The Journal of prosthetic dentistry · 2025
Comparative agreement among traditional, digital, and experimental AI-based shade selection methods in dentistry: A clinical study.
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Ünal Mehmet, Polatoğlu Selin
Аннотация
STATEMENT OF PROBLEM: Shade selection remains subjective, but digital shade selection methods and applications promise more consistent and objective results. However, consensus on which method provides the best agreement and consistency is lacking.
PURPOSE: The purpose of this clinical study was to investigate the agreement among traditional, digital, and artificial intelligence (AI)-assisted shade selection methods.
MATERIAL AND METHODS: A total of 85 participants without caries, periodontal disease, or restoration in the left maxillary central incisor were recruited. Color analysis was performed using 4 different methods on the middle third of the left maxillary central incisor: traditional method (TM) (VITA 3D Master; VITA Zahnfabrik); spectrophotometer (S) (VITA Easyshade V; VITA Zahnfabrik); intraoral scanner (IOS) (TRIOS; 3Shape A/S); and AI-assisted application (ChatGPT-4). ChatGPT-4 was not designed as an AI for diagnostic purposes in clinical settings but was used experimentally for color selection and required human intervention. Color analysis was performed according to the VITA 3D Master color scale. The Cohen kappa method was used to analyze the agreement between 2 methods. The Fleiss kappa method was used to analyze the agreement among the 4 methods (α=.05).
RESULTS: A statistically moderate agreement was found between TM and IOS (kappa=.421; P<.001), and a statistically low agreement was found between TM and AI (kappa=.064; P=.287). A slight yet statistically significant agreement was found among the 4 methods (Fleiss kappa=.071, P<.05).
CONCLUSIONS: Shade selection methods are changing and developing with the digitalization of dentistry. This study showed that the shade selection methods have very low agreement, highlighting the need for these methods to complement each other.
PURPOSE: The purpose of this clinical study was to investigate the agreement among traditional, digital, and artificial intelligence (AI)-assisted shade selection methods.
MATERIAL AND METHODS: A total of 85 participants without caries, periodontal disease, or restoration in the left maxillary central incisor were recruited. Color analysis was performed using 4 different methods on the middle third of the left maxillary central incisor: traditional method (TM) (VITA 3D Master; VITA Zahnfabrik); spectrophotometer (S) (VITA Easyshade V; VITA Zahnfabrik); intraoral scanner (IOS) (TRIOS; 3Shape A/S); and AI-assisted application (ChatGPT-4). ChatGPT-4 was not designed as an AI for diagnostic purposes in clinical settings but was used experimentally for color selection and required human intervention. Color analysis was performed according to the VITA 3D Master color scale. The Cohen kappa method was used to analyze the agreement between 2 methods. The Fleiss kappa method was used to analyze the agreement among the 4 methods (α=.05).
RESULTS: A statistically moderate agreement was found between TM and IOS (kappa=.421; P<.001), and a statistically low agreement was found between TM and AI (kappa=.064; P=.287). A slight yet statistically significant agreement was found among the 4 methods (Fleiss kappa=.071, P<.05).
CONCLUSIONS: Shade selection methods are changing and developing with the digitalization of dentistry. This study showed that the shade selection methods have very low agreement, highlighting the need for these methods to complement each other.