The Association Between Craniofacial Morphological Parameters and the Severity of Obstructive Sleep Apnea: A Multivariate Analysis Using the Apnea–Hypopnea Index and Nocturnal Oxygen Desaturation DOI Open Access
Zhili Dong,

Jinmei Wu,

Liping Wu

et al.

Healthcare, Journal Year: 2025, Volume and Issue: 13(8), P. 913 - 913

Published: April 16, 2025

Background: Obstructive sleep apnea (OSA) is characterized by repetitive complete or partial closure of the upper airway during sleep, which a potentially life-threatening disorder. A cephalogram simple and effective examination to predict risk OSA in orthodontic clinical practice. This study aims analyze relationship between craniofacial characteristics severity using polysomnography data. Gender differences these parameters are also investigated. Methods: included 112 patients who underwent examination, standard study, cephalometric analysis diagnose obstructive apnea. divided participants into male female groups correlation OSA. The involved 39 parameters. was evaluated apnea–hypopnea index (AHI) lowest nocturnal oxygen saturation (LSaO2). Results: final assessment adult (male/female = 67:45, mean age: 28.4 ± 7.29 years, 28.8 7.62 27.8 6.79 years). Multivariate revealed that mandibular position, incisor inclination, facial height, maxillary first molar position were strongly associated with severity. Gender-specific predictors identified, distinct correlating AHI LSaO2 males females. Notably, demonstrated stronger associations morphology females than males. Conclusions: Cephalometric can be assessing based on AHI/LSaO2. There clear difference individuals. gender-dependent pattern may assist personalized diagnosis management

Language: Английский

Accuracy and Reliability of 3D Cephalometric Landmark Detection with Deep Learning DOI Creative Commons
Boyan Liu, Chang Liu, Yutao Xiong

et al.

Research Square (Research Square), Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 13, 2025

Abstract Objective: Three-dimensional (3D) landmark detection is essential for assessing craniofacial growth and planning surgeries such as orthodontic, orthognathic, traumatic, plastic procedures. This study aimed to develop an automatic 3D landmarking model oral maxillofacial regions validate its accuracy, robustness, generalizability in both spiral computed tomography (SCT, 41 landmarks) cone-beam (CBCT, 14 scans. Methods: The was constructed using optimized lightweight U-Net network architecture. Its were thoroughly evaluated validated through a multicenter retrospective diagnostic study. internal dataset included 480 SCT 240 CBCT cases. For external validation, 320 150 cases assessed mean radial error (MRE) success rate within 2-, 3-, 4-mm thresholds the primary evaluation metrics. Error analyses along each coordinate axis performed. Consistency tests among index observers conducted. Results: average MRE consistently below 1.3 mm and, notably, 1.4 complex conditions malocclusion, missing dental landmarks, presence of metal artifacts. No significant differences SDR at 2-4 observed between sets. bone landmarks more precise than ones, with no difference bone/soft tissue dental/soft tissue. exhibited greater precision compared landmarks. A detailed analysis across axes showed that coronal had highest rates. implementation this significantly improved proficiency senior junior specialists by 15.9% 28.9%, respectively, while also accelerating process factor 6 9.5 times. Conclusions: This shows AI-driven delivers high-precision localization structures, even scenarios. can aid all experience levels conducting accurate efficient analyses, owing strong clinical utility, generalizability. Clinical Relevance: 3D cephalometric crucial diverse surgical procedures, trauma, aesthetic interventions. traditional manual identification time-consuming requires expertise. proposed AI method provides measurements soft hard tissues, streamlines digital planning, decreases reliance on expert knowledge, enhances efficiency treatments.

Language: Английский

Citations

0
Relationship between Björk–Jarabak Cephalometrics Analysis Elements and Facial Profile for Yemeni Adult Samples DOI Open Access

Husham E. Homeida,

Mohammed M. Al Moaleem,

Abdulkareem M Al-Kuhlani

et al.

World Journal of Dentistry, Journal Year: 2025, Volume and Issue: 15(10), P. 897 - 901

Published: Jan. 27, 2025

Language: Английский

Citations

0
Accuracy of cephalometric landmark identification by artificial intelligence platform versus expert orthodontist in unilateral cleft palate patients: A retrospective study DOI

Mostafa A Tageldin,

Yomna M. Yacout,

Farah Y. Eid

et al.

International Orthodontics, Journal Year: 2025, Volume and Issue: 23(2), P. 100990 - 100990

Published: Feb. 19, 2025

Language: Английский

Citations

0
The Association Between Craniofacial Morphological Parameters and the Severity of Obstructive Sleep Apnea: A Multivariate Analysis Using the Apnea–Hypopnea Index and Nocturnal Oxygen Desaturation DOI Open Access
Zhili Dong,

Jinmei Wu,

Liping Wu

et al.

Healthcare, Journal Year: 2025, Volume and Issue: 13(8), P. 913 - 913

Published: April 16, 2025

Background: Obstructive sleep apnea (OSA) is characterized by repetitive complete or partial closure of the upper airway during sleep, which a potentially life-threatening disorder. A cephalogram simple and effective examination to predict risk OSA in orthodontic clinical practice. This study aims analyze relationship between craniofacial characteristics severity using polysomnography data. Gender differences these parameters are also investigated. Methods: included 112 patients who underwent examination, standard study, cephalometric analysis diagnose obstructive apnea. divided participants into male female groups correlation OSA. The involved 39 parameters. was evaluated apnea–hypopnea index (AHI) lowest nocturnal oxygen saturation (LSaO2). Results: final assessment adult (male/female = 67:45, mean age: 28.4 ± 7.29 years, 28.8 7.62 27.8 6.79 years). Multivariate revealed that mandibular position, incisor inclination, facial height, maxillary first molar position were strongly associated with severity. Gender-specific predictors identified, distinct correlating AHI LSaO2 males females. Notably, demonstrated stronger associations morphology females than males. Conclusions: Cephalometric can be assessing based on AHI/LSaO2. There clear difference individuals. gender-dependent pattern may assist personalized diagnosis management

Language: Английский

Citations

0