Abdominal radiology (New York) · 2025
Development and validation of a nomogram model based on ultrasound and contrast-enhanced ultrasound features for differentiating mass-forming pancreatitis and pancreatic ductal adenocarcinoma.
СтатьяВалидационное исследованиеПоддержка исследования: вне правительства СШАНазвание и аннотация: Перевод пока не подготовлен
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Liang Hua, Gui Yang, Chen Xueqi, Chen Tianjiao, Zhang Jing, Tan Li, Jia Wanying, Dai Menghua, Wang Weibin, Guo Junchao, Xu Qiang, Lv Ke, Jiang Yuxing
Аннотация
PURPOSE: To explore the value of ultrasound (US) and contrast-enhanced ultrasound (CEUS) in differentiating mass-forming Pancreatitis (MFP) and pancreatic ductal adenocarcinoma (PDAC).
METHODS: This retrospective study analyzed clinical and imaging data from 281 patients who underwent pancreatic CEUS between January 2018 and December 2023. Patients were randomly divided into training (n = 196) and validation (n = 85) sets. Logistic regression analyses were conducted to identify independent predictive imaging features for differentiating PDAC from MFP in the training set. Based on the identified predictors, two nomogram models were constructed: the US model and the US + CEUS model. The diagnostic performance of both models was assessed via the area under the receiver operating characteristic curve (AUC), calibration plots, Hosmer-Lemeshow test, and decision-curve analysis (DCA).
RESULTS: Multivariate logistic regression analysis based on these factors identified taller-than-wide shape (P = 0.002, OR = 0.12), calcification (P = 0.003, OR = 13.76), and washout pattern (P = 0.002, OR = 0.13) as independent predictive factors for distinguishing PDAC from MFP. Compared to the US model, the US + CEUS model demonstrated better performance with AUC values 0.930 (95% CI: 0.895-0.965) in the training set and 0.914 (95% CI: 0.853-0.976) in the validation set. Calibration curve plots and the Hosmer-Lemeshow test (P > 0.05) confirmed that the model has good calibration, and DAC showed significant clinical benefit.
CONCLUSION: The nomogram model constructed using taller-than-wide shape, calcification, and washout pattern demonstrated excellent discriminative ability, accuracy, and clinical utility in differentiating PDAC from MFP.
METHODS: This retrospective study analyzed clinical and imaging data from 281 patients who underwent pancreatic CEUS between January 2018 and December 2023. Patients were randomly divided into training (n = 196) and validation (n = 85) sets. Logistic regression analyses were conducted to identify independent predictive imaging features for differentiating PDAC from MFP in the training set. Based on the identified predictors, two nomogram models were constructed: the US model and the US + CEUS model. The diagnostic performance of both models was assessed via the area under the receiver operating characteristic curve (AUC), calibration plots, Hosmer-Lemeshow test, and decision-curve analysis (DCA).
RESULTS: Multivariate logistic regression analysis based on these factors identified taller-than-wide shape (P = 0.002, OR = 0.12), calcification (P = 0.003, OR = 13.76), and washout pattern (P = 0.002, OR = 0.13) as independent predictive factors for distinguishing PDAC from MFP. Compared to the US model, the US + CEUS model demonstrated better performance with AUC values 0.930 (95% CI: 0.895-0.965) in the training set and 0.914 (95% CI: 0.853-0.976) in the validation set. Calibration curve plots and the Hosmer-Lemeshow test (P > 0.05) confirmed that the model has good calibration, and DAC showed significant clinical benefit.
CONCLUSION: The nomogram model constructed using taller-than-wide shape, calcification, and washout pattern demonstrated excellent discriminative ability, accuracy, and clinical utility in differentiating PDAC from MFP.