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Dual-Energy CT-Derived Extracellular Volume Fraction for Prediction of Recurrence in Rectal Cancer: A Bicenter Study
Shuo Wang1, Xia Liu1, Yisha Liu1
1Department of Radiology, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, 32# Second Section of First Ring Road, Qingyang District, Chengdu 610070, Sichuan, China (S.W., X.L., Y.L., X.L., F.L., H.H., H.L.).
Rationale And Objectives:
To assess the value of quantitative dual-energy CT (DECT) parameters for predicting resectable rectal cancer recurrence.
Materials And Methods:
This retrospective study included 264 consecutive patients (182 in training cohort and 82 in validation cohort) with resectable rectal cancer who underwent upfront surgery without neoadjuvant therapy and preoperative contrast-enhanced CT at two centers between May 2019 and July 2022. DECT quantitative parameters, including iodine concentration (IC), normalized iodine concentration (NIC), electron density (Rho), effective atomic number (Z), spectral slope (K) and extracellular volume fraction (ECV) derived from both arterial and venous phases, were analysed. Univariate and multivariate Cox proportional hazards models were used to identify independent risk predictors of recurrence. A combined model was established and evaluated using the C-index, time-dependent ROC curves, calibration, decision curve analysis (DCA). The Kaplan-Meier survival curves were compared using the log-rank test.
Results:
Recurrence occurred in 47 (25.8%) training cases and 21 (25.6%) in validation cases. The extracellular volume at venous phase (ECVV) (HR=1.82, 95%CI: 1.45-2.28, p<0.001), extramural venous invasion (EMVI) (HR=3.37, 95%CI: 1.83-6.20, p<0.001), carcinoembryonic antigen (CEA) (HR=1.87, 95%CI: 1.02-3.44, p=0.042), and carbohydrate antigen 19-9 (CA19-9) (HR=2.49, 95%CI: 1.31-4.74, p=0.005) were verified as significant predictors of recurrence. The combined model yielded a C-index of 0.792 (95% CI: 0.658-0.894) for predicting 3-year recurrence. Kaplan-Meier analysis showed significant differences in recurrence-free survival between the model-defined high- and low-risk groups (log-rank p values ranging from <0.001 to 0.020).
Conclusion:
Combining DECT-derived ECVV, EMVI, CEA, and CA19-9 demonstrates improved predictive discrimination for predicting rectal cancer recurrence.