Image-guidance for transcatheter aortic valve implantation (TAVI) and cerebral embolic protection

Artificial intelligence in cardiovascular imaging and intervention

Recent progress in artificial intelligence (AI) includes generative models, multimodal foundation models, and federated learning, which enable a wide spectrum of novel exciting applications and scenarios for cardiac image analysis and cardiovascular interventions. The disruptive nature of these novel technologies enables concurrent text and image analysis by so-called vision-language transformer models. They not only allow for automatic derivation of image reports, synthesis of novel images conditioned on certain textual properties, and visual questioning and answering in an oral or written dialogue style, but also for the retrieval of medical images from a large database based on a description of the pathology or specifics of the dataset of interest. Federated learning is an additional ingredient in these novel developments, facilitating multi-centric collaborative training of AI approaches and therefore access to large clinical cohorts. In this review paper, we provide an overview of the recent developments in the field of cardiovascular imaging and intervention and offer a future outlook.

Fighting Cardiac Thromboembolism during Transcatheter Procedures: An Update on the Use of Cerebral Protection Devices in Cath Labs and EP Labs

Intraprocedural stroke is a well-documented and feared potential risk of cardiovascular transcatheter procedures (TPs). Moreover, subclinical neurological events or covert central nervous system infarctions are concerns related to the development of dementia, future stroke, cognitive decline, and increased risk of mortality. Cerebral protection devices (CPDs) were developed to mitigate the risk of cardioembolic embolism during TPs. They are mechanical barriers designed to cover the ostium of the supra-aortic branches in the aortic arch, but newer devices are able to protect the descending aorta. CPDs have been mainly designed and tested to provide cerebral protection during transcatheter aortic valve replacement (TAVR), but their use in both Catheterization and Electrophysiology laboratories is rapidly increasing. CPDs have allowed us to perform procedures that were previously contraindicated due to high thromboembolic risk, such as in cases of intracardiac thrombosis identified at preprocedural assessment. However, several concerns related to their employment have to be defined. The selection of patients at high risk of thromboembolism is still a subjective choice of each center. The aim of this review is to update the evidence on the use of CPDs in either Cath labs or EP labs, providing an overview of their structural characteristics. Future perspectives focusing on their possible future employment are also discussed.

Computed tomography angiography/magnetic resonance imaging-based preprocedural planning and guidance in the interventional treatment of structural heart disease

Preprocedural planning and periprocedural guidance based on image fusion are widely established techniques supporting the interventional treatment of structural heart disease. However, these two techniques are typically used independently. Previous works have already demonstrated the benefits of integrating planning details into image fusion but are limited to a few applications and the availability of the proprietary tools used. We propose a vendor-independent approach to integrate planning details into periprocedural image fusion facilitating guidance during interventional treatment. In this work, we demonstrate the feasibility of integrating planning details derived from computer tomography and magnetic resonance imaging into periprocedural image fusion with open-source and commercially established tools. The integration of preprocedural planning details into periprocedural image fusion has the potential to support safe and efficient interventional treatment of structural heart disease.

3D localization from 2D X-ray projection

PURPOSE

Most cardiology procedures are guided using X-ray (XR) fluoroscopy. However, the projective nature of the XR fluoroscopy does not allow for true depth perception as required for safe and efficient intervention guidance in structural heart diseases. For improving guidance, different methods have been proposed often being radiation-intensive, time-consuming, or expensive. We propose a simple 3D localization method based on a single monoplane XR projection using a co-registered centerline model.

METHODS

The method is based on 3D anatomic surface models and corresponding centerlines generated from preprocedural imaging. After initial co-registration, 2D working points identified in monoplane XR projections are localized in 3D by minimizing the angle between the projection lines of the centerline points and the working points. The accuracy and reliability of the located 3D positions were assessed in 3D using phantom data and in patient data projected to 2D obtained during placement of embolic protection system in interventional procedures.

RESULTS

With the proposed methods, 2D working points identified in monoplane XR could be successfully located in the 3D phantom and in the patient-specific 3D anatomy. Accuracy in the phantom (3D) resulted in 1.6 mm (± 0.8 mm) on average, and 2.7 mm (± 1.3 mm) on average in the patient data (2D).

