Correlation between super-resolution ultrasound imaging features and microvascular invasion in hepatocellular
Chaonan Chen1,2, Xin Li2,3, Shizhe An4
1Department of Interventional Radiology, Beijing Friendship Hospital, Capital Medical University, Beijing, China.
Background:
Microvascular invasion (MVI) is a critical histopathological determinant of poor prognosis in hepatocellular carcinoma (HCC). Conventional imaging modalities remain limited in their ability to depict microvascular architecture or quantify vascular parameters in vivo . Super-resolution ultrasound (SR-US), based on ultrasound localization microscopy (ULM), facilitates the visualization and quantitative assessment of intratumoral microvasculature beyond the diffraction limit, even in deep hepatic lesions. This study aimed to evaluate the clinical feasibility of SR-US in patients with HCC and explore the relationship between quantitative vascular parameters and MVI.
Methods:
Patients with pathologically confirmed HCC who underwent preoperative SR-US were prospectively enrolled. Microbubble tracking was performed using ULM to reconstruct super-resolution microvascular maps. Quantitative vascular parameters-including vessel density, flow velocity, complexity, and perfusion index-were extracted. MVI status was obtained from surgical pathology. Comparative analyses were conducted using Student's t-tests and Chi-square tests.
Results:
SR-US was successfully performed in 70 patients. Quantitative analysis revealed that the complexity of the entire tumor was significantly higher in the non-MVI group than in the MVI group (1.63 ± 0.70 vs. 1.59 ± 0.52, P = 0.024). A similar trend was observed in tumor center complexity (1.57 ± 0.94 vs. 1.51 ± 0.77, P = 0.004). No significant between-group differences were found in perfusion index, microbubble density, or microbubble velocity (all P > 0.05).
Conclusion:
SR-US is a feasible, noninvasive technique for visualizing and quantifying intratumoral microvasculature in human HCC. Its quantitative parameters, particularly complexity, are significantly associated with MVI, demonstrating its potential for preoperative risk stratification in clinical settings.
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