Three-dimensional reconstruction of myocardial contrast perfusion from biplane cineangiograms by means of linear programming techniques

The assessment of coronary flow reserve from the instantaneous distribution of the contrast agent within the coronary vessels and myocardial muscle at the control state and at maximal flow has been limited by the superimposition of myocardial regions of interest in the two-dimensional images. To overcome these limitations, we are in the process of developing a three-dimensional (3D) reconstruction technique to compute the contrast distribution in cross sections of the myocardial muscle from two orthogonal cineangiograms. To limit the number of feasible solutions in the 3D-reconstruction space, the 3D-geometry of the endo- and epicardial boundaries of the myocardium must be determined. For the geometric reconstruction of the epicardium, the centerlines of the left coronary arterial tree are manually or automatically traced in the biplane views. Next, the bifurcations are detected automatically and matched in these two views, allowing a 3D-representation of the coronary tree. Finally, the circumference of the left ventricular myocardium in a selected cross section can be computed from the intersection points of this cross section with the 3D coronary tree using B-splines. For the geometric reconstruction of the left ventricular cavity, we envision to apply the elliptical approximation technique using the LV boundaries defined in the two orthogonal views, or by applying more complex 3D-reconstruction techniques including densitometry. The actual 3D-reconstruction of the contrast distribution in the myocardium is based on a linear programming technique (Transportation model) using cost coefficient matrices. Such a cost coefficient matrix must contain a maximum amount of a priori information, provided by a computer generated model and updated with actual data from the angiographic views. We have only begun to solve this complex problem. However, based on our first experimental results we expect that the linear programming approach with advanced cost coefficient matrices and computed model will lead to a

Three-dimensional reconstruction of stenosed coronary artery segments with assessment of the flow impedance

In this paper preliminary results of a study about the diagnostic benefits of 3D visualization and quantitation of stenosed coronary artery segments are presented. As is well known, even biplane angiographic images do not provide enough information for binary reconstruction. Therefore,a priori information about the slice to be reconstructed must be incorporated into the reconstruction algorithm. One approach is to assume a circular cross-section of the coronary artery. Hence, the diameter is estimated from the contours of the vessels in both projections. Another approach is to search for a solution of the reconstruction problem close to the previously reconstructed adjacent slice. In this paper we follow the first method based on contour information. The reconstructed coronary segment is visualized in three dimensions. Based on the obtained geometry of the obstruction the pertinent blood flow impedance is estimated on the basis of fluid dynamic principles. The results of applying the reconstruction algorithms to clinical coronary biplane exposures are presented with an indication of the assessed flow impedance

Analysis of left ventricular behaviour in diastole by means of finite element method

The human left ventricle in diastole can be modelled as a passive structure with incremental internal pressure change being considered as the load. Recent developments in engineering stress analysis provide techniques for predicting the behaviour of structures with complex geometry and material properties, as is the case with the left ventricle. That which is most appropriate is the finite element method which requires the use of a large digital computer. The ventricles of 2 patients have been studied during diastole, the geometries having been derived from cineangiographic data (biplane), and the pressure by means of catheter-tip manometers. Various descriptions of myocardial stress/strain relations have been assumed and applied to the left ventricular wall in order to obtain the best match between the calculated and observed deformation patterns. The manner in which the value and distribution of stiffness in the left ventricle influences the shape change can therefore be determined, and possible clinical implications deduced

Improved 3D MR Image Acquisition and Processing in Congenital Heart Disease

Congenital heart disease (CHD) is the most common type of birth defect, affecting about 1% of the population. MRI is an essential tool in the assessment of CHD, including diagnosis, intervention planning and follow-up. Three-dimensional MRI can provide particularly rich visualization and information. However, it is often complicated by long scan times, cardiorespiratory motion, injection of contrast agents, and complex and time-consuming postprocessing. This thesis comprises four pieces of work that attempt to respond to some of these challenges. The first piece of work aims to enable fast acquisition of 3D time-resolved cardiac imaging during free breathing. Rapid imaging was achieved using an efficient spiral sequence and a sparse parallel imaging reconstruction. The feasibility of this approach was demonstrated on a population of 10 patients with CHD, and areas of improvement were identified. The second piece of work is an integrated software tool designed to simplify and accelerate the development of machine learning (ML) applications in MRI research. It also exploits the strengths of recently developed ML libraries for efficient MR image reconstruction and processing. The third piece of work aims to reduce contrast dose in contrast-enhanced MR angiography (MRA). This would reduce risks and costs associated with contrast agents. A deep learning-based contrast enhancement technique was developed and shown to improve image quality in real low-dose MRA in a population of 40 children and adults with CHD. The fourth and final piece of work aims to simplify the creation of computational models for hemodynamic assessment of the great arteries. A deep learning technique for 3D segmentation of the aorta and the pulmonary arteries was developed and shown to enable accurate calculation of clinically relevant biomarkers in a population of 10 patients with CHD

