龋病诊断方法的研究进展

doi:10.3877/cma.j.issn.1674-1366.2024.02.001

随着新型口腔材料与数字化技术等的发展，龋病的基础和临床研究不断进步，加快了龋病诊治新技术、新材料和新器械的临床验证，为龋病早期诊断、综合预防，以及功能与美学并重的微创诊疗提供了有力手段。本文通过搜索文献，总结了目前可用于检测和诊断龋病的各项新技术及其临床应用范围和优缺点，旨在为临床工作提供依据和参照。

关键词: 龋齿, 早期诊断, 光学诊断技术, 人工智能

Due to the development of novel dental materials and digital techniques, the basic and clinical researches focusing on dental caries have been accumulated recently, which also promotes the clinical validation for the early diagnosis, comprehensive prevention, and functional-aesthetic treatment with minimal invasive intervention. By searching the literature, this article reviewed the current novel techniques that can be used to detect and diagnose caries, along with their clinical application, advantages and disadvantages, so as to provide references for the clinical application.

Key words: Dental caries, Early diagnosis, Optical diagnosis, Artificial intelligence

[1]	陈智，陈瑞甜.龋病再认识[J].口腔医学研究，2020，36（1）：1-6. DOI：10.13701/j.cnki.kqyxyj.2020.01.001.
[2]	Machiulskiene V，Campus G，Carvalho JC，et al. Terminology of dental caries and dental caries management：Consensus report of a workshop organized by orca and cariology research group of IADR[J]. Caries Res，2020，54（1）：7-14. DOI：10.1159/000503309.
[3]	Young DA，Nový BB，Zeller GG，et al. The american dental association caries classification system for clinical practice：A report of the american dental association council on scientific affairs[J]. J Am Dent Assoc，2015，146（2）：79-86. DOI：10.1016/j.adaj.2014.11.018.
[4]	Uribe SE，Innes N，Maldupa I. The global prevalence of early childhood caries：A systematic review with meta-analysis using the WHO diagnostic criteria[J]. Int J Paediatr Dent，2021，31（6）：817-830. DOI：10.1111/ipd.12783.
[5]	冯希平.中国居民口腔健康状况——第四次中国口腔健康流行病学调查报告[C]//中华口腔医学会口腔预防医学专业委员会. 2018年中华口腔医学会第十八次口腔预防医学学术年会论文汇编.西安，2018：14+13.
[6]	Cheng L，Zhang L，Yue L，et al. Expert consensus on dental caries management[J]. Int J Oral Sci，2022，14（1）：17. DOI：10.1038/s41368-022-00167-3.
[7]	Pitts NB，Stamm JW. International Consensus Workshop on Caries Clinical Trials（ICW-CCT）--final consensus statements：Agreeing where the evidence leads[J]. J Dent Res，2004：C125-C128. DOI：10.1177/154405910408301s27.
[8]	梁景平.龋病早期诊断新技术的研究与应用[J].中华口腔医学杂志，2021，56（1）：33-38. DOI：10.3760/cma.j.cn112144-20201108-00558.
[9]	徐欣，周学东.龋病病因学研究与临床诊疗新进展[J].中华口腔医学杂志，2021，56（1）：3-9. DOI：10.3760/cma.j.cn112144-20201102-00548.
[10]	Janjic Rankovic M，Kapor S，Khazaei Y，et al. Systematic review and meta-analysis of diagnostic studies of proximal surface caries[J]. Clin Oral Investig，2021，25（11）：6069-6079. DOI：10.1007/s00784-021-04113-1.
[11]	Masthoff M，Gerwing M，Masthoff M，et al. Dental Imaging—A basic guide for the radiologist[J]. Rofo，2019，191（3）：192-198. DOI：10.1055/a-0636-4129.
[12]	Oliveira LB，Massignan C，Oenning AC，et al. Validity of micro-CT for in vitro caries detection：A systematic review and meta-analysis[J]. Dentomaxillofac Radiol，2020，49（7）：20190347. DOI：10.1259/dmfr.20190347.
