OBJECTIVE: The current study aims to elucidate the two-way fluid-structure interaction (FSI) analysis of the blood flow and the effect of stenosis on hemodynamic parameters.
METHODS: A patient-specific 3D model of the left coronary artery was constructed based on computed tomography (CT) images. The blood is assumed to be incompressible, homogenous, and behaves as Non-Newtonian, while the artery is considered as a nonlinear elastic, anisotropic, and incompressible material. Pulsatile flow conditions were applied at the boundary. Two-way coupled FSI modeling approach was used between fluid and solid domain. The hemodynamic parameters such as the pressure, velocity streamline, and wall shear stress were analyzed in the fluid domain and the solid domain deformation.
RESULTS: The simulated results reveal that pressure drop exists in the vicinity of stenosis and a recirculation region after the stenosis. It was noted that stenosis leads to high wall stress. The results also demonstrate an overestimation of wall shear stress and velocity in the rigid wall CFD model compared to the FSI model.
OBJECTIVE: To evaluate the performance of the model and control strategies, benchmarking simulations are performed using the PlatEMO platform.
METHODS: The Pure Multi-objective Optimal Control Problem (PMOCP) and the Hybrid Multi-objective Optimal Control Problem (HMOCP) are two different forms of optimal control problems that are solved using revolutionary metaheuristic optimisation algorithms. The utilization of the Hypervolume (HV) performance indicator allows for the comparison of various metaheuristic optimization algorithms in their efficacy for solving the PMOCP and HMOCP.
RESULTS: Results indicate that the MOPSO algorithm excels in solving the HMOCP, with M-MOPSO outperforming for PMOCP in HV analysis.
CONCLUSION: Despite not directly addressing immediate clinical concerns, these findings indicates that the stability shifts at critical thresholds may impact treatment efficacy.
METHODS: This review article discusses the experimental and computational methods in the study of HUA. The discussion includes computational fluid dynamics approach and steps involved in the modeling used to investigate the flow characteristics of HUA. From inception to May 2020, databases of PubMed, Embase, Scopus, the Cochrane Library, BioMed Central, and Web of Science have been utilized to conduct a thorough investigation of the literature. There had been no language restrictions in publication and study design of the database searches. A total of 117 articles relevant to the topic under investigation were thoroughly and critically reviewed to give a clear information about the subject. The article summarizes the review in the form of method of studying the HUA, CFD approach in HUA, and the application of CFD for predicting HUA obstacle, including the type of CFD commercial software are used in this research area.
RESULTS: This review found that the human upper airway was well studied through the application of computational fluid dynamics, which had considerably enhanced the understanding of flow in HUA. In addition, it assisted in making strategic and reasonable decision regarding the adoption of treatment methods in clinical settings. The literature suggests that most studies were related to HUA simulation that considerably focused on the aspects of fluid dynamics. However, there is a literature gap in obtaining information on the effects of fluid-structure interaction (FSI). The application of FSI in HUA is still limited in the literature; as such, this could be a potential area for future researchers. Furthermore, majority of researchers present the findings of their work through the mechanism of airflow, such as that of velocity, pressure, and shear stress. This includes the use of Navier-Stokes equation via CFD to help visualize the actual mechanism of the airflow. The above-mentioned technique expresses the turbulent kinetic energy (TKE) in its result to demonstrate the real mechanism of the airflow. Apart from that, key result such as wall shear stress (WSS) can be revealed via turbulent kinetic energy (TKE) and turbulent energy dissipation (TED), where it can be suggestive of wall injury and collapsibility tissue to the HUA.
OBJECTIVE: To develop effective hybrid techniques that combine the optimal control theory (OCT) with the evolutionary algorithm and multi-objective swarm algorithm. The developed technique is aimed to reduce the number of cancerous cells while utilizing the minimum necessary chemotherapy medications and minimizing toxicity to protect patients' health.
METHODS: Two hybrid techniques are proposed in this paper. Both techniques combined OCT with the evolutionary algorithm and multi-objective swarm algorithm which included MOEA/D, MOPSO, SPEA II and PESA II. This study evaluates the performance of two hybrid techniques in terms of reducing cancer cells and drug concentrations, as well as computational time consumption.
RESULTS: In both techniques, MOEA/D emerges as the most effective algorithm due to its superior capability in minimizing tumour size and cancer drug concentration.
CONCLUSION: This study highlights the importance of integrating OCT and evolutionary algorithms as a robust approach for optimizing cancer chemotherapy treatment.