• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

定量光诱导荧光(QLF):一种用于早期窝沟龋检测的工具,并支持体内的决策制定。

Quantitative light-induced fluorescence (QLF): a tool for early occlusal dental caries detection and supporting decision making in vivo.

机构信息

Department of Health Services Research and School of Dentistry, University of Liverpool, Liverpool, United Kingdom.

出版信息

J Dent. 2013 Feb;41(2):127-32. doi: 10.1016/j.jdent.2012.08.013. Epub 2012 Aug 30.

DOI:10.1016/j.jdent.2012.08.013
PMID:22940557
Abstract

OBJECTIVES

This study reports the development and assessment of a novel method using quantitative light-induced fluorescence (QLF), to determine whether QLF parameters ΔF and ΔQ were appropriate for aiding diagnosis and clinical decision making of early occlusal mineral loss by comparing QLF analysis with actual restorative management.

METHODS

Following ethical approval, 46 subjects attending a dental teaching hospital were enrolled. White light digital (WL) and QLF images/analyses of 46 unrestored posterior teeth with suspected occlusal caries were made after a clinical decision had already been taken to explore fissures operatively. WL and QLF imaging/analysis were repeated after initial cavity preparation. The type of restorative treatment was determined by the supervising clinician independent of any imaging performed. Actual restorative management carried out was recorded as fissure sealant/preventive resin restoration (F/P) or class I occlusal restoration (Rest.) thus reflecting the extent of intervention (=gold standard). All QLF images were analysed independently.

RESULTS

The results showed statistically significant differences between the two treatment groups ΔF (p=0.002) (mean 22.60 - F/P and 28.80 - Rest.) and ΔQ (p=0.012) (mean 230.49 - F/P and 348.30 - Rest.).

CONCLUSIONS

ΔF and ΔQ values may be useful in aiding clinical diagnosis and decision making in relation to the management of early mineral loss and restorative intervention of occlusal caries.

CLINICAL SIGNIFICANCE

QLF has the potential to be a valuable tool for caries diagnosis in clinical practice.

摘要

目的

本研究报告了一种使用定量光诱导荧光(QLF)的新方法的开发和评估,通过比较 QLF 分析与实际修复管理,确定 QLF 参数 ΔF 和 ΔQ 是否适合辅助诊断和临床决策早期咬合面矿物质损失。

方法

在获得伦理批准后,纳入 46 名就诊于牙科教学医院的受试者。在已经决定对可疑窝沟龋的 46 颗未修复的后牙进行手术探查裂沟后,对其进行白光数字(WL)和 QLF 图像/分析。在初次备洞后重复进行 WL 和 QLF 成像/分析。监督临床医生独立于任何进行的成像来确定修复治疗类型。实际进行的修复治疗记录为窝沟封闭/预防性树脂修复(F/P)或 I 类咬合面修复(Rest.),从而反映干预程度(=金标准)。所有 QLF 图像均独立进行分析。

结果

结果显示,两种治疗组的 ΔF(p=0.002)(均值 22.60-F/P 和 28.80-Rest.)和 ΔQ(p=0.012)(均值 230.49-F/P 和 348.30-Rest.)之间存在统计学显著差异。

