A novel AI-based score for assessing the prognostic value of intra-epithelial lymphocytes in oral epithelial dysplasia.

Background: Oral epithelial dysplasia (OED) poses a significant clinical challenge due to its potential for malignant transformation and the lack of reliable prognostic markers. Current OED grading systems do not reliably predict transformation and suffer from considerable observer variability. Recent studies have highlighted that peri-epithelial lymphocytes may play an important role in OED malignant transformation, with indication that intra-epithelial lymphocytes (IELs) may also be important.

Methods: We propose a novel artificial intelligence (AI) based IEL score from Haematoxylin and Eosin (H&E) stained Whole Slide Images (WSIs) of OED tissue slides. We determine the prognostic value of our IEL score on a digital dataset of 219 OED WSIs (acquired using three different scanners), compared to pathologist-led clinical grading.

Results: Our IEL scores demonstrated significant prognostic value (C-index = 0.67, p < 0.001) and were shown to improve both the binary/WHO grading systems in multivariate analyses (p < 0.001). Nuclear analyses confirmed the positive association between higher IEL scores, more severe OED and malignant transformation (p < 0.05).

Conclusions: This underscores the potential importance of IELs, and by extension our IEL score, as prognostic indicators in OED. Further validation through prospective multi-centric studies is warranted to confirm the clinical utility of IELs.