Objective To propose a 4-type ultrasound classification system based on the pathological features of hepatic alveolar echinococcosis (HAE), and to explore its consistency with pathological classification and clinical application value. Methods A retrospective analysis was performed on patients who were pathologically diagnosed with HAE after surgery at the First Affiliated Hospital of Xinjiang Medical University from January 2018 to December 2024. The ultrasound data, pathological data and treatment modalities of the patients were collected. Ultrasound examinations were conducted to record the location, maximum diameter, internal echo of the lesion, liquefactive necrosis area and calcification range. Referring to the ultrasound results and postoperative pathological features of the lesions, the lesions were divided into 4 types: infiltrative type, calcified type, liquefied type and complex type. The inter-observer consistency of ultrasound classification and the consistency between ultrasound classification and pathological results were comparatively analyzed, and the consistency evaluation was performed using the Kappa value. The differences in ultrasound-related parameters among the 4 types of lesions were compared, including the maximum diameter, the proportion of solid area, the proportion of calcified area, the proportion of liquefied area, and the hypoechoic halo around the lesion. The patient type was determined based on the classification of the largest lesion of the patient, and the clinical treatment measures of the patients were collected simultaneously to analyze the correlation between patient types and treatment modalities. Statistical analysis was carried out using SPSS 26.0 software. Results A total of 344 HAE patients and 469 HAE lesions were finally included. The ultrasound classification results showed 227 infiltrative lesions, 73 calcified lesions, 106 liquefied lesions and 63 complex lesions; the pathological classification results showed 217 infiltrative lesions, 81 calcified lesions, 110 liquefied lesions and 61 complex lesions. The overall coincidence rate of ultrasound classification was 94.5% (443/469), and the coincidence rates of each type of lesion were 100% (73/73) for calcified type, 97.2% (103/106) for liquefied type, 92.5% (210/227) for infiltrative type, and 90.5% (57/63) for complex type, respectively. The inter-observer consistency Kappa value was 0.936, and the Kappa value for the consistency between ultrasound classification and pathological results was 0.918. The differences in the proportions of solid, calcified, liquefied components and the maximum diameter among the 4 types of lesions were all statistically significant (H = 381.729, 237.657, 384.372, 101.102, all P < 0.05). 76.7% (264/344) of the patients underwent radical resection for HAE, 21.2% (73/344) underwent autologous liver transplantation, and 2.0% (7/344) underwent allogeneic liver transplantation. Preoperatively, 12.8% (44/344) of the patients received palliative treatment, including 16 cases of percutaneous transhepatic biliary decompression, and 25 cases of liquefied type and 3 cases of complex type underwent puncture drainage of the abscess cavity. The proportions of patients with different types were 44.5% (153/344) for infiltrative type, 12.5% (43/344) for calcified type, 27.3% (94/344) for liquefied type, and 15.7% (54/344) for complex type. Correlation analysis showed that there was a statistically significant difference in the selection rate of abscess cavity puncture and drainage among different patient types (χ² = 47.32, P < 0.01). Although the difference in the selection rate of radical lesion resection among different patient types was statistically significant (χ² = 10.47, P < 0.05), after Bonferroni correction (α = 0.008 33), there was no statistically significant difference in the selection rate between any two types. Conclusion This HAE ultrasound classification is highly consistent with pathological features and demonstrates high reproducibility, with each subtype possessing characteristic ultrasound parameters. This classification method, by identifying the main components of the lesion preoperatively, provides the imaging basis for the individualized treatment of hepatic alveolar echinococcosis.