School of Design, University of Leeds, Leeds, UK.
Prosthodontic Division, Department for Restorative Science and Biomaterials, Boston University Henry M. Goldman School of Dental Medicine, Boston, USA; Medical Center, University of Freiburg, Center for Dental Medicine, Department of Prosthetic Dentistry, Faculty of Medicine, University of Freiburg, Freiburg, Germany.
Dent Mater. 2024 Oct;40(10):1497-1506. doi: 10.1016/j.dental.2024.07.003. Epub 2024 Aug 1.
This multicenter study aimed to evaluate visual-instrumental agreement of six color measurement devices and optimize three color difference equations using a dataset of visual color differences (∆V) from expert observers.
A total of 154 expert observers from 16 sites across 5 countries participated, providing visual scaling on 26 sample pairs of artificial teeth using magnitude estimation. Three color difference equations (ΔE*, ∆E, and CAM16-UCS) were tested. Optimization of all three equations was performed using device-specific weights, and the standardized residual sum of squares (STRESS) index was used to evaluate visual-instrumental agreement.
The ΔE* formula exhibited STRESS values from 18 to 40, with visual-instrumental agreement between 60 % and 82 %. The ∆E formula showed STRESS values from 26 to 32, representing visual-instrumental agreement of 68 % to 74 %. CAM16-UCS demonstrated STRESS values from 32 - 39, with visual-instrumental agreement between 61-68 %. Following optimization, STRESS values decreased for all three formulas, with ΔE demonstrating average visual-instrumental agreement of 79 % and ∆E of 78 %. CAM16-UCS showed average visual-instrumental agreement of 76 % post optimization.
Optimization of color difference equations notably improved visual-instrumental agreement, overshadowing device performance. The optimzed ΔE formula demonstrated the best overall performance combining computational simplicty with outstanding visual-instrumental agreement.
本多中心研究旨在评估六种颜色测量设备的视觉仪器一致性，并使用来自专家观察者的视觉色差（∆V）数据集优化三个色差方程。
共有来自 5 个国家 16 个地点的 154 名专家观察员参与，使用幅度估计法对 26 对人工牙样本对进行视觉标度。测试了三种色差方程（ΔE*、∆E 和 CAM16-UCS）。使用设备特定权重对所有三个方程进行了优化，并使用标准化残差和（STRESS）指数评估视觉仪器一致性。
ΔE*公式的 STRESS 值为 18 至 40，视觉仪器一致性为 60%至 82%。∆E 公式的 STRESS 值为 26 至 32，代表 68%至 74%的视觉仪器一致性。CAM16-UCS 的 STRESS 值为 32-39，视觉仪器一致性为 61-68%。优化后，所有三个公式的 STRESS 值均降低，ΔE 平均视觉仪器一致性为 79%，∆E 为 78%。CAM16-UCS 优化后的平均视觉仪器一致性为 76%。
色差方程的优化显著提高了视觉仪器的一致性，超过了设备性能。优化后的ΔE 公式在具有出色视觉仪器一致性的同时，还具有计算简单的最佳整体性能。