CONCLUSION

The use of co-registered centerline models allows reliable and accurate 3D localization of devices from a single monoplane XR projection during placement of the embolic protection system in TAVR. The extension to different vascular interventions and combination with automatic methods for device detection and registration might be promising.

Computational Analysis of Balloon Catheter Behaviour at Variable Inflation Levels

Aortic valvuloplasty is a minimally invasive procedure for the dilatation of stenotic aortic valves. Rapid ventricular pacing is an established technique for balloon stabilization during this procedure. However, low cardiac output due to the pacing is one of the inherent risks, which is also associated with several potential complications. This paper proposes a numerical modelling approach to understand the effect of different inflation levels of a valvuloplasty balloon catheter on the positional instability caused by a pulsating blood flow. An unstretched balloon catheter model was crimped into a tri-folded configuration and inflated to several levels. Ten different inflation levels were then tested, and a Fluid-Structure Interaction model was built to solve interactions between the balloon and the blood flow modelled in an idealised aortic arch. Our computational results show that the maximum displacement of the balloon catheter increases with the inflation level, with a small step at around 50% inflation and a sharp increase after reaching 85% inflation. This work represents a substantial progress towards the use of simulations to solve the interactions between a balloon catheter and pulsating blood flow.

Real-time registration of 3D echo to x-ray fluoroscopy based on cascading classifiers and image registration

Three-dimensional (3D) transesophageal echocardiography (TEE) is one of the most significant advances in cardiac imaging. Although TEE provides real-time 3D visualization of heart tissues and blood vessels and has no ionizing radiation, x-ray fluoroscopy still dominates in guidance of cardiac interventions due to TEE having a limited field of view and poor visualization of surgical instruments. Therefore, fusing 3D echo with live x-ray images can provide a better guidance solution. This paper proposes a novel framework for image fusion by detecting the pose of the TEE probe in x-ray images in real-time. The framework does not require any manual initialization. Instead it uses a cascade classifier to compute the position and in-plane rotation angle of the TEE probe. The remaining degrees of freedom are determined by fast marching against a template library. The proposed framework is validated on phantoms and patient data. The target registration error for the phantom was 2.1 mm. In addition, 10 patient datasets, seven of which were acquired from cardiac electrophysiology procedures and three from trans-catheter aortic valve implantation procedures, were used to test the clinical feasibility as well as accuracy. A mean registration error of 2.6 mm was achieved, which is well within typical clinical requirements.

3D-XGuide: open-source X-ray navigation guidance system

PURPOSE

With the growing availability and variety of imaging modalities, new methods of intraoperative support have become available for all kinds of interventions. The basic principles of image fusion and image guidance have been widely adopted and are commercialized through a number of platforms. Although multimodal systems have been found to be useful for guiding interventional procedures, they all have their limitations. The integration of more advanced guidance techniques into the product functionality is, however, not easy due to the proprietary solutions of the vendors. Therefore, the purpose of this work is to introduce a software system for image fusion, real-time navigation, and working points documentation during transcatheter interventions performed under X-ray (XR) guidance.

METHODS

An interactive software system for cross-modal registration and image fusion of XR fluoroscopy with CT or MRI-derived anatomic 3D models is implemented using Qt application framework and VTK visualization pipeline. DICOM data can be imported in retrospective mode. Live XR data input is realized by a video capture card application interface.

RESULTS

The actual software release offers a graphical user interface with basic functionality including data import and handling, calculation of projection geometry and transformations between related coordinate systems, rigid 3D-3D registration, and template matching-based tracking and motion compensation algorithms in 2D and 3D. The link to the actual software release on GitHub including source code and executable is provided to support independent research and development in the field of intervention guidance.

CONCLUSION

The introduced system provides a common foundation for the rapid prototyping of new approaches in the field of XR fluoroscopic guidance. As a pure software solution, the developed system is potentially vendor-independent and can be easily extended to be used with the XR systems of different manufacturers.

