摘要
目的:探讨磁共振平扫、磁共振动态增强(DCE-MRI)和扩散加权成像(DWI)对骨肿瘤及肿瘤样病变的诊断和鉴别诊断价值。方法:选择61例临床资料完整的骨肿瘤及肿瘤样病变患者,先行常规MRI平扫,然后依次进行不同b值的DWI扫描、DCE-MRI,最后进行延迟MRI增强扫描。结果:良、恶性骨肿瘤边缘形态和边界清晰度比较,差异均有统计学意义(χ2=32.262和45.131,P均<0.001),病变内信号均匀性和病灶周围有无骨髓水肿比较,差异无统计学意义(χ2=0.713和1.915,P均>0.05)。良、恶性骨肿瘤强化程度(Z=3.488,P<0.001)、时间-信号强度曲线(TIC)分布类型(χ2=15.826,P=0.001)比较,差异有统计学意义。TIC取Ⅰ、Ⅱ型曲线为恶性诊断标准,诊断恶性肿瘤的特异性为69.57%,准确性为72.13%,敏感性为73.68%,阳性预测值为80.00%,阴性预测值为61.54%。良、恶性骨肿瘤之间的DWI信号比较,差异无统计学意义(χ2=1.225,P=0.268)。结论:磁共振平扫、DCE-MRI和DWI有助于鉴别骨肿瘤良、恶性病变。
Aim:To analyze bone tumors and tumor-like lesions in plain MRI,dynamic contrast-enhanced MRI(DCE-MRI)and diffusion weighted imaging(DWI) and to explore the clinical diagnosis and differential diagnosis of them.Methods:A total of 61 cases were selected.The first step was MRI plain scan,and then turned to different b-value DWI scan,the DCE MRI scan,and finally conventional contrast-enhanced MRI scan.Results:The shape of the edge and boundary definition between benign and malignant lesions were both of statistical significance(χ2=32.262,45.131,P0.001).The signal uniformity within lesions and the availability of bone marrow edema around lesions was not different(χ2=0.713,1.915,P0.05).In the matter of strengthening extent,benign and malignant lesions were different(Z=3.488,P0.001).TIC types of distribution between benign and malignant bone tumors were different(χ2=15.826,P=0.001).Ⅰ,Ⅱ-type time-signal intensity curves were defined as malignant diagnostic criteria,and the sensitivity of diagnosis of malignant tumors reached 73.68%,specificity was 69.57%,accuracy was 72.13%,positive predicted value was 80.00%,and negative predicted value was 61.54%.DWI signal between benign and malignant bone tumor was not different(χ2=1.225,P=0.268).Conclusion:Plain MRI,DCE-MRI and DWI might be helpful for the differentiation of bone tumors and tumor-like lesions.
出处
《郑州大学学报(医学版)》
CAS
北大核心
2012年第6期850-853,共4页
Journal of Zhengzhou University(Medical Sciences)
关键词
骨肿瘤
磁共振成像
动态增强
扩散加权成像
bone tumor
magnetic resonance imaging
dynamic contrast-enhance
diffusion-weighted imaging