Description Module
The Description Module contains narrative descriptions of the clinical trial, including a brief summary and detailed description. These descriptions provide important information about the study's purpose, methodology, and key details in language accessible to both researchers and the general public.
Description Module path is as follows:
Study -> Protocol Section -> Description Module
Description Module
Ignite Creation Date:
2025-12-25 @ 4:51 AM
Ignite Modification Date:
2025-12-25 @ 4:51 AM
NCT ID:
NCT07246018
Brief Summary:
This study compares the accuracy and reliability of artificial intelligence (AI) software for analyzing dental X-rays to the traditional manual tracing method used by dentists.
Lateral cephalometric radiographs are special X-rays of the head used in orthodontics (teeth straightening) to measure jawbone positions, tooth angles, and facial proportions. Traditionally, orthodontists manually trace these X-rays using pencil and paper to identify key landmarks and make measurements. This manual method is time-consuming and can vary between different practitioners or even when the same practitioner measures twice.
AI-based software can automatically identify these landmarks and perform measurements instantly. This study examined 40 dental X-rays to determine if the AI software (WeDoCeph) is as accurate and more reliable than manual tracing.
Each X-ray was measured twice - once manually by a trained examiner and once by AI software - at two different times (4 weeks apart). The researchers compared 15 different measurements, including 8 angles and 7 distances, to assess accuracy and reliability.
Detailed Description:
Lateral cephalometric analysis is essential for orthodontic diagnosis and treatment planning. The traditional manual tracing method involves identifying anatomical landmarks on radiographs using pencil, ruler, and protractor, which is subjective, time-consuming, and prone to intra- and inter-observer variability.
This diagnostic accuracy study evaluated the WeDoCeph AI-based cephalometric analysis software against conventional manual tracing. The study used a comparative repeated-measures design where each radiograph was analysed by both methods at two time points (T₀ and T₁, separated by 4 weeks) to assess both accuracy and reliability.
Sample size calculation was based on 95% power and a 0.05 significance level, resulting in 40 lateral cephalometric radiographs. All measurements included angular parameters (SNA, SNB, ANB, FMPA, MMPA, UIA, LIA, IIA) and linear parameters (A-N perpendicular, POG-N perpendicular, ANS-Me, SN, UFH, MxPI, MnPI).
Paired T-Test will be employed as the statistical analysis method for comparisons and Intraclass Correlation Coefficient (ICC) for reliability assessment. The study aimed to determine whether AI-based cephalometric analysis provides sufficient accuracy and superior reliability for clinical application in orthodontic practice.
Study:
NCT07246018
Study Brief:
Protocol Section:
NCT07246018