Academic radiology · 2026
Dual-layer Spectral Detector CT Quantitative Parameters for Predicting Tumor Budding Grade and Prognosis in Stage Ⅱ Colorectal Cancer.
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Tang Pingtai, Wei Dan, Tang Langlang, Ma Junli, Deng Huipeng, Liu Jinkai
Аннотация
RATIONALE AND OBJECTIVES: Tumor budding (TB) is a critical prognostic biomarker in stage Ⅱ colorectal cancer (CRC), but postoperative histopathological assessment limits preoperative risk stratification. Dual-layer spectral detector CT (SDCT) quantitative parameters may non-invasively predict TB grade and prognosis in stage Ⅱ CRC.
MATERIALS AND METHODS: We retrospectively studied 153 stage II CRC patients undergoing SDCT prior to curative resection. Spectral CT parameters (iodine concentration [IC], effective atomic number [Zeff], the slope of the energy spectrum [λHU]) during arterial phase (AP) and venous phase (VP) were analyzed. TB grade was assessed by pathology; three-year disease-free survival (DFS) was the primary endpoint. Logistic regression and Cox regression identified predictive factors.
RESULTS: SDCT parameters (A-IC, A-Zeff, A-λHU) during AP significantly differentiated high-grade TB (Bd 3) from low/intermediate (Bd 1+2) (all P <0.05). The combined model integrating these parameters achieved AUCs of 0.937 (training set) and 0.893 (validation set). The value of the combined model was significantly associated with worse three-year DFS (HR 8.811, P=0.005).
CONCLUSION: SDCT quantitative parameters during AP effectively stratify TB grade and predict prognosis in stage Ⅱ CRC, offering a non-invasive preoperative tool for personalized therapy.
MATERIALS AND METHODS: We retrospectively studied 153 stage II CRC patients undergoing SDCT prior to curative resection. Spectral CT parameters (iodine concentration [IC], effective atomic number [Zeff], the slope of the energy spectrum [λHU]) during arterial phase (AP) and venous phase (VP) were analyzed. TB grade was assessed by pathology; three-year disease-free survival (DFS) was the primary endpoint. Logistic regression and Cox regression identified predictive factors.
RESULTS: SDCT parameters (A-IC, A-Zeff, A-λHU) during AP significantly differentiated high-grade TB (Bd 3) from low/intermediate (Bd 1+2) (all P <0.05). The combined model integrating these parameters achieved AUCs of 0.937 (training set) and 0.893 (validation set). The value of the combined model was significantly associated with worse three-year DFS (HR 8.811, P=0.005).
CONCLUSION: SDCT quantitative parameters during AP effectively stratify TB grade and predict prognosis in stage Ⅱ CRC, offering a non-invasive preoperative tool for personalized therapy.