Extension of a Biology-First Morphometric Framework to Field Cancerization in Breast Cancer: Preliminary Analysis on Routine H&E-Stained Ductal Tissue

This proof-of-concept study extends a transparent, biology-first morphometric framework—originally developed for colorectal cancer—to breast cancer. The approach uses only routine hematoxylin and eosin (H&E)-stained slides and open-source tools (Fiji/ImageJ) to extract four interpretable quantitative features: cell density (D), variance of nearest-neighbor intercellular distances (σ²), local hematoxylin–eosin color correlation (C), and ductal architectural order (A, adapted from crypt order to ductal/lobular alignment). Feasibility and robustness are demonstrated through controlled synthetic perturbations. Preliminary application to publicly available datasets (BreakHis and TCGA-BRCA) reveals systematic differences across normal ductal epithelium, cancer-associated stroma, and invasive ductal carcinoma epithelium. These trends—particularly intermediate alterations in stroma—are consistent with known field cancerization effects in breast cancer, including desmoplastic remodeling and ductal irregularity. By prioritizing biological plausibility, interpretability, and low-cost accessibility, this extension offers a reproducible complement to complex deep learning methods, with potential as an adjunct tool for early risk stratification in breast pathology. Prospective validation in clinical cohorts is warranted to assess diagnostic utility.

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-12-21
DOI
https://doi.org/10.5281/zenodo.18011120
Primary Topic
AI in cancer detection
Type
article
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article

Extension of a Biology-First Morphometric Framework to Field Cancerization in Breast Cancer: Preliminary Analysis on Routine H&E-Stained Ductal Tissue

saadat samadidinani
Zenodo (CERN European Organization for Nuclear Research)
AI in cancer detection
article

Extension of a Biology-First Morphometric Framework to Field Cancerization in Breast Cancer: Preliminary Analysis on Routine H&E-Stained Ductal Tissue

saadat samadidinani
article en

Abstract

This proof-of-concept study extends a transparent, biology-first morphometric framework—originally developed for colorectal cancer—to breast cancer. The approach uses only routine hematoxylin and eosin (H&E)-stained slides and open-source tools (Fiji/ImageJ) to extract four interpretable quantitative features: cell density (D), variance of nearest-neighbor intercellular distances (σ²), local hematoxylin–eosin color correlation (C), and ductal architectural order (A, adapted from crypt order to ductal/lobular alignment). Feasibility and robustness are demonstrated through controlled synthetic perturbations. Preliminary application to publicly available datasets (BreakHis and TCGA-BRCA) reveals systematic differences across normal ductal epithelium, cancer-associated stroma, and invasive ductal carcinoma epithelium. These trends—particularly intermediate alterations in stroma—are consistent with known field cancerization effects in breast cancer, including desmoplastic remodeling and ductal irregularity. By prioritizing biological plausibility, interpretability, and low-cost accessibility, this extension offers a reproducible complement to complex deep learning methods, with potential as an adjunct tool for early risk stratification in breast pathology. Prospective validation in clinical cohorts is warranted to assess diagnostic utility.

Zenodo (CERN European Organization for Nuclear Research)
Openalex Percentile: Top 19%
AI in cancer detection
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Extension of a Biology-First Morphometric Framework to Field Cancerization in Breast Cancer: Preliminary Analysis on Routine H&E-Stained Ductal Tissue — saadat samadidinani · Zenodo (CERN European Organization for Nuclear Research) (2025) | TGRS Research Map | TGRS