Topology observing 3D device reconstruction from continuous-sweep limited angle fluoroscopy

Abstract

Background: Minimally invasive procedures usually require navigating a microcatheter and guidewire through endoluminal structures such as blood vessels and airways to sites of the disease. For numerous clinical applications, two-dimensional (2D) fluoroscopy is the primary modality used for real-time image guidance during navigation. However, 2D imaging can pose challenges for navigation in complex structures. Real-time 3D visualization of devices within the anatomic context could provide considerable benefits for these procedures. Continuous-sweep limited angle (CLA) fluoroscopy has recently been proposed to provide a compromise between conventional rotational 3D acquisitions and real-time fluoroscopy.

Purpose: The purpose of this work was to develop and evaluate a noniterative 3D device reconstruction approach for CLA fluoroscopy acquisitions, which takes into account endoluminal topology to avoid impossible paths between disconnected branches.

Methods: The algorithm relies on a static 3D roadmap (RM) of vessels or airways, which may be generated from conventional cone beam CT (CBCT) acquisitions prior to navigation. The RM is converted to a graph representation describing its topology. During catheter navigation, the device is segmented from the live 2D projection images using a deep learning approach from which the centerlines are extracted. Rays from the focal spot to detector pixels representing 2D device points are identified and intersections with the RM are computed. Based on the RM graph, a subset of line segments is selected as candidates to exclude device paths through disconnected branches of the RM. Depth localization for each point along the device is then performed by finding the point closest to the previous 3D reconstruction along the candidate segments. This process is repeated as the projection angle changes for each CLA image frame. The approach was evaluated in a phantom study in which a catheter and guidewire were navigated along five pathways within a complex vessel phantom. The result was compared to static cCBCT acquisitions of the device in the final position.

Results: The average root mean squared 3D distance between CLA reconstruction and reference centerline was $1.87\pm 0.30$ mm. The Euclidean distance at the device tip was $2.92\pm 2.35$ mm. The correct pathway was identified during reconstruction in $100\%$ of frames ( $n=1475$ ). The percentage of 3D device points reconstructed inside the 3D roadmap was $91.83\pm 2.52\%$ with an average distance of $0.62\pm 0.30$ mm between the device points outside the roadmap and the nearest point within the roadmap.

Conclusions: This study demonstrates the feasibility of reconstructing curvilinear devices such as catheters and guidewires during endoluminal procedures including intravascular and transbronchial interventions using a noniterative reconstruction approach for CLA fluoroscopy. This approach could improve device navigation in cases where the structure of vessels or airways is complex and includes overlapping branches.

Keywords: 3D reconstruction; C‐arm; catheter navigation; fluoroscopy; real‐time.