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This work aimed to investigate values of contrast-enhanced ultrasound (CEUS) under DEFLATE in the classification and diagnosis of the common bile duct and superficial lymphoid lesions. 88 patients with lower common bile duct lesions and 126 patients with superficial lymphoid lesions were selected as the subjects investigated and examined by CEUS under DEFLATE to compare characteristics and diagnostic efficiency of CEUS in different types of lesions. The time-intensity curve (TIC) was for quantitative analysis on CEUS results. The results showed that there were statistically significant differences in the comparison of time to peak (TTP), area under the curve (AUC), and gradient (Grad) of common bile duct walls in patients from the malignant group ( P  < 0.05), while the comparison of three indicators of patients in the benign group was not statistically remarkable ( P  > 0.05). In addition, there were statistically great differences in TTP, AUC, and Grad among patients in the benign and malignant groups ( P  < 0.05). The sensitivity, specificity, accuracy, and positive/negative predictive value of CEUS + ultrasound (US) in the diagnosis of benign and malignant lymph nodes were 92.83%, 87.14%, 89.54%, 91.23%, and 86.43%, respectively. The values of maximal intensity ( I  max ) in the reactive hyperplasia group (group A), lymphoma group (group B), and metastatic lymph nodes group (group C) were compared, showing statistical differences ( P  < 0.05). The TTP and AUC of group B were higher than those of groups A and C, respectively ( P  < 0.05), and the base-to-peak ascending slope ( K  UP ) and the absolute value of the semidescending slope ( K  DOWN ) in group C increased hugely compared to group A ( P  < 0.05). It indicated that CEUS examination under DEFLATE could be applied in the qualitative diagnosis of lower common bile duct lesions and superficial lymphoid lesions, which was worthy of clinical application.

Values of Contrast-Enhanced Ultrasound in Classification and Diagnosis of Common Bile Duct and Superficial Organ Lesions under Compression Algorithm