Dynamic Analysis of X-ray Angiography for Image-Guided Coronary Interventions

Percutaneous coronary intervention (PCI) is a minimally-invasive procedure for treating patients with coronary artery disease. PCI is typically performed with image guidance using X-ray angiograms (XA) in which coronary arter

Reconstruction of coronary arteries from X-ray angiography: A review.

Despite continuous progress in X-ray angiography systems, X-ray coronary angiography is fundamentally limited by its 2D representation of moving coronary arterial trees, which can negatively impact assessment of coronary artery disease and guidance of percutaneous coronary intervention. To provide clinicians with 3D/3D+time information of coronary arteries, methods computing reconstructions of coronary arteries from X-ray angiography are required. Because of several aspects (e.g. cardiac and respiratory motion, type of X-ray system), reconstruction from X-ray coronary angiography has led to vast amount of research and it still remains as a challenging and dynamic research area. In this paper, we review the state-of-the-art approaches on reconstruction of high-contrast coronary arteries from X-ray angiography. We mainly focus on the theoretical features in model-based (modelling) and tomographic reconstruction of coronary arteries, and discuss the evaluation strategies. We also discuss the potential role of reconstructions in clinical decision making and interventional guidance, and highlight areas for future research

A novel real-time computational framework for detecting catheters and rigid guidewires in cardiac catheterization procedures

Purpose: Catheters and guidewires are used extensively in cardiac catheterization procedures such as heart arrhythmia treatment (ablation), angioplasty and congenital heart disease treatment. Detecting their positions in fluoroscopic X-ray images is important for several clinical applications, for example, motion compensation, co-registration between 2D and 3D imaging modalities and 3D object reconstruction. Methods: For the generalized framework, a multiscale vessel enhancement filter is first used to enhance the visibility of wire-like structures in the X-ray images. After applying adaptive binarization method, the centerlines of wire-like objects were extracted. Finally, the catheters and guidewires were detected as a smooth path which is reconstructed from centerlines of target wire-like objects. In order to classify electrode catheters which are mainly used in electrophysiology procedures, additional steps were proposed. First, a blob detection method, which is embedded in vessel enhancement filter with no additional computational cost, localizes electrode positions on catheters. Then the type of electrode catheters can be recognized by detecting the number of electrodes and also the shape created by a series of electrodes. Furthermore, for detecting guiding catheters or guidewires, a localized machine learning algorithm is added into the framework to distinguish between target wire objects and other wire-like artifacts. The proposed framework were tested on total 10,624 images which are from 102 image sequences acquired from 63 clinical cases. Results: Detection errors for the coronary sinus (CS) catheter, lasso catheter ring and lasso catheter body are 0.56 ± 0.28 mm, 0.64 ± 0.36 mm and 0.66 ± 0.32 mm, respectively, as well as success rates of 91.4%, 86.3% and 84.8% were achieved. Detection errors for guidewires and guiding catheters are 0.62 ± 0.48 mm and success rates are 83.5%. Conclusion: The proposed computational framework do not require any user interaction or prior models and it can detect multiple catheters or guidewires simultaneously and in real-time. The accuracy of the proposed framework is sub-mm and the methods are robust toward low-dose X-ray fluoroscopic images, which are mainly used during procedures to maintain low radiation dose

3D reconstruction of cerebral blood flow and vessel morphology from x-ray rotational angiography

Three-dimensional (3D) information on blood flow and vessel morphology is important when assessing cerebrovascular disease and when monitoring interventions. Rotational angiography is nowadays routinely used to determine the geometry of the cerebral vasculature. To this end, contrast agent is injected into one of the supplying arteries and the x-ray system rotates around the head of the patient while it acquires a sequence of x-ray images. Besides information on the 3D geometry, this sequence also contains information on blood flow, as it is possible to observe how the contrast agent is transported by the blood. The main goal of this thesis is to exploit this information for the quantitative analysis of blood flow. I propose a model-based method, called flow map fitting, which determines the blood flow waveform and the mean volumetric flow rate in the large cerebral arteries. The method uses a model of contrast agent transport to determine the flow parameters from the spatio-temporal progression of the contrast agent concentration, represented by a flow map. Furthermore, it overcomes artefacts due to the rotation (overlapping vessels and foreshortened vessels at some projection angles) of the c-arm using a reliability map. For the flow quantification, small changes to the clinical protocol of rotational angiography are desirable. These, however, hamper the standard 3D reconstruction. Therefore, a new method for the 3D reconstruction of the vessel morphology which is tailored to this application is also presented. To the best of my knowledge, I have presented the first quantitative results for blood flow quantification from rotational angiography. Additionally, the model-based approach overcomes several problems which are known from flow quantification methods for planar angiography. The method was mainly validated on images from different phantom experiments. In most cases, the relative error was between 5% and 10% for the volumetric mean flow rate and between 10% and 15% for the blood flow waveform. Additionally, the applicability of the flow model was shown on clinical images from planar angiographic acquisitions. From this, I conclude that the method has the potential to give quantitative estimates of blood flow parameters during cerebrovascular interventions