Image Fusion and 3-Dimensional Roadmapping in Endovascular Surgery. Review uri icon

Overview

abstract

  • Practitioners of endovascular surgery have historically used 2-dimensional (2D) intraoperative fluoroscopic imaging, with intravascular contrast opacification, to treat complex 3-dimensional (3D) pathology. Recently, major technical developments in intraoperative imaging have made image fusion techniques possible, the creation of a 3D patient-specific vascular roadmap based on preoperative imaging which aligns with intraoperative fluoroscopy, with many potential benefits. First, a 3D model is segmented from preoperative imaging, typically a computed tomography scan. The model is then used to plan for the procedure, with placement of specific markers and storing of C-arm angles that will be used for intraoperative guidance. At the time of the procedure, an intraoperative cone beam computed tomography is performed, and the 3D model is registered to the patient's on-table anatomy. Finally, the system is used for live guidance in which the 3D model is codisplayed with overlying fluoroscopic images. There are many applications for image fusion in endovascular surgery. We have found it to be particularly useful for endovascular aneurysm repair (EVAR), complex EVAR, thoracic EVAR, carotid stenting, and for type 2 endoleaks. Image fusion has been shown in various settings to lead to decreased radiation dose, less iodinated contrast use, and shorter procedure times. In the future, fusion models may be able to account for vessel deformation caused by the introduction of stiff wires and devices, and the user-dependent steps may become more automated. In its current form, image fusion has already proven itself to be an essential component in the planning and success of complex endovascular procedures.

publication date

  • May 22, 2018

Research

keywords

  • Computed Tomography Angiography
  • Cone-Beam Computed Tomography
  • Endovascular Procedures
  • Imaging, Three-Dimensional
  • Multimodal Imaging
  • Radiographic Image Interpretation, Computer-Assisted
  • Radiography, Interventional
  • Surgery, Computer-Assisted
  • Vascular Diseases

Identity

Scopus Document Identifier

  • 85048809069

Digital Object Identifier (DOI)

  • 10.1016/j.avsg.2018.03.032

PubMed ID

  • 29793018

Additional Document Info

volume

  • 52