ArticleCancer imaging : the official publication of the International Cancer Imaging Society2026
Quantitative parameters of dual-layer spectral CT for differentiating metastatic and non-metastatic lymph nodes in colorectal cancer.
Article in Cancer imaging : the official publication of the International Cancer Imaging Society, 2026. 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
backgroundTo investigate the value of quantitative parameters obtained from dual layer spectrum CT (DLSCT) in distinguishing metastatic and non-metastatic lymph nodes in colorectal cancer (CRC).
methodsThis retrospective study enrolled 211 LNs from 66 CRC patients, including 78 metastatic LNs and 133 non-metastatic LNs. The morphological characteristics and quantitative DLSCT parameters of each identified lymph node were evaluated and compared. Univariate and multivariable logistic regression analyses were used to identify the independent factors for predicting LN metastasis. Receiver operating characteristic curve (ROC) and decision curve analysis (DCA) were employed to evaluate the diagnostic performance and clinical usefulness of the models.
resultsAll morphological features differed between metastatic and non-metastatic LNs. Metastatic LNs showed significantly lower iodine concentration (IC) and normalized iodine concentration (NIC) in the arterial phase, while exhibiting higher effective atomic number (Zeff), normalized effective atomic number (nZeff) in the venous phase, and slope of the spectral Hounsfield unit curve (λHu) values in both phases. A positive correlation was found between λHu values of LNs and tumors in both the arterial and venous phases within the LN metastasis group. For differentiating metastatic and non-metastatic LNs, combined morphological features yielded an AUC of 0.695, with 66.7% sensitivity and 68.4% specificity, while a multivariate model incorporating DLSCT parameters improved this to 0.901, with 82.1% sensitivity and 87.2% specificity. The DeLong test and decision curve analysis (DCA) showed that quantitative multiparameter model offered better predictive performance and benefits for LN metastasis than the morphological features.
conclusionQuantitative parameters from DLSCT provide significant value in distinguishing lymph node metastasis in colorectal cancer.
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