Automatic 2D-3D Registration without Contrast Agent during Neurovascular Interventions

TL;DR

This paper presents a novel image-based 2D-3D registration method for neurovascular interventions that does not require contrast agents, achieving high accuracy and robustness suitable for clinical and retrospective applications.

Contribution

It introduces a contrast-agent-free registration algorithm that uses gradient features for alignment, validated with phantom and clinical data, enabling retrospective analysis without workflow disruption.

Findings

97% success rate in phantom experiments with <1mm and 3° errors

87% clinical registration success with <1mm error

84% clinical registration success with <3° rotational error

Abstract

Fusing live fluoroscopy images with a 3D rotational reconstruction of the vasculature allows to navigate endovascular devices in minimally invasive neuro-vascular treatment, while reducing the usage of harmful iodine contrast medium. The alignment of the fluoroscopy images and the 3D reconstruction is initialized using the sensor information of the X-ray C-arm geometry. Patient motion is then corrected by an image-based registration algorithm, based on a gradient difference similarity measure using digital reconstructed radiographs of the 3D reconstruction. This algorithm does not require the vessels in the fluoroscopy image to be filled with iodine contrast agent, but rather relies on gradients in the image (bone structures, sinuses) as landmark features. This paper investigates the accuracy, robustness and computation time aspects of the image-based registration algorithm. Using phantom experiments 97% of the registration attempts passed the success criterion of a residual registration error of less than 1 mm translation and 3{\deg} rotation. The paper establishes a new method for validation of 2D-3D registration without requiring changes to the clinical workflow, such as attaching fiducial markers. As a consequence, this method can be retrospectively applied to pre-existing clinical data. For clinical data experiments, 87% of the registration attempts passed the criterion of a residual translational error of < 1 mm, and 84% possessed a rotational error of < 3{\deg}.