  The quantification of tumor-infiltrating lymphocytes (TILs) has been shown to
be an independent predictor for prognosis of breast cancer patients. Typically,
pathologists give an estimate of the proportion of the stromal region that
contains TILs to obtain a TILs score. The Tumor InfiltratinG lymphocytes in
breast cancER (TiGER) challenge, aims to assess the prognostic significance of
computer-generated TILs scores for predicting survival as part of a Cox
proportional hazards model. For this challenge, as the TIAger team, we have
developed an algorithm to first segment tumor vs. stroma, before localising the
tumor bulk region for TILs detection. Finally, we use these outputs to generate
a TILs score for each case. On preliminary testing, our approach achieved a
tumor-stroma weighted Dice score of 0.791 and a FROC score of 0.572 for
lymphocytic detection. For predicting survival, our model achieved a C-index of
0.719. These results achieved first place across the preliminary testing
leaderboards of the TiGER challenge.
