Patient-specific registration of 3D CT angiography (CTA) with X-ray fluoroscopy for image fusion during transcatheter aortic valve implantation (TAVI) increases performance of the procedure

Impact of cardiac and respiratory motion on the 3D accuracy of image-guided interventions on monoplane systems

PURPOSE

Image-guided intervention (IGI) systems have the potential to increase the efficiency in interventional cardiology but face limitations from motion. Even though motion compensation approaches have been proposed, the resulting accuracy has rarely been quantified using in vivo data. The purpose of this study is to investigate the potential benefit of motion-compensation in IGS systems.

METHODS

Patients scheduled for left atrial appendage closure (LAAc) underwent pre- and postprocedural non-contrast-enhanced cardiac magnetic resonance imaging (CMR). According to the clinical standard, the final position of the occluder device was routinely documented using x-ray fluoroscopy (XR). The accuracy of the IGI system was assessed retrospectively based on the distance of the 3D device marker location derived from the periprocedural XR data and the respective location as identified in the postprocedural CMR data.

RESULTS

The assessment of the motion-compensation depending accuracy was possible based on the patient data. With motion synchronization, the measured accuracy of the IGI system resulted similar to the estimated accuracy, with almost negligible distances of the device marker positions identified in CMR and XR. Neglection of the cardiac and/or respiratory phase significantly increased the mean distances, with respiratory motion mainly reducing the accuracy with rather low impact on the precision, whereas cardiac motion decreased the accuracy and the precision of the image guidance.

CONCLUSIONS

In the presented work, the accuracy of the IGI system could be assessed based on in vivo data. Motion consideration clearly showed the potential to increase the accuracy in IGI systems. Where the general decrease in accuracy in non-motion-synchronized data did not come unexpected, a clear difference between cardiac and respiratory motion-induced errors was observed for LAAc data. Since sedation and intervention location close to the large vessels likely impacts the respiratory motion contribution, an intervention-specific accuracy analysis may be useful for other interventions.

Improved stereo perception in coronary angiography using the X-ray tube as the viewpoint and validation with 3D printed models

Coronary angiography (CAG) provides two-dimensional images, but a clinician who is experienced in percutaneous coronary interventions can use information from these images to interpret spatial depth and infer the three-dimensional (3D) locations of vessels. We hypothesized that CAG results were equivalent to the mirror image of a coronary artery perspective projection, and a stereo perception could be easily established when the viewpoint of the angiogram was the X-ray tube instead of the detector. To eliminate the influence of heartbeat and respiration, a 3D-printed a coronary artery model was constructed for analysis. The effects of gantry movements during digital subtraction angiography (DSA) on the image were used to identify factors that affected DSA image transformation. Then, based on these factors, DSA imaging was simulated using UG NX software with three methods: (i) a perspective projection with the detector as the viewpoint; (ii) a parallel projection; and (iii) a mirror image of the perspective projection with the X-ray tube as the viewpoint. Finally, the resulting 3D images were compared with the DSA image. Our mirror image of the coronary artery perspective projection that used the X-ray tube as the viewpoint fused precisely with the CAG results and provided exact simulations of all the effects of DSA gantry movements on the DSA image. CAG results were equivalent to the mirror image of coronary artery perspective projection, and the stereo perception was easily established using the X-ray tube as the viewpoint.

Multi-modality cardiac image computing: A survey

Multi-modality cardiac imaging plays a key role in the management of patients with cardiovascular diseases. It allows a combination of complementary anatomical, morphological and functional information, increases diagnosis accuracy, and improves the efficacy of cardiovascular interventions and clinical outcomes. Fully-automated processing and quantitative analysis of multi-modality cardiac images could have a direct impact on clinical research and evidence-based patient management. However, these require overcoming significant challenges including inter-modality misalignment and finding optimal methods to integrate information from different modalities. This paper aims to provide a comprehensive review of multi-modality imaging in cardiology, the computing methods, the validation strategies, the related clinical workflows and future perspectives. For the computing methodologies, we have a favored focus on the three tasks, i.e., registration, fusion and segmentation, which generally involve multi-modality imaging data, either combining information from different modalities or transferring information across modalities. The review highlights that multi-modality cardiac imaging data has the potential of wide applicability in the clinic, such as trans-aortic valve implantation guidance, myocardial viability assessment, and catheter ablation therapy and its patient selection. Nevertheless, many challenges remain unsolved, such as missing modality, modality selection, combination of imaging and non-imaging data, and uniform analysis and representation of different modalities. There is also work to do in defining how the well-developed techniques fit in clinical workflows and how much additional and relevant information they introduce. These problems are likely to continue to be an active field of research and the questions to be answered in the future.

