Abstract #0858

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

Jyun-Ru Chen¹, Cheng-Chia Lee^2,3, Huai-Che Yang^2,3, Wen-Yuh Chung⁴, Hsiu-Mei Wu^3,5, Wan-You Guo^3,5, and Chia-Feng Lu¹

¹Department of Biomedical Imaging and Radiological Sciences, National Yang Ming Chiao Tung University, Taipei, Taiwan, ²Department of Neurosurgery, Neurological Institute, Taipei Veterans General Hospital, Taipei, Taiwan, ³School of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan, ⁴Department of Neurosurgery, Kaohsiung Veterans General Hospital, Kaohsiung, Taiwan, ⁵Department of Radiology, Taipei Veterans General Hospital, Taipei, Taiwan

Synopsis

Keywords: Diagnosis/Prediction, Radiomics, Brain metastasis

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.

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