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不同非对比增强的MRA技术对血管流模型中的流量可见度的影响

Yigit Ozpeynirci¹, Margarita Gorodezky², Augusto Fava Sanches¹

¹Institute for Diagnostic and Interventional Neuroradiology, University Hospital, Ludwig-Maximilians-University (LMU), Marchioninistr. 15, 81377 Munich, Germany.

Diagnostics (Basel, Switzerland)

|June 19, 2024

概括

带有深度学习重建的静音MRA增强了流量转移支架的可视化,优于传统的TOF MRA. 这种技术可以提高对治疗内动脉瘤的支架穿透率的评估.

科学领域:

医疗成像医学成像
生物医学工程生物医学工程
神经干预放射学神经干预放射学

背景情况:

静态磁共振血管学 (MRA) 显示了评估内动脉瘤治疗支架的潜力.
开发了一种新的深度学习 (DL) 算法,用于消除和破坏静音MRA.
流量转移支架对于治疗内动脉瘤至关重要.

研究的目的:

为了比较不同MRA技术在模型中的流量转移支架的流量可见性.
在这种情况下,评估基于DL的静音MRA重建算法的有效性.

主要方法:

两个尺寸的Surpass Evolve支架被放置在流动循环中的管中.
使用飞行时间 (TOF) MRA和静音MRA进行了3.0TMRI扫描.
对静音MRA数据进行DL重建;测量信号强度.

主要成果:

与TOF MRA相比,静音MRA和DL重建显示了较高的内信号与背景和信号与容器的比率.
TOF MRA 图像显示了来自支架尖端的严重工件,这些在静音MRA 扫描中不存在.

结论:

DL重建显著改善了静音MRA质量,用于评估流转变器支架的通透性.
与这些设备的TOF MRA相比,具有DL的静音MRA提供了优越的光度可视化.

关键词:

深度学习是一种深度学习.流量转移器是一个流量转移器.头骨内动脉瘤是什么意思没有声音的MRA.

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