摘要目的 探讨MRI对膝关节半月板放射状撕裂的检出能力.方法 回顾性分析1085例经关节镜证实的膝关节半月板损伤中的半月板放射状撕裂107例(9.9%)患者的MRI资料,同时按住院号顺序采用等足巨抽样方法 ,抽取100例经关节镜证实的非放射状撕裂的半月板损伤患者作为对照组.所有患者均经MR检查,观察裂隙征及裂隙行走征、半月板分离征、半月板消失征及小半月板征4种征象,与关节镜结果 比较.结果 (1)107例半月板放射状撕裂患者中,最常见的发生部位是外侧半月板体部(71例,66.4%)和前体交界部(25例,23.4%).(2)107例半月板放射状撕裂中,MRI诊断放射状撕裂102例.100例半月板非放射状撕裂的半月板损伤中,MRI诊断11例为放射状撕裂,MRI诊断半月板放射状撕裂的敏感度、特异度、阳性预测值、阴性预测值分别为95.3%(102/107)、89.0%(89/100)、90.3%(102/113)、94.7%(89/94).(3)裂隙征和半月板分离征出现频率最高,102例中分别出现59例(57.8%)和43例(42.2%),是诊断放射状撕裂最重要的MRI征象.结论 MRI诊断半月板放射状撕裂的准确率较高,是目前术前无创诊断的最佳方法 .

abstractsObjective To access the ability of MRI for detecting the radial meniscal tears.Methods Arthroscopy of the knee was performed by a single orthopedic surgeon on 1085 patients. On the basis of the results of arthroscopy, 107(9.9%) knees had radial tears of menisci. Through interval sampling of the patients with meniscal tears but not radial tears, 100 patients were selected as a controlled group. All MR images were analyzed by two radiologists independently. Four radiological signs were used to detect radial tears: cleft and marching cleft sign, detached sign, ghost sign, and small meniscal sign. All the features of MRI were compared with the results of the arthroscopy. Results (1) The most frequent location of radial tears was the midbody of lateral meniscus (71/107, 66. 4%)followed by the boundary of anterior horn and midbody of the lateral meniscus (25/107, 23.4%). (2) One hundred and two of 107 patients were identified as radial tears on MRI. However, 11 of 100 patients with non-radial tears were misdiagnosed as radial tears by MRI. The sensitivity, specificity, positive predictive value, and negative predictive value of MRI were 95.3% (102/107),89.0% (89/100),90.3% (102/113), and 94.7% (89/94),respectively. (3) The cleft sign (59/102, 57.8%) and detached sign (43/102, 42.2%) were the most frequent and important MRI signs. Conclusion The accuracy of MRI to identify the radial meniseal tears'is very high and MRI is the best imaging modality for patients suspected of radial meniscal tears.