AI-guided Prognostication and Cranial Radiotherapy Optimization in EGFR-TKI-treated Non-small Cell Lung Cancer Patients With Baseline Brain Metastases
Artificial Intelligence-guided Prognostication and Cranial Radiotherapy Optimization in First-line Third-generation EGFR-TKI-treated EGFR-mutant Non-small Cell Lung Cancer With Baseline Brain Metastases: a Multicenter, Observational Study
Fudan University
800 participants
Sep 30, 2024
OBSERVATIONAL
Conditions
Summary
The goal of this observational study is to extract the imaging features of brain lesions and primary lung lesions in NSCLC patients with brain metastases by deep learning, as well as common clinicopathological parameters, which are used to construct a multimode model that can accurately predict the treatment efficacy and survival of the third-generation EGFR-TKI treatment, and to use the model to assist in screening high-risk populations suitable for upfront cranial radiotherapy. Participants receiving third-generation EGFR-TKI treatment will be enrolled in our study and we will collect their regular contrast-enhanced chest CT and contrast-enhanced brain MRI for model construction.
Eligibility
Plain Language Summary
Simplified for easier understanding
This summary was AI-generated to explain the trial in plain language. It is not medical advice. Always discuss eligibility with your doctor before enrolling in a clinical trial.
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Interventions
EGFR-mutated NSCLC patients with brain metastases who met the inclusion and exclusion criteria, would receive first-line third-generation EGFR-TKI treatment (monotherapy or combined with upfront cranial radiotherapy)
Locations(1)
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NCT06604689