3D CT to 2D X-ray image registration for improved visualization of tibial vessels in endovascular procedures.

IF 2.3 3区 医学 Q3 ENGINEERING, BIOMEDICAL
Moujan Saderi, Jaykumar H Patel, Calder D Sheagren, Judit Csőre, Trisha L Roy, Graham A Wright
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引用次数: 0

Abstract

Purpose: During endovascular revascularization interventions for peripheral arterial disease, the standard modality of X-ray fluoroscopy (XRF) used for image guidance is limited in visualizing distal segments of infrapopliteal vessels. To enhance visualization of arteries, an image registration technique was developed to align pre-acquired computed tomography (CT) angiography images and to create fusion images highlighting arteries of interest.

Methods: X-ray image metadata capturing the position of the X-ray gantry initializes a multiscale iterative optimization process, which uses a local-variance masked normalized cross-correlation loss to rigidly align a digitally reconstructed radiograph (DRR) of the CT dataset with the target X-ray, using the edges of the fibula and tibia as the basis for alignment. A precomputed library of DRRs is used to improve run-time, and the six-degree-of-freedom optimization problem of rigid registration is divided into three smaller sub-problems to improve convergence. The method was tested on a dataset of paired cone-beam CT (CBCT) and XRF images of ex vivo limbs, and registration accuracy at the midline of the artery was evaluated.

Results: On a dataset of CBCTs from 4 different limbs and a total of 17 XRF images, successful registration was achieved in 13 cases, with the remainder suffering from input image quality issues. The method produced average misalignments of less than 1 mm in horizontal projection distance along the artery midline, with an average run-time of 16 s.

Conclusion: The sub-mm spatial accuracy of artery overlays is sufficient for the clinical use case of identifying guidewire deviations from the path of the artery, for early detection of guidewire-induced perforations. The semiautomatic workflow and average run-time of the algorithm make it feasible for integration into clinical workflows.

三维 CT 与二维 X 光图像配准,改善血管内手术中胫骨血管的可视化。
目的:在外周动脉疾病的血管内血管重建术干预过程中,用于图像引导的x线透视(XRF)标准模式在观察腘下血管远段时受到限制。为了增强动脉的可视化,研究人员开发了一种图像配准技术,用于对齐预获取的计算机断层扫描(CT)血管造影图像,并创建突出显示感兴趣动脉的融合图像。方法:捕获x射线龙门位置的x射线图像元数据初始化一个多尺度迭代优化过程,该过程使用局部方差掩盖归一化互相关损失,以腓骨和胫骨边缘为基础,将CT数据集的数字重建x射线(DRR)与目标x射线严格对齐。采用预先计算的drr库来提高运行时间,并将刚性配准的六自由度优化问题分解成三个较小的子问题来提高收敛性。在离体肢体的配对锥形束CT (CBCT)和XRF图像数据集上对该方法进行了测试,并评估了动脉中线的配准精度。结果:在来自4个不同肢体的cbct数据集中,共有17张XRF图像,其中13例成功配准,其余患者存在输入图像质量问题。该方法沿动脉中线水平投影距离平均误差小于1mm,平均运行时间为16s。结论:动脉覆盖层的亚毫米空间精度足以用于临床病例识别导丝偏离动脉路径,早期发现导丝引起的穿孔。该算法的半自动化工作流程和平均运行时间使其能够集成到临床工作流程中。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
International Journal of Computer Assisted Radiology and Surgery
International Journal of Computer Assisted Radiology and Surgery ENGINEERING, BIOMEDICAL-RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING
CiteScore
5.90
自引率
6.70%
发文量
243
审稿时长
6-12 weeks
期刊介绍: The International Journal for Computer Assisted Radiology and Surgery (IJCARS) is a peer-reviewed journal that provides a platform for closing the gap between medical and technical disciplines, and encourages interdisciplinary research and development activities in an international environment.
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