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Abstract Background Gastric cancer stands as one of the most prevalent malignancies globally, conventional endoscopic specimens have been the primary means of diagnosing preoperative gastric histopathology, however, their limitations in capturing intra-tumor heterogeneity compromise their efficacy in evaluating angiogenesis. Perfusion Computed Tomography (P-CT) emerges as a pivotal functional imaging modality, facilitating objective assessment of tissue perfusion, serving as a marker of angiogenesis. So, our research objective was to evaluate the efficacy of CT perfusion imaging in the prediction of histological grades of gastric tumors using quantitative perfusion parameters such as permeability surface (PS), blood flow (BF), mean transient time (MTT), and blood volume (BV), in addition to the qualitative scoring system then comparing the findings with the histopathological results. Results PS and BF were statistically significant predictors of the grade of differentiation, their odds ratio (OR) was (1.05, 95% CI 1.02–1.09, for each of them) (P = 0.004, P = 0.009, respectively). MTT also emerged as a significant predictor of the grade of differentiation with an OR of 0.76 (95% CI 0.57–0.93, P = 0.025). Using multivariate logistic regression model, PS was the most potent individual P-CT predictor of differentiation of the grade and the diagnosis of poorly differentiated tumors at ≥ 39 mL/100 g/min cut off point, followed by BF at ≥ 82.2 mL/100 g/min, and MTT at |
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