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Updated: Jun 3, 2025
Lung CT Segmentation to Identify Consolidations and Ground Glass Areas for Quantitative Assesment of SARS-CoV Pneumonia
Published on: December 19, 2020
Investigating lung cancer microenvironment from cell segmentation of pathological image and its application in
Xu Zhang1,2, Zi-Han Zhang3, Yong-Min Liu4
1Department of Thoracic Surgery, The First Affiliated Hospital of Dalian Medical University, Dalian Medical University, Dalian, 116011, China.
Abstract:
Lung cancer, particularly adenocarcinoma, ranks high in morbidity and mortality rates worldwide, with a relatively low five-year survival rate. To achieve precise prognostic assessment and clinical intervention for patients, thereby enhancing their survival prospects, there is an urgent need for more accurate stratification schemes. Currently, the TNM staging system is predominantly used in clinical practice for prognostic evaluation, but its accuracy is constrained by the reliance on physician experience. Although biomarker discovery based on molecular pathology offers a new perspective for prognostic assessment, its dependence on expensive gene panel testing limits its widespread clinical application. Pathological images contain abundant diagnostic information, providing a new avenue for prognostic evaluation. In this study, we employed advanced Hover-Net technology to accurately quantify the abundance of epithelial cells, lymphocytes, macrophages, and neutrophils from pathological images, and delved into the clinical and biological significance of these cellular abundances. Our research findings reveal that, in contrast to patients classified as N0 stage, those belonging to the N1 stage demonstrated a marked elevation in the infiltration of epithelial cells, lymphocytes, macrophages, and neutrophils. Notably, the infiltration patterns of lymphocytes and neutrophils exhibited an inverse relationship with the activation status of numerous pivotal gene pathways, including the HALLMARK_HEME_METABOLISM pathway. Furthermore, our analysis distinguished FABP7 as a prognostic biomarker, exhibiting pronounced differential expression between patients with high and low levels of neutrophil infiltration, indicate that cellular abundance analysis based on pathological images can provide a more accurate and cost-effective prognostic evaluation, offering new strategies for the clinical management of lung adenocarcinoma.
