Abstract

Objective To discuss the value of double contrast-enhanced ultrasound(DCEUS) as a method to predict the pathologic grade of regression to preoperative neoadjuvant chemotherapy(NAC) in advanced gastric cancer(AGC) patients, the contrast parameters of gastric carcinoma were measured and its correlation with pathologic response degree was analyzed. Methods Fifty seven patients with endoscopic biopsy-proven AGC were considered for a complete resection of the lesion and had a DCEUS prior to and following XELOX pre-operative NAC therapy for 3 cycles. The arrival time (AT), time-to-peak (TTP), baseline intensity (BI) and peak intensity (PI) of the primary gastric tumor were measured.The enhanced intensity (EI) was defined as PI minus BI. The percentage of change of DCEUS parameters before and after NAC therapy and its correlation with phathologic grades of regression was calculated. Patients were divided into responder and nonreponder group according to different pathologic response grade. The differences of DCEUS parameters between two groups were compared. The diagnostic accuracy of DCEUS in prediction of benefit from preoperative NAC was represented by means of receive operating characteristic (ROC) curves. Results After NAC, the PI and EI values of local gastric cancer were significantly lower than before NAC. There were significant differences in PI and EI after NAC between the responder and nonresponder groups. Among the DCEUS parameters showed significant correlation with pathologic grade of regression, the correlation factor was highest in percentage of EI reduction of primary gastric tumor(ρ=-0.501, P=0.007). When the optimal cutoff value of EI reduction rate of gastric tumor determined was 27%, a sensitivity of 81.8% and specificity of 66.7% were achieved. Conclusions DCEUS might be a novel, noninvasive, liable and potential method to select the benefit responder from the preoperative NAC in AGC patient. Key words: Contrast-enhanced ultrasound; Microbubbles; Stomach neoplasms; Neoadjuvant chemotherapy

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