[13]	Tetradis S，Anstey P，Graff-Radford S. Cone beam computed tomography in the diagnosis of dental disease[J]. Tex Dent J，2011，128（7）：620-628.
[14]	Macey R，Walsh T，Riley P，et al. Visual or visual-tactile examination to detect and inform the diagnosis of enamel caries：A Cochrane review[J]. Dental Cadmos，2022，90（5）：346-355. DOI：10.19256/d.cadmos.05.2022.05.
[15]	Aumann S，Donner S，Fischer J，et al. Optical coherence tomography（OCT）：Principle and technical realization[M]//Bille JF. High resolution imaging in microscopy and ophthalmology：New frontiers in biomedical optics. Cham（CH）：Springer，2019：59-85. DOI：10.1007/978-3-030-16638-0_3.
[16]	Shimada Y，Yoshiyama M，Tagami J，et al. Evaluation of dental caries，tooth crack，and age-related changes in tooth structure using optical coherence tomography[J]. Jpn Dent Sci Rev，2020，56（1）：109-118. DOI：10.1016/j.jdsr.2020.08.001.
[17]	Mohamad Saberi FN，Sukumaran P，Ung NM，et al. Assessment of demineralized tooth lesions using optical coherence tomography and other state-of-the-art technologies：A review[J]. Biomed Eng Online，2022，21（1）：83. DOI：10.1186/s12938-022-01055-x.
[18]	Ali S，Gilani SBS，Shabbir J，et al. Optical coherence tomography′s current clinical medical and dental applications：A review[J]. F1000Res，2021，10：310. DOI：10.12688/f1000research.52031.1.
[19]	Serban C，Lungeanu D，Bota SD，et al. Emerging technologies for dentin caries detection-a systematic review and meta-analysis[J]. J Clin Med，2022，11（3）：674. DOI：10.3390/jcm11030674.
[20]	Shimada Y，Sadr A，Sumi Y，et al. Application of optical coherence tomography（OCT）for diagnosis of caries，cracks，and defects of restorations[J]. Curr Oral Health Rep，2015，2（2）：73-80. DOI：10.1007/s40496-015-0045-z.
[21]	Macey R，Walsh T，Riley P，et al. Transillumination and optical coherence tomography for the detection and diagnosis of enamel caries[J]. Cochrane Database Syst Rev，2021，1（1）：CD013855. DOI：10.1002/14651858.CD013855.
[22]	Abdelaziz M，Zuluaga AF，Betancourt F，et al. Optical coherence tomography（OCT）for the evaluation of internal adaptation of Class V resin restorations on Dentin[J]. Proc SPIE Int Soc Opt Eng，2020，11217：1121706. DOI：10.1117/12.2544684.
[23]	Das A，Raposo GCC，Lopes DS，et al. Exploiting nanomaterials for optical coherence tomography and photoacoustic imaging in nanodentistry[J]. Nanomaterials（Basel），2022，12（3）：506. DOI：10.3390/nano12030506.
[24]	Chan KH，Tom H，Lee RC，et al. Clinical monitoring of smooth surface enamel lesions using CP-OCT during nonsurgical intervention[J]. Lasers Surg Med，2016，48（10）：915-923. DOI：10.1002/lsm.22500.
[25]	Thanh MTG，van Toan N，Toan DTT，et al. Diagnostic value of fluorescence methods，visual inspection and photographic visual examination in initial caries lesion：A systematic review and meta-analysis[J]. Dent J（Basel），2021，9（3）：30. DOI：10.3390/dj9030030.
[26]	Slimani A，Terrer E，Manton DJ，et al. Carious lesion detection technologies：Factual clinical approaches[J]. Br Dent J，2020，229（7）：432-442. DOI：10.1038/s41415-020-2116-3.
[27]	Chu CH，Lo EC，You DS. Clinical diagnosis of fissure caries with conventional and laser-induced fluorescence techniques[J]. Lasers Med Sci，2010，25（3）：355-362. DOI：10.1007/s10103-009-0655-6.