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.

Deep learning-based framework for motion-compensated image fusion in catheterization procedures

OBJECTIVE

Augmenting X-ray (XR) fluoroscopy with 3D anatomic overlays is an essential technique to improve the guidance of the catheterization procedures. Unfortunately, cardiac and respiratory motion compromises the augmented fluoroscopy. Motion compensation methods can be applied to update the overlay of a static model with regard to respiratory and cardiac motion. We investigate the feasibility of motion detection between two fluoroscopic frames by applying a convolutional neural network (CNN). Its integration in the existing open-source software framework 3D-XGuide is demonstrated, such extending its functionality to automatic motion detection and compensation.

METHODS

The CNN is trained on reference data generated from tracking of the rapid pacing catheter tip by applying template matching with normalized cross-correlation (CC). The developed CNN motion compensation model is packaged in a standalone web service, allowing for independent use via a REST API. For testing and demonstration purposes, we have extended the functionality of 3D-XGuide navigation framework by an additional motion compensation module, which uses the displacement predictions of the standalone CNN model service for motion compensation of the static 3D model overlay. We provide the source code on GitHub under BSD license.

RESULTS

The performance of the CNN motion compensation model was evaluated on a total of 1690 fluoroscopic image pairs from ten clinical datasets. The CNN model-based motion compensation method clearly overperformed the tracking of the rapid pacing catheter tip with CC with prediction frame rates suitable for live application in the clinical setting.

CONCLUSION

A novel CNN model-based method for automatic motion compensation during fusion of 3D anatomic models with XR fluoroscopy is introduced and its integration with a real software application demonstrated. Automatic motion extraction from 2D XR images using a CNN model appears as a substantial improvement for reliable augmentation during catheter interventions.

Establishment of Standard Human Blood Vessel Model Based on Image Registration and Fitting Technology

Purpose

The blood vessel gives key information for pathological changes in a variety of diseases. In view of the crucial role of blood vessel structure, the present study aims to establish a digital human blood vessel standard model for diagnosing blood vessel-related diseases.

Methods

The present study recruited eight healthy volunteers, and reconstructed their bilateral upper extremity arteries according to CTA. The reconstructed vessels were segmented, registered, and merged into a bunch. After being cut by continuous cut planes, the dispersion of the blood vessel bunches on each cut plane were calculated.

Results

The results demonstrated that the middle segment of the brachial artery, the proximal segment of the ulnar artery, and the middle and distal segments of the radial artery had a low degree of dispersion. A standard blood vessel model was finally established by the integral method using the low-dispersion segments above. The accuracy of the standard blood vessel model was also verified by an actual contralateral vessel, which revealed that the deviation between the model and the actual normal contralateral brachial artery was relatively small.

Conclusion

The structure of the model was highly accordant with the real ones, which can be of great help in evaluating the blood vessel changes in blood vessel-related diseases, bone and soft-tissue tumors, and creating accurate surgical plans.

A Tensor-based Catheter and Wire Detection and Tracking Framework and Its Clinical Applications

OBJECTIVE

Catheters and wires are used extensively in cardiac catheterization procedures. Detecting their positions in fluoroscopic X-ray images is important for several clinical applications such as motion compensation and co-registration between 2D and 3D imaging modalities. Detecting the complete length of a catheter or wire object as well as electrode positions on the catheter or wire is a challenging task.

METHOD

In this paper, an automatic detection framework for catheters and wires is developed. It is based on path reconstruction from image tensors, which are eigen direction vectors generated from a multiscale vessel enhancement filter. A catheter or a wire object is detected as the smooth path along those eigen direction vectors. Furthermore, a real-time tracking method based on a template generated from the detection method was developed.

