智能手机应用程序与电脑软件在头影测量中的一致性评价

doi:10.13701/j.cnki.kqyxyj.2021.08.007

摘要/Abstract

摘要： 目的: 探讨智能手机应用程序(App)头影测量数据的准确性。方法: 选取55例患者的头颅侧位片,分别使用电脑软件和智能手机App测量12个项目。采用组内相关系数(ICC)分析测量方法的可靠性,配对t检验比较2种方法测量结果的差异。Bland-Altman法计算测量结果差值的95%一致性界限(LoA)的95%可信区间(CI),以评价2种测量方法的一致性。结果: 2种方法所有项目的重复测量ICC值均大于0.9。2种方法各项测量数据的比较均无显著差异(P>0.05)。除U1-NA、L1-NB和U1-L1外,SNA、SNB、ANB、SN-MP、Y-Axis、U1-NA(mm)、L1-NB(mm)、UL-E line及LL-E line测量差值的95% LoA的95% CI均在临床可接受范围内。结论: 智能手机App与电脑软件的骨性及软组织头影测量数据具有较好的一致性。智能手机App作为一种便携、准确、可靠的方法,可在头影测量中推广应用。

关键词: 头影测量, 智能手机, 应用程序, Bland-Altman法

Abstract: Objective: To investigate the accuracy of cephalometric measurements performed by smartphone application (App). Methods: Both computer software and smartphone app were used to trace total twelve measurements of 55 patients' lateral cephalograms. The intra-class correlation coefficient (ICC) was used to assess the intra-tool reliability. Statistic differences between two methods were evaluated using the paired t-test. The agreement of these two methods was evaluated by the 95% confidence interval (CI) of 95% limits of agreement (LoA), which was calculated by the Bland-Altman method. Results: All ICC values from repeated measurements by each method were above 0.9. There was no significant statistically difference between two methods in all cephalometric measurements (P>0.05). The 95% CI of 95% LoA of SNA, SNB, ANB, SN-MP, Y-Axis, U1-NA (mm), L1-NB (mm), UL-E line, and LL-E line were within clinically acceptable limits, except for U1-NA, L1-NB, and U1-L1. Conclusion: Smartphone app showed good agreement with computer software in skeletal and soft tissue measurements of cephalometric analysis. It was recommended to use Smartphone app in cephalometric analysis for its portable, accurate, and reliable property.

Key words: cephalometrics, smartphone, application, Bland-Altman method

刘恒朗, 冯琳静, 王莉丽. 智能手机应用程序与电脑软件在头影测量中的一致性评价[J]. 口腔医学研究, 2021, 37(8): 702-707.

LIU Henglang, FENG Linjing, WANG Lili. Agreement Evaluation of Cephalometric Analysis between Smartphone Application and Computer Software[J]. Journal of Oral Science Research, 2021, 37(8): 702-707.

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