Machine Learning for Preoperative Prediction of EGFR Mutation in Lung Cancer Brain Metastasis
Motivation: Lung cancer is the most common primary tumor showing brain metastasis (BM). Epidermal growth factor receptor (EGFR) mutations are detected in a significant proportion of lung cancer patients. Goal(s): However, a subset of patients may show discordance in EGFR mutation status between the primary lung tumor and the corresponding BMs, which may affect decision-making in treatments.Approach: We used machine learning (ML) based on pretreatment brain MRI and clinical data for prediction of EGFR mutation status in BMs of lung cancer.Results: Among various ML algorithms, the best predictive performance with accuracy of 89%, precision of 88%, and AUC of 0.97 were obtained.Impact: Machine learning based on pretreatment clinical data and brain MRI provides the potential to predict the EGFR mutation status in brain metastasis of lung cancer, and may affect decision-making in treatments.
Authors
- Hsun-Ping Hsieh (ORCID: https://orcid.org/0000-0001-6924-1337)
- Ching‐Chung Ko (ORCID: https://orcid.org/0000-0003-0721-9606)
- Yang Fan-Chiang
Publication Details
- Journal
- Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition
- Published
- 2024-11-26
- DOI
- https://doi.org/10.58530/2024/3772
- Primary Topic
- Lung Cancer Treatments and Mutations
- Type
- article
- Field-Weighted Citation Impact
- 0.00