MOSAIC: Explainable AI for Reproducible Histologic Grading and Prognostic Stratification in Breast Cancer

Nottingham histologic grading is essential for breast cancer prognostication but suffers from inter-observer variability in assessing mitotic activity, nuclear pleomorphism, and tubule formation. We developed MOSAIC (Mammary Oncology Spatial Analysis and Intelligent Classification), an explainable AI framework designed to perform component-wise grading by independently modeling these three histologic features. Model outputs were calibrated using a two-phase pathology study to establish clinically reproducible scoring thresholds and were subsequently evaluated across public datasets and multi-institutional Indian cohorts. MOSAIC demonstrated robust performance, with AI-derived grades providing independent prognostic information (HR >= 1.8 in two datasets, p = < 0.001) and improved survival stratification compared to traditional methods. In pathologist calibration studies, AI-assisted scoring significantly reduced variability, specifically achieving near-perfect agreement in mitotic scoring with a weighted {kappa} up to 0.98. Accuracy and Cohens kappa ({kappa}) analysis further characterized the models technical performance across components: Tubule formation showed the highest agreement (Accuracy >= 0.6607, {kappa} = 0.549), followed by overall Grade (Accuracy = 0.5637, {kappa} = 0.539) and Mitotic activity (Accuracy = 0.4985, {kappa} = 0.4), while Nuclear pleomorphism proved the most challenging (Accuracy = 0.3303, {kappa} = 0.271). Comparative survival models confirmed that AI-derived grades were more significant predictors of risk than manual pathologist-assigned grades, with the AI model yielding a superior global p-value (5.9 x 10-7) and lower AIC (769.61). These results indicate that MOSAIC enables reproducible, interpretable grading by decomposing assessment into pathology-aligned components. By enhancing consistency while preserving prognostic relevance, this framework supports explainable AI as a viable assistive tool for routine breast cancer pathology.