Multimodal radiomic analysis to determine high-Consistency prognostic phenotypes associated with epidermal growth factor receptor mutations in non-small cell lung cancer brain metastases.

INTRODUCTION

Limited linkage between epidermal growth factor receptor (EGFR) mutations and recurrence-predictive radiomic signatures restricts the application of radiomics-guided therapy for brain metastases (BMs) from non-small-cell lung cancer (NSCLC). This study aimed to establish an EGFR-associated radiomic signature (EGFR-RS), compare its consistency with that of conventional whole radiomic features-based radiomic signature (WF-RS), and evaluate its efficacy in predicting local recurrence for BMs treated with radiosurgery.

METHODS

Brain magnetic resonance (MR) and computed tomography (CT) images of NSCLC patients with BMs undergoing radiosurgery between 2008 and 2020 were examined. The least absolute shrinkage and selection operator was utilized to select features and develop signatures. Discriminative abilities were assessed using the area under the curve, while univariable and multivariable competing risk regression determined predictors and established a clinical-radiomic model.

RESULTS

In total, 318 patients with 759 BMs were enrolled. The EGFR-RS, incorporating 11 MR and six CT EGFR-associated prognostic radiomic features, displayed better consistency, and superior predictive performance than the WF-RS, with C-indices of 0.746 (95 %CI 0.616, 0.876) in the test cohort, compared with 0.655 (95 %CI 0.527, 0.784) for the WF-RS. Multivariable analysis indicated EGFR-RS as the sole significant predictor of local recurrence in both the discovery and test sets (P < 0.001, hazard ratio [HR] = 2.75; and P = 0.01, HR = 2.13, respectively). The clinical-radiomic model (EGFR-RS + EGFR mutation status + BM size) outperformed the clinical model in identifying high-risk lesions with local recurrence (discovery: P < 0.001; HR = 4.54; test: P = 0.002; HR = 5.1).

CONCLUSION

The multimodal EGFR-RS, demonstrating better consistency than the WF-RS, effectively predicted the local recurrence of NSCLC BMs.