Department of Oral and Maxillofacial Surgery, Peking University School and Hospital of Stomatology, Beijing 100081, PR China; National Center of Stomatology & National Clinical Research Center for Oral Diseases & National Engineering Laboratory for Digital and Material Technology of Stomatology, Beijing 100081, PR China.
Department of Oral and Maxillofacial Radiology, Peking University School and Hospital of Stomatology, Beijing 100081, PR China; National Center of Stomatology & National Clinical Research Center for Oral Diseases & National Engineering Laboratory for Digital and Material Technology of Stomatology, Beijing 100081, PR China.
Oral Surg Oral Med Oral Pathol Oral Radiol. 2024 Sep;138(3):440-452. doi: 10.1016/j.oooo.2024.04.014. Epub 2024 Apr 25.
To compare clinicopathological and imaging features of micro- and minitumors of the parotid gland and provide a reference for preoperative prediction of benign vs malignant status.
Patients with parotid gland tumors treated surgically were selected. Relevant clinicopathological and imaging data were collected for patients with maximum tumor diameters ≤20 mm on preoperative computed tomography (CT). The lesions were divided into 2 groups, microtumors and minitumors, based on maximum tumor diameter. CT imaging features of benign and malignant tumors were compared through binary logistic regression analysis.
Microtumors and minitumors were categorized by maximum diameters <10 mm (n = 74) and 10-20 mm (n = 611), respectively. Benign and malignant minitumors exhibited significant differences in boundary, tumor density, margin morphology, spiculation margin, and CT values in the plain and arterial phase (P ≤ .027), resembling those found in typical malignant parotid gland tumors. However, no significant differences were observed between benign and malignant microtumors. Logistic regression analysis identified boundary, margin morphology, and spiculation margin as independent predictors of malignancy. The prediction model excelled in identifying benign lesions but was less successful in identifying malignancies.
Parotid gland minitumors had imaging features similar to typical larger malignant tumors. Active exclusion of the malignant risk and early surgical treatment is recommended for these tumors.
比较腮腺微、小肿瘤的临床病理和影像学特征,为术前预测良恶性状态提供参考。
选择接受手术治疗的腮腺肿瘤患者。收集术前计算机断层扫描(CT)最大肿瘤直径≤20mm的患者的相关临床病理和影像学资料。根据最大肿瘤直径将病变分为微肿瘤和小肿瘤两组。通过二元逻辑回归分析比较良性和恶性肿瘤的 CT 影像学特征。
微肿瘤和小肿瘤的最大直径分别为<10mm(n=74)和10-20mm(n=611)。良性和恶性小肿瘤在边界、肿瘤密度、边缘形态、毛刺边缘和平扫及动脉期 CT 值方面存在显著差异(P≤.027),与典型的恶性腮腺肿瘤相似。然而,良性和恶性微肿瘤之间没有观察到显著差异。逻辑回归分析确定边界、边缘形态和毛刺边缘是恶性的独立预测因素。该预测模型在识别良性病变方面表现出色,但在识别恶性病变方面效果较差。
腮腺小肿瘤具有与典型较大恶性肿瘤相似的影像学特征。对于这些肿瘤,建议积极排除恶性风险并进行早期手术治疗。