Objective:To evaluate the effectiveness of contrast-enhanced ultrasound in the differential diagnosis of atypical adenomyosis and fibroids using a decision tree model.Methods:The data of cases with difficulty in differentiating atypical adenomyosis from fibroids on conventional ultrasound examination at Shengjing Hospital of China Medical University from April 2021 to April 2022 were selected and analyzed. Ninety-five patients with contrast-enhanced ultrasound examination were finally selected, including 64 patients in the pathologically confirmed adenomyosis group and 31 patients in the fibroids group. The data from the qualitative analysis and the quantitative analysis of the time-intensity curve (TIC) curve were collected separately, including the temporal variability of contrast entry into the lesion, i.e.the difference between the time when the contrast agent started to enter the lesion and the time when the contrast agent finally filled the lesion completely. Indicators were first screened for inclusion in the decision tree model by univariate and multifactorial analyses, and decision tree models based on qualitative analysis indicators, and qualitative and TIC-based analyses were developed to further assess the diagnostic efficacy of both models.Results:Through the univariate analysis, it showed that the qualitative analysis indicators of lesion onset enhancement pattern, enhancement intensity, intra-lesion contrast distribution, and post-contrast lesion border were of statistical significance (all P<0.05) between the two groups. The differences in contrast arrive time (AT), contrast time to peak (TTP), |ΔAT|, and |ΔTTP| in the TIC curve analysis indexes were statistically significant between the two groups (all P<0.05). The difference in lesion temporal phase variability was statistically significant between the two groups ( P<0.05). After further screening by multifactorial analysis, the accuracy and misdiagnosis rates were 87.40% and (17.90±3.90)% in the qualitative analysis-based decision tree model respectively, and 90.50% and (21.10±4.20) % in the qualitative and TIC curve-based analysis decision tree model respectively. The ROC curves were plotted according to the two groups of models, and the areas under the curves were 0.915 and 0.931 respectively. Conclusions:A decision tree model based on ultrasonographic image analysis has diagnostic value for the differential diagnosis of atypical adenomyosis and uterine fibroids.