An Iterative Diffeomorphic Algorithm for Registration of Subdivision Surfaces: Application to Congenital Heart Disease.

In this paper, we present a new diffeomorphic registration algorithm for the registration of 3D models to 3D points. A biventricular template is iteratively fitted to the data by a series of implicitly constrained diffeomorphic linear least squares fits with decreasing regularization weights before performing an explicitly constrained diffeomorphic fit. The algorithm has been tested on a set of manual contours from 20 patients with a variety of congenital heart disease. Registration accuracy was assessed by calculating the mean point-to-point distance and the Dice overlap metric. Results showed that the method was able to accurately fit the biventricular model to 3D points and that the deformable model was able to fit all the pathologies while being diffeomorphic. The algorithm took approximately 5 minutes to fit each case, with an average of 52,580 points per case.

4D modelling for rapid assessment of biventricular function in congenital heart disease.

Although more patients with congenital heart disease (CHD) are now living longer due to better surgical interventions, they require regular imaging to monitor cardiac performance. There is a need for robust clinical tools which can accurately assess cardiac function of both the left and right ventricles in these patients. We have developed methods to rapidly quantify 4D (3D + time) biventricular function from standard cardiac MRI examinations. A finite element model was interactively customized to patient images using guide-point modelling. Computational efficiency and ability to model large deformations was improved by predicting cardiac motion for the left ventricle and epicardium with a polar model. In addition, large deformations through the cycle were more accurately modeled using a Cartesian deformation penalty term. The model was fitted to user-defined guide points and image feature tracking displacements throughout the cardiac cycle. We tested the methods in 60 cases comprising a variety of congenital heart diseases and showed good correlation with the gold standard manual analysis, with acceptable inter-observer error. The algorithm was considerably faster than standard analysis and shows promise as a clinical tool for patients with CHD.

An interactive tool for rapid biventricular analysis of congenital heart disease.

Cardiac malformations are the most common birth defect. Better interventions in early life have improved mortality for children with congenital heart disease, but heart failure is a significant problem in adulthood. These patients require regular imaging and analysis of biventricular (left and right ventricular) function. In this study, we describe a rapid method to analyse left and right ventricular shape and function from cardiac MRI examinations. A 4D (3D+time) finite element model template is interactively customized to the anatomy and motion of the biventricular unit. The method was validated in 17 patients and 10 ex-vivo hearts. Interactive model updates were achieved through preconditioned conjugate gradient optimization on a multithread system, and by precomputing points predicted from a coarse mesh optimization.

Application of Arterial Spin Labelling in the Assessment of Ocular Tissues.

Arterial spin labelling (ASL) is a noninvasive magnetic resonance imaging (MRI) modality, capable of measuring blood perfusion without the use of a contrast agent. While ASL implementation for imaging the brain and monitoring cerebral blood flow has been reviewed in depth, the technique is yet to be widely used for ocular tissue imaging. The human retina is a very thin but highly stratified structure and it is also situated close to the surface of the body which is not ideal for MR imaging. Hence, the application of MR imaging and ASL in particular has been very challenging for ocular tissues and retina. That is despite the fact that almost all of retinal pathologies are accompanied by blood perfusion irregularities. In this review article, we have focused on the technical aspects of the ASL and their implications for its optimum adaptation for retinal blood perfusion monitoring. Retinal blood perfusion has been assessed through qualitative or invasive quantitative methods but the prospect of imaging flow using ASL would increase monitoring and assessment of retinal pathologies. The review provides details of ASL application in human ocular blood flow assessment.