# Deep Learning Image Analysis Algorithms to Improve Oral Cancer Risk Assessment for Oral Potentially Malignant Disorders

> **NIH NIH R01** · YALE UNIVERSITY · 2024 · $670,324

## Abstract

Abstract
Oral potentially malignant disorders (OPMD) are a group of mucosal diseases in the oral cavity with a risk of
progressing to oral squamous cell carcinoma. Risk assessment is traditionally done through a combination of
clinical and histologic evaluation. Leukoplakia is a common type of OPMD that is given a histologic grading
score that is supposed to be related to its risk of progression. However, there is tremendous intra- and inter-
observer heterogeneity in dysplasia grading, leading to variability and uncertainty in risk assessment and
treatment planning. This also hinders the ability to study the biology of these lesions. We propose to use whole
slide imaging on routine hematoxylin and eosin (H&E) stained sections in combination with deep learning
methods to build a consistent risk scoring system for OPMD. Our methods will identify cell, nucleus, and tissue
architectural features relevant to risk of progression in OPMD. These features will be tested in a large
retrospective case-control study and then validated prospectively. We will also explore combining them with
genomic and immune biomarkers in order to improve the prognostic power and explore the biolo gy of
progression in OPMD. We hope that these efforts will improve and standardize risk assessment for OPMD.
This could lead to improved treatment and prevention options by enabling risk stratification and allowing future
clinical trials be conducted in a more uniform patient cohort. Similarly, it could improve our understanding for
the biology of OPMD and the process of progression to cancer.

## Key facts

- **NIH application ID:** 10833217
- **Project number:** 5R01DE030656-04
- **Recipient organization:** YALE UNIVERSITY
- **Principal Investigator:** Curtis Pickering
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $670,324
- **Award type:** 5
- **Project period:** 2023-05-01 → 2026-04-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10833217

## Citation

> US National Institutes of Health, RePORTER application 10833217, Deep Learning Image Analysis Algorithms to Improve Oral Cancer Risk Assessment for Oral Potentially Malignant Disorders (5R01DE030656-04). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10833217. Licensed CC0.

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