Abstract:Background and Aims Ki-67 is an important biomarker reflecting proliferative activity in breast cancer and plays a critical role in prognosis evaluation and treatment decision-making. Currently, Ki-67 assessment mainly relies on invasive immunohistochemical examination, and effective non-invasive evaluation methods remain limited. This study aimed to develop a nomogram based on dual-energy computed tomography (DECT) quantitative parameters for predicting Ki-67 expression in invasive breast cancer.Methods A total of 128 patients with pathologically confirmed invasive breast cancer who underwent DECT examination at Suining Central Hospital between October 2023 and June 2024 were prospectively enrolled. According to a Ki-67 cutoff value of 20%, patients were classified into a high-expression group (n=85) and a low-expression group (n=43). Quantitative DECT parameters from the non-contrast, arterial, and venous phases were collected, including spectral curve slope (λ), iodine concentration (IC), normalized iodine concentration (NIC), effective atomic number (Zeff), normalized effective atomic number (NZeff), and tumor-arterial iodine fraction (TAIF). Receiver operating characteristic (ROC) analysis was used to evaluate the predictive performance of each parameter. Subsequently, the Boruta algorithm was employed to select feature variables, and a logistic regression model was constructed to develop a nomogram. Internal validation was performed using Bootstrap resampling, and model performance was evaluated by ROC analysis, calibration curves, and decision curve analysis (DCA).Results Compared with the low-expression group, the high Ki-67 expression group showed significantly higher values in non-contrast λ, arterial-phase λ, arterial-phase IC, arterial-phase NIC, arterial-phase Zeff, arterial-phase NZeff, venous-phase NIC, venous-phase Zeff, and TAIF (all P<0.05). ROC analysis demonstrated that all DECT quantitative parameters had predictive value for Ki-67 expression, among which arterial-phase IC showed the best performance (AUC=0.721). Five variables, including TAIF, arterial-phase Zeff, arterial-phase IC, arterial-phase λ, and venous-phase λ, were selected to establish the prediction model. Internal validation showed that the model achieved an AUC of 0.818 (95% CI=0.728-0.900). The calibration curve demonstrated good agreement between predicted and observed probabilities (Hosmer-Lemeshow test, P=0.312), and DCA indicated favorable clinical utility across a wide range of threshold probabilities.Conclusion The nomogram based on DECT quantitative parameters can effectively predict high Ki-67 expression in invasive breast cancer and may provide a useful non-invasive tool for molecular characterization and clinical decision-making.