High spatial resolution myocardial perfusion cardiac magnetic resonance for the detection of coronary artery disease

To evaluate the feasibility and diagnostic performance of high spatial resolution myocardial perfusion cardiac magnetic resonance (perfusion-CMR). Methods and results Fifty-four patients underwent adenosine stress perfusion-CMR. An in-plane spatial resolution of 1.4 x 1.4 mm(2) was achieved by using 5x k-space and time sensitivity encoding (k-t SENSE). Perfusion was visually graded for 16 left ventricular and two right ventricular (RV) segments on a scale from 0 = normal to 3 = abnormal, yielding a perfusion score of 0-54. Diagnostic accuracy of the perfusion score to detect coronary artery stenosis of >50% on quantitative coronary angiography was determined. Sources and extent of image artefacts were documented. Two studies (4%) were non-diagnostic because of k-t SENSE-related and breathing artefacts. Endocardial dark rim artefacts if present were small (average width 1.6 mm). Analysis by receiver-operating characteristics yielded an area under the curve for detection of coronary stenosis of 0.85 [95% confidence interval (CI) 0.75-0.95] for all patients and 0.82 (95% CI 0.65-0.94) and 0.87 (95% CI 0.75-0.99) for patients with single and multi-vessel disease, respectively. Seventy-four of 102 (72%) RV segments could be analysed. Conclusion High spatial resolution perfusion-CMR is feasible in a clinical population, yields high accuracy to detect single and multi-vessel coronary artery disease, minimizes artefacts and may permit the assessment of RV perfusion

Data reconciliation of immersive heart inspection

IVUS images are complicated medical datasets suffering from some artifacts caused by the data acquisition method of immersive heart inspection. Data reconciliation, which removes tracing and tracking uncertainties of these datasets, is an important step for the medical application of remodeling the arteries in virtual reality to aid diagnosing and treating heart diseases. This paper provides an empirical data reconciliation method, which fuses the features of the coronary longitudinal movement with motion compensation model. It explains the distortion of the data set well and provides a method to analyze and reconcile the dataset

Cardiovascular Magnetic Resonance Imaging for the Investigation of Patients with Coronary Heart Disease

Objectives To evaluate the role of stress perfusion cardiovascular magnetic resonance (CMR) in the investigation of stable coronary artery disease (CAD). Background Coronary artery disease remains the biggest cause of morbidity and mortality. The multi-parametric CMR examination is established as an investigative strategy for the investigation of CAD. Methods Study 1 & 2: Patients with stable coronary artery disease underwent a multi-parametric CMR protocol assessing 4 components: i) left ventricular function; ii) myocardial perfusion; iii) viability (late gadolinium enhancement (LGE)) and iv) coronary magnetic resonance angiography (MRA). The diagnostic accuracy of the individual components were assessed. The ischaemic burden of stress CMR Vs. Single Photon Emission Computed Tomography (SPECT) was determined. Study 3: Volunteers and patients were scanned with perfusion sequence which adapts the spatial resolution to the available scanning time and field-of-view. Study 4: A multi-centre pragmatic randomised controlled trial of patients with stable angina comparing CMR guided-care Vs. SPECT guided-care Vs. National Institute of Health and Care Excellence guided-care. Results Study 1 demonstrated the stress perfusion component of the multi-parametric CMR exam was the single most important component for overall diagnostic accuracy. However, the full combined multi-parametric protocol was the optimal approach for disease rule-out, and the LGE component best for rule-in. Study 2 showed that there was reasonable agreement of the summed stress scores between CMR and SPECT (a well established investigation with significant amounts of prognostic data). In study 3, a perfusion pulse sequence which automatically adapts the acquisition sequence to the available scanning time results in spatial resolution improvement and reduction in dark rim artefact. Finally in study 4 in patients with suspected angina using CMR as an initial investigative strategy produced a significantly lower probability of unnecessary angiography compared to NICE guidance. There were similar rates of CAD detection were comparable suggesting no penalty for using functional imaging as a gatekeeper for angiography. Conclusion CMR has high diagnostic accuracy for the detection of coronary artery disease; with similar detection of ischaemic burden to established tests and can be used safely and effectively as a gate keeper to invasive coronary angiography