ArticleInternational journal of colorectal disease2025
Dual-energy CT combined with histogram parameters in the assessment of perineural invasion in colorectal cancer.
Article in International journal of colorectal disease, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
purposeThe purpose is to evaluate the predictive value of dual-energy CT (DECT) combined with histogram parameters and a clinical prediction model for perineural invasion (PNI) in colorectal cancer (CRC).
methodsWe retrospectively analyzed clinical and imaging data from 173 CRC patients who underwent preoperative DECT-enhanced scanning at two centers. Data from Qinghai University Affiliated Hospital (n = 120) were randomly divided into training and validation sets, while data from Lanzhou University Second Hospital (n = 53) served as the external validation set. Regions of interest (ROIs) were delineated to extract spectral and histogram parameters, and multivariate logistic regression identified optimal predictors. Six machine learning models-support vector machine (SVM), decision tree (DT), random forest (RF), logistic regression (LR), k-nearest neighbors (KNN), and extreme gradient boosting (XGBoost)-were constructed. Model performance and clinical utility were assessed using receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA).
resultsFour independent predictive factors were identified through multivariate analysis: entropy, CT40
conclusionDual-energy CT-based combined with histogram parameters and clinical prediction modeling can be effectively used for preoperative noninvasive assessment of perineural invasion in colorectal cancer.
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