These positions were within the range of x = 0.120 to 0.159 m in the horizontal direction from the patient’s mouth to the suction inlet. The suction inlet was placed laterally in front of the patient, along the trajectory of the particles emitted from the patient’s mouth. Particle removal rates of over 98% at various suction speeds indicates that the position and direction of the suction inlet are more important than the suction speed. The adjustment of suction devices based on the results of this study would help reduce the risk of infection in healthcare settings.

Obstructive sleep apnea syndrome (OSAS) is a disorder that causes sleep apnea and hypopnea, which in turn causes various disorders in daily life. Because of the difficulty in measuring airflow dynamics, computational fluid dynamics (CFD) simulations are performed to evaluate upper airway airflow in OSAS in detail. However, the relationship between the severity of OSAS, as measured by the apnea hypopnea index (AHI), and airflow dynamics is unclear. In this study, CFD simulations of human snoring during sleep were performed to determine the correlation between AHI and pressure drops in the nasal cavity and throat, as well as between AHI and minimum cross-sectional area of the throat. For the simulation, 3D models of snoring in the open-mouth state, which is a common form of snoring, were reconstructed based on computed tomography images acquired from four patients with mild OSAS and six with severe OSAS. Each relationship was evaluated using Spearman’s rank correlation coefficient. The correlation coefficient between AHI and pressure drop in the nasal cavity was 0.745, with a significant correlation. There was no significant correlation between AHI and pressure drop in the throat or between AHI and minimum cross-sectional area of the throat. These results suggest that the pressure drop in the nasal cavity affects the severity of OSAS.

Healthcare providers are vulnerable to infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) because of their close proximity to patients with coronavirus disease 2019. SARS-CoV-2 is mainly transmitted via direct and indirect contact with respiratory droplets, and its airborne transmission has also been identified. However, evidence for environmental factors is scarce, and evidence-based measures to minimize the risk of infection in clinical settings are insufficient. Using computational fluid dynamics, we simulated exhalation of large and small aerosol particles by patients in an otolaryngology examination room, where medical procedures require the removal of a face mask. The effects of coughing were analyzed, as well as those of humidity as a controllable environmental factor and of a suction device as an effective control method. Our results show that a suction device can minimize aerosol exposure of healthcare workers by efficiently removing both large (11.6-98.2%) and small (39.3-99.9%) aerosol particles. However, for coughing patients, the removal efficiency varies inversely with the particle size, and the humidity notably affects the aerosol behavior, indicating the need for countermeasures against smaller aerosols. Overall, these results highlight the potential and limitation of using a suction device to protect against SARS-CoV-2 and future respiratory infections.