Enhancing Prognosis Prediction for Lung Cancer Patients with Brain Metastasis by Combining Brain MR and Lung CT Radiomic Features

Motivation: Control of metastatic and primary tumors has been identified as prognostic factors for lung cancer patients with brain metastasis. However, prognosis prediction by combining imaging features of metastatic and primary tumors was less explored. Goal(s): This study investigated the prediction efficacy based on image traits of brain metastasis and primary lung cancer. Approach: The radiomic features separately extracted from brain MRI and chest CT images were merged to build the survival prediction models. Results: The proposed prediction model showed superior performance compared to the models based on a single modality in lung cancer with brain metastasis. Impact: This study suggested that survival prediction can be enhanced by combining features of brain metastasis MRI and lung cancer CT. Imaging characteristics of both primary and secondary (metastatic) tumors are valuable for prognostic prediction in lung cancer with brain metastasis.