ArticleScientific reports2018
Computationally-Guided Development of a Stromal Inflammation Histologic Biomarker in Lung Squamous Cell Carcinoma.
Article in Scientific reports, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed, 15 citations in OpenAlex.
- Application of artificial intelligence in lung cancer diagnosis, therapy, and prognosis.BMC medical genomics · 2026Review
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- Clinician Perspectives on Digital and Computational Pathology: Clinical Benefits, Concerns, and Willingness to Adopt.Diagnostics (Basel, Switzerland) · 2025Article
- Comparative performance of PD-L1 scoring by pathologists and AI algorithms.Histopathology · 2025Article
- Computational analysis of whole slide images predicts PD-L1 expression and progression-free survival in immunotherapy-treated non-small cell lung cancer patients.Journal of translational medicine · 2025Article
- Prediction of Ovarian Cancer Response to Therapy Based on Deep Learning Analysis of Histopathology Images.Cancers · 2023Article
- An integrative web-based software tool for multi-dimensional pathology whole-slide image analytics.Physics in medicine and biology · 2022Article
- Prognostic Value of Selected Histologic Features for Lung Squamous Cell Carcinoma.Exploratory research and hypothesis in medicine · 2022Article
- The Role of Pathology-Based Methods in Qualitative and Quantitative Approaches to Cancer Immunotherapy.Cancers · 2022Review
- The state of the art for artificial intelligence in lung digital pathology.The Journal of pathology · 2022Review
- Biopsy-free in vivo virtual histology of skin using deep learning.Light, science & applications · 2021Article
- IASLC Multidisciplinary Recommendations for Pathologic Assessment of Lung Cancer Resection Specimens After Neoadjuvant Therapy.Journal of thoracic oncology : official publication of the International Association for the Study of Lung Cancer · 2020Review
- Deep Learning Based on Standard H&E Images of Primary Melanoma Tumors Identifies Patients at Risk for Visceral Recurrence and Death.Clinical cancer research : an official journal of the American Association for Cancer Research · 2020Article
Corrections and comments
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Authors and funding
7 authors at 3 institutions in 3 countries.
Funding
Abstract
The goal of this study is to use computational pathology to help guide the development of human-based prognostic H&E biomarker(s) suitable for research and potential clinical use in lung squamous cell carcinoma (SCC). We started with high-throughput computational image analysis with tissue microarrays (TMAs) to screen for histologic features associated with patient overall survival, and found that features related to stromal inflammation were the most strongly prognostic. Based on this, we developed an H&E stromal inflammation (SI) score. The prognostic value of the SI score was validated by two blinded human observers on two large cohorts from a single institution. The SI score was found to be reproducible on TMAs (Spearman rho = 0.88 between the two observers), and highly prognostic (e.g. hazard ratio = 0.32; 95% confidence interval: 0.19-0.54; p-value = 2.5 × 10
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