Development and validation of A CT-based radiomics nomogram for prediction of synchronous distant metastasis in clear cell renal cell carcinoma

BackgroundEarly identification of synchronous distant metastasis (SDM) in patients with clear cell Renal cell carcinoma (ccRCC) can certify the reasonable diagnostic examinations. MethodsThis retrospective study recruited 463 ccRCC patients who were divided into two cohorts (training and internal validation) at a 7:3 ratio. Besides, 115 patients from other hospital were assigned external validation cohort. A radiomics signature was developed based on features by means of the least absolute shrinkage and selection operator method. Demographics, laboratory variables and CT findings were combined to develop clinical factors model. Integrating radiomics signature and clinical factors model, a radiomics nomogram was developed. ResultsTen features were used to build radiomics signature, which yielded an area under the curve (AUC) 0.882 in the external validation cohort. By incorporating the clinical independent predictors, the clinical model was developed with AUC of 0.920 in the external validation cohort. Radiomics nomogram (external validation, 0.925) had better performance than clinical factors model or radiomics signature. Decision curve analysis demonstrated the superiority of the radiomics nomogram in terms of clinical usefulness. ConclusionsThe CT-based nomogram could help in predicting SDM status in patients with ccRCC, which might provide assistance for clinicians in making diagnostic examinations.

Automated summary

A retrospective study developed a mathematical model combining radiomics and clinical factors to predict synchronous distant metastasis in patients with clear cell renal cell carcinoma. The model showed high accuracy and clinical usefulness in the external validation group.