Abstract
Objective: To investigate the correlations between dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) perfusion histogram parameters and vascular endothelial growth factor (VEGF) and epidermal growth factor receptor (EGFR) expressions in advanced gastric cancer (AGC). Methods: This retrospective study included 80 pathologically confirmed patients with AGC who underwent DCE-MRI before surgery from February 2017 to May 2021. The DCE-MRI perfusion histogram parameters were calculated by Omni Kinetics software in four quantitative parameter maps. Immunohistochemical methods were used to detect VEGF and EGFR expressions and calculate the immunohistochemical score. Results: VEGF expression was relatively lower in patients with intestinal-type AGC than those with diffuse-type AGC (p < 0.05). For VEGF, Receiver operating characteristics (ROC) curve analysis revealed that Quantile 90 of Ktrans, Meanvalue of Kep and Quantile 50 of Ve provided the perfect combination of sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) for distinguishing high and low VEGF expression, For EGFR, Skewness of Ktrans, Energy of Kep and Entropy of Vp provided the perfect combination of sensitivity, specificity, PPV and NPV for distinguishing high and low EGFR expression. Ktrans (Quantile 90, Entropy) showed the strongest correlation with VEGF and EGFR in patients with intestinal-type AGC (r = 0.854 and r = 0.627, respectively); Ktrans (Mean value, Entropy) had the strongest correlation with VEGF and EGFR in patients with diffuse-type AGC (r = 0.635 and 0.656, respectively). Conclusion: DCE-MRI perfusion histogram parameters can serve as imaging biomarkers to reflect VEGF and EGFR expressions and estimate their difference in different Lauren classifications of AGC.
Highlights
Gastric cancer (GC) is the fifth most common cancer worldwide and the leading cause of cancer-related mortality [1]
For vascular endothelial growth factor (VEGF), Receiver operating characteristics (ROC) curve analysis revealed that Quantile 90 of Ktrans, Meanvalue of Kep and Quantile 50 of volume fraction (Ve) provided the perfect combination of sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) for distinguishing high and low VEGF expression, For epidermal growth factor receptor (EGFR), Skewness of Ktrans, Energy of Kep and Entropy of Vp provided the perfect combination of sensitivity, specificity, PPV and NPV for distinguishing high and low EGFR expression
dynamic contrast-enhanced magnetic resonance imaging (DCE-magnetic resonance imaging (MRI)) perfusion histogram parameters can serve as imaging biomarkers to reflect VEGF and EGFR expressions and estimate their difference in different Lauren classifications of advanced gastric cancer (AGC)
Summary
Gastric cancer (GC) is the fifth most common cancer worldwide and the leading cause of cancer-related mortality [1]. The treatment methods of advanced gastric cancer (AGC) mainly include preoperative chemoradiotherapy, immunotherapy, and molecular-targeted therapy, with molecular-targeted therapy emerging as an effective method to improve prognosis. Targets for targeted therapy of AGC mainly include vascular endothelial growth factor (VEGF) and epidermal growth factor receptor (EGFR) [3]. Accurate knowledge of VEGF and EGFR expressions and their differences in different Lauren classifications before operation might assist in selecting the appropriate treatment methods for patients with AGC. VEGF and EGFR expressions are mainly detected by immunohistochemistry (IHC), which is influenced by sampling and may not be adequately comprehensive.
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