PFI:BIC - Smart Laser-Based Imaging and Optical Spectroscopy System: optical quantification of bacterial load, oral health surveillance, and caries prediction.

龋齿和牙龈疾病在低收入和农村社区尤其普遍和严重，这些社区往往无法获得方便和负担得起的牙科保健。这些社区的成员更有可能因需要手术治疗的晚期口腔疾病而前往医院急诊科；这增加了家庭的牙科护理费用，增加了医院资源的负担。龋齿是美国6-19岁儿童和青少年中最常见的慢性疾病，尽管它是一种可预防的疾病。2010年，未经治疗的蛀牙或龋齿影响了全球24亿人。幼儿期龋齿会导致疼痛、感染和不适。在成年人中，慢性口腔感染可能会增加早产和糖尿病、动脉粥样硬化等疾病的风险。该项目将开发一种手持电动牙刷式设备，具有用户友好的界面，可在家中使用，也可由学校或农村诊所的社区卫生工作者使用。这种魔杖使用安全的光学扫描方法，将数据和图像发送给牙医，牙医将能够监测牙科治疗的效果。通过分析该设备收集的数据和图像，可以发现菌斑和细菌存在的位置，从而提供一种预测和预防疾病的方法。魔杖将能够提示用户解决问题的地方。该系统将远程用户与牙科提供者连接起来，有可能改善口腔疾病的预防和治疗，并改善那些无法方便地获得定期亲自牙科护理的人的生活质量。为了实现这一愿景，该项目将开发一种智能系统，为人们提供筛查、监测和预测，以改善口腔健康和预防疾病。一种成熟的基于激光成像的荧光光谱分析技术将被用于研究口腔生物膜和牙齿脱矿的复杂性。细菌测量使用手持式单波长光学扫描探针进行，通过反射和荧光对比形成图像，并可选择采用激光诱导荧光光谱诊断牙釉质脱矿。为提供智能接口，对光学信息进行分析以识别趋势，这是牙科领域的一种新模式。通过对牙菌斑沉积物的荧光信号进行分析，使用者可以与临床医生合作，监测口腔健康的变化和治疗的有效性。研究团队将使用迭代过程来开发、设计、评估和改进工具。该工具将在三种情况下进行测试：(1)针对未经培训的“患者”（例如，针对儿童的家长、针对小学生的学校护士、针对幼儿的儿科医生或针对患者的偏远农村诊所工作人员）的训练有素的外行用户的牙菌斑和龋齿筛查程序；(2)针对训练有素的外行用户的龋病监测程序，该程序与可以指导使用该工具的牙医进行电子连接；(3)龋齿预测程序，初步面向临床用户。该项目汇集了华盛顿州西雅图华盛顿大学（UW）的多学科团队，具有以人为本的设计，工程，传感和机器学习，口腔生物学和牙科方面的专业知识：Eric J. Seibel （PI首席研究员），机械工程；肖恩·曼森（共同负责人），以人为中心的设计与工程；Shwetak Patel，计算机科学与工程；郑旭，儿科牙科学院DDS；杰夫·麦克莱恩，牙科学院牙周病专业。主要的行业合作伙伴Water Pik， Inc (Fort Collins, CO .)，为消费者带来了建造、营销和分销先进牙科设备的经验和知识：Deborah Lyle，专业和临床事务总监，Jay McCulloch，全球营销副总裁，口腔护理。更广泛的合作伙伴是UW CoMotion（西雅图，华盛顿州），技术转让合作伙伴；QualComm Tech, Inc. (San Diego， CA)，无线技术领导者；Open Photonics, Inc. (Winter Park， FL)，商业合作伙伴；以及阿拉斯加土著部落健康联盟（安克雷奇，AK），这是一个非营利性社区合作伙伴，有兴趣开发一种光学诊断设备，供其农村受益者使用。该奖项部分由计算机和信息科学与工程理事会（CISE）、计算机和网络系统司（CNS）的资金支持。

Caries and gum disease are especially prevalent and severe in low-income and rural communities, which often lack access to convenient and affordable dental care. Members of these communities are more likely to visit hospital emergency departments with advanced stages of oral disease that need surgical treatment; this increases the cost of dental care for families and burdens hospital resources. Tooth decay is the most common chronic disease in American children and adolescents age 6-19 despite being a preventable disease. In 2010, untreated tooth decay, or caries, affected 2.4 billion people worldwide. Early childhood caries leads to pain, infection, and discomfort. And in adults, chronic oral infections may increase the risk of preterm birth and diseases like diabetes and atherosclerosis (hardening of the arteries). This project will develop a hand-held electric-toothbrush-like device with a user-friendly interface that can be used in the home or by community health workers in schools or rural clinics. The wand, which uses a safe optical scanning method, will send data and images to a dentist, who will be able to monitor how well dental treatments are working. The data and images collected by the device can be analyzed to discover where plaque and bacteria are present, providing a way to predict, and then prevent, disease. The wand will be able to prompt the user to address problem areas. This system, which will connect remote users to a dental provider, has the potential to improve the prevention and treatment of oral disease and the quality of life for people who do not have convenient access to regular, in-person dental care. To enable this vision, this project will develop a smart system that offers screening, surveillance, and prediction for people to improve their oral health and prevent disease. A mature technology of laser-based imaging that is spatially registered with fluorescence spectral analysis will be used to study the complexities of the oral biofilm and dental demineralization. The bacterial measurement is performed with a hand-held single wavelength optical scanning probe that forms images from both reflectance and fluorescence contrast, with the option of taking laser-induced fluorescence spectra for diagnosis of enamel demineralization. To provide a smart interface, the optical information will be analyzed to identify trends, a new modality for the dental field. With analyses of the fluorescence signal from the plaque deposits displayed as a trend, the user, in collaboration with clinician, can monitor variations in oral health and the effectiveness of treatments. The research team will use an iterative process to develop, design, evaluate, and refine the tool. The tool will be tested for three scenarios: (1) a plaque- and caries-screening program for a trained lay user on an untrained "patient" (e.g., parent for a child, school nurse for pupils, pediatrician for young children, or staff at a remote rural clinic for patients); (2) a caries surveillance program for trained lay users electronically connected to a dentist who can guide the use of the tool; and (3) a caries prediction program, initially for clinical users. This project brings together a multidisciplinary team from the University of Washington (UW), in Seattle, Washington, with expertise in human centered design, engineering, sensing and machine learning, oral biology, and dentistry: Eric J. Seibel (Principal Investigator, PI), Mechanical Engineering; Sean Munson (co-PI), Human Centered Design & Engineering; Shwetak Patel, Computer Science & Engineering; Zheng Xu, DDS, School of Dentistry, Pediatric Dentistry; Jeff McLean, School of Dentistry, Periodontics. Lead industry partner Water Pik, Inc. (Fort Collins, CO), brings experience and knowledge about building, marketing, and distributing advanced dental devices to consumers: Deborah Lyle, Director of Professional & Clinical Affairs, and Jay McCulloch, Vice President, Global Marketing, Oral Care. Broader context partners are UW CoMotion (Seattle, WA), a technology transfer partner; QualComm Tech, Inc. (San Diego, CA), a wireless technology leader; Open Photonics, Inc. (Winter Park, FL), a business partner; and the Alaska Native Tribal Health Consortium (Anchorage, AK), a non-profit community partner interested in the development of an optical diagnosis device for use with its rural beneficiaries.This award is partially supported by funds from the Directorate for Computer and Information Science and Engineering (CISE), Division of Computer and Network Systems (CNS).