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Related Concept Videos

Sleep Apnea01:21

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Sleep apnea is a condition where breathing stops intermittently during sleep, often leading to significant health issues. Each episode can last from 10 to 20 seconds or more and is frequently accompanied by a brief arousal from sleep. This disturbance, largely unnoticed by the individual, can lead to severe daytime fatigue. Commonly, individuals seek help after being informed by their partners about loud snoring and noticeable breathing pauses during sleep.
The condition is more prevalent among...
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Related Experiment Video

Updated: Jul 13, 2025

Drug-Induced Sleep Endoscopy DISE with Target Controlled Infusion TCI and Bispectral Analysis in Obstructive Sleep Apnea
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Computational fluid dynamics study in children with obstructive sleep apnea.

Wei-Chung Hsu1,2,3, Kun-Tai Kang1,4,5, Yunn-Jy Chen3,6

  • 1Department of Otolaryngology, National Taiwan University Hospital, Taipei, Taiwan.

Clinical Otolaryngology : Official Journal of ENT-UK ; Official Journal of Netherlands Society for Oto-Rhino-Laryngology & Cervico-Facial Surgery
|October 19, 2023
PubMed
Summary
This summary is machine-generated.

Computational fluid dynamics (CFD) can identify airway differences in children with obstructive sleep apnea (OSA). Higher airway pressure and resistance in OSA patients suggest CFD is a valuable diagnostic tool.

Keywords:
childcone-beam computed tomographypressureresistancesleep apnea syndromesupper airwayvelocity

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Area of Science:

  • Pediatric Pulmonology
  • Medical Imaging
  • Biomedical Engineering

Background:

  • Obstructive sleep apnea (OSA) is a common condition in children.
  • Accurate diagnosis of OSA relies on objective measures of upper airway patency.
  • Image-based computational fluid dynamics (CFD) offers a non-invasive method to assess airway dynamics.

Purpose of the Study:

  • To identify distinct image-based computational fluid dynamics (CFD) characteristics in children diagnosed with obstructive sleep apnea (OSA).
  • To evaluate the utility of CFD in differentiating between children with OSA and those with primary snoring.

Main Methods:

  • A diagnostic study involving a hospital-based cohort of children with symptoms suggestive of OSA.
  • Three-dimensional CFD models were generated from cone-beam computed tomography (CBCT) scans.
  • Polysomnography was used to diagnose OSA and categorize participants based on apnea-hypopnea index (AHI).

Main Results:

  • Children with moderate-to-severe OSA (AHI > 5) exhibited significantly higher total airway pressure, total airway resistance, and velocity at minimal cross-sectional area compared to those with primary snoring (AHI < 1).
  • Optimal cut-off points for identifying moderate-to-severe OSA were determined for total airway pressure (46.2 Pa), total airway resistance (2373 Nm), and velocity at minimal cross-sectional area (12.6 m/s).
  • Conditional logistic regression confirmed that these CFD parameters were significantly associated with an increased risk of moderate-to-severe OSA.

Conclusions:

  • Image-based computational fluid dynamics (CFD) is a promising tool for assessing upper airway patency in pediatric OSA.
  • CFD parameters like airway pressure, resistance, and velocity can aid in the diagnosis and risk stratification of OSA in children.
  • Further research can explore the integration of CFD into routine clinical practice for OSA evaluation.