Shu Hua, Ma Qian, Li Ao, Wang Pingping, Gao Yingqian, Yao Qiyu, Hu Yu, Ye Xinhua
Department of Ultrasound, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China.
Department of Ultrasound, Affiliated Zhongda Hospital of Southeast University, Nanjing, China.
Front Oncol. 2022 Apr 29;12:853232. doi: 10.3389/fonc.2022.853232. eCollection 2022.
To assess the diagnostic performance of US and MRI in predicting malignancy of soft tissue masses by using a scoring system.
A total of 120 cases of pathologically confirmed soft tissue masses (71 cases of malignant lesions and 49 cases of benign lesions) were enrolled. All patients underwent ultrasound and MRI examination prior to biopsy or surgical excision. A scoring system based on the parameters of conventional US and MRI to distinguish malignant and benign masses was established by the regression model. The receiver operating characteristic (ROC) analysis was used to evaluate the diagnostic performance of US and MRI.
Multivariate analysis showed that margin, maximum diameter, and vascular density were independent predictors for malignancy found by US, while maximum diameter, margin, and affected peripheral soft tissue were independent predictors for malignancy found by MRI. The mean scores of the benign and malignant groups were 2.8 ± 1.6, 5.1 ± 1.1 on US and 1.3 ± 1.2, 3.5 ± 0.9 on MRI. Based on the cut-off score of 3.5 and 2.5 calculated by ROC analysis, US and MRI had 92% and 87% sensitivity, 72% and 76% specificity, 86% and 89% accuracy, respectively. The combination of these two modalities achieved the sensitivity of 91%, specificity of 82%, and accuracy of 93%.
Both US and MRI can provide valuable information about the differential diagnosis between benign and malignant soft tissue masses. The combination of the two imaging-based scoring systems can increase the diagnostic performance, especially in specificity.
通过使用评分系统评估超声(US)和磁共振成像(MRI)在预测软组织肿块恶性程度方面的诊断性能。
纳入120例经病理证实的软组织肿块患者(71例恶性病变和49例良性病变)。所有患者在活检或手术切除前均接受了超声和MRI检查。通过回归模型建立了基于传统超声和MRI参数区分恶性和良性肿块的评分系统。采用受试者操作特征(ROC)分析评估超声和MRI的诊断性能。
多因素分析显示,边界、最大直径和血管密度是超声发现的恶性肿瘤的独立预测因素,而最大直径、边界和受累外周软组织是MRI发现的恶性肿瘤的独立预测因素。良性和恶性组在超声上的平均评分为2.8±1.6、5.1±1.1,在MRI上的平均评分为1.3±1.2、3.5±0.9。根据ROC分析计算出的截断分数3.5和2.5,超声和MRI的敏感性分别为92%和87%,特异性分别为72%和76%,准确性分别为86%和89%。这两种检查方式联合使用时,敏感性为91%,特异性为82%,准确性为93%。
超声和MRI均可为良性和恶性软组织肿块的鉴别诊断提供有价值的信息。两种基于成像的评分系统联合使用可提高诊断性能,尤其是在特异性方面。