Cardio‐respiratory motion compensation for coronary roadmapping in fluoroscopic imaging

• Published in: Medical physics (Lancaster) 2024-09, Vol.51 (9), p.6103-6119
• Main Authors: Chen, Ying, Ai, Danni, Yu, Yang, Fan, Jingfan, Yu, Wenyuan, Xiao, Deqiang, Lin, Yucong, Yang, Jian
• Format: Article
• Language: English
• Subjects: cardiac state synchronization; cardio‐respiratory motion compensation; catheter motion estimation; Coronary Angiography; Coronary Vessels - diagnostic imaging; dynamic coronary roadmapping; Electrocardiography; Fluoroscopy; Heart - diagnostic imaging; Humans; Image Processing, Computer-Assisted - methods; Movement; Respiration
• ISSN: 0094-2405; 2473-4209; 2473-4209
• DOI: 10.1002/mp.17241

Background 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. Purpose 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. Methods 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. Results 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. Conclusions 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.