A nomogram integrating contrast-enhanced CT histogram analysis and clinical-radiological features for preoperative differentiation between TFE3-rearranged renal cell carcinoma and clear cell renal cell carcinoma

<title>Abstract</title> <p>Objective To develop a nomogram model integrating contrast-enhanced computed tomography (CECT) whole-tumor histogram analysis and clinical-radiological features for preoperative differentiation between TFE3-rearranged renal cell carcinoma (TFE3 rRCC) and clear cell renal cell carcinoma (CCRCC). Methods We retrospectively analyzed clinical, imaging, and pathological data from patients with pathologically confirmed TFE3 rRCC (n = 34) and CCRCC (n = 56). Two radiologists independently assessed conventional CT features and extracted whole-tumor histogram parameters from axial CECT images acquired during the parenchyma phase (PP) using FireVoxel software. We applied least absolute shrinkage and selection operator (LASSO) logistic regression for analysis. The selected variables were then incorporated into a multivariate logistic regression analysis to develop a nomogram model that integrates clinical-radiologic and histogram parameters for the preoperative differentiation of TFE3 rRCC from CCRCC. Results LASSO and multivariate logistic regression identified four significant independent predictors: calcification (OR = 61.802, 95% CI: 4.409-866.348, P = 0.002), necrosis and cystic (OR = 20.323, 95% CI: 2.266-182.754, P = 0.007), cortex phase CT value (CT CP) (OR = 0.942, 95% CI: 0.911–0.974, P &lt; 0.001), and Perc.50 (OR = 1.109, 95% CI: 1.042–1.180, P = 0.001). The nomogram model demonstrated excellent performance, with an area under the curve (AUC) of 0.968 (95% CI: 0.878–0.998; sensitivity: 0.912; specificity: 0.929). calibration curves, decision curve analysis (DCA), and Hosmer-Lemeshow tests all confirmed the model's robustness in distinguishing TFE3 rRCC from CCRCC. Conclusion The nomogram model based on CECT whole-tumor histogram analysis and clinical-radiologic features can effectively aid in the noninvasive preoperative discrimination between TFE3 rRCC and CCRCC, offering a novel strategy for personalized clinical management.</p>