Quantitative parameters of dual-layer spectral CT for differentiating metastatic and non-metastatic lymph nodes in colorectal cancer

Sep 23, 2026

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Dual-layer spectral CT (DLSCT) quantitative parameters were assessed for their ability to distinguish metastatic from non-metastatic lymph nodes in colorectal cancer. A retrospective cohort analyzed 211 lymph nodes from 66 patients, comparing morphologic features and DLSCT-derived metrics. Univariate and multivariable logistic regression identified independent predictors, while ROC curves and decision curve analysis evaluated diagnostic accuracy and clinical usefulness. Results showed distinct spectral iodine and effective atomic number-related trends across phases, with a multiparameter model outperforming morphology alone.

LanguageEnglish

CategoryHealthcare

FormatPDF

Pages12

Reading Time30 min

AccessFree to download

Background

Methods

Results

Morphological and quantitative DLSCT findings

Diagnostic performance of combined and quantitative models

Conclusion

Tang et al. Cancer Imaging (2026) 26:56 [https://doi.org/10.1186/s40644-026-01019-7](https://doi.org/10.1186/s40644-026-01019-7) Cancer Imaging RESEARCH Open Access Quantitative parameters of dual-layer spectral CT for differentiating metastatic and nonmetastatic lymph nodes in colorectal cancer Liyan Tang1,2, Guoqing Liu 1, Xia Lv 1, Weicui Chen1* and Xian Liu 1* Abstract Background To 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) . Methods This retrospective study enrolled 211 LNs from 66 CRC patients, including 78 metastatic LNs and 133 nonmetastatic 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. Results All 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. Conclusion Quantitative parameters from DLSCT provide significant value in distinguishing lymph node metastasis in colorectal cancer. Keywords Dual-layer spectral detector CT, Colorectal cancer, Lymph node metastasis *Correspondence: Weicui Chen [weicuichen@126.com](weicuichen@126.com)[ ](weicuichen@126.com)Xian Liu [liuxian74@hotmail.com](liuxian74@hotmail.com) 1Department of Radiology, The Second Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou 510120, China 2The Second Clinical College of Guangzhou University of Chinese Medicine, Guangzhou 510006, China © The Author(s) 2026. Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit [http://creati](http://creati)[vecommons.org/licenses/by-nc-nd/4.0/](vecommons.org/licenses/by-nc-nd/4.0/.)[.](vecommons.org/licenses/by-nc-nd/4.0/.) Tang et al. Cancer Imaging (2026) 26:56 Backgroun

FAQs

What was the purpose of this study using dual-layer spectral CT?

To determine the value of quantitative DLSCT parameters for differentiating metastatic and non-metastatic lymph nodes in colorectal cancer.

How were metastatic and non-metastatic lymph nodes evaluated?

The study retrospectively analyzed 211 lymph nodes from 66 CRC patients, comparing morphologic characteristics and quantitative DLSCT parameters, then using logistic regression to identify independent predictors.

Which model performed better for predicting lymph node metastasis?

A multivariate model incorporating quantitative DLSCT parameters improved performance (AUC 0.901, higher sensitivity and specificity) compared with combined morphological features (AUC 0.695).

Sep 23, 2026

Uploaded by Angel