An MRI-based nomogram predicts brain metastasis response to targeted therapy in lung cancer patients: A multi-center study

Motivation: To determine an effective individualized treatment decision for lung cancer patients with brain metastasis (BrM) to receive targeted therapy. Goal(s): we developed an MRI-based nomogram that can predict the response of lung cancer BrM to targeted therapy using multi-center data. Approach: Clinical predictors, radiomics and deep learning features extracted from BrM baseline MR images were incorporated to establish the nomogram using the LASSO logistics coefficients. Results: The nomogram can accurately predict the 6-month and 12-month responses of BrM to targeted therapy across the training cohort, internal validation cohort, and external test set, outperforming all other models. Impact: The MRI-based nomogram can be used as a pretreatment and personalized tool to predict response to targeted therapy in lung cancer patients with BrMs and thus assist in optimizing treatment for lung cancer patients who suffer from BrMs.