Mobile oral cancer screening system for low-resource settings

适用于资源匮乏环境的移动口腔癌筛查系统

• 批准号: 10323692
• 负责人: PETRA E WILDER-SMITH
• 金额: $ 95.29万
• 依托单位: LIGHT RESEARCH, INC.
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-09-13 至 2023-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10323692
• 关键词: Address; Adopted; Americas; Arizona; Biopsy; Cancer Center; Cancer Detection; Cancer Patient; Caring; Cellular Phone; Classification; Clinical; Data; Data Set; Decision Making; Detection; Devices; Diagnosis; Diagnostic; Disease; Disease Progression; Dysplasia; Early Diagnosis; Electronics; Europe; Goals; Health; Healthcare; Histopathology; Image; Imaging Device; Imaging Techniques; India; Infrastructure; Internet; Learning; Lesion; Licensing; Light; Lighting; Location; Malignant - descriptor; Malignant Neoplasms; Mechanics; Methods; Modality; Morbidity - disease rate; Oral; Oral cavity; Oropharyngeal Squamous Cell Carcinoma; Participant; Patient Triage; Patients; Performance; Phase; Prevention; Process; Production; Quality of life; Research; Resources; Schedule; Screening for Oral Cancer; Solid; South Asian; Specialist; Survival Rate; System; Techniques; Technology; Telephone; Time; Treatment outcome; Triage; Universities; base; cancer diagnosis; cancer prevention; classification algorithm; clinical practice; cloud based; community setting; cost; deep learning; deep learning algorithm; design; flexibility; handheld mobile device; high resolution imaging; high risk population; imaging modality; imaging probe; imaging system; impression; improved; innovation; intraoral probe; low and middle-income countries; malignant mouth neoplasm; mobile application; mortality; multimodality; neural network architecture; optical imaging; oral care; oral lesion; portability; prototype; recruit; remote diagnosis; rural area; screening; social; southeast Asian; standard of care; tongue root

Two-thirds of oral and oropharyngeal squamous cell carcinoma (OSCC) occur in low- and middle-income countries (LMICs), the 5-year survival rate is only 10-40. Enough is already known about the disease and its prevention for action to be taken. The poor survival rate in LMICs is mainly due to late diagnosis. Therefore, it is imperative to detect precursor and malignant lesions early and expeditiously. To meet the need for technologies that enable oral cancer screening and diagnosis in low resource settings (LRS), Light Research Inc (LRI) will develop, validate, and commercialize a low-cost smartphone-based imaging system that provides remote specialist access and triage decision-making guidance tailored to non-specialist use in LRS. To achieve the project goal, LRI will license technologies from University of Arizona (UA), and partner with UA and Mazumdar-Shaw Cancer Center (MSCC) (Bangalore, India) to develop and validate a multimodal mobile oral imaging system for oral cancer detection and diagnosis in LRS. In the past few years, the project team has developed and evaluated a dual-mode (polarized white light imaging [pWLI]) and autofluorescence imaging [AFI])) mobile imaging device that specifically addresses critical barriers in LRS to improve oral cancer screening. To address one of the key hurdles in adopting optical imaging techniques for oral cancer screening in LRS, the team has also developed and evaluated cloud-based and mobile-based deep learning image classification methods for guiding patient triage. Since the key techniques proposed in this mobile imaging system have been successfully evaluated for oral cancer screening with 3,000 high-risk population in LRS, the potential of successfully transitioning it to the low- resource regions for accurate, objective and location-resolved detection of oral cancer is very high. The project objective will be achieved through three Aims: (1) to optimize a mobile intraoral imaging system for LRS, (2) to optimize deep learning-based dual-modality image classification methods, and (3) to validate the clinical usefulness of the mobile oral imaging system for oral cancer screening and triage in LSR. Successful completion of this project will lead to a mobile oral imaging system with deep learning image classification method that delivers urgently-needed capabilities to the end users in LRS. LRI will partner with Jana Care Inc (New Delhi, India) for low-cost production, with Ergo Healthcare (Mumbai, India) for product distribution in south and southeast Asian, and with DentalEZ Group for product distribution in America and Europe. The use of this mobile-based screening approach for early detection and triage of oral cancers will eventually improve oral cancer detection rates, treatment outcomes, and quality of life of patients in LRS.

三分之二的口腔和口咽鳞状细胞癌（OSCC）发生在低收入和中等收入