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Research on Adenoid Automated Segmentation and Nasopharyngeal Airway Obstruction Degree Indicators Based on Deep Learning: Analysis of Association with Pediatric OSA

Research on Adenoid Automated Segmentation and Nasopharyngeal Airway Obstruction Degree Indicators Based on Deep Learning: Analysis of Association with Pediatric OSA

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2500105732
Enrollment
Unknown
Registered
2025-07-09
Start date
2025-07-10
Completion date
Unknown
Last updated
2025-07-14

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Pediatric Obstructive Sleep Apnea-Hypopnea Syndrome

Interventions

Have a CBCT pre-adenoidectomy and at least 6 months postoperatively:NA
Have CBCT after at least 6 months after adenoidectomy:NA
Analysis of the Correlation between 3D-AN and Pediatric OSAHS.:NA

Sponsors

Shanghai Stomotological Hospital
Lead Sponsor

Eligibility

Sex/Gender
All
Age
6 Years to 12 Years

Inclusion criteria

Inclusion criteria: 1.Age 6-12 years; 2.Presence of adenoid hypertrophy and related medical history records.

Exclusion criteria

Exclusion criteria: 1.Children with Central Sleep Apnea-Hypopnea Syndrome (CSAHS); 2.Children with any chronic childhood diseases (e.g., asthma); 3.Children with severe craniofacial deformities, such as cleft lip and palate; 4.Children with a history of maxillofacial surgery or multiple orthodontic treatments; 5.Children with pathological obesity; 6.Children with unclear or damaged imaging data that are unavailable.

Design outcomes

Primary

MeasureTime frame
Three dimensional adenoidal-nasopharyngeal ratio (3D-AN);PSG related metrics;—

Countries

China

Contacts

Public ContactYuanyuan Li

Shanghai Stomotological Hospital

li_yuanyuan0650@fudan.edu.cn+86 188 1736 7760

Outcome results

None listed

Source: ChiCTR (via WHO ICTRP) · Data processed: Feb 4, 2026