Breast Cancer Segmentation and Scoring in H&E


Logo for Breast Cancer Segmentation and Scoring in H&E

About

Image Version:
b069eac0-f3a5-4567-89ea-3b2013f9b109
Last updated:
Aug. 16, 2022, 6:49 p.m.

Interfaces

This algorithm implements all of the following input-output combinations:

Inputs Outputs
1
  • Generic Medical Image (Image)
  • TIL Score (Float)
  • Breast Cancer Segmentation for TILs (Segmentation)
  • Lymphocyte Tumor Ratio (Float)
  • Inflamed Tumor Ratio (Float)
  • Challenge Performance

    Date Challenge Phase Rank
    May 2, 2022 tiger Segmentation and Detection (Experimental) 287

    Model Facts

    Summary

    Tumor infiltrating lymphocytes have been shown to have predictive value for survival and chemotherapy response prediction in breast cancer. We developed a fully automated deep-learning based algorithm to segment breast H&E tissue into the classes Tumor, Normal, Fat, Stroma, Necrosis and Lymphocytes and compute three lymphocyte based biomarkers including the (computational) tumor infiltrating lymphocytes score. Tumor infiltrating lymphocytes have been shown to have predictive value for survival and chemotherapy response prediction in breast cancer. We developed a fully automated deep-learning based algorithm to segment breast H&E tissue into the classes Tumor, Normal, Fat, Stroma, Necrosis and Lymphocytes and compute three lymphocyte based biomarkers including the (computational) tumor infiltrating lymphocytes score.

    Citation: Aswolinskiy, Witali, et al. "Predicting pathological complete response to neoadjuvant chemotherapy in breast cancer from routine diagnostic histopathology biopsies." medRxiv (2022)

    Mechanism

    The algorithm has three steps:

    1. Preprocessing: Tissue is separated from background using a convolutional neural network
    2. Segmentation: The tissue is segmented into the classes Tumor, Normal, Fat, Stroma, Necrosis and Lymphocytes using a U-Net.
    3. From the segmentation, three biomarkers are computed: the computational tumor infiltrating lymphocytes score (TILs), inflamed tumor ratio (ITR) measuring the proportion of tumor within 80 microns of lymphocytes and the lymphocyte to tumor ratio (LTR).

    Validation and Performance

    Uses and Directions

    This algorithm was developed for research purposes only. The terms of usage for Grand Challenge apply to the uploaded slides.

    Warnings

    Common Error Messages

    Information on this algorithm has been provided by the Algorithm Editors, following the Model Facts labels guidelines from Sendak, M.P., Gao, M., Brajer, N. et al. Presenting machine learning model information to clinical end users with model facts labels. npj Digit. Med. 3, 41 (2020). 10.1038/s41746-020-0253-3