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Purpose <p>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.</p> Methods <p>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.</p> Results <p>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&#xa0;mm in horizontal projection distance along the artery midline, with an average run-time of 16&#xa0;s.</p> Conclusion <p>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.</p>

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

  • 期刊论文

  • 发表日期：

    2025年1月5日

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  • Moujan Saderi,
  • Jaykumar H. Patel,
  • Calder D. Sheagren,
  • Judit Csőre,
  • Trisha L. Roy,
  • Graham A. Wright

摘要

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.