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. 2025 May;35(5):2692-2701.
doi: 10.1007/s00330-024-11143-2. Epub 2024 Oct 24.

The preoperative prediction of lymph node metastasis of resectable pancreatic ductal adenocarcinoma using dual-layer spectral computed tomography

Yi Chen #  1   2 , Tiansong Xie #  1   3 , Lei Chen  3 , Zehua Zhang  3 , Yu Wang  4 , Zhengrong Zhou  5   6 , Wei Liu  7
Affiliations

The preoperative prediction of lymph node metastasis of resectable pancreatic ductal adenocarcinoma using dual-layer spectral computed tomography

Yi Chen et al. Eur Radiol. 2025 May.

Abstract

Objectives: To investigate the value of dual-layer spectral computed tomography (DLCT) parameters derived from primary tumors in predicting lymph node metastasis (LNM) of resectable pancreatic ductal adenocarcinoma (PDAC).

Materials and methods: In this retrospective study, patients with resectable PDAC who underwent DLCT within 2-week intervals before surgery were enrolled and randomly divided into training and validation sets at a 7:3 ratio. The patients' clinical data, CT morphological features, and DLCT parameters were analyzed. Univariate and multivariate logistic analyses were used to identify the predictors and construct a predictive model, and receiver operator characteristic (ROC) curves were programmed to evaluate the predictive efficacy.

Results: We enrolled 107 patients (44 patients with LNM and 63 patients without LNM). Among all variables, iodine concentration in the venous phase, extracellular volume, and tumor size were identified as independent predictors of LNM. The nomogram model, incorporating the two DLCT parameters and the morphological feature, achieved an area under the curve (AUC) of 0.877 (95% confidence interval [CI]: 0.803-0.952) and 0.842 (95% CI: 0.707-0.977) for predicting LNM in the training and validation sets, respectively. Furthermore, the AUC of the nomogram model was greater than that of morphological features of lymph nodes in the training (AUC = 0.877 vs. 0.570) and validation (AUC = 0.842 vs. 0.583) sets.

Conclusions: DLCT has the potential to predict LNM in patients with resectable PDAC and show a better predictive value than morphological features of lymph nodes.

Key points: Question Morphological features of lymph nodes are of limited value in detecting metastatic lymph nodes in pancreatic ductal adenocarcinoma (PDAC). Findings Dual-layer spectral computed tomography (DLCT) parameters and morphological features derived from PDAC lesions show good preoperatively predictive efficacy for lymph node metastasis. Clinical relevance The proposed DLCT-based nomogram model may serve as an effective and convenient tool for preoperatively predicting lymph node metastasis of resectable PDAC.

Keywords: Dual-layer spectral CT; Lymph node metastasis; Nomogram; Pancreatic ductal adenocarcinoma.

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Conflict of interest statement

Compliance with ethical standards. Guarantor: The scientific guarantor of this publication is W.L. Conflict of interest: Y.W. is an employee of Philips Healthcare. The remaining authors of this manuscript declare no relationships with any companies, whose products or services may be related to the subject matter of the article. Statistics and biometry: One of the authors has significant statistical expertise (Y.W.). Informed consent: This was a retrospective study and no informed consent was required. Ethical approval: Institutional Review Board approval was obtained. Methodology: Retrospective Diagnostic study Performed at one institution

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