A Novel Digital Score for Abundance of Tumour Infiltrating Lymphocytes Predicts Disease Free Survival in Oral Squamous Cell Carcinoma

Table of Contents

0. Introduction
1. Citation
2. Dataset
3. Model
4. Prerequisites
5. License

Introduction

This repository contains the implementation of TILAb-score as described in the paper.

Citation

The journal paper on this work has been published in Nature Scientific Reports. If you use this code in your research, please cite this work:

@article{shaban2019novel,
  title={A novel Digital Score for Abundance of Tumour Infiltrating Lymphocytes predicts Disease free Survival in oral Squamous cell carcinoma},
  author={Shaban, Muhammad and Khurram, Syed Ali and Fraz, Muhammad Moazam and Alsubaie, Najah and Masood, Iqra and Mushtaq, Sajid and Hassan, Mariam and Loya, Asif and Rajpoot, Nasir M},
  journal={Scientific reports},
  volume={9},
  number={1},
  pages={1--13},
  year={2019},
  publisher={Nature Publishing Group}
}

Dataset

The datset for training should be organized in following hierarchy:

dataset
   -- train
       -- 0_Stroma
       -- 1_Non_ROI
       -- 2_Tumour
       -- 3_Lymphocyte
   -- valid
       -- 0_Stroma
       -- 1_Non_ROI
       -- 2_Tumour
       -- 3_Lymphocyte

Please contact Prof. Nasir Rajpoot ([email protected]) for dataset related queries.

Training

The training.py file in src/ directory will train the model using the dataset in dataset/ directory. You may need to tune the hyperparameters for training on your own dataset to train an optimal model.

Model

The trained model used to produce the results in the paper is available in the models/ directory.

Prerequisites

Following software packages will be required to run this code:

-- Python 3.5
   -- tensorflow-gpu=1.8.0
   -- keras=2.1.6
   -- openslide
   -- opencv_python
   -- scipy
-- R packages
   -- survival
   -- survMisc
   -- gdata
   -- ggplot2
   -- survminer
   -- rms

Authors

See the list of contributors who participated in this project.

License

This project is licensed under the GNU General Public License - see the LICENSE.md file for details.