Assessing the Efficacy of Radiotherapy for Brain Metastases in Advanced Non-Small Cell Lung Cancer through Raidomics Prediction

Motivation: Magnetic resonance imaging (MRI) raidomics has shown unique advantages and potential in non-invasive evaluation of therapeutic efficacy in cancer patients. Goal(s): To construct a model that can predict the prognosis of patients with advanced non-small cell lung cancer (NSCLC) brain metastases after radiotherapy. Approach: For patients with advanced NSCLC brain metastasis who underwent pre-treatment MRI examination, stable and reproducible raidomics features were quantitatively extracted and screened. Additionally, artificial intelligence methods were utilized to construct raidomics labels. Results: The potential of the MRI raidomics-based method in predicting the efficacy of radiotherapy for brain metastases from advanced NSCLC was preliminarily confirmed. Impact: The method based on MRI raidomics (T1, T2, DWI, DCE) can not only enhance the precision of radiation therapy efficacy assessment for patients with NSCLC brain metastasis, but also offer clinicians a more scientific basis for treatment decision-making.