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Head and Neck Pathology

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01-12-2024 | Artificial Intelligence | Review

An Update on the Use of Artificial Intelligence in Digital Pathology for Oral Epithelial Dysplasia Research

Authors: Shahd A. Alajaji, Zaid H. Khoury, Maryam Jessri, James J. Sciubba, Ahmed S. Sultan

Published in: Head and Neck Pathology | Issue 1/2024

Abstract

Introduction

Oral epithelial dysplasia (OED) is a precancerous histopathological finding which is considered the most important prognostic indicator for determining the risk of malignant transformation into oral squamous cell carcinoma (OSCC). The gold standard for diagnosis and grading of OED is through histopathological examination, which is subject to inter- and intra-observer variability, impacting accurate diagnosis and prognosis. The aim of this review article is to examine the current advances in digital pathology for artificial intelligence (AI) applications used for OED diagnosis.

Materials and Methods

We included studies that used AI for diagnosis, grading, or prognosis of OED on histopathology images or intraoral clinical images. Studies utilizing imaging modalities other than routine light microscopy (e.g., scanning electron microscopy), or immunohistochemistry-stained histology slides, or immunofluorescence were excluded from the study. Studies not focusing on oral dysplasia grading and diagnosis, e.g., to discriminate OSCC from normal epithelial tissue were also excluded.

Results

A total of 24 studies were included in this review. Nineteen studies utilized deep learning (DL) convolutional neural networks for histopathological OED analysis, and 4 used machine learning (ML) models. Studies were summarized by AI method, main study outcomes, predictive value for malignant transformation, strengths, and limitations.

Conclusion

ML/DL studies for OED grading and prediction of malignant transformation are emerging as promising adjunctive tools in the field of digital pathology. These adjunctive objective tools can ultimately aid the pathologist in more accurate diagnosis and prognosis prediction. However, further supportive studies that focus on generalization, explainable decisions, and prognosis prediction are needed.

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Title: An Update on the Use of Artificial Intelligence in Digital Pathology for Oral Epithelial Dysplasia Research
Authors: Shahd A. Alajaji
Zaid H. Khoury
Maryam Jessri
James J. Sciubba
Ahmed S. Sultan
Publication date: 01-12-2024
Publisher: Springer US
Keywords: Artificial Intelligence
Pathology
Published in: Head and Neck Pathology / Issue 1/2024
Electronic ISSN: 1936-0568
DOI: https://doi.org/10.1007/s12105-024-01643-4

Keynote webinar | Spotlight on medication adherence

Springer Medicine

An Update on the Use of Artificial Intelligence in Digital Pathology for Oral Epithelial Dysplasia Research

Abstract

Introduction

Materials and Methods

Results

Conclusion

Keynote webinar | Spotlight on medication adherence

Springer Medicine

Abstract

Introduction

Materials and Methods

Results

Conclusion

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