CT-Overlay Hybrid Imaging to Facilitate Sentinel Cerebral Protection System Deployment in the Presence of an Anomalous Vertebral Artery Originating From the Aortic Arch During Transcatheter Aortic Valve Implantation

Stroke remains an important risk during transcatheter aortic valve implantation (TAVI). Though the use of the double-filter Sentinel cerebral protection system (Boston Scientific, Marlborough, MA, USA) may lower the stroke risk, the deployment of this device requires manipulation within the aortic arch and cranial arch vessels potentially causing dislodgment of atherosclerotic debris in the process thereby possibly offsetting its benefit with regards to reducing cerebral embolization. Apart from patient selection, minimizing maneuvering during deployment may improve the safety of device deployment. In this context, we illustrate a case using three-dimensional computed tomography (CT) - overlay to facilitate Sentinel cerebral protection system deployment during TAVI. Emphasis in this case rests on demonstration of how aforementioned periprocedural imaging may facilitate negotiation of anatomical variants and avoid inadvertent cannulation of an anomalous left vertebral artery originating from the aortic arch. Imaging guidance with this concept may minimize device manipulation and reduce the risk of cerebral embolization. Further systematic evaluation is needed to demonstrate whether this approach improves clinical outcomes.

Automatic aorta and left ventricle segmentation for TAVI procedure planning using convolutional neural networks

Transcatheter aortic valve implantation (TAVI) is a minimally invasive procedure which is performed on patients with aortic valve defects that are posing a high-risk for conducting a surgical treatment. Preoperative surgical planning and valve sizing play a crucial role in reducing surgery complications and adverse effects such as paravalvular leakage or stroke. Planning process incorporates performing measurements, detecting landmarks and visualizing relevant structures in 3D. To automatize this process, a segmentation is required. Due to the lack of methods enabling parallel aorta and left ventricle segmentation we propose a fully automatic neural network approach based on 2D U-Net architecture. Convolutional neural network architecture was trained on 44 studies (22 raw CTA datasets and 22 elastic deformed scans) and tested on another 18 stacks of data. During every epoch of network learning process cross validation was performed on 8 stacks. As a result, we achieve 0.95 mean Dice coefficient score with standard deviation 0.02 determining high precision of predicted aorta and left ventricle label maps.

Cerebral protection devices for transcatheter aortic valve replacement

Aortic stenosis is the most prevalent primary valve disease in developed countries. Its prevalence is increasing due to population aging. Transcatheter aortic valve replacement (TAVR) is a sterling therapy for symptomatic patients with severe aortic stenosis and high or intermediate surgery risk. The number of procedures has increased exponentially expanding to younger and lower risk patients. Despite new-generation TAVR devices and enhanced operator skills, cerebrovascular events (CVEs) carry on being one of the most severe complications, increasing morbi-mortality. CVE might be under reported because there are few studies with rigorous neurological clinical assessment. Several imaging studies show most of CVE after TAVR has a probable embolic etiology. The risk of CVE ranges from 2.7% to 5.5% at 30 days. As TAVR expands to younger and lower risk patients, the prevention of stroke plays an increasingly important role. Cerebral protection devices (CPD) were designed to reduce the risk of CVE during TAVR. This review describes the scientific evidence on CVE after TAVR and summarizes the performance and results of the main CPDs.

Cerebral embolic protection systems for transcatheter aortic valve replacement

In the recent years, ischemic brain injury related to embolization after transcatheter aortic valve replacement (TAVR) has received increased attention as new embolic protection strategies emerged to protect the brain. Diverse cerebral protection devices have been developed to reduce cerebral embolization during TAVR. These devices work through various mechanisms and are in different stages of clinical translation. This review provides the evidence-based review of peri-procedural stroke prevention during TAVR and summarizes currently available cerebral embolic protection devices.

Improved Registration of 3D CT Angiography with X-ray Fluoroscopy for Image Fusion During Transcatheter Aortic Valve Implantation

The fusion of 3D anatomical models derived from high-fidelity pre-interventional computed tomography angiography (CTA), and x-ray (XR) fluoroscopy to facilitate anatomical guidance is of huge interest for complex cardiac interventions like TAVI procedures with cerebral protection. Co-registration of CTA and XR has been introduced either based on additional intraoperative non-/contrast-enhanced cone-beam computed tomography (CBCT) or two separate aortograms. With the related increase of radiation exposure and/or contrast agent (CA) dose, a potential additional risk for the patient is introduced. Here, we propose a modified co-registration approach making use of arteriograms of the iliofemoral arteries, routinely performed during the femoral puncture and sheath introduction. On-the-fly refinement of the co-registration during the on-going procedure enables accurate co-registration without any additional angiograms, thus reducing CA, XR dose and procedure time, while simultaneously improving operator confidence and procedure safety.