Department of Interventional Neuroradiology, Pitié-Salpêtrière Hospital, Paris VI University, 47, Bd de l'Hôpital, 75013, Paris, France,
Eur Radiol. 2015 Feb;25(2):436-43. doi: 10.1007/s00330-014-3421-5. Epub 2014 Sep 20.
The purpose of our study was to distinguish the different components of a brain arteriovenous malformation (bAVM) on 3D rotational angiography (3D-RA) using a semi-automated segmentation algorithm.
Data from 3D-RA of 15 patients (8 males, 7 females; 14 supratentorial bAVMs, 1 infratentorial) were used to test the algorithm. Segmentation was performed in two steps: (1) nidus segmentation from propagation (vertical then horizontal) of tagging on the reference slice (i.e., the slice on which the nidus had the biggest surface); (2) contiguity propagation (based on density and variance) from tagging of arteries and veins distant from the nidus. Segmentation quality was evaluated by comparison with six frame/s DSA by two independent reviewers. Analysis of supraselective microcatheterisation was performed to dispel discrepancy.
Mean duration for bAVM segmentation was 64 ± 26 min. Quality of segmentation was evaluated as good or fair in 93% of cases. Segmentation had better results than six frame/s DSA for the depiction of a focal ectasia on the main draining vein and for the evaluation of the venous drainage pattern.
This segmentation algorithm is a promising tool that may help improve the understanding of bAVM angio-architecture, especially the venous drainage.
• The segmentation algorithm allows for the distinction of the AVM's components • This algorithm helps to see the venous drainage of bAVMs more precisely • This algorithm may help to reduce the treatment-related complication rate.
我们的研究目的是使用半自动分割算法在三维旋转血管造影（3D-RA）上区分脑动静脉畸形（bAVM）的不同成分。
使用 15 名患者（8 名男性，7 名女性；14 例幕上 bAVM，1 例幕下）的 3D-RA 数据来测试算法。分割分为两步进行：（1）从标记在参考切片（即包含最大表面的 nidus 的切片）上的传播（垂直然后水平）分割核；（2）从远离核的动脉和静脉的标记进行连续性传播（基于密度和方差）。分割质量通过两位独立审阅者与六帧/秒 DSA 的比较进行评估。分析超选择性微导管插入术以消除差异。
bAVM 分割的平均持续时间为 64±26 分钟。93%的病例分割质量评估为良好或尚可。与六帧/秒 DSA 相比，该分割算法在显示主引流静脉上的局灶性扩张和评估静脉引流模式方面具有更好的结果。
该分割算法是一种很有前途的工具，可以帮助提高对 bAVM 血管结构的理解，特别是静脉引流。
• 分割算法允许区分 AVM 的成分。• 该算法有助于更精确地观察 bAVMs 的静脉引流。• 该算法可能有助于降低治疗相关并发症的发生率。
