医学
环空(植物学)
腰椎间盘突出症
椎间盘突出
腰椎
腰椎穿刺
解剖
外科
脑脊液
病理
植物
生物
作者
Vonne M. van Heeswijk,Ashvin Thambyah,Peter A. Robertson,Neil D. Broom
出处
期刊:Spine
[Lippincott Williams & Wilkins]
日期:2018-04-01
卷期号:43 (7): 467-476
被引量:12
标识
DOI:10.1097/brs.0000000000002336
摘要
Study Design. A study of mechanically induced herniation in punctured ovine discs followed by structural analysis. Objective. To investigate whether an annular puncture influences the path that herniation takes by providing direct passage for nucleus through the annulus and therefore whether it increases the risk of acute herniation from overload at the site of damage independent of any longer-term degeneration. Summary of Background Data. Ten years after treatment with discography both degenerative changes and frequency of herniation have been shown to increase compared to untreated discs. Although the effect of an annular puncture over time has been widely investigated the question of whether it increases the risk of acute herniation has not been resolved. Methods. The posterolateral annuli of healthy ovine lumbar discs were punctured with either a 25-gauge (n = 8) or a larger 18-gauge (n = 8) needle and then compressed in a flexed posture of 10° until initial indications of failure. The entire volume of the disc was visually assessed for structural damage by obtaining progressive, full transverse cross-sections of its entire height thus exposing all regions of the disc. Results. There was no association between the 25-gauge puncture and disc disruption and herniation. In contrast, nuclear material was observed to migrate through the 18-gauge needle puncture. Disruption of the lateral inner annulus was observed in 12 out of the 16 discs tested. Conclusion. The risk of acute herniation through the puncture site is dependent on the needle diameter used. Under the conditions employed the lateral inner annulus remains the site most vulnerable to disruption independent of the presence of a posterolateral puncture. Level of Evidence: N /A
科研通智能强力驱动
Strongly Powered by AbleSci AI