[28]	Nokhbatolfoghahaie H，Alikhasi M，Chiniforush N，et al. Evaluation of accuracy of DIAGNOdent in diagnosis of primary and secondary caries in comparison to conventional methods[J]. J Lasers Med Sci，2013，4（4）：159-167. DOI：10.1299/kikaib.64.4077.
[29]	Steier L，Sidhu P，Qasim SS，et al. Visualization of initial bacterial colonization on dentin using fluorescence activating headlight for fluorescence enhanced theragnosis[J]. Photodiagnosis Photodyn Ther，2022，38：102732. DOI：10.1016/j.pdpdt.2022.102732.
[30]	Zhang X，Tu R，Yin W，et al. Micro-computerized tomography assessment of fluorescence aided caries excavation（FACE）technology：Comparison with three other caries removal techniques[J]. Aust Dent J，2013，58（4）：461-467. DOI：10.1111/adj.12106.
[31]	Lai G，Zhu L，Xu X，et al. An in vitro comparison of fluorescence-aided caries excavation and conventional excavation by microhardness testing[J]. Clinical Oral Investig，2014，18（2）：599-605. DOI：10.1007/s00784-013-0999-y.
[32]	Koç-Vural U，Ergin E，Gurgan S. Microhardness and shear bond-strength of carious dentin after fluorescence-aided or conventionally excavation：（An in-vitro comparison）[J]. J Clin Exp Dent，2018，10（7）：e668-e672. DOI：10.4317/jced.53592.
[33]	Lennon AM，Attin T，Martens S，et al. Fluorescence-aided caries excavation（FACE），caries detector，and conventional caries excavation in primary teeth[J]. Pediatric Dentistry，2009，31（4）：316-319. DOI：10.5167/uzh-27086.
[34]	Sardana D，Ekambaram M，Yang Y，et al. Caries-preventive effectiveness of two different fluoride varnishes：A randomised clinical trial in patients with multi-bracketed fixed orthodontic appliances[J]. Int J Paediatr Dent，2023，33（1）：50-62. DOI：10.1111/ipd.13013.
[35]	Dayo AF，Wolff MS，Syed AZ，et al. Radiology of dental caries[J]. Dent Clin North Am，2021，65（3）：427-445. DOI：10.1016/j.cden.2021.02.002.
[36]	Lee JW，Lee ES，Kim BI. Optical diagnosis of dentin caries lesions using quantitative light-induced fluorescence technology[J]. Photodiagnosis Photodyn Ther，2018，23：68-70. DOI：10.1016/j.pdpdt.2018.05.011.
[37]	Park KJ，Meißner T，Günther E，et al. Arrest of root caries with an adjuvant chlorhexidine-fluoride varnish over a 12-months observation period：A QLF-analyzed，placebo-controlled，randomized，clinical trial（RCT）[J]. Odontology，2022，110（1）：193-202. DOI：10.1007/s10266-021-00637-w.
[38]	Walsh T，Macey R，Ricketts D，et al. Enamel caries detection and diagnosis：An analysis of systematic reviews[J]. J Dent Res，2022，101（3）：261-269. DOI：10.1177/00220345211042795.
[39]	Marmaneu-Menero A，Iranzo-Cortés JE，Almerich-Torres T，et al. diagnostic validity of digital imaging fiber-optic transillumination （DIFOTI）and near-infrared light transillumination（NILT）for caries in dentine[J]. J Clin Med，2020，9（2）：420. DOI：10.3390/jcm9020420.
[40]	Fujimoto M，Yoshii S，Ikezawa S，et al. Development of an image sensor for dentistry - fiber connecting technique with the gradient index（GRIN）rod lens[J]. Solid State Phenomena，2017，260：77-84. DOI：10.4028/www.scientific.net/SSP.260.77.
[41]	Kalashnikova NP，Avraamova OG，Kulajenko TV，et al. Modern instrumental methods for early diagnosis of dental caries[J]. Stomatologiia（Mosk），2022，101（1）：89-95. DOI：10.17116/stomat202210101189.
