Quantification of Dental Plaque Based on Auto-Fluorescence Imaging
CHEN Chao-jia1, LAO Wei-wei2, LIN Bin1*, CHEN Qing-guang3, ZHU Hai-hua4, CAO Xiang-qun1, CHEN Hui2,4
1. State Key Laboratory of Modern Optical Instrumentation，National Engineering Research Center for Optical Instrument, College of Optical Science and Engineering, Zhejiang University, Hangzhou 310027, China
2. Department of Oral Medicine, the Affiliated Hospital of Stomatology, School of Medicine, Zhejiang University, Hangzhou 310027, China
3. College of Life Information Science and Instrument Engineering, Hangzhou Dianzi University, Hangzhou 310018, China
4. The Affiliated Hospital of Stomatology, School of Medicine, Zhejiang University, Hangzhou 310027, China
Abstract：Dental plaque is one of the main etiologic factors that lead to dental caries and periodontal disease, and the amount of plaque on teeth could be served as reference for the teeth health condition to some extent. Therefore, the detection of dental plaque plays a very important role for maintaining the oral health. However, identification of dental plaque is difficult for both patient and dentist because the tooth and dental plaque often look similar, especially when plaque is present in scanty amounts. Excited by the light source with the wavelength of 405 nm, the auto-fluorescence effect will appear in both dental plaque and dental tissue, but the auto-fluorescence spectrum of dental tissue mainly locates at the wavelength range of blue and green light, while the auto-fluorescence spectrum of dental plaque mainly locates at the wavelength range of red light, and the spectrum intensity caused by the different leveled dental plaque are also diverse. Based on the differences between auto-fluorescence spectra of dental plaque and dental tissues, a potable auto-fluorescence color imaging dental plaque detection system was developed. In the detection system, five surface-mounted LEDs whose central wavelength are all 405 nm are assembled as the excitation source, besides, a long pass optical filter with central wavelength of 520 nm is configured to improve the signal to noise ratio (SNR), and the excited auto-fluorescence was collected and imaged through the imaging lens to the array sensor of a color CCD with a resolution of 640×480. Finally, the amount of dental plaque is analyzed by processing the captured fluorescence images. An experiment was designed to confirm the reliability of the detection system. The anterior teeth auto-fluore scence images of seven recruited subjects with various amounts of dental plaque were captured by the system, after the subjects chewed the disclosing agent for 1 minute and rinsed their mouth with 100 mL distilled water, the Quigley Hein plaque index (PI) modified by Tureksy and disclosing images were both recorded. The plaque percent index (PPI) which is defined as the proportion of the dental plaque area and entire teeth surface area. The statistic analysis shows: The Spearman rank correlation coefficient between the PPI of fluorescence image and the PI is 0.944, and the Pearson correlation coefficient between PPI of fluorescence image and PPI of disclosing image is 0.875. PPI of fluorescence image has an increasing trend with increase in plaque grade and the PPI show statistically significant differences (p<0.01) between different grades. As conclusions, the proposed noninvasive detection system using the optical detecting approach ensures a fairly good accuracy and reliability, besides, the evaluation index of the PPI is more precise compared with the PI. We envision it has the potential to be a homecare practice and convince people of the demand for proper oral hygiene.
基金资助: the Science and Technology Major Projects of Zhejiang Province, China(2013C03043-5)；Chinese National Natural Science Foundation for Young Scholars(61405050)；Natural Science Foundation of Zhejiang (LQ15H140002)
通讯作者:
林 斌
E-mail: wjlin@zju.edu.cn
作者简介: CHEN Chao-jia, (1992—), female, pursuing Master degre at College of Optical Science and Engineering, Zhejiang University e-mail:
chencjiajy@sina.com
引用本文:
陈超佳，劳玮炜，林 斌，陈庆光，朱海华，曹向群，陈 晖. 利用自体荧光成像量化分析牙菌斑[J]. 光谱学与光谱分析, 2017, 37(07): 2311-2316.
CHEN Chao-jia, LAO Wei-wei, LIN Bin, CHEN Qing-guang, ZHU Hai-hua, CAO Xiang-qun, CHEN Hui. Quantification of Dental Plaque Based on Auto-Fluorescence Imaging. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2017, 37(07): 2311-2316.
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