Purpose To establish and evaluate a nomogram based on quantitative spectral CT parameters for predicting microsatellite instability (MSI) and deficient mismatch repair (dMMR) status in patients with esophagogastric junction adenocarcinoma (EGJA). Materials and Methods In this study including retrospective and prospective datasets (enrollment period: May 2021 to January 2026), patients from two centers were divided into training, validation, external test, prospective test, and neoadjuvant chemotherapy cohorts. A nomogram was constructed integrating clinical characteristics with quantitative spectral CT parameters. Model efficacy in predicting MSI/dMMR and its associations with disease-free survival were evaluated. Primary statistical methods included logistic and Cox regression analyses. Results In total, 511 patients (median age, 67 years [IQR, 60-73 years]; 333 male) were included. The nomogram incorporated sex, clinical N stage, CT attenuation on 40-keV virtual monoenergetic images, and normalized iodine density during the venous phase. It achieved areas under the receiver operating characteristic curve of 0.87 (95% CI: 0.81, 0.93), 0.87 (95% CI: 0.78, 0.96), 0.91 (95% CI: 0.83, 0.99), 0.89 (95% CI: 0.80, 0.98), and 0.86 (95% CI: 0.76, 0.96) across the five respective cohorts: training, validation, external test, prospective test, and neoadjuvant chemotherapy. In the external test cohort, the nomogram correctly identified 9.76% (four of 41) of the patients misclassified with preoperative biopsy. Furthermore, it stratified patients into distinct disease-free survival risk groups in the training (hazard ratio, 2.04 [95% CI: 1.35, 3.09]; P < .001) and validation (hazard ratio, 2.97 [95% CI: 1.46, 6.05]; P = .003) cohorts. Conclusion The spectral CT-based nomogram enabled preoperative prediction of MSI/dMMR status and prognostic assessment in patients with EGJA. Keywords: Esophagogastric Junction Adenocarcinoma, Spectral CT, Nomogram, Primary Neoplasms, CT-Spectral, Neoplasms-Primary, Pathology, Tumor Immune Microenvironment, Pre-clinical Models Chinese Clinical Trial Registry identifier nos. ChiCTR2500097335 and ChiCTR2500101639 Supplemental material is available for this article. © The Author(s) 2026. Published by the Radiological Society of North America under a CC BY 4.0 license.
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