Comparison of AI-assisted cephalometric analysis and orthodontist-performed digital tracing analysis

被引:2
作者
Bor, Sabahattin [1 ]
Cigerim, Saadet Cinarsoy [2 ]
Kotan, Seda [2 ]
机构
[1] Inonu Univ, Fac Dent, Dept Orthodont, Malatya, Turkiye
[2] Van Yuzuncu Yil Univ, Fac Dent, Dept Orthodont, Van, Turkiye
来源
PROGRESS IN ORTHODONTICS | 2024年 / 25卷 / 01期
关键词
AI-assisted cephalometric analysis; Angular and linear measurements; 2D lateral films; Diagnostic accuracy; ARTIFICIAL-INTELLIGENCE; REPRODUCIBILITY;
D O I
10.1186/s40510-024-00539-x
中图分类号
R78 [口腔科学];
学科分类号
1003 ;
摘要
Background The aim of this study was to compare and evaluate three AI-assisted cephalometric analysis platforms-CephX, WeDoCeph, and WebCeph-with the traditional digital tracing method using NemoCeph software. Material and method A total of 1500 lateral cephalometric films that met the inclusion criteria were classified as Class I, Class II, and Class III. Subsequently, 40 patients were randomly selected from each class. These selected films were uploaded to 3 AI-assisted cephalometric analysis platforms and analyzed without any manual intervention. The same films were also analyzed by an orthodontist using the NemoCeph program. Results The results revealed significant differences in key angular measurements (ANB, FMA, IMPA, and NLA) across Class I, II, and III patients when comparing the four cephalometric analysis methods (WebCeph, WeDoCeph, CephX, and NemoCeph). Notably, ANB (p < 0.05), FMA (p < 0.001), IMPA (p < 0.001), and NLA (p < 0.001) varied significantly. Linear measurements also differed, with significant differences in U1-NA (p = 0.002) and Co-A (p = 0.002) in certain classes. Repeated measurement analysis revealed variation in SNA (p = 0.011) and FMA (p = 0.030), particularly in the Class II NemoCeph group, suggesting method-dependent variability. Conclusion AI-assisted cephalometric analysis platforms such as WebCeph, WeDoCeph, and CephX give rise to notable variation in accuracy and reliability compared to traditional manual digital tracing, specifically in terms of angular and linear measurements. These results emphasize the importance of meticulous selection and assessment of analysis methods in orthodontic diagnostics and treatment planning.
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页数:9
相关论文
共 37 条
[1]  
Al-Ubaydi AS, 2023, Sci World J
[2]   Trends and Application of Artificial Intelligence Technology in Orthodontic Diagnosis and Treatment Planning-A Review [J].
Albalawi, Farraj ;
Alamoud, Khalid A. .
APPLIED SCIENCES-BASEL, 2022, 12 (22)
[3]  
Alessandri-Bonetti A., 2023, BioMedInformatics, V3, P44, DOI [10.3390/biomedinformatics3010003, DOI 10.3390/BIOMEDINFORMATICS3010003]
[4]   Evaluation of an online website-based platform for cephalometric analysis [J].
Alqahtani, H. .
JOURNAL OF STOMATOLOGY ORAL AND MAXILLOFACIAL SURGERY, 2020, 121 (01) :53-57
[5]   Review of deep learning: concepts, CNN architectures, challenges, applications, future directions [J].
Alzubaidi, Laith ;
Zhang, Jinglan ;
Humaidi, Amjad J. ;
Al-Dujaili, Ayad ;
Duan, Ye ;
Al-Shamma, Omran ;
Santamaria, J. ;
Fadhel, Mohammed A. ;
Al-Amidie, Muthana ;
Farhan, Laith .
JOURNAL OF BIG DATA, 2021, 8 (01)
[6]  
Bao H, 2023, BMC Oral Health, P23
[7]   A Knowledge-Based Algorithm for Automatic Monitoring of Orthodontic Treatment: The Dental Monitoring System. Two Cases [J].
Caruso, Silvia ;
Caruso, Sara ;
Pellegrino, Marianna ;
Skafi, Rayan ;
Nota, Alessandro ;
Tecco, Simona .
SENSORS, 2021, 21 (05) :1-14
[8]   Comparison of cephalometric measurements with digital versus conventional cephalometric analysis [J].
Celik, Erkan ;
Polat-Ozsoy, Omur ;
Memikoglu, T. Ufuk Toygar .
EUROPEAN JOURNAL OF ORTHODONTICS, 2009, 31 (03) :241-246
[9]   Machine learning in orthodontics: Introducing a 3D auto-segmentation and auto-landmark finder of CBCT images to assess maxillary constriction in unilateral impacted canine patients [J].
Chen, Si ;
Wang, Li ;
Li, Gang ;
Wu, Tai-Hsien ;
Diachina, Shannon ;
Tejera, Beatriz ;
Kwon, Jane Jungeun ;
Lin, Feng-Chang ;
Lee, Yan-Ting ;
Xu, Tianmin ;
Shen, Dinggang ;
Ko, Ching-Chang .
ANGLE ORTHODONTIST, 2020, 90 (01) :77-84
[10]  
Coban G, 2022, Dent Press J Orthod., V27