Alois Nöttling

Automatic Aorta Segmentation and Valve Landmark Detection in C-Arm CT for Transcatheter Aortic Valve Implantation

Transcatheter aortic valve implantation (TAVI) is a minimally invasive procedure to treat severe aortic valve stenosis. As an emerging imaging technique, C-arm computed tomography (CT) plays a more and more important role in TAVI on both pre-operative surgical planning (e.g., providing 3-D valve measurements) and intra-operative guidance (e.g., determining a proper C-arm angulation). Automatic aorta segmentation and aortic valve landmark detection in a C-arm CT volume facilitate the seamless integration of C-arm CT into the TAVI workflow and improve the patient care. In this paper, we present a part-based aorta segmentation approach, which can handle structural variation of the aorta in case that the aortic arch and descending aorta are missing in the volume. The whole aorta model is split into four parts: aortic root, ascending aorta, aortic arch, and descending aorta. Discriminative learning is applied to train a detector for each part separately to exploit the rich domain knowledge embedded in an expert-annotated dataset. Eight important aortic valve landmarks (three hinges, three commissures, and two coronary ostia) are also detected automatically with an efficient hierarchical approach. Our approach is robust under all kinds of variations observed in a real clinical setting, including changes in the field-of-view, contrast agent injection, scan timing, and aortic valve regurgitation. Taking about 1.1 s to process a volume, it is also computationally efficient. Under the guidance of the automatically extracted patient-specific aorta model, the physicians can properly determine the C-arm angulation and deploy the prosthetic valve. Promising outcomes have been achieved in real clinical applications.

System to guide transcatheter aortic valve implantations based on interventional c-arm CT imaging

Transcatheter aortic valve implantation is an emerging technique to be applied in patients with aortic valve defects. Angiographic and fluoroscopic X-ray imaging with a C-arm system is crucial in these minimally invasive procedures. We describe a prototypical system based on the ability to acquire a 3D C-arm CT image during transcatheter aortic valve implantations. It supports the physician in measuring critical anatomical parameters, finding an optimum C-arm angulation, and guiding the positioning and deployment of the prosthesis by 3D overlay with fluoroscopic images. To yield high acceptance by the physicians in the operating room, our approach is fast, fully integrated into an angiographic C-arm system, and designed to minimize the necessary user interaction. We evaluate the accuracy of our system on 20 clinical cases.

A planning system for transapical aortic valve implantation

Stenosis of the aortic valve is a common cardiac disease. It is usually corrected surgically by replacing the valve with a mechanical or biological prosthesis. Transapical aortic valve implantation is an experimental minimally invasive surgical technique that is applied to patients with high operative risk to avoid pulmonary arrest. A stented biological prosthesis is mounted on a catheter. Through small incisions in the fifth intercostal space and the apex of the heart, the catheter is positioned under flouroscopy in the aortic root. The stent is expanded and unfolds the valve which is thereby implanted into the aortic root. Exact targeting is crucial, since major complications can arise from a misplaced valve. Planning software for the perioperative use is presented that allows for selection of the best fitting implant and calculation of the safe target area for that implant. The software uses contrast enhanced perioperative DynaCT images acquired under rapid pacing. In a semiautomatic process, a surface segmentation of the aortic root is created. User selected anatomical landmarks are used to calculate the geometric constraints for the size and position of the implant. The software is integrated into a PACS network based on DICOM communication to query and receive the images and implants templates from a PACS server. The planning results can be exported to the same server and from there can be rertieved by an intraoperative catheter guidance device.

C-arm CT: Reconstruction of dynamic high contrast objects applied to the coronary sinus

For many interventional procedures the 3-D reconstruction of dynamic high contrast objects from C-arm data is desirable. We present a method for compensating artifacts from periodic motions by providing a modified filtered backprojection algorithm. The proposed algorithm comprises three steps: First, the reconstruction of an initial reference volume from a phase-consistent subset of the projection data. Secondly, the selection of proper data for a motion corrected reconstruction using as many projections as possible in the third step. The first step is addressed by gating in combination with a modified backprojection operator which reduces streak artifacts, the second by analysis of the cardiac motion characteristics and the impact on gated reconstruction quality and the third by accumulating gated sub-reconstructions registered with the reference volume. We present first clinical results from real patient data for the reconstruction of the coronary sinus.

Significant acceleration of 2D-3D registration-based fusion of ultrasound and x-ray images by mesh-based DRR rendering

For transcatheter-based minimally invasive procedures in structural heart disease ultrasound and X-ray are the two enabling imaging modalities. A live fusion of both real-time modalities can potentially improve the workflow and the catheter navigation by combining the excellent instrument imaging of X-ray with the high-quality soft tissue imaging of ultrasound. A recently published approach to fuse X-ray fluoroscopy with trans-esophageal echo (TEE) registers the ultrasound probe to X-ray images by a 2D-3D registration method which inherently provides a registration of ultrasound images to X-ray images. In this paper, we significantly accelerate the 2D-3D registration method in this context. The main novelty is to generate the projection images (DRR) of the 3D object not via volume ray-casting but instead via a fast rendering of triangular meshes. This is possible, because in the setting for TEE/X-ray fusion the 3D geometry of the ultrasound probe is known in advance and their main components can be described by triangular meshes. We show that the new approach can achieve a speedup factor up to 65 and does not affect the registration accuracy when used in conjunction with the gradient correlation similarity measure. The improvement is independent of the underlying registration optimizer. Based on the results, a TEE/X-ray fusion could be performed with a higher frame rate and a shorter time lag towards real-time registration performance. The approach could potentially accelerate other applications of 2D-3D registrations, e.g. the registration of implant models with X-ray images.

A Hybird Optimization Approach for 2D-3D Registrationbased Fusion of Ultrasound and X-Ray.

For transcatheter-based minimally invasive procedures in structural heart disease ultrasound and Xray are the two main imaging modalities. A live fusion of both real-time modalities could benefit the clinical workflow by combining the excellent instrument imaging of Xray with soft tissue imaging of ultrasound. A recent approach to fuse X-ray fluoroscopy with trans-esophageal echo (TEE) registers the ultrasound probe to X-ray images by a 2D-3D registration. We enhance the capture range of the current registration by first applying an evolutionary multi-resolution optimization before improving the accuracy with a local optimization. The capture range was increased up to 40 mm (single X-ray image per registration). Our final registration error is in the range of 4.3 mm (3D error) and 2.7 mm (projected error).