Clinical Features and Ultrasonographic Manifestations of Retroperitoneal Nerve Sheath Tumors.

Objectives: Retroperitoneal nerve sheath tumors are uncommon, representing a small fraction of all primary retroperitoneal neoplasms. Accurate differentiation between benign and malignant forms is essential for optimal clinical management. This study assessed the clinical profiles and sonographic traits of retroperitoneal nerve sheath tumors with the goal of enhancing diagnostic precision and developing therapeutic strategies.

Methods: A retrospective analysis of patients diagnosed with benign retroperitoneal nerve sheath tumors who completed surgical treatment and underwent ultrasound imaging was carried out. Tumors were classified based on sonographic features and blood flow characteristics as per Adler's grading system. Statistical analysis was performed using SPSS 25.0. ROC curve analysis was carried out to determine the optimal diagnostic cutoff values.

Results: A total of 49 patients were included in the study. There were no significant variances in age, gender, or tumor localization among the groups. However, pronounced disparities were observed in tumor number, size, shape, definition of borders, internal echo pattern, structural composition, presence of calcification, and blood flow signals between the classic and malignant groups. Notably, malignant tumors tended to manifest as larger masses with indistinct margins and irregular shapes. The maximum tumor diameter emerged as a discriminating factor for malignancy, with a diagnostic cutoff of 9.9 cm, yielding an AUC of 0.754 from the ROC curve analysis.

Conclusion: This study outlines the distinctive clinical and sonographic features of retroperitoneal nerve sheath tumors, with a particular focus on malignant subtypes. Ultrasonography emerges as a valuable diagnostic tool, contributing to the differentiation of tumor categories and potentially to the development of targeted treatment strategies. The identification of specific sonographic markers may facilitate the early detection and detailed characterization of these tumors, which could contribute to improved patient outcomes.