ArticleAnnals of biomedical engineering2023
Analysis of Upper Airway Flow Dynamics in Robin Sequence Infants Using 4-D Computed Tomography and Computational Fluid Dynamics.
Article in Annals of biomedical engineering, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 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.
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Who cites it
2 citing papers in PubMed, 5 citations in OpenAlex.
- Patient-Specific Computational Fluid Dynamics Modeling of Airway Collapse in Infants With Robin Sequence.International journal for numerical methods in biomedical engineering · 2026Article
- MicroNAPS: A Novel Classification for Infants with Micrognathia, Robin Sequence, and Tongue-based Airway Obstruction.Plastic and reconstructive surgery. Global open · 2023Article
Corrections and comments
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Authors and funding
7 authors at 3 institutions in 1 country.
Funding
Abstract
Robin Sequence (RS) is a potentially fatal craniofacial condition characterized by undersized jaw, posteriorly displaced tongue, and resultant upper airway obstruction (UAO). Accurate assessment of UAO severity is crucial for management and diagnosis of RS, yet current evaluation modalities have significant limitations and no quantitative measures of airway resistance exist. In this study, we combine 4-dimensional computed tomography and computational fluid dynamics (CFD) to assess, for the first time, UAO severity using fluid dynamic metrics in RS patients. Dramatic intrapopulation differences are found, with the ratio between most and least severe patients in breathing resistance, energy loss, and peak velocity equal to 40:1, 20:1, and 6:1, respectively. Analysis of local airflow dynamics characterized patients as presenting with primary obstructions either at the location of the tongue base, or at the larynx, with tongue base obstructions resulting in a more energetic stenotic jet and greater breathing resistance. Finally, CFD-derived flow metrics are found to correlate with the level of clinical respiratory support. Our results highlight the large intrapopulation variability, both in quantitative metrics of UAO severity (resistance, energy loss, velocity) and in the location and intensity of stenotic jets for RS patients. These results suggest that computed airflow metrics may significantly improve our understanding of UAO and its management in RS.
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Registered trials
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