摘要

目的探讨动态增强MRI时间-信号强度曲线(TIC)上升段最大斜率值和曲线类型在骨骼肌肉系统良、恶性肿瘤鉴别中的作用。方法采用多时相增强快速采集梯度回波序列，对93例骨骼肌肉系统肿瘤进行MR动态增强扫描，在斜率图上选取ROI，经Functool软件后处理，得到TIC，并将曲线分为Ⅰ、Ⅱ、Ⅲ型，计算曲线上升段最大斜率值。以病理结果为金标准，对TIC类型在良、恶性肿瘤中的分布差异和曲线的上升斜率值进行Χ^2检验或t检验。结果49例恶性肿瘤中，37例为Ⅰ型曲线，12例为Ⅱ型曲线；44例良性肿瘤中，26例为Ⅰ型曲线，7例为Ⅱ型曲线，11例为Ⅲ型曲线，曲线类型在良、恶性肿瘤中的分布差异具有统计学意义(Χ^2=14．008，P〈0．01)。良、恶性肿瘤曲线上升斜率值分别为6．80±3．35和6．80±2．71，差异无统计学意义(t=0．008，P〉0．05)。与形态学表现相结合，应用TIC类型对骨骼肌肉系统恶性肿瘤定性诊断的敏感度为100％，特异度为50％，阳性预测值为78％，阴性预测值为100％，准确度为82％。结论TIC类型结合形态学表现，能够提高MRI对骨骼肌肉系统肿瘤良、恶性鉴别的能力。

Objective To investigate enhancement MR imaging in the discrimination the value of time-intensity curve of dynamic contrast of benign and malignancy in musculoskeletal tumors. Methods Ninety patients were examined with fast acquisition with muhiphase enhanced fast GRE series. The TIC of lesions were obtained using slope images in which pixel intensity reflected the slope value. The curves were classified according to their shapes as type Ⅰ , washout enhancement; type Ⅱ, plateau enhancement; typeⅢ, gradual enhancement. Taking pathological diagnosis as gold standard, the power of the maximal enhancement slope and curve types in discriminating benign and malignant lesions was evaluated by appropriate statistic analysis. Results There were 49 malignant and 44 benign lesions. The distribution of curve types for malignant tumors was type Ⅰ 75.5 % ( 37/49 ) , type Ⅱ 24. 5 % ( 12/49 ). While the numbers for benign tumors was type Ⅰ 59. 1% ( 26/44 ), type Ⅱ 15.9% ( 7/44 ) and type Ⅲ 25.0% ( 11/44 ), respectively. The patterns of curve types in malignant lesions were different from benign lesions significantly (Χ^2 = 14. 008, P 〈 0. 01 ). The slope value in benign lesion was 6. 80 ± 3.35 and that in malignant lesion was 6. 80 ± 2.71. The difference was not statistically significant( t = 0. 008, P 〉 0. 05 ). Type Ⅰ and type Ⅱ (excluding lesions with typical benign morphology ) were suggestive of malignant tumors. Type Ⅲ was indicator of a benign lesion. The diagnostic indices for the shape of TIC criterion were： sensitivity 100% , specificity 50%, positive predictive value 78%, negative predictive value 100% and accuracy 82%, respectively. Conclusion Combined with the characteristic of morphology, the TIC improves the power of MR imaging in discriminating benign from malignant musculoskeletal tumors.