# Reflectance confocal microscopy-optical coherence tomography (RCM-OCT) imaging of oral lesions: Toward an affordable device and approach for developing countries > **NIH NIH R01** · SLOAN-KETTERING INST CAN RESEARCH · 2024 · $712,376 ## Abstract High rates of incidence and prevalence of oral cancers occur in 15-20 developing low-and-middle income countries (LMICs) in Asia and Africa. Visual clinical examination followed by biopsy is the standard for diag- nosing oral lesions. But the low and variable specificity of 16-100% of visual examinations results in biopsies of an estimated 37-51% indeterminate lesions (1.4-2.1 million lesions in India, alone) and in benign-to-malig- nant biopsy ratios of 2-24. Patient compliance for biopsy and follow-up care is low (35-63%) in LMIC settings due to pain, fear, time and cost. Our novel solution is noninvasive imaging with a low-cost handheld reflec- tance confocal microscopy (RCM) - optical coherence tomography (OCT) device. Diagnosis and grading of oral dysplasia are based on cellular atypia in the epithelium and underlying architectural changes. RCM imag- ing shows cellular morphology in the entire epithelium to depth of 300 µm. OCT imaging shows epithelial lay- ers and underlying lamina propria to deeper depth of 1 mm. Combined RCM-OCT imaging with a single de- vice will enable simultaneous imaging of cellular atypia and architectural changes in co-located fields of view to guide diagnosis, grade dysplasia, monitor progression to malignancy and assess invasion. Stratification, with a quantitative RCM-OCT scoring algorithm, will guide triage of oral lesions into low-grade dysplasia, which can be monitored or immediately treated with non-surgical therapies, versus high-grade, which may be immediately biopsied, versus carcinoma, which will be surgically excised. Diagnosis may be combined with treatment, all integrated in a single patient visit - a “one stop shop” patient care paradigm. We are an academic-industry team at Memorial Sloan Kettering Cancer Center (New York, NY), Physical Sciences Inc. (Andover, MA), Cali- ber Imaging and Diagnostics (Rochester, NY) and our LMIC collaborators at Tata Memorial Hospital (TMH, Mumbai). For FOA PAR-21-166, innovation is defined to be “likelihood of delivering a new capability to end- users.” Innovations will be in delivering an RCM-OCT device with a new probe for intra-oral imaging and in designing a quantitative diagnostic scoring algorithm to guide diagnosis and treatment, in real-time, at the bed- side. The device will be delivered to TMH and will ultimately cost $25,000, when scaled up and locally manu- factured in LMICs, which will support dissemination of RCM-OCT as a new and affordable imaging capability in LMICs. In preliminary studies, RCM-OCT imaging detected oral lesions and cancers with sensitivity of 100% and specificity of 80%. Our specific aims are (1) to design a handheld RCM-OCT device for imaging in the oral cavity; (2) to prospectively test on 4,422 patients for diagnosis, grading of dysplasia and assessment of invasion in oral lesions and cancers in vivo. Testing will be in LMIC settings, at TMH in Mumbai and in their regional clinic in Varanasi. Affordability, delivery of care in LMICs:... ## Key facts - **NIH application ID:** 10904938 - **Project number:** 5R01CA275789-02 - **Recipient organization:** SLOAN-KETTERING INST CAN RESEARCH - **Principal Investigator:** Pankaj Chaturvedi - **Activity code:** R01 (R01, R21, SBIR, etc.) - **Funding institute:** NIH - **Fiscal year:** 2024 - **Award amount:** $712,376 - **Award type:** 5 - **Project period:** 2023-08-15 → 2028-07-31 ## Primary source NIH RePORTER: https://reporter.nih.gov/project-details/10904938 ## Citation > US National Institutes of Health, RePORTER application 10904938, Reflectance confocal microscopy-optical coherence tomography (RCM-OCT) imaging of oral lesions: Toward an affordable device and approach for developing countries (5R01CA275789-02). Retrieved via AI Analytics 2026-06-05 from https://api.ai-analytics.org/grant/nih/10904938. Licensed CC0. --- *[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*