CT-derived extracellular volume fraction as a predictive marker for postoperative recurrence in pStage II-III gastric cancer.

Abstract

This study assessed the prognostic value of CT-derived extracellular volume fraction (CT-ECV) in predicting postoperative recurrence in patients with pathological stage (pStage) II-III gastric cancer (GC). A retrospective analysis was conducted on 112 patients with pathologically confirmed pStage II-III gastric adenocarcinoma who underwent preoperative triphasic contrast-enhanced CT and curative gastrectomy without neoadjuvant therapy. The relationship between preoperative CT-ECV and recurrence risk was evaluated using comprehensive imaging and clinicopathological data. The optimal CT-ECV threshold for recurrence prediction was determined using receiver operating characteristic (ROC) curve analysis. Disease-free survival (DFS) was assessed using Kaplan-Meier and Cox regression analyses. The mean CT-ECV was 56.4 ± 16.7%. Patients with recurrence (n = 28) had significantly higher CT-ECV values than those without recurrence (n = 84) (65.3 ± 14.3% vs 53.5 ± 16.5%; p < 0.001). The optimal CT-ECV cutoff for recurrence prediction was ≥ 56.9%, with an area under the curve of 0.71 (sensitivity 82.1%, specificity 61.9%). Multivariate analysis revealed that high CT-ECV was independently associated with worse DFS (HR: 5.93; 95% CI: 1.77-19.86; p = 0.004). Patients with high CT-ECV had significantly lower DFS rates compared to those with low CT-ECV (5-year DFS rate: 49.9% vs 93.7%; p < 0.001). High CT-ECV values correlate with increased recurrence risk and shorter DFS in pStage II-III GC, highlighting its potential as a predictive imaging biomarker for preoperative risk stratification. Question Identifying prognostic markers is crucial for improving outcomes in stage II-III GC with high recurrence rates post-treatment. Findings High preoperative CT-ECV values are independently associated with increased recurrence risk and reduced DFS in pStage II-III GC. Clinical relevance CT-ECV can facilitate personalised treatment strategies and potentially improve patient management and outcomes.