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脊柱侧弯融合区域及其相应 Lenke 分类的 Kohonen 神经网络描述。

A Kohonen neural network description of scoliosis fused regions and their corresponding Lenke classification.

机构信息

Laboratoire de recherche en imagerie et orthopédie, École de technologie supérieure Centre de recherche du CHUM, Hôpital Notre-Dame, 1560 rue Sherbrooke Est, local Y-1615, Montreal, QC, H2L 4M1, Canada.

出版信息

Int J Comput Assist Radiol Surg. 2012 Mar;7(2):257-64. doi: 10.1007/s11548-011-0667-0. Epub 2012 Jan 13.

Abstract

PURPOSE

Surgical instrumentation for adolescent idiopathic scoliosis (AIS) is a complex procedure where selection of the appropriate curve segment to fuse, i.e., fusion region, is a challenging decision in scoliosis surgery. Currently, the Lenke classification model is used for fusion region evaluation and surgical planning. Retrospective evaluation of Lenke classification and fusion region results was performed.

METHODS

Using a database of 1,776 surgically treated AIS cases, we investigated a topologically ordered self organizing Kohonen network, trained using Cobb angle measurements, to determine the relationship between the Lenke class and the fusion region selection. Specifically, the purpose was twofold (1) produce two spatially matched maps, one of Lenke classes and the other of fusion regions, and (2) associate these two maps to determine where the Lenke classes correlate with the fused spine regions.

RESULTS

Topologically ordered maps obtained using a multi-center database of surgically treated AIS cases, show that the recommended fusion region agrees with the Lenke class except near boundaries between Lenke map classes. Overall agreement was 88%.

CONCLUSION

The Lenke classification and fusion region agree in the majority of adolescent idiopathic scoliosis when reviewed retrospectively. The results indicate the need for spinal fixation instrumentation variation associated with the Lenke classification.

摘要

目的

青少年特发性脊柱侧凸(AIS)的手术器械是一项复杂的程序,选择要融合的适当的曲线段,即融合区域,是脊柱侧凸手术中的一个具有挑战性的决策。目前,Lenke 分类模型用于融合区域评估和手术规划。对 Lenke 分类和融合区域结果进行了回顾性评估。

方法

使用 1776 例接受手术治疗的 AIS 病例数据库,我们研究了拓扑有序的自组织 Kohonen 网络,该网络使用 Cobb 角测量值进行训练,以确定 Lenke 类与融合区域选择之间的关系。具体来说,目的有两个(1)生成两个空间匹配的地图,一个是 Lenke 类,另一个是融合区域,(2)将这两个地图关联起来,以确定 Lenke 类与融合脊柱区域的关联。

结果

使用接受手术治疗的 AIS 多中心病例数据库获得的拓扑有序地图表明,除了 Lenke 地图类之间的边界附近,推荐的融合区域与 Lenke 类一致。总体一致性为 88%。

结论

回顾性审查时,大多数青少年特发性脊柱侧凸的 Lenke 分类和融合区域是一致的。结果表明需要与 Lenke 分类相关联的脊柱固定器械变化。

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