Predictive Modeling of Lung Cancer Subtype with Integration of Clinical and Thoracic Imaging Features to Guide Early Brain Metastasis Management

<title>Abstract</title> <p> <bold>Purpose:</bold> Optimal treatment for synchronous brain metastases at lung cancer diagnosis depends on subtype, but histologic/molecular profiling is often delayed. We developed machine-learning models using clinical and imaging data to classify lung cancer into three subtypes with distinct brain metastasis treatment implications: small cell lung cancer (SCLC), EGFR-mutated non-small cell lung cancer (NSCLC), and EGFR–wild-type NSCLC. <bold>Methods:</bold> We retrospectively identified patients with metastatic lung cancer diagnosed from 2016–2025 at a single institution. Patients without brain metastases at diagnosis formed the training cohort; those with synchronous brain metastases formed the validation cohort. Clinical variables and thoracic imaging features from diagnostic chest CT reports were used to train LASSO logistic regression and random forest models, evaluated via AUC and standard diagnostic metrics. Feature contributions were assessed using logistic regression coefficients and random forest permutation importance. <bold>Results:</bold> Of 305 patients, 182 were used for training and 123 for validation. Logistic regression achieved AUCs of 0.900, 0.797, and 0.799 for EGFR-mutated NSCLC, SCLC, and EGFR–wild-type NSCLC, respectively; random forest achieved 0.914, 0.766, and 0.808. Adding imaging features to clinical variables improved prediction for EGFR-mutated NSCLC and SCLC. Contributory imaging features included fibrosis, emphysema, mediastinal lymphadenopathy, pleural attachment, and vessel encasement, among others. Three-way prediction showed highest positive predictive value for EGFR-mutated NSCLC and high negative predictive value for SCLC. <bold>Conclusion:</bold> Combined clinical and chest imaging features can help predict lung cancer subtype, supporting early multidisciplinary discussions for patients with synchronous brain metastases. </p>