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

Coronary Artery Segmentation and Motion Modelling

Conventional coronary artery bypass surgery requires invasive sternotomy and the use of a cardiopulmonary bypass, which leads to long recovery period and has high infectious potential. Totally endoscopic coronary artery bypass (TECAB) surgery based on image guided robotic surgical approaches have been developed to allow the clinicians to conduct the bypass surgery off-pump with only three pin holes incisions in the chest cavity, through which two robotic arms and one stereo endoscopic camera are inserted. However, the restricted field of view of the stereo endoscopic images leads to possible vessel misidentification and coronary artery mis-localization. This results in 20-30% conversion rates from TECAB surgery to the conventional approach. We have constructed patient-specific 3D + time coronary artery and left ventricle motion models from preoperative 4D Computed Tomography Angiography (CTA) scans. Through temporally and spatially aligning this model with the intraoperative endoscopic views of the patient's beating heart, this work assists the surgeon to identify and locate the correct coronaries during the TECAB precedures. Thus this work has the prospect of reducing the conversion rate from TECAB to conventional coronary bypass procedures. This thesis mainly focus on designing segmentation and motion tracking methods of the coronary arteries in order to build pre-operative patient-specific motion models. Various vessel centreline extraction and lumen segmentation algorithms are presented, including intensity based approaches, geometric model matching method and morphology-based method. A probabilistic atlas of the coronary arteries is formed from a group of subjects to facilitate the vascular segmentation and registration procedures. Non-rigid registration framework based on a free-form deformation model and multi-level multi-channel large deformation diffeomorphic metric mapping are proposed to track the coronary motion. The methods are applied to 4D CTA images acquired from various groups of patients and quantitatively evaluated

Deep Learning in Cardiology

The medical field is creating large amount of data that physicians are unable to decipher and use efficiently. Moreover, rule-based expert systems are inefficient in solving complicated medical tasks or for creating insights using big data. Deep learning has emerged as a more accurate and effective technology in a wide range of medical problems such as diagnosis, prediction and intervention. Deep learning is a representation learning method that consists of layers that transform the data non-linearly, thus, revealing hierarchical relationships and structures. In this review we survey deep learning application papers that use structured data, signal and imaging modalities from cardiology. We discuss the advantages and limitations of applying deep learning in cardiology that also apply in medicine in general, while proposing certain directions as the most viable for clinical use.Comment: 27 pages, 2 figures, 10 table

VALIDATION OF COMPUTATIONAL FLUID DYNAMIC SIMULATIONS OF MEMBRANE ARTIFICIAL LUNGS WITH X-RAY IMAGING

The functional performance of membrane oxygenators is directly related to the perfusion dynamics of blood flow through the fiber bundle. Non-uniform flow and design characteristics can limit gas exchange efficiency and influence susceptibility of thrombus development in the fiber membrane. Computational fluid dynamics (CFD) is a powerful tool for predicting properties of the flow field based on prescribed geometrical domains and boundary conditions. Validation of numerical results in membrane oxygenators has been predominantly based on experimental pressure measurements with little emphasis placed on confirmation of the velocity fields due to opacity of the fiber membrane and limitations of optical velocimetric methods. A novel approach was developed using biplane X-ray digital subtraction angiography to visualize flow through a commercial membrane artificial lung at 1–4.5 L/min. Permeability based on the coefficients of the Ergun equation, α and β, were experimentally determined to be 180 and 2.4, respectively, and the equivalent spherical diameter was shown to be approximately equal to the outer fiber diameter. For all flow rates tested, biplane image projections revealed non-uniform radial perfusion through the annular fiber bundle, yet without flow bias due to the axisymmetric position of the outlet. At 1 L/min, approximately 78.2% of the outward velocity component was in the radial (horizontal) plane verses 92.0% at 4.5 L/min. The CFD studies were unable to predict the non-radial component of the outward perfusion. Two-dimensional velocity fields were generated from the radiographs using a cross-correlation tracking algorithm and compared with analogous image planes from the CFD simulations. Velocities in the non-porous regions differed by an average of 11% versus the experimental values, but simulated velocities in the fiber bundle were on average 44% lower than experimental. A corrective factor reduced the average error differences in the porous medium to 6%. Finally, biplane image pairs were reconstructed to show 3-D transient perfusion through the device. The methods developed from this research provide tools for more accurate assessments of fluid flow through membrane oxygenators. By identifying non-invasive techniques to allow direct analysis of numerical and experimental velocity fields, researchers can better evaluate device performance of new prototype designs

Use of advanced echocardiography imaging techniques in the critically ill

Background: Critical care echocardiography has become standard of care in the ICU. New technologies have been developed and have shown potential clinical utility to elucidate myocardial dysfunction not seen with conventional imaging. We sought to determine the feasibility and potential clinical benefit of these techniques in common situations seen in the ICU. Hypothesis: Advanced echo techniques would be feasible in the majority of critically ill patients and have prognostic significance, clinical utility and diagnose cardiac abnormalities, potentially in a more sensitive manner than conventional techniques. Results: (a) Speckle tracking echocardiography (STE) Left ventricle and RV analysis with STE was feasibly in ~80% of patients. More dysfunction was found using STE vs conventional analysis. RV dysfunction assessed by STE held significant prognostic relevance in those with septic shock and highlighted subtle dysfunction induced by mechanical ventilation, both in animal and human studies. (b) 3D transthoracic echocardiography (3D TTE) Despite finding 3D TTE feasible in mechanically ventilated ICU patients (LV 72% and RV 55%), it lacked necessary low variability and high precision vs standard measures. (c) Myocardial contrast perfusion echocardiography (MCPE) Assessing acute coronary artery occlusion in the ICU patient is challenging. Troponin elevation, acute ECG changes, regional wall motion analysis on echo and overall clinical acumen often lack diagnostic capabilities. MCPE was found to be feasible in the critically ill and had better association predicting acute coronary artery occlusion vs clinical acumen alone. Conclusions: STE, 3D TTE and MCPE are feasible in the majority of ICU patients. STE may show dysfunction not recognised by conventional imaging. 3D TTE for volumetric analysis is likely not suitable for clinical use at this stage. MCPE may help guide interventions in acute coronary artery occlusion

Investigation into diagnostic accuracy of common strategies for automated perfusion motion correction

Respiratory motion is a significant obstacle to the use of quantitative perfusion in clinical practice. Increasingly complex motion correction algorithms are being developed to correct for respiratory motion. However, the impact of these improvements on the final diagnosis of ischemic heart disease has not been evaluated. The aim of this study was to compare the performance of four automated correction methods in terms of their impact on diagnostic accuracy. Three strategies for motion correction were used: (1) independent translation correction for all slices, (2) translation correction for the basal slice with transform propagation to the remaining two slices assuming identical motion in the remaining slices, and (3) rigid correction (translation and rotation) for the basal slice. There were no significant differences in diagnostic accuracy between the manual and automatic motion-corrected datasets (p=0.88). The area under the curve values for manual motion correction and automatic motion correction were 0.93 and 0.92, respectively. All of the automated motion correction methods achieved a comparable diagnostic accuracy to manual correction. This suggests that the simplest automated motion correction method (method 2 with translation transform for basal location and transform propagation to the remaining slices) is a sufficiently complex motion correction method for use in quantitative myocardial perfusion