Mileman P A, van den Hout W B, Sanderink G C H
Department of Oral Radiology, Academic Centre for Dentistry Amsterdam (ACTA), The Netherlands.
Dentomaxillofac Radiol. 2003 Mar;32(2):116-23. doi: 10.1259/dmfr/58225203.
To investigate whether using a computer-assisted learning (CAL) calibration program improves the accuracy of dental students in caries detection from bitewing radiographs.
Dental students were assigned to an experimental (n=33) and control (n=34) group using a randomized block design. The experimental group used the CAL program with feedback to calibrate themselves against experts in radiographic caries detection and a histological gold standard of the actual clinical condition. Feedback was provided visually of the actual tooth surface condition and in the form of graphics showing diagnostic accuracy performance measures. Performance was tested before the program (for the control group) and after the program (for the experimental group) by assessing surfaces (n=56) from a new independent digital test set of evaluation radiographs for the presence, histologically, of dentine caries (n=23). The summary receiver operating characteristic (SROC) method for summarizing true positive ratio (TPR) (sensitivity) and false positive ratio (FPR) (1-specificity) was used to analyse the dichotomous data. Differences between the control and experimental groups were tested for (a) the area under the SROC curve (A(z)) and (b) the TPR, FPR and diagnostic odds ratio (DOR) using the Mann-Whitney test (P<0.05).
The mean TPR for dentine caries detection was 76.3% (SD 13.0%) for the experimental group and 66.9% (SD 14.8%) for the control group (P=0.005). Mean FPRs were similar (experimental 28.1% and control 28.7%; P>0.5). The area under the SROC curve A(z) was 0.832 for the experimental group and 0.773 for the control group (P=0.002). The mean DOR for dentine caries in the experimental group (12.4) was better than that in the control group (8.8) (P=0.003).
The CAL program does improve diagnostic performance. Improving the cognitive feedback provided by the program should be considered before implementation.
研究使用计算机辅助学习（CAL）校准程序是否能提高牙科学生从咬合翼片X线片中检测龋齿的准确性。
采用随机区组设计将牙科学生分为实验组（n = 33）和对照组（n = 34）。实验组使用带有反馈的CAL程序，对照放射龋齿检测专家和实际临床状况的组织学金标准进行自我校准。以实际牙齿表面状况的可视化形式以及显示诊断准确性性能指标的图形形式提供反馈。在程序实施前（针对对照组）和程序实施后（针对实验组），通过评估来自一组新的独立数字测试评估X线片的表面（n = 56）是否存在组织学上的牙本质龋（n = 23）来测试性能。采用汇总接受者操作特征（SROC）方法汇总真阳性率（TPR）（敏感性）和假阳性率（FPR）（1-特异性）来分析二分数据。使用曼-惠特尼检验（P<0.05）对对照组和实验组之间的差异进行测试，包括（a）SROC曲线下面积（A(z)）和（b）TPR、FPR和诊断比值比（DOR）。
实验组检测牙本质龋的平均TPR为76.3%（标准差13.0%），对照组为66.9%（标准差14.8%）（P = 0.005）。平均FPR相似（实验组28.1%，对照组28.7%；P>0.5）。实验组的SROC曲线下面积A(z)为0.832，对照组为0.773（P = 0.002）。实验组牙本质龋的平均DOR（12.4）优于对照组（8.8）（P = 0.003）。
CAL程序确实能提高诊断性能。在实施前应考虑改进该程序提供的认知反馈。
