Predictive Value of TRUS and CEUS Parameters for Lymph Node Metastasis in Rectal Cancer: A Retrospective Study
Shitao Su1, Xuanzhang Huang1, Xigui Li1
1Department of Medical Ultrasound, the First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi Zhuang Autonomous Region, People's Republic of China.
Purpose:
To assess the predictive value of transrectal ultrasound (TRUS) combined with qualitative and quantitative parameters of contrast-enhanced ultrasound (CEUS) for lymph node metastasis (LNM) in rectal cancer (RC).
Patients And Methods:
This retrospective study analyzed preoperative clinical data, qualitative and quantitative TRUS and CEUS parameters, and postoperative pathological data from 535 patients with RC confirmed by surgical pathology. Independent predictors of LNM were identified through univariate and multivariate binary logistic regression analysis. Two predictive models were developed: one based on TRUS/CEUS parameters, and another combining ultrasonographic parameters with clinical indicators. Model calibration was evaluated using the Hosmer-Lemeshow test, and diagnostic performance was quantified via receiver operating characteristic (ROC) curve analysis.
Results:
Multivariate analysis revealed ultrasonographic tumor (uT) stage(OR=1.751,P=0.042), ultrasonographic nodal (uN) stage (OR=2.279,P<0.001), peak intensity ratio(PI-ratio: OR=0.799,P<0.001), and slope ratio (S-ratio: OR=0.997,P=0.008) as independent predictors of LNM. When incorporating clinical indicators, the combined model identified uN stage (OR=2.351,P<0.001), PI-ratio (OR=0.784,P<0.001), PI-difference (OR=0.997,P=0.011), S-ratio (OR=1.046,P=0.048), CEA (OR=2.324,P<0.001), and CA199 (OR=3.020,P=0.003) as significant predictors. The US model demonstrated an AUC of 0.792 (95% CI: 0.755-0.829), while the combined model achieved superior performance with an AUC of 0.815 (95% CI: 0.780-0.850) (Z=-2.076, P=0.038). Both models showed satisfactory calibration (Hosmer-Lemeshow test: P>0.05).
Conclusion:
The predictive model constructed based on preoperative TRUS combined with CEUS quantitative parameters, along with its combined model incorporating clinical biomarkers (CEA, CA199), can effectively predict LNM in RC, providing a non-invasive and quantifiable preoperative assessment tool for clinical practice.
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