AI-Based Imaging Technology May Predict Lung Cancer Outcomes

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Advanced imaging technology that uses AI can potentially predict which patients with lungcancer are likely to experience cancer progression after surgery, according to new data. OncTwitter

Lung adenocarcinoma, a non–small cell lung cancer, is the most common subtype and is characterized by distinct cellular and molecular features. The tumor immune microenvironment influences disease progression and therapy response, the authors write. Understanding the spatial landscape of the microenvironment could provide insight into disease progression, therapeutic vulnerabilities, and biomarkers of response to existing treatments.

High-grade solid tumors had the greatest immune infiltrate , compared with micropapillary , acinar , papillary , and lepidic architectures . Macrophages were the most frequent cell population in the tumor immune microenvironment, representing 12.3% of total cells and 34.1% of immune cells.immunoregulatory T cells in the solid pattern. This relationship was less pronounced in low-grade lepidic and papillary architectures.

Walsh and colleagues are now validating the predictive tool using a lower-plex technology. In addition, they are investigating the immune landscapes of primary and metastatic brain tumors.

 

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