摘要
目的通过构建基于深度学习模型的计算机辅助龋病诊断系统,检测根尖X线片图像中恒牙邻面龋,为邻面龋的早期诊断提供参考。方法选择福建医科大学附属口腔医院口腔颌面外科门诊提供的因正畸需要或无保留价值而拔除的人离体恒前磨牙及磨牙160颗(外观完整或邻面龋洞缘位于釉质牙骨质界之上),拍摄根尖X线片,进行组织学检测并分级(0级:无龋坏;1级:龋坏达釉质外1/2;2级:龋坏达釉质内1/2;3级:龋坏达釉质牙本质界;4级:龋坏达牙本质外1/2;5级:龋坏达牙本质内1/2)。根据组织学分级将160颗离体牙根尖X线片均分为训练集和测试集(各80颗)。由2名评估者参照组织学图像对训练集根尖X线片进行龋坏标记,建立基于深度学习模型的计算机辅助龋病诊断系统。由另2名评估者和计算机辅助龋病诊断系统分别对测试集根尖X线片进行邻面龋诊断。以组织学检测结果作为金标准,通过受试者工作特征曲线(receiver operating characteristic curve,ROC)综合评估肉眼诊断和计算机辅助龋病诊断系统的灵敏度和特异度,利用ROC曲线下面积(areas under the ROC curve,AUC)值比较两种诊断方法的总体诊断准确性。通过查准率-查全率(precision-recall,P-R)曲线综合评估两种诊断方法对龋坏样本的查准查全能力。通过灵敏度(即查全率)、特异度、阳性预测值(positive predictive value,PPV)(即查准率)和阴性预测值(negative predictive value,NPV)及其95%置信区间(confidence interval,CI)进一步比较两种诊断方法的准确性。结果对测试集离体牙根尖X线片,肉眼诊断与计算机辅助龋病诊断系统诊断的AUC值分别为0.729(95%CI:0.650~0.808)和0.762(95%CI:0.685~0.839),差异无统计学意义(P>0.05)。计算机辅助龋病诊断系统与肉眼诊断的特异度、PPV、NPV差异均无统计学意义(P>0.05)。计算机辅助龋病诊断系统的灵敏度(76.7%)显著大于肉眼诊断(59.3%)(P<0.05)。肉眼诊断对恒牙邻面1级龋坏的灵敏度(27%)显著小于计算机辅助龋病诊断系统(77%)(P<0.05)。结论与肉眼相比,计算机辅助龋病诊断系统对恒牙邻面釉质龋,尤其是局限于釉质内的早期龋坏更灵敏。本项研究建立的计算机辅助龋病诊断系统诊断准确性与评价者肉眼诊断的准确性相似。
Objective To establish and to evaluate a computer-aided system based on deep-learning for detection and diagnosis of dental approximal caries on periapical radiographs.Methods One hundred and sixty human premolars and molars extracted for orthodontic or periodontal reasons were obtained from Department of Oral and Maxillofacial Surgery,Affiliated Stomatological Hospital,Fujian Medical University.A total of 160 periapical radiographic images were divided into a training dataset(n=80)and a test dataset(n=80).A deep-learning based computer-aided caries diagnosis system was established and trained.The performances of computer-aided diagnosis system and human observer were compared using receiver operating characteristic(ROC)curves,precision-recall(P-R)curves,the area under the curve(AUC),sensitivity,specificity,positive predictive value(PPV),and negative predictive value(NPV).The AUC values of human observers and caries diagnosis system was compared by using an online statistical tool(SPSSAU 20.0).Chi-square test was used to analyze the differences between human observers and caries diagnosis system(ɑ=0.05).Results The AUC values of human observers and caries diagnosis system were 0.729(95%CI:0.650-0.808)and 0.762(95%CI:0.685-0.839),respectively(P>0.05).No significant differences were found for the specificity,PPV and NPV between the caries diagnosis system and human observers(P all>0.05).The caries diagnosis system was significantly more sensitive in detecting dental proximal caries than human observers(P<0.05).For the diagnosis of level-1 caries(caries limited to outer 1/2 of enamel),the sensitivity of human observers and computer-aided detection system were 27%and 77%,respectively(P<0.05).Conclusions The computer-aided diagnosis system provided similar accuracy as human observers and significantly better sensitivity than human observers,especially for shallow caries in enamel.
作者
林秀娇
张栋
黄明毅
程辉
于皓
Lin Xiujiao;Zhang Dong;Huang Mingyi;Cheng Hui;Yu Hao(Department of Prosthodontics,Affiliated Stomatological Hospital,Fujian Medical University,Fuzhou 350002,China;School of Mathematics and Computer Science,Fuzhou University,Fuzhou 350108,China)
出处
《中华口腔医学杂志》
CAS
CSCD
北大核心
2020年第9期654-660,共7页
Chinese Journal of Stomatology
基金
福建省社会发展引导性(重点)项目(2018Y0029)。
关键词
诊断
计算机辅助
龋齿
根尖X线片
深度学习
Diagnosis,computer-assisted
Dental caries
X-ray periapical radiography
Deep learning
