3D ablation catheter localisation using individual C-arm x-ray projections

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

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 was1.87 ± 0.30 $1.87 \pm 0.30$ mm. The Euclidean distance at the device tip was2.92 ± 2.35 $2.92 \pm 2.35$ mm. The correct pathway was identified during reconstruction in100 % $100\%$ of frames (n = 1475 $n=1475$ ). The percentage of 3D device points reconstructed inside the 3D roadmap was91.83 ± 2.52 % $91.83 \pm 2.52\%$ with an average distance of0.62 ± 0.30 $0.62 \pm 0.30$ 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.

Recent technological advancements in thermometry

Thermometry is the key factor for achieving successful thermal therapy. Although invasive thermometry with a probe has been used for more than four decades, this method can only detect the local temperature within the probing volume. Noninvasive temperature imaging using a tomographic technique is ideal for monitoring hot-spot formation in the human body. Among various techniques, such as X-ray computed tomography, microwave tomography, echo sonography, and magnetic resonance (MR) imaging, the proton resonance frequency shift method of MR thermometry is the only method currently available for clinical practice because its temperature sensitivity is consistent in most aqueous tissues and can be easily observed using common clinical scanners. New techniques are being proposed to improve the robustness of this method against tissue motion. MR techniques for fat thermometry were also developed based on relaxation times. One of the latest non-MR techniques to attract attention is photoacoustic imaging.

A dynamic model-based approach to motion and deformation tracking of prosthetic valves from biplane x-ray images

PURPOSE

Transcatheter aortic valve replacement (TAVR) is a minimally invasive procedure in which a prosthetic heart valve is placed and expanded within a defective aortic valve. The device placement is commonly performed using two-dimensional (2D) fluoroscopic imaging. Within this work, we propose a novel technique to track the motion and deformation of the prosthetic valve in three dimensions based on biplane fluoroscopic image sequences.

METHODS

The tracking approach uses a parameterized point cloud model of the valve stent which can undergo rigid three-dimensional (3D) transformation and different modes of expansion. Rigid elements of the model are individually rotated and translated in three dimensions to approximate the motions of the stent. Tracking is performed using an iterative 2D-3D registration procedure which estimates the model parameters by minimizing the mean-squared image values at the positions of the forward-projected model points. Additionally, an initialization technique is proposed, which locates clusters of salient features to determine the initial position and orientation of the model.

RESULTS

The proposed algorithms were evaluated based on simulations using a digital 4D CT phantom as well as experimentally acquired images of a prosthetic valve inside a chest phantom with anatomical background features. The target registration error was 0.12 ± 0.04 mm in the simulations and 0.64 ± 0.09 mm in the experimental data.

CONCLUSIONS

The proposed algorithm could be used to generate 3D visualization of the prosthetic valve from two projections. In combination with soft-tissue sensitive-imaging techniques like transesophageal echocardiography, this technique could enable 3D image guidance during TAVR procedures.

4D interventional device reconstruction from biplane fluoroscopy

PURPOSE

Biplane angiography systems provide time resolved 2D fluoroscopic images from two different angles, which can be used for the positioning of interventional devices such as guidewires and catheters. The purpose of this work is to provide a novel algorithm framework, which allows the 3D reconstruction of these curvilinear devices from the 2D projection images for each time frame. This would allow creating virtual projection images from arbitrary view angles without changing the position of the gantries, as well as virtual endoscopic 3D renderings.

METHODS

The first frame of each time sequence is registered to and subtracted from the following frame using an elastic grid registration technique. The images are then preprocessed by a noise reduction algorithm using directional adaptive filter kernels and a ridgeness filter that emphasizes curvilinear structures. A threshold based segmentation of the device is then performed, followed by a flux driven topology preserving thinning algorithm to extract the segments of the device centerline. The exact device path is determined using Dijkstra's algorithm to minimize the curvature and distance between adjacent segments as well as the difference to the device path of the previous frame. The 3D device centerline is then reconstructed using epipolar geometry.

RESULTS

The accuracy of the reconstruction was measured in a vascular head phantom as well as in a cadaver head and a canine study. The device reconstructions are compared to rotational 3D acquisitions. In the phantom experiments, an average device tip accuracy of 0.35 ± 0.09 mm, a Hausdorff distance of 0.65 ± 0.32 mm, and a mean device distance of 0.54 ± 0.33 mm were achieved. In the cadaver head and canine experiments, the device tip was reconstructed with an average accuracy of 0.26 ± 0.20 mm, a Hausdorff distance of 0.62 ± 0.08 mm, and a mean device distance of 0.41 ± 0.08 mm. Additionally, retrospective reconstruction results of real patient data are presented.

CONCLUSIONS

The presented algorithm is a novel approach for the time resolved 3D reconstruction of interventional devices from biplane fluoroscopic images, thus allowing the creation of virtual projection images from arbitrary view angles as well as virtual endoscopic 3D renderings. Availability of this technique would enhance the ability to accurately position devices in minimally invasive endovascular procedures.