ArticleComputational and structural biotechnology journal2022
Artificial intelligence for quantifying Crohn's-like lymphoid reaction and tumor-infiltrating lymphocytes in colorectal cancer.
Article in Computational and structural biotechnology journal, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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2 citing papers in PubMed.
- Development and evaluation of the mrTE scoring system for MRI-detected tumor deposits and extramural venous invasion in rectal cancer.Abdominal radiology (New York) · 2025Article
- Recent Advancements in Deep Learning Using Whole Slide Imaging for Cancer Prognosis.Bioengineering (Basel, Switzerland) · 2023Review
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12 authors.
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Abstract
Crohn's-like lymphoid reaction (CLR) and tumor-infiltrating lymphocytes (TILs) are crucial for the host antitumor immune response. We proposed an artificial intelligence (AI)-based model to quantify the density of TILs and CLR in immunohistochemical (IHC)-stained whole-slide images (WSIs) and further constructed the CLR-I (immune) score, a tissue level- and cell level-based immune factor, to predict the overall survival (OS) of patients with colorectal cancer (CRC). The TILs score and CLR score were obtained according to the related density. And the CLR-I score was calculated by summing two scores. The development (Hospital 1, N = 370) and validation (Hospital 2 & 3, N = 144) cohorts were used to evaluate the prognostic value of the CLR-I score. The C-index and integrated area under the curve were used to assess the discrimination ability. A higher CLR-I score was associated with a better prognosis, which was identified by multivariable analysis in the development (hazard ratio for score 3 vs score 0 = 0.22, 95% confidence interval 0.12-0.40, P < 0.001) and validation cohort (0.21, 0.05-0.78, P = 0.020). The AI-based CLR-I score outperforms the single predictor in predicting OS which is objective and more prone to be deployed in clinical practice.
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