Preoperative prediction of tumor budding and lymphovascular invasion in colon cancer using dual-energy CT: a prospective study with internal model validation

被引:0
作者
Shao, Chuanyang [1 ]
He, Changjiu [1 ]
Zheng, Ping [2 ]
Zhou, Peng [1 ]
Chen, Xiaoli [1 ]
机构
[1] Univ Elect Sci & Technol China, Affiliated Canc Hosp,Dept Radiol, Sichuan Clin Res Ctr Canc,Sichuan Canc Hosp & Inst, Sichuan Canc Ctr,Radiat Oncol Key Lab Sichuan Prov, Chengdu 610000, Peoples R China
[2] Univ Elect Sci & Technol China, Sichuan Canc Hosp & Inst, Sichuan Clin Res Ctr Canc, Sichuan Canc Ctr,Dept Pathol,Affiliated Canc Hosp, Chengdu 610000, Peoples R China
关键词
Intestine; Colonic neoplasms; Dual-energy computed tomography; Tumor budding; Lymphovascular invasion; COLORECTAL-CANCER; IODINE CONCENTRATION; GASTRIC-CANCER; LYMPH-NODES; SPECTRAL CT; COLONOGRAPHY;
D O I
10.1007/s00261-025-04803-4
中图分类号
R8 [特种医学]; R445 [影像诊断学];
学科分类号
1002 ; 100207 ; 1009 ;
摘要
ObjectiveThis study evaluates the potential of dual-energy CT (DECT) for preoperative prediction of tumor budding (TB) and lymphovascular invasion (LVI) in colon cancer.MethodsThis prospective study enrolled 153 patients (mean age 61.33 years +/- 0.88) with pathologically confirmed colon cancer. All participants underwent arterial and venous phase DECT scans within one week before surgery. Two radiologists independently analyzed the images, assessing tumor location, clinical N stage (cN stage), iodine concentration (IC), effective atomic number (Z-eff), and dual-energy index (DEI). The normalized iodine concentration (nIC) was obtained by comparing measured IC to the abdominal aortic IC. Logistic regression identified independent risk factors for high-grade TB and LVI positivity. The Akaike Information Criterion guided model selection, and the area under the curve (AUC) was calculated. Bootstrap validation with 1000 iterations was used for internal validation.ResultsTumor location and cN stage were identified as independent risk factors for high-grade TB, and nICA tumor and cN stage for LVI positivity. The optimal model for predicting high-grade TB included tumor location, cN stage, and DEIV tumor, with an AUC of 0.763 (sensitivity: 75.0%; specificity: 64.7%) and a mean AUC of 0.712. Similarly, the model for LVI positivity included nICA tumor, cN stage, and nICA peripheral fat, with an AUC of 0.811 (sensitivity: 71.7%; specificity: 76.6%) and a mean AUC of 0.814.ConclusionDECT could consistently quantify colon cancer characteristics, and DECT-based models performed well in the preoperative prediction of TB and LVI.
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页数:9
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