METHODS: Computational Fluid Dynamics (CFD) approach is used to simulate the airflow in a neonate, an infant and an adult in sedentary breathing conditions. The healthy CT scans are segmented using MIMICS 21.0 (Materialise, Ann arbor, MI). The patient-specific 3D airway models are analyzed for low Reynolds number flow using ANSYS FLUENT 2020 R2. The applicability of the Grid Convergence Index (GCI) for polyhedral mesh adopted in this work is also verified.
RESULTS: This study shows that the inferior meatus of neonates accounted for only 15% of the total airflow. This was in contrast to the infants and adults who experienced 49 and 31% of airflow at the inferior meatus region. Superior meatus experienced 25% of total flow which is more than normal for the neonate. The highest velocity of 1.8, 2.6 and 3.7 m/s was observed at the nasal valve region for neonates, infants and adults, respectively. The anterior portion of the nasal cavity experienced maximum wall shear stress with average values of 0.48, 0.25 and 0.58 Pa for the neonates, infants and adults.
CONCLUSIONS: The neonates have an underdeveloped nasal cavity which significantly affects their airway distribution. The absence of inferior meatus in the neonates has limited the flow through the inferior regions and resulted in uneven flow distribution.
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.
SUMMARY ANSWER: High-throughput flagellar waveform tracking and analysis enable measurement of experimentally intractable quantities such as energy dissipation, disturbance of the surrounding medium and viscous stresses, which are not possible by tracking the sperm head alone.
WHAT IS KNOWN ALREADY: The clinical gold standard for sperm motility analysis comprises a manual analysis by a trained professional, with existing automated sperm diagnostics [computer-aided sperm analysis (CASA)] relying on tracking the sperm head and extrapolating measures. It is not currently possible with either of these approaches to track the sperm flagellar waveform for large numbers of cells in order to unlock the potential wealth of information enclosed within.
STUDY DESIGN, SIZE, DURATION: The software tool in this manuscript has been developed to enable high-throughput, repeatable, accurate and verifiable analysis of the sperm flagellar beat.
PARTICIPANTS/MATERIALS, SETTING, METHODS: Using the software tool [Flagellar Analysis and Sperm Tracking (FAST)] described in this manuscript, we have analysed 176 experimental microscopy videos and have tracked the head and flagellum of 205 progressive cells in diluted semen (DSM), 119 progressive cells in a high-viscosity medium (HVM) and 42 stuck cells in a low-viscosity medium. Unscreened donors were recruited at Birmingham Women's and Children's NHS Foundation Trust after giving informed consent.
MAIN RESULTS AND THE ROLE OF CHANCE: We describe fully automated tracking and analysis of flagellar movement for large cell numbers. The analysis is demonstrated on freely motile cells in low- and high-viscosity fluids and validated on published data of tethered cells undergoing pharmacological hyperactivation. Direct analysis of the flagellar beat reveals that the CASA measure 'beat cross frequency' does not measure beat frequency; attempting to fit a straight line between the two measures gives ${\mathrm{R}}^2$ values of 0.042 and 0.00054 for cells in DSM and HVM, respectively. A new measurement, track centroid speed, is validated as an accurate differentiator of progressive motility. Coupled with fluid mechanics codes, waveform data enable extraction of experimentally intractable quantities such as energy dissipation, disturbance of the surrounding medium and viscous stresses. We provide a powerful and accessible research tool, enabling connection of the mechanical activity of the sperm to its motility and effect on its environment.
LARGE SCALE DATA: The FAST software package and all documentation can be downloaded from www.flagellarCapture.com.
LIMITATIONS, REASONS FOR CAUTION: The FAST software package has only been tested for use with negative phase contrast microscopy. Other imaging modalities, with bright cells on a dark background, have not been tested but may work. FAST is not designed to analyse raw semen; it is specifically for precise analysis of flagellar kinematics, as that is the promising area for computer use. Flagellar capture will always require that cells are at a dilution where their paths do not frequently cross.
WIDER IMPLICATIONS OF THE FINDINGS: Combining tracked flagella with mathematical modelling has the potential to reveal new mechanistic insight. By providing the capability as a free-to-use software package, we hope that this ability to accurately quantify the flagellar waveform in large populations of motile cells will enable an abundant array of diagnostic, toxicological and therapeutic possibilities, as well as creating new opportunities for assessing and treating male subfertility.
STUDY FUNDING/COMPETING INTEREST(S): M.T.G., G.C., J.C.K-B. and D.J.S. gratefully acknowledge funding from the Engineering and Physical Sciences Research Council, Healthcare Technologies Challenge Award (Rapid Sperm Capture EP/N021096/1). J.C.K-B. is funded by a National Institute of Health Research (NIHR) and Health Education England, Senior Clinical Lectureship Grant: The role of the human sperm in healthy live birth (NIHRDH-HCS SCL-2014-05-001). This article presents independent research funded in part by the NIHR and Health Education England. The views expressed are those of the authors and not necessarily those of the NHS, the NIHR or the Department of Health. The data for experimental set (2) were funded through a Wellcome Trust-University of Birmingham Value in People Fellowship Bridging Award (E.H.O.).The authors declare no competing interests.