Beijing Engineering Research Center of Mixed Reality and Advanced Display, School of Optics and Photonics, Beijing Institute of Technology, Beijing, China.
Department of Cardiac Surgery, Beijing Anzhen Hospital, Capital Medical University, Beijing, China.
Med Phys. 2024 Sep;51(9):6103-6119. doi: 10.1002/mp.17241. Epub 2024 Jun 12.
Inferring the shape and position of coronary artery poses challenges when using fluoroscopic image guidance during percutaneous coronary intervention (PCI) procedure. Although angiography enables coronary artery visualization, the use of injected contrast agent raises concerns about radiation exposure and the risk of contrast-induced nephropathy. To address these issues, dynamic coronary roadmapping overlaid on fluoroscopic images can provide coronary visual feedback without contrast injection.
This paper proposes a novel cardio-respiratory motion compensation method that utilizes cardiac state synchronization and catheter motion estimation to achieve coronary roadmapping in fluoroscopic images.
For more accurate cardiac state synchronization, video frame interpolation is applied to increase the frame rate of the original limited angiographic images, resulting in higher framerate and more adequate roadmaps. The proposed method also incorporates a multi-length cross-correlation based adaptive electrocardiogram (ECG) matching to address irregular cardiac motion situation. Furthermore, a shape-constrained path searching method is proposed to extract catheter structure from both fluoroscopic and angiographic image. Then catheter motion is estimated using a cascaded matching approach with an outlier removal strategy, leading to a final corrected roadmap.
Evaluation of the proposed method on clinical x-ray images demonstrates its effectiveness, achieving a 92.8% F1 score for catheter extraction on 589 fluoroscopic and angiographic images. Additionally, the method achieves a 5.6-pixel distance error of the coronary roadmap on 164 intraoperative fluoroscopic images.
Overall, the proposed method achieves accurate coronary roadmapping in fluoroscopic images and shows potential to overlay accurate coronary roadmap on fluoroscopic image in assisting PCI.
在经皮冠状动脉介入治疗（PCI）过程中使用荧光透视图像引导时，推断冠状动脉的形状和位置具有挑战性。尽管血管造影术能够使冠状动脉可视化，但使用注射的造影剂会引起辐射暴露和对比剂诱导肾病的风险。为了解决这些问题，可以在荧光透视图像上叠加动态冠状动脉路标，而无需注射对比剂，从而提供冠状动脉的视觉反馈。
本文提出了一种新颖的心电呼吸运动补偿方法，该方法利用心脏状态同步和导管运动估计来实现荧光透视图像中的冠状动脉路标。
为了更准确的心脏状态同步，应用视频帧插值来提高原始有限血管造影图像的帧率，从而获得更高的帧率和更充分的路标。该方法还采用了基于多长度互相关的自适应心电图（ECG）匹配，以解决不规则的心脏运动情况。此外，提出了一种形状约束的路径搜索方法，从荧光透视和血管造影图像中提取导管结构。然后，使用带有异常值去除策略的级联匹配方法估计导管运动，最终得到校正后的路标。
在临床 X 射线图像上对所提出的方法进行评估，证明了其有效性，在 589 张荧光透视和血管造影图像上实现了导管提取的 92.8% F1 分数。此外，该方法在 164 张术中荧光透视图像上实现了冠状动脉路标 5.6 像素的距离误差。
总的来说，该方法实现了荧光透视图像中冠状动脉的精确路标，并且有可能在协助 PCI 时将准确的冠状动脉路标叠加在荧光透视图像上。
