Qutieshat Abubaker, Salem Abdurahman, Kyranides Melina N
Adult Restorative Dentistry Oman Dental College, Muscat, Oman.
Restorative Dentistry Dental School University of Dundee, Dundee, UK.
Int J Dent. 2024 Aug 10;2024:3965641. doi: 10.1155/2024/3965641. eCollection 2024.
The current study introduces a novel, algorithm-based software developed to objectively evaluate dental cavity preparations. The software aims to provide an alternative or complement to traditional, subjective assessment methods used in operative dentistry education.
The software was tested on cavity preparations carried out by 70 participants on artificial molar teeth. These cavities were also independently assessed by an experienced academic panel. The software, using 3D imaging, calculated cavity dimensions and assigned an error score based on deviation from ideal measurements. Statistical analyses included sensitivity, specificity, positive predictive value, negative predictive value, Cohen's kappa, the intraclass correlation coefficient (ICC3k), Spearman's rho, Kendall's tau correlation coefficients, and a confusion matrix.
The software demonstrated a high degree of accuracy and agreement with the panel assessments. The average software and panel scores were 64.1 and 60.91, respectively. Sensitivity (0.98) was high, specificity (0.55) was moderate, and the ICC3k value (0.857) indicated a strong agreement between the software and the panel. Further, Spearman's rho (0.73) and Kendall's tau (0.56) suggested a strong correlation between the two grading methods.
The results support the algorithm-based software as a valid and reliable tool for dental cavity preparation assessments. The software's potential use in dental education is promising, though future research is necessary to validate and optimize this technology for wider application.
本研究介绍了一种新开发的基于算法的软件，用于客观评估牙洞预备情况。该软件旨在为牙体牙髓病学教育中使用的传统主观评估方法提供替代或补充。
该软件在70名参与者对人工磨牙进行的牙洞预备上进行了测试。这些牙洞也由一个经验丰富的学术小组进行了独立评估。该软件利用三维成像技术计算牙洞尺寸，并根据与理想测量值的偏差给出误差分数。统计分析包括敏感性、特异性、阳性预测值、阴性预测值、科恩kappa系数、组内相关系数（ICC3k）、斯皮尔曼等级相关系数、肯德尔等级相关系数以及混淆矩阵。
该软件与小组评估显示出高度的准确性和一致性。软件和小组的平均分数分别为64.1和60.91。敏感性（0.98）较高，特异性（0.55）中等，ICC3k值（0.857）表明软件与小组之间有很强的一致性。此外，斯皮尔曼等级相关系数（0.73）和肯德尔等级相关系数（0.56）表明两种分级方法之间有很强的相关性。
结果支持基于算法的软件作为牙洞预备评估的有效且可靠工具。该软件在牙科教育中的潜在应用前景广阔，不过未来还需要进行研究以验证和优化这项技术，使其能更广泛地应用。
