摘要
目的探讨MRI上股骨头坏死面积比例测量对股骨头坏死早期诊断的准确性,并用于前瞻性预测坏死后塌陷的风险率。方法2002年3月至2005年10月,对32例（47髋）股骨头坏死患者,进行24个月的随访,测量MRI上的坏死面积比例,并与同期X线片进行图像分析处理对比,所得数据行统计学分析。结果①经过随访,共有26例（37髋）发生了塌陷,原Ⅰ期的股骨头坏死有17例发生了塌陷,进展率为81%;原Ⅱ期的股骨头坏死有20例发生了塌陷,进展率为76%,两者相比无统计学意义（P〉0.05）。②在发生塌陷组,平均坏死面积比例为（58.7±14.4）%（32.5%～92.5%）;在未塌陷组,平均坏死面积的比例为（17.3±11.9）%（4.7%～41.6%）,两者相比,差异有统计学意义（P〈0.05）。股骨头坏死面积比例小于30时为低危险组;在30～42之间时为中等危险组;大于43时为高危险组。结论MRI上坏死面积比例的计算能较精确的反映股骨头坏死的程度,能前瞻性的预测坏死后塌陷的风险率。
Objective To explore the accuracy of percentage of necrotic surface of area in earlier diagnosing collapse of femoral head osteonecrosis and predicting collapse of the osteonecrosis. Methods From Mach 2002 to October 2005, percentage of necrotic surface of area of 32 cases （47 hips） Of femoral head osteonecrosis were calculated according to MRI imaging in 24 months follow - up, and contrast to the X - ray in same period. The data were analysed. Results ①According to follow - up, of the 21 hips that had been classified as stage I , 17 hip had collapsed. The rate of progression was 81% ; of the 26 hip that had been classified as stage Ⅱ , 20 hips had collapsed. The rate of progression was 76%. There is no significant difference between I and Ⅱ stage（ P 〉0.05）. ②In collapsed group, the ratio of necrotic articular surface area （NASA） to whole articular surface area （WASA） was（58.7 ± 14. 4）% （32.5%～92.5% ） ;In no collapsed group, the ratio of NASA to WASA was （ 17.3 ± 11.9 ） % （4. 7%～ 41.6% ） ; There is significant difference between them （P 〈 0.05）. The collapse rate for three groups of the index of necrotic extent was 0 （index 〈 30） , 50% （ index 30～42 ）, 100% （ index 〉 42 ） respectively. There is significant difference between three groups （P 〈 0. 05 ） . Conclusion The ratio of NASA to WASA in patients with femoral head osteonecrosis can be accurately calculated with the MRI pictures. The possibility of collapse can be predicted by this method.
出处
《医药论坛杂志》
2008年第2期1-3,6,共4页
Journal of Medical Forum
基金
河南省科技厅重点攻关项目(0123030300)
关键词
磁共振
股骨头坏死面积比例
塌陷预测
MRI
The ratio of necrotic articular surface area
Predicting collapse
