Diagnostic accuracy of dual-energy CT-based nomograms to predict lymph node metastasis in gastric cancer

To develop and validate a dual-energy CT based nomogram for the preoperative prediction of lymph node metastasis (LNM) in patients with gastric cancer (GC).

A total of 210 surgically confirmed GC patients (159 males, 51 females; mean age: 59.8 ± 7.7 years, range: 28-79 years) who underwent spectral CT scans were retrospectively enrolled and split into a primary cohort (n = 140) and validation cohort (n = 70). Clinical information and follow-up data including overall survival (OS) and progression-free survival (PFS) were collected. The iodine concentration (IC) of the primary tumors at the arterial phase (AP) and venous phase (VP) were measured and then normalized to the aorta (nICs). Univariate, multivariable logistic regression and Cox regression analyses were performed to screen predictive indicators for LNM and outcome. A nomogram for risk factors of LNM was developed, and its performance was measured using the ROC, accuracy and Harrell’s concordance index (C-index).

Tumor thickness, Borrmann classification and ICVP were independent predictors of LNM. The nomogram was significantly associated with LN status (p < 0.001). It yielded an AUC of 0.793 [95% confidence interval (95% CI), 0.678-0.908] and an accuracy of 0.757 (95% CI, 0.640-0.852) in the internal-validation cohort. The nomogram also exhibited a prognostic ability with C-indices of 0.675 (95% CI, 0.571-0.779; p < 0.001) for PFS and 0.643 (95% CI, 0.518-0.768; p = 0.025) for OS.

This study presented a dual-energy quantification-based nomogram, which can be used to facilitate the preoperative individualized prediction of LNM in patients with GC.