Background and purpose: Radiomics is an emerging field that generates large amounts of valuable clinical information through extracting quantitative imaging features. The purpose of this study was to use the radiomics approach to assess the value of features captured from PET and CT in predicting the therapeutic effect in stage Ⅰ non-small cell lung cancer (NSCLC) after stereotactic ablative radiotherapy (SABR). Methods: Patients with stage Ⅰ NSCLC confirmed by pathology and treated with SABR were included retrospectively. The gross tumor volume (GTV) was defined by two radiologists. PET and CT scan images were collected

and radiomic features were further extracted and analyzed. Non-negative matrix factorization was used to distinguish patients with or without local control. Results: Sixteen patients were eligible for analysis. This study identified two PET features (LL_GLCM_Maximal_Correlation_Coefficient and HL_GLRMS_LRE) captured from PET/CT as having significance in classifying patients with or without disease development. This study not find similar results in CT scans. Conclusion: It seems feasible to use radiomics information effects from PET/CT to predict therapeutic effects of SABR in stage Ⅰ NSCLC. Further investigation is needed.