Division of Dentistry, School of Medical Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, UK.
Cochrane Oral Health, Division of Dentistry, School of Medical Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, UK.
Cochrane Database Syst Rev. 2021 Jan 27;1(1):CD013855. doi: 10.1002/14651858.CD013855.
Caries is one of the most prevalent and preventable conditions worldwide. If identified early enough then non-invasive techniques can be applied, and therefore this review focusses on early caries involving the enamel surface of the tooth. The cornerstone of caries detection and diagnosis is a visual and tactile dental examination, although alternative approaches are available. These include illumination-based devices that could potentially support the dental examination. There are three categories of illumination devices that exploit various methods of application and interpretation, each primarily defined by different wavelengths, optical coherence tomography (OCT), near-infrared (NIR), and fibre-optic technology, which incorporates more recently developed digital fibre optics (FOTI/DIFOTI).
To estimate the diagnostic test accuracy of different illumination tests for the detection and diagnosis of enamel caries in children or adults. We also planned to explore the following potential sources of heterogeneity: in vitro or in vivo studies with different reference standards; tooth surface (occlusal, proximal, smooth surface, or adjacent to a restoration); single or multiple sites of assessment on a tooth surface; and the prevalence of caries into dentine.
Cochrane Oral Health's Information Specialist undertook a search of the following databases: MEDLINE Ovid (1946 to 15 February 2019); Embase Ovid (1980 to 15 February 2019); US National Institutes of Health Ongoing Trials Register (ClinicalTrials.gov, to 15 February 2019); and the World Health Organization International Clinical Trials Registry Platform (to 15 February 2019). We studied reference lists as well as published systematic review articles.
We included diagnostic accuracy study designs that compared the use of illumination-based devices with a reference standard (histology, enhanced visual examination with or without radiographs, or operative excavation). These included prospective studies that evaluated the diagnostic accuracy of a single index test and studies that directly compared two or more index tests. Both in vitro and in vivo studies of primary and permanent teeth were eligible for inclusion. We excluded studies that explicitly recruited participants with caries into dentine or frank cavitation. We also excluded studies that artificially created carious lesions and those that used an index test during the excavation of dental caries to ascertain the optimum depth of excavation.
Two review authors extracted data independently and in duplicate using a standardised data extraction form and quality assessment based on QUADAS-2 specific to the clinical context. Estimates of diagnostic accuracy were determined using the bivariate hierarchical method to produce summary points of sensitivity and specificity with 95% confidence regions. The comparative accuracy of different illumination devices was conducted based on indirect and direct comparisons between methods. Potential sources of heterogeneity were pre-specified and explored visually and more formally through meta-regression.
We included 24 datasets from 23 studies that evaluated 16,702 tooth surfaces. NIR was evaluated in 6 datasets (673 tooth surfaces), OCT in 10 datasets (1171 tooth surfaces), and FOTI/DIFOTI in 8 datasets (14,858 tooth surfaces). The participant selection domain had the largest number of studies judged at high risk of bias (16 studies). Conversely, for the index test, reference standard, and flow and timing domains the majority of studies were judged to be at low risk of bias (16, 12, and 16 studies respectively). Concerns regarding the applicability of the evidence were judged as high or unclear for all domains. Notably, 14 studies were judged to be of high concern for participant selection, due to selective participant recruitment, a lack of independent examiners, and the use of an in vitro study design. The summary estimate across all the included illumination devices was sensitivity 0.75 (95% confidence interval (CI) 0.62 to 0.85) and specificity 0.87 (95% CI 0.82 to 0.92), with a diagnostic odds ratio of 21.52 (95% CI 10.89 to 42.48). In a cohort of 1000 tooth surfaces with a prevalence of enamel caries of 57%, this would result in 142 tooth surfaces being classified as disease free when enamel caries was truly present (false negatives), and 56 tooth surfaces being classified as diseased in the absence of enamel caries (false positives). A formal comparison of the accuracy according to device type indicated a difference in sensitivity and/or specificity (Chi(4) = 34.17, P < 0.01). Further analysis indicated a difference in the sensitivity of the different devices (Chi(2) = 31.24, P < 0.01) with a higher sensitivity of 0.94 (95% CI 0.88 to 0.97) for OCT compared to NIR 0.58 (95% CI 0.46 to 0.68) and FOTI/DIFOTI 0.47 (95% CI 0.35 to 0.59), but no meaningful difference in specificity (Chi(2) = 3.47, P = 0.18). In light of these results, we planned to formally assess potential sources of heterogeneity according to device type, but due to the limited number of studies for each device type we were unable to do so. For interpretation, we presented the coupled forest plots for each device type according to the potential source of heterogeneity. We rated the certainty of the evidence as low and downgraded two levels in total due to avoidable and unavoidable study limitations in the design and conduct of studies, indirectness arising from the in vitro studies, and imprecision of the estimates.
AUTHORS' CONCLUSIONS: Of the devices evaluated, OCT appears to show the most potential, with superior sensitivity to NIR and fibre-optic devices. Its benefit lies as an add-on tool to support the conventional oral examination to confirm borderline cases in cases of clinical uncertainty. OCT is not currently available to the general dental practitioner, and so further research and development are necessary. FOTI and NIR are more readily available and easy to use; however, they show limitations in their ability to detect enamel caries but may be considered successful in the identification of sound teeth. Future studies should strive to avoid research waste by ensuring that recruitment is conducted in such a way as to minimise selection bias and that studies are clearly and comprehensively reported. In terms of applicability, any future studies should be undertaken in a clinical setting that is reflective of the complexities encountered in caries assessment within the oral cavity.
