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Proposal of a scoring system for predicting pathological risk based on a semiautomated analysis of whole slide images in oral squamous cell carcinoma.


ABSTRACT:

Background

The study aimed to evaluate the risk factors based on pathological findings comprehensively in oral squamous cell carcinoma (OSCC) using image analysis.

Methods

Scanned images of hematoxylin and eosin-, pan-cytokeratin-, CD3-, and CD8-stained slides of OSCC cases from 256 patients were analyzed, and six variables were obtained including the tumor-stroma ratio, tumor budding per tumor bed area, and tumor infiltrating lymphocytes-associated variables. We determined the "score" of all cases based on the variables, and all cases were classified into low-, intermediate-, and high-risk groups.

Results

A significant difference in prognosis was confirmed between the risk groups (p < 0.001), and even when evaluated within different tumor-node-metastasis (TNM) stages, the high-risk groups were associated with poor survival.

Conclusions

We report our work on a possible descriptive model that can predict prognosis based on pathological and imaging findings regardless of the TNM stage.

SUBMITTER: Sung YE 

PROVIDER: S-EPMC8247849 | biostudies-literature |

REPOSITORIES: biostudies-literature

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