Radiomics of Spinal Metastases Originating From Primary Nonsmall Cell Lung Cancer or Breast Cancer and Ability to Predict Epidermal Growth Factor Receptor Mutation/Ki-67 Levels

Abstract

Objectives The aims of the study are to explore spinal magnetic resonance imaging (MRI)-based radiomics to differentiate spinal metastases from primary nonsmall cell lung cancer (NSCLC) or breast cancer (BC) and to further predict the epidermal growth factor receptor (EGFR) mutation and Ki-67 expression level. Methods In total, 268 patients with spinal metastases from primary NSCLC (n = 148) and BC (n = 120) were enrolled between January 2016 and December 2021. All patients underwent spinal contrast-enhanced T1-weighted MRI before treatment. Two- and 3-dimensional radiomics features were extracted from the spinal MRI images of each patient. The least absolute shrinkage and selection operator regression were applied to identify the most important features related to the origin of the metastasis and the EGFR mutation and Ki-67 level. Radiomics signatures (RSs) were established using the selected features and evaluated using receiver operating characteristic curve analysis. Results We identified 6, 5, and 4 features from spinal MRI to develop Ori-RS, EGFR-RS, and Ki-67-RS for predicting the metastatic origin, EGFR mutation, and Ki-67 level, respectively. The 3 RSs performed well in the training (area under the receiver operating characteristic curves: Ori-RS vs EGFR-RS vs Ki-67-RS, 0.890 vs 0.793 vs 0.798) and validation (area under the receiver operating characteristic curves: Ori-RS vs EGFR-RS vs Ki-67-RS, 0.881 vs 0.744 vs 0.738) cohorts. Conclusions Our study demonstrated the value of spinal MRI-based radiomics for identifying the metastatic origin and evaluating the EGFR mutation status and Ki-67 level in patients with NSCLC and BC, respectively, which may have the potential to guide subsequent individual treatment planning.