ArticleCancer imaging : the official publication of the International Cancer Imaging Society2026
Lauren classification-based combined model integrating clinicopathological and spectral CT features for disease-free survival prediction in gastric 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
backgroundThe Lauren classification (intestinal versus diffuse type) is pivotal for prognosing gastric cancer and guiding treatment selection. This study developed an integrated preoperative prediction model that merges preoperatively available clinicopathological characteristics with spectral CT parameters to distinguish Lauren subtypes and predict disease-free survival (DFS).
methodsThis single-centre, retrospective diagnostic-accuracy study included 224 chemotherapy-treated gastric cancer patients with histopathologically confirmed intestinal or diffuse-type Lauren classification and two-year disease-free survival outcomes. Portal-venous phase spectral computed tomography (CT) parameters (CT₇₀ₖₑ
resultsMultivariate analysis identified poor differentiation (OR = 9.80, P < < 0.001) and Borrmann type III/IV (OR = 2.65, P = 0.004) as clinicopathological predictors, while portal-venous phase CT at 70 keV (OR = 1.34, P < < 0.001), iodine concentration (OR = 2.08, P = 0.001), and normalized iodine concentration (OR = 2.09, P < < 0.001) were significant spectral CT predictors of diffuse-type histology. The combined model demonstrated an area under the curve (AUC) of 0.901 (95% CI: 0.859-0.944) for Lauren classification, outperforming both the pathological model (AUC = 0.810) and the spectral CT model (AUC = 0.861). The optimism-corrected AUC was 0.901 (95% CI: 0.857-0.943) based on 1000-bootstrap validation. For disease-free survival (DFS) prediction, the model achieved an AUC of 0.896 (95% CI: 0.851-0.941) at a cut-off value of 0.646, with an optimism-corrected AUC of 0.895 (95% CI: 0.850-0.939). Calibration curves and decision curve analysis indicated satisfactory agreement and a superior net benefit. Kaplan-Meier analysis revealed significant separation between high-risk and low-risk groups (2-year DFS rates: 7.2% versus 84.4%; log-rank chi2 = 158.88, P < < 0.001), and Cox regression analysis confirmed a substantially increased recurrence risk in the high-risk group (HR = 10.97, 95% CI: 6.68-17.99, P < < 0.001).
conclusionThe integrated model provides accurate preoperative Lauren classification and robust DFS prediction, serving as a multimodal tool for gastric cancer risk stratification and treatment planning.
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