Using Artificial Intelligence to Predict Treatment Success and Guide Brain Radiotherapy in Adults with EGFR-Mutant Advanced Non-small Cell Lung Cancer and Brain Metastases Receiving Third-Generation EGFR-TKI Therapy

What this Trial Is About

Researchers are studying advanced non-small cell lung cancer NSCLC patients who have brain metastases and carry specific EGFR mutations. The study aims to use deep learning to analyze imaging features from brain and lung lesions, along with clinical data, to build a model that predicts how well patients respond to third-generation EGFR-TKI treatments and their survival. This model will also help identify patients who may benefit from early cranial radiotherapy. Participants in this observational study are receiving first-line treatment with third-generation EGFR-TKIs such as Almonertinib, Furmonertinib, or Osimertinib, either alone or combined with upfront cranial radiotherapy. The study involves collecting regular contrast-enhanced chest CT scans and brain MRI images to construct and validate the AI-based prediction model using both retrospective and prospective patient data. During the study, researchers will monitor patient outcomes including progression-free survival, intracranial response rates, and overall survival over one year. Participants will undergo standard imaging and clinical follow-up assessments, and their data will help evaluate the models ability to guide treatment decisions. The total study duration includes follow-up periods to assess treatment efficacy and safety.

AI-guided Prognostication and Cranial Radiotherapy Optimization in EGFR-TKI-treated Non-small Cell Lung Cancer Patients With Baseline Brain Metastases