ReviewBioengineering (Basel, Switzerland)2024
Computational Rhinology: Unraveling Discrepancies between In Silico and In Vivo Nasal Airflow Assessments for Enhanced Clinical Decision Support.
Review in Bioengineering (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
11 citing papers in PubMed, 10 citations in OpenAlex.
- CFD-Enabled Deep Insert Nasal Delivery for Precision Sinus Targeting.Pharmaceutical research · 2026Article
- Determinants of olfactory cleft targeting in intranasal aerosol delivery: a combined computational and experimental study.European archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery · 2026Article
- From Conventional Septoplasty to Patient-Specific Cartilage Reshaping: A Systematic Review of Laser-Mediated and Electromechanical Approaches.Journal of personalized medicine · 2026Review
- Mechanotherapeutic Modulation of the Nasal Microenvironment: RAMPA-Induced Maxillofacial Remodeling and Its Pathophysiological Impact on Mucus Rheology and Chronic Inflammation.Bioengineering (Basel, Switzerland) · 2026Article
- Association Between Anterior Maxillary Sinus Wall Position and Nasal Bone Asymmetry with Patient-Reported Outcomes Following Septorhinoplasty.Journal of clinical medicine · 2026Article
- Transformative biomechanics and mechanobiology breakthroughs shaping the future of health and medicine.Innovation (Cambridge (Mass.)) · 2026Review
- Deposition of Occupational Aerosol Particles in a Three-Dimensional Adult Nasal Cavity Model: An Experimental Study.Bioengineering (Basel, Switzerland) · 2026Article
- Understanding the mismatch between in-vivo and in-silico rhinomanometry.Medical & biological engineering & computing · 2026Article
- A Study on the Effects of Embodied and Cognitive Interventions on Adolescents' Flow Experience and Cognitive Patterns.Behavioral sciences (Basel, Switzerland) · 2025Article
- Sphenoid sinus hyperpneumatization: anatomical variants, molecular blueprints, and AI-augmented roadmaps for skull base surgery.Frontiers in endocrinology · 2025Review
- Fundamentals and Applications of Fluid Mechanics and Acoustics in Biomedical Engineering.Bioengineering (Basel, Switzerland) · 2024Article
Corrections and comments
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Authors and funding
1 author at 1 institution in 1 country.
Funding
Abstract
Computational rhinology is a specialized branch of biomechanics leveraging engineering techniques for mathematical modelling and simulation to complement the medical field of rhinology. Computational rhinology has already contributed significantly to advancing our understanding of the nasal function, including airflow patterns, mucosal cooling, particle deposition, and drug delivery, and is foreseen as a crucial element in, e.g., the development of virtual surgery as a clinical, patient-specific decision support tool. The current paper delves into the field of computational rhinology from a nasal airflow perspective, highlighting the use of computational fluid dynamics to enhance diagnostics and treatment of breathing disorders. This paper consists of three distinct parts-an introduction to and review of the field of computational rhinology, a review of the published literature on in vitro and in silico studies of nasal airflow, and the presentation and analysis of previously unpublished high-fidelity CFD simulation data of in silico rhinomanometry. While the two first parts of this paper summarize the current status and challenges in the application of computational tools in rhinology, the last part addresses the gross disagreement commonly observed when comparing in silico and in vivo rhinomanometry results. It is concluded that this discrepancy cannot readily be explained by CFD model deficiencies caused by poor choice of turbulence model, insufficient spatial or temporal resolution, or neglecting transient effects. Hence, alternative explanations such as nasal cavity compliance or drag effects due to nasal hair should be investigated.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.