结论

ΔF 和 ΔQ 值可能有助于辅助临床诊断和决策,以管理早期矿物质损失和窝沟龋的修复干预。

临床意义

QLF 有潜力成为临床实践中龋病诊断的有用工具。

相似文献

1
Quantitative light-induced fluorescence (QLF): a tool for early occlusal dental caries detection and supporting decision making in vivo.定量光诱导荧光(QLF):一种用于早期窝沟龋检测的工具,并支持体内的决策制定。
J Dent. 2013 Feb;41(2):127-32. doi: 10.1016/j.jdent.2012.08.013. Epub 2012 Aug 30.
2
Detection of initial caries lesions on smooth surfaces by quantitative light-induced fluorescence and visual examination: an in vivo comparison.通过定量光诱导荧光和视觉检查检测光滑表面的初始龋损:一项体内比较研究。
Eur J Oral Sci. 2005 Dec;113(6):494-8. doi: 10.1111/j.1600-0722.2005.00255.x.
3
In vivo detection of non-cavitated caries lesions on occlusal surfaces by visual inspection and quantitative light-induced fluorescence.通过视觉检查和定量光诱导荧光对咬合面非龋洞性龋损进行体内检测。
Acta Odontol Scand. 2007 Jun;65(3):183-8. doi: 10.1080/00016350701291685.
4
Assessing caries removal by undergraduate dental students using quantitative light-induced fluorescence.使用定量光诱导荧光评估牙科专业本科生的龋齿去除情况。
J Dent Educ. 2008 Nov;72(11):1318-23.
5
The effect of surface defects in early caries assessment using quantitative light-induced fluorescence (QLF) and micro-digital-photography (MDP).定量光诱导荧光(QLF)和微数字摄影(MDP)评估早期龋齿表面缺陷的效果。
J Dent. 2012 Nov;40(11):955-61. doi: 10.1016/j.jdent.2012.08.001. Epub 2012 Aug 11.
6
Ability of quantitative light-induced fluorescence (QLF) to assess the activity of white spot lesions during dehydration.定量光诱导荧光(QLF)评估脱水过程中白斑病变活性的能力。
Am J Dent. 2006 Feb;19(1):15-8.
7
Clinical applications of new advances in occlusal caries diagnosis.咬合面龋诊断新进展的临床应用
N Z Dent J. 2000 Mar;96(423):23-6.
8
Detection of in vitro demineralization adjacent to restorations using quantitative light induced fluorescence (QLF).使用定量光诱导荧光(QLF)检测修复体周围的体外脱矿情况。
Dent Mater. 2003 Jul;19(5):368-74. doi: 10.1016/s0109-5641(02)00079-9.
9
Changes in Occlusal Caries Lesion Management in France from 2002 to 2012: A Persistent Gap between Evidence and Clinical Practice.2002年至2012年法国咬合面龋损治疗的变化:证据与临床实践之间持续存在差距。
Caries Res. 2015;49(4):408-16. doi: 10.1159/000381355. Epub 2015 Jun 24.
10
Early detection of secondary caries using quantitative, light-induced fluorescence.使用定量光诱导荧光早期检测继发龋
Oper Dent. 2003 Jul-Aug;28(4):415-22.

引用本文的文献

1
Comparison of Human and Porcine Natural Tooth Fluorescence-A Scoping Study to Inform Research on Dental Materials and Forensic Dentistry.人与猪天然牙齿荧光的比较——一项为牙科材料和法医牙科学研究提供信息的范围界定研究。
Clin Exp Dent Res. 2024 Dec;10(6):e70052. doi: 10.1002/cre2.70052.
2
In-vitro and in-vivo comparative studies of treatment effects on enamel demineralization during orthodontic therapy: implications for clinical early-intervention strategy.正畸治疗过程中釉质脱矿的体外和体内治疗效果比较研究:对临床早期干预策略的影响。
Clin Oral Investig. 2024 Sep 24;28(10):545. doi: 10.1007/s00784-024-05944-4.
3
Caries lesions diagnosis with deep convolutional neural network in intraoral QLF images by handheld device.
手持设备在口腔 QLF 图像中使用深度卷积神经网络进行龋病病变诊断。
BMC Oral Health. 2024 Jun 29;24(1):754. doi: 10.1186/s12903-024-04517-x.
4
Enhancing prediction of tooth caries using significant features and multi-model classifier.利用显著特征和多模型分类器增强龋齿预测
PeerJ Comput Sci. 2023 Oct 31;9:e1631. doi: 10.7717/peerj-cs.1631. eCollection 2023.
5
Tooth caries classification with quantitative light-induced fluorescence (QLF) images using convolutional neural network for permanent teeth in vivo.利用卷积神经网络对活体恒牙进行定量光诱导荧光(QLF)图像的龋齿分类。
BMC Oral Health. 2023 Dec 8;23(1):981. doi: 10.1186/s12903-023-03669-6.
6
An Explainable Deep Learning Model to Prediction Dental Caries Using Panoramic Radiograph Images.一种用于使用全景X光图像预测龋齿的可解释深度学习模型。
Diagnostics (Basel). 2023 Jan 7;13(2):226. doi: 10.3390/diagnostics13020226.
7
Uses of Different Machine Learning Algorithms for Diagnosis of Dental Caries.不同机器学习算法在龋齿诊断中的应用。
J Healthc Eng. 2022 Mar 31;2022:5032435. doi: 10.1155/2022/5032435. eCollection 2022.
8
Emerging Technologies for Dentin Caries Detection-A Systematic Review and Meta-Analysis.用于检测牙本质龋的新兴技术——系统评价与荟萃分析
J Clin Med. 2022 Jan 28;11(3):674. doi: 10.3390/jcm11030674.
9
Detection of Dental Caries and Cracks with Quantitative Light-Induced Fluorescence in Comparison to Radiographic and Visual Examination: A Retrospective Case Study.定量光诱导荧光技术与放射学及肉眼检查在龋齿和裂纹检测中的对比:一项回顾性病例研究。
Sensors (Basel). 2021 Mar 3;21(5):1741. doi: 10.3390/s21051741.
10
Knowledge and Use of Caries Detection Methods among Dental Students and Dental Practitioners in Riyadh, Saudi Arabia.沙特阿拉伯利雅得牙科学生和牙科从业者对龋齿检测方法的了解与应用
Int J Dent. 2020 Dec 2;2020:8825890. doi: 10.1155/2020/8825890. eCollection 2020.