[42]	Kulajenko TV，Avraamova OG，Kalashnikova NP，et al. Efficiency of the transillumination method in the diagnosis of caries of permanent teeth in children[J]. Stomatologiia（Mosk），2021，100（4）：20-25. DOI：10.17116/stomat202110004120.
[43]	Kühnisch J，Söchtig F，Pitchika V，et al. In vivo validation of near-infrared light transillumination for interproximal dentin caries detection[J]. Clin Oral Investig，2016，20（4）：821-829. DOI：10.1007/s00784-015-1559-4.
[44]	Ghodasra R，Brizuela M. Dental caries diagnostic testing[M]. StatPearls，Treasure Island（FL）：StatPearls Publishing LLC，2023.
[45]	Ozkan G，Guzel KGU. Clinical evaluation of near-infrared light transillumination in approximal dentin caries detection[J]. Lasers Med Sci，2017，32（6）：1417-1422. DOI：10.1007/s10103-017-2265-z.
[46]	Yang V，Zhu Y，Curtis D，et al. Thermal imaging of root caries in vivo[J]. J Dent Res，2020，99（13）：1502-1508. DOI：10.1177/0022034520951157.
[47]	Chang NY，Zhu Y，Curtis D，et al. SWIR，Thermal and CP-OCT imaging probes for the in vivo assessment of the activity of root caries lesions[J]. Proc SPIE Int Soc Opt Eng，2020，11217：1121708. DOI：10.1117/12.2550982.
[48]	Silvertown JD，Wong BPY，Abrams SH，et al. Comparison of The Canary System and DIAGNOdent for the in vitro detection of caries under opaque dental sealants[J]. J Investig Clin Dent，2017，8（4）：e12239. DOI：10.1111/jicd.12239.
[49]	Macey R，Walsh T，Riley P，et al. Electrical conductance for the detection of dental caries[J]. Cochrane Database Syst Rev，2021，3（3）：CD014547. DOI：10.1002/14651858.Cd014547.
[50]	Golovanenko AL，Tretyakova EV，Patlusova ES，et al. Study of remineralizing activity of dosage forms for treatment of initial enamel caries[J]. Pharmacy & Pharmacology，2018，6（4）：380-388. DOI：10.19163/2307-9266-2018-6-4-380-388.
[51]	Cohen JE. The association between cariescan pro readings and histologic depth of caries in non cavitated occlusal lesion in vitro[J]. Dissertations & Theses-Gradworks，2013，98（Pt2）：235-253. DOI：10.1002/cne.901220307.
[52]	Popuri VD，Nirmala S，Mallineni SK，et al. In vivo comparative enactment of CarieScanPRO^TM with conventional methods to detect occlusal carious lesions in the mandibular primary molars[J]. Int J Clin Pediatr Dent，2019，12（4）：325-331. DOI：10.5005/jp-journals-10005-1649.
[53]	Huysmans MC，Longbottom C. The challenges of validating diagnostic methods and selecting appropriate gold standards[J]. J Dent Res，2004，83 Spec No C：C48-C52. DOI：10.1177/154405910408301s10.
[54]	Surme K，Kara NB，Yilmaz Y. In vitro evaluation of occlusal caries detection methods in primary and permanent teeth：A comparison of CarieScan PRO，DIAGNOdent Pen，and DIAGNOcam methods[J]. Photobiomodul Photomed Laser Surg，2020，38（2）：105-111. DOI：10.1089/photob.2019.4686.
[55]	Roongruangsilp P，Khongkhunthian P. Artificial intelligence with the application in medicine and dentistry[J]. J Osseointegr，2022，14（3）：166-173. DOI：10.23805/jo.2022.14.22.
[56]	Wenzel A. Radiographic modalities for diagnosis of caries in a historical perspective：From film to machine-intelligence supported systems[J]. Dentomaxillofac Radiol，2021，50（5）：20210010. DOI：10.1259/dmfr.20210010.
[57]	Khanagar SB，Al-Ehaideb A，Maganur PC，et al. Developments，application，and performance of artificial intelligence in dentistry—A systematic review[J]. J Dent Sci，2021，16（1）：508-522. DOI：10.1016/j.jds.2020.06.019.