RESULTS

The proposed framework was tested on a total of 7,754 X-ray images. Detection errors for catheters and guidewires are 0.56 0.28 mm and 0.68 0.33 mm, respectively. The proposed framework was also tested and validated in two clinical applications. For motion compensation using catheter tracking, the 2D target registration errors (TRE) of 1.8 mm 0.9 mm was achieved. For co-registration between 2D X-ray images and 3D models from MRI images, a TRE of 2.3 0.9 mm was achieved.

CONCLUSION

A novel and fully automatic detection framework and its clinical applications are developed.

SIGNIFICANCE

The proposed framework can be applied to improve the accuracy of image-guidance systems for cardiac catheterization procedures.

Computed Tomography-Derived 3D Modeling to Guide Sizing and Planning of Transcatheter Mitral Valve Interventions

A plethora of catheter-based strategies have been developed to treat mitral valve disease. Evolving 3-dimensional (3D) multidetector computed tomography (MDCT) technology can accurately reconstruct the mitral valve by means of 3-dimensional computational modeling (3DCM) to allow virtual implantation of catheter-based devices. 3D printing complements computational modeling and offers implanting physician teams the opportunity to evaluate devices in life-size replicas of patient-specific cardiac anatomy. MDCT-derived 3D computational and 3D-printed modeling provides unprecedented insights to facilitate hands-on procedural planning, device training, and retrospective procedural evaluation. This overview summarizes current concepts and provides insight into the application of MDCT-derived 3DCM and 3D printing for the planning of transcatheter mitral valve replacement and closure of paravalvular leaks. Additionally, future directions in the development of 3DCM will be discussed.

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.

Fusion imaging in interventional cardiology

The number and complexity of percutaneous interventions for the treatment of structural heart disease has increased in clinical practice in parallel with the development of new imaging technologies, in order to render these interventions safer and more accurate. Complementary imaging modalities are commonly used, but they require additional mental reconstruction and effort by the interventional team. The concept of fusion imaging, where two different modalities are fused in real time and on a single monitor, aims to solve these limitations. This is an important tool to guide percutaneous interventions, enabling a good visualization of catheters, guidewires and devices employed, with enhanced spatial resolution and anatomical definition. It also allows the marking of anatomical reference points of interest for the procedure. Some studies show decreased procedural time and total radiation dose with fusion imaging; however, there is a need to obtain data with more robust scientific methodology to assess the impact of this technology in clinical practice. The aim of this review is to describe the concept and basic principles of fusion imaging, its main clinical applications and some considerations about the promising future of this imaging technology.

Clinical utility of intraprocedural three-dimensional integrated image guided transcatheter aortic valve implantation using novel automated computed tomography software: A single-center preliminary experience

OBJECTIVES

Novel automated computed tomography (CT) software (Valve ASSIST 2) has been developed for transcatheter aortic valve implantation (TAVI), which not only provides three-dimensional (3D) reconstruction of multidetector (MD) CT images, but also enables intraprocedural real-time fusion of fluoroscopic and MDCT images. We aimed to clarify the reproducibility and accuracy of this software in the aortic annulus assessment and verify the potential of intraprocedural integrated MDCT imaging for TAVI.

METHODS AND RESULTS

We examined 50 patients with severe aortic stenosis undergoing transfemoral TAVI. Aortic annulus measurements were performed using 3mensio and the novel planning software. For intraprocedural imaging, preoperative CT dataset was overlaid onto fluoroscopy with the fusion software. The two images were aligned using the aortic root anatomy visible on both modalities. Novel planning software provided excellent reproducibility for the measurement of aortic annulus area (intraobserver intraclass correlation coefficients [ICC] 0.959, interobserver ICC 0.941), and perimeter (intraobserver ICC 0.915, interobserver ICC 0.912). Excellent correlation was found between novel planning software and 3mensio (ICC 0.952 for aortic annulus area, and 0.923 for perimeter). Intraprocedural fusion image of CT aortography and fluoroscopic aortic root aortography generated by this novel software identified coronary orifices and the distribution of aortic valve calcification during the device positioning. Fusion image displayed coronary orifices after device implantation.

CONCLUSIONS

Novel planning software showed excellent reproducibility and accuracy in the assessment of aortic root anatomy. Furthermore, the integrated 3D fusion image might have a potential as an intraprocedural imaging modality to contribute to the development of a safer TAVI procedure.

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.