A Comparative Analysis of Shade Selection between Smartphone and Conventional Visual Method – An in Vivo Study
- 1. International Journal of Dental Science and Innovative Research (IJDSIR)
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Abstract
Background: Accurate shade selection is essential for achieving optimal aesthetics in prosthetic rehabilitation. Conventional visual methods are widely used but remain subjective and are influenced by operator experience and lighting conditions. Smartphone-based digital photography has emerged as a potential tool to improve objectivity and reproducibility in shade matching.
Materials and methods: In this randomized controlled study, 100 patients requiring prosthetic rehabilitation were equally divided into two groups: Group 1—visual shade selection and Group 2—digital shade selection using smartphone photography. Three experienced prosthodontists served as independent judges and were blinded to the method used. Each prosthesis was evaluated under three lighting conditions: natural daylight, fluorescent light, and incandescent light. Shade matching was assessed using a 10-point scale, where a score of 10 represented a perfect shade match. Statistical analysis was performed to compare mean shade matching scores between the two methods under each lighting condition.
Results: The smartphone-based digital method demonstrated consistently higher mean shade matching scores across all lighting conditions. Under natural light, statistically significant differences were observed for Judge 1 (t=2.51, p=0.014) and Judge 3 (t=5.02, p<0.001). In fluorescent lighting, all judges reported significantly higher scores with the digital method (p<0.01). Under incandescent light, significant differences were noted for Judge 1 (t=3.55, p<0.001) and Judge 2 (t=2.65, p=0.009). Overall, the digital method achieved significantly higher cumulative ratings across all lighting conditions (p<0.01).
Conclusion: Smartphone-assisted shade selection showed superior accuracy and consistency compared to the conventional visual method, offering an objective and clinically predictable approach for shade selection.
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