龋齿是全球最普遍和可预防的疾病之一。如果能够及早发现,就可以采用非侵入性技术,因此本综述重点关注涉及牙釉质表面的早期龋齿。龋齿检测和诊断的基石是视觉和触觉牙科检查,尽管还可以采用其他方法。这些方法包括可能支持牙科检查的基于光照的设备。有三类光照设备利用不同的应用和解释方法,每种方法主要由不同的波长、光学相干断层扫描(OCT)、近红外(NIR)和光纤技术定义,其中光纤技术最近又发展了数字光纤技术(FOTI/DIFOTI)。
评估不同光照测试用于检测和诊断儿童或成人牙釉质龋齿的诊断测试准确性。我们还计划探讨以下可能的异质性来源:不同参考标准的体外或体内研究;牙面(咬合面、邻面、光滑面或临近修复体);牙面的单个或多个部位评估;以及牙本质龋齿的患病率。
Cochrane 口腔健康信息专家对以下数据库进行了检索:MEDLINE Ovid(1946 年至 2019 年 2 月 15 日);Embase Ovid(1980 年至 2019 年 2 月 15 日);美国国立卫生研究院正在进行的临床试验登记处(ClinicalTrials.gov,截至 2019 年 2 月 15 日);以及世界卫生组织国际临床试验注册平台(截至 2019 年 2 月 15 日)。我们还研究了参考文献列表以及已发表的系统评价文章。
我们纳入了比较光照设备与参考标准(组织学、增强视觉检查伴或不伴放射影像学检查、或手术挖掘)的诊断准确性研究设计。这些研究包括评估单个索引测试准确性的前瞻性研究和直接比较两种或多种索引测试的研究。原发性和永久性牙齿的体内和体外研究都符合纳入标准。我们排除了明确招募有牙本质龋齿或明显空洞的参与者的研究。我们还排除了人为制造龋齿病变的研究,以及在挖掘龋齿以确定最佳挖掘深度时使用索引测试的研究。
两名综述作者独立并重复使用标准数据提取表和基于 QUADAS-2 的质量评估表提取数据,该评估表专门针对临床背景。使用二变量分层方法确定诊断准确性估计值,生成具有 95%置信区间的敏感性和特异性汇总点。根据间接和直接比较方法,对不同的光照设备进行了比较准确性评估。预先指定了异质性来源,并通过视觉和更正式的元回归进行了探索。
我们纳入了 23 项研究的 24 个数据集,评估了 16702 个牙面。NIR 评估了 6 个数据集(673 个牙面),OCT 评估了 10 个数据集(1171 个牙面),FOTI/DIFOTI 评估了 8 个数据集(14858 个牙面)。参与者选择域的研究被判断为偏倚风险最高(16 项研究)。相反,对于索引测试、参考标准和流程和时间域,大多数研究被判断为偏倚风险低(16、12 和 16 项研究)。所有领域的证据适用性都被判断为高度关注或不明确。值得注意的是,14 项研究因选择性招募参与者、缺乏独立检查者以及使用体外研究设计而被判断为对参与者选择存在高关注。纳入的所有光照设备的汇总估计值为敏感性 0.75(95%置信区间 0.62 至 0.85)和特异性 0.87(95%置信区间 0.82 至 0.92),诊断优势比为 21.52(95%置信区间 10.89 至 42.48)。在一个 1000 个牙面的队列中,牙釉质龋齿的患病率为 57%,这将导致 142 个牙面在真正存在牙釉质龋齿时被归类为无病(假阴性),56 个牙面在无牙釉质龋齿时被归类为有病(假阳性)。根据设备类型对准确性进行正式比较表明存在敏感性和/或特异性差异(Chi(4) = 34.17,P < 0.01)。进一步分析表明,不同设备的敏感性存在差异(Chi(2) = 31.24,P < 0.01),OCT 的敏感性为 0.94(95%置信区间 0.88 至 0.97),而 NIR 为 0.58(95%置信区间 0.46 至 0.68)和 FOTI/DIFOTI 为 0.47(95%置信区间 0.35 至 0.59),但特异性无明显差异(Chi(2) = 3.47,P = 0.18)。鉴于这些结果,我们计划根据设备类型正式评估潜在的异质性来源,但由于每种设备类型的研究数量有限,我们无法进行评估。对于解释,我们根据潜在的异质性来源,按每个设备类型呈现了耦合森林图。我们将证据的确定性评级为低,并因研究设计和实施中的可避免和不可避免的局限性、来自体外研究的间接性以及估计值的不准确性而总共降低了两个级别。
在评估的设备中,OCT 似乎显示出最大的潜力,其敏感性优于 NIR 和光纤设备。其优势在于作为常规口腔检查的附加工具,用于确认临床不确定病例的边界情况。OCT 目前不适用于普通牙医,因此需要进一步的研究和开发。FOTI 和 NIR 更易于获得和使用;然而,它们在检测牙釉质龋齿方面存在局限性,但在识别健康牙齿方面可能是成功的。未来的研究应通过确保招募过程将选择偏差最小化,并全面和清楚地报告研究结果,努力避免研究浪费。就适用性而言,任何未来的研究都应在临床环境中进行,该环境反映了在口腔评估中遇到的龋齿评估的复杂性。