[58]	Holtkamp A，Elhennawy K，Cejudo Grano De Oro JE，et al. Generalizability of deep learning models for caries detection in near-infrared light transillumination images[J]. J Clin Med，2021，10（5）：961. DOI：10.3390/jcm10050961.
[59]	Devlin H，Williams T，Graham J，et al. The ADEPT study：A comparative study of dentists′ ability to detect enamel-only proximal caries in bitewing radiographs with and without the use of AssistDent artificial intelligence software[J]. Br Dent J，2021，231（8）：481-485. DOI：10.1038/s41415-021-3526-6.
[60]	Schwendicke F，Elhennawy K，Paris S，et al. Deep learning for caries lesion detection in near-infrared light transillumination images：A pilot study[J]. J Dent，2020，92：103260. DOI：10.1016/j.jdent.2019.103260.
[61]	Prados-Privado M，García Villalón J，Martínez-Martínez CH，et al. Dental caries diagnosis and detection using neural networks：A systematic review[J]. J Clin Med，2020，9（11）：3579. DOI：10.3390/jcm9113579.
[62]	Cantu AG，Gehrung S，Krois J，et al. Detecting caries lesions of different radiographic extension on bitewings using deep learning[J]. J Dent，2020，100：103425. DOI：10.1016/j.jdent.2020.103425.
[63]	Bayrakdar IS，Orhan K，Akarsu S，et al. Deep-learning approach for caries detection and segmentation on dental bitewing radiographs[J]. Oral Radiol，2022，38（4）：468-479. DOI：10.1007/s11282-021-00577-9.
[64]	Zhu H，Cao Z，Lian L，et al. CariesNet：A deep learning approach for segmentation of multi-stage caries lesion from oral panoramic X-ray image[J]. Neural Comput Appl，2022：1-9. DOI：10.1007/s00521-021-06684-2.
[65]	Talpur S，Azim F，Rashid M，et al. Uses of different machine learning algorithms for diagnosis of dental caries[J]. J Healthc Eng，2022：50324350 DOI：10.1155/2022/5032435.
[66]	Lee JH，Kim DH，Jeong SN，et al. Detection and diagnosis of dental caries using a deep learning-based convolutional neural network algorithm[J]. J Dent，2018，77：106-111. DOI：10.1016/j.jdent.2018.07.015.
[67]	Singh NK，Raza K. Progress in deep learning-based dental and maxillofacial image analysis：A systematic review[J]. Expert Systems With Applications，2022，199：116968 DOI：10.1016/j.eswa.2022.116968.
[68]	Revilla-León M，Gómez-Polo M，Vyas S，et al. Artificial intelligence applications in restorative dentistry：A systematic review[J]. J Prosthet Dent，2022，128（5）：867-875. DOI：10.1016/j.prosdent.2021.02.010.
[69]	林秀娇.基于深度学习医学影像数据的牙齿龋损分析与诊断[D].福州：福建医科大学，2023. DOI：10.27020/d.cnki.gfjyu.2020.000816.
[70]	李若竹，朱俊霞，王媛媛，等.基于深度学习的儿童龋齿人工智能识别系统雏形的开发[J].中华口腔医学杂志，2021，56（12）：1253-1260. DOI：10.3760/cma.j.cn112144-20210712-00323.
[71]	Ding B，Zhang Z，Liang Y，et al. Detection of dental caries in oral photographs taken by mobile phones based on the YOLOv3 algorithm[J]. Ann Transl Med，2021，9（21）：1622. DOI：10.21037/atm-21-4805.
[72]	Li S，Liu J，Zhou Z，et al. Artificial intelligence for caries and periapical periodontitis detection[J]. J Dent，2022，122：104107. DOI：10.1016/j.jdent.2022.104107.
[73]	Taleb A，Rohrer C，Bergner B，et al. Self-supervised learning methods for label-efficient dental caries classification[J]. Diagnostics（Basel），2022，12（5）：1237. DOI：10.3390/diagnostics12051237.

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