Nic Smith

Preterm heart in adult life: cardiovascular magnetic resonance reveals distinct differences in left ventricular mass, geometry, and function.

Background— Preterm birth leads to an early switch from fetal to postnatal circulation before completion of left ventricular in utero development. In animal studies, this results in an adversely remodeled left ventricle. We determined whether preterm birth is associated with a distinct left ventricular structure and function in humans. Methods and Results— A total of 234 individuals 20 to 39 years of age underwent cardiovascular magnetic resonance. One hundred two had been followed prospectively since preterm birth (gestational age=30.3±2.5 week; birth weight=1.3±0.3 kg), and 132 were born at term to uncomplicated pregnancies. Longitudinal and short-axis cine images were used to quantify left ventricular mass, 3-dimensional geometric variation by creation of a unique computational cardiac atlas, and myocardial function. We then determined whether perinatal factors modify these left ventricular parameters. Individuals born preterm had increased left ventricular mass (66.5±10.9 versus 55.4±11.4 g/m2; P<0.001) with greater prematurity associated with greater mass (r = −0.22, P=0.03). Preterm-born individuals had short left ventricles with small internal diameters and a displaced apex. Ejection fraction was preserved (P>0.99), but both longitudinal systolic (peak strain, strain rate, and velocity, P<0.001) and diastolic (peak strain rate and velocity, P<0.001) function and rotational (apical and basal peak systolic rotation rate, P =0.05 and P =0.006; net twist angle, P=0.02) movement were significantly reduced. A diagnosis of preeclampsia during the pregnancy was associated with further reductions in longitudinal peak systolic strain in the offspring (P=0.02, n=29). Conclusions— Individuals born preterm have increased left ventricular mass in adult life. Furthermore, they exhibit a unique 3-dimensional left ventricular geometry and significant reductions in systolic and diastolic functional parameters. Clinical Trial Registration— URL: http://www.clinicaltrials.gov. Unique identifier: NCT01487824.Background— Preterm birth leads to an early switch from fetal to postnatal circulation before completion of left ventricular in utero development. In animal studies, this results in an adversely remodeled left ventricle. We determined whether preterm birth is associated with a distinct left ventricular structure and function in humans. Methods and Results— A total of 234 individuals 20 to 39 years of age underwent cardiovascular magnetic resonance. One hundred two had been followed prospectively since preterm birth (gestational age=30.3±2.5 week; birth weight=1.3±0.3 kg), and 132 were born at term to uncomplicated pregnancies. Longitudinal and short-axis cine images were used to quantify left ventricular mass, 3-dimensional geometric variation by creation of a unique computational cardiac atlas, and myocardial function. We then determined whether perinatal factors modify these left ventricular parameters. Individuals born preterm had increased left ventricular mass (66.5±10.9 versus 55.4±11.4 g/m2; P 0.99), but both longitudinal systolic (peak strain, strain rate, and velocity, P <0.001) and diastolic (peak strain rate and velocity, P <0.001) function and rotational (apical and basal peak systolic rotation rate, P =0.05 and P =0.006; net twist angle, P =0.02) movement were significantly reduced. A diagnosis of preeclampsia during the pregnancy was associated with further reductions in longitudinal peak systolic strain in the offspring ( P =0.02, n=29). Conclusions— Individuals born preterm have increased left ventricular mass in adult life. Furthermore, they exhibit a unique 3-dimensional left ventricular geometry and significant reductions in systolic and diastolic functional parameters. Clinical Trial Registration— URL: . Unique identifier: [NCT01487824][1]. # Clinical Perspective {#article-title-37} [1]: /lookup/external-ref?link_type=CLINTRIALGOV&access_num=NCT01487824&atom=%2Fcirculationaha%2F127%2F2%2F197.atom

euHeart: personalized and integrated cardiac care using patient-specific cardiovascular modelling

The loss of cardiac pump function accounts for a significant increase in both mortality and morbidity in Western society, where there is currently a one in four lifetime risk, and costs associated with acute and long-term hospital treatments are accelerating. The significance of cardiac disease has motivated the application of state-of-the-art clinical imaging techniques and functional signal analysis to aid diagnosis and clinical planning. Measurements of cardiac function currently provide high-resolution datasets for characterizing cardiac patients. However, the clinical practice of using population-based metrics derived from separate image or signal-based datasets often indicates contradictory treatments plans owing to inter-individual variability in pathophysiology. To address this issue, the goal of our work, demonstrated in this study through four specific clinical applications, is to integrate multiple types of functional data into a consistent framework using multi-scale computational modelling.

An accurate, fast and robust method to generate patient-specific cubic Hermite meshes.

In-silico continuum simulations of organ and tissue scale physiology often require a discretisation or mesh of the solution domain. Cubic Hermite meshes provide a smooth representation of anatomy that is well-suited for simulating large deformation mechanics. Models of organ mechanics and deformation have demonstrated significant potential for clinical application. However, the production of a personalised mesh from patients anatomy using medical images remains a major bottleneck in simulation workflows. To address this issue, we have developed an accurate, fast and automatic method for deriving patient-specific cubic Hermite meshes. The proposed solution customises a predefined template with a fast binary image registration step and a novel cubic Hermite mesh warping constructed using a variational technique. Image registration is used to retrieve the mapping field between the template mesh and the patient images. The variational warping technique then finds a smooth and accurate projection of this field into the basis functions of the mesh. Applying this methodology, cubic Hermite meshes are fitted to the binary description of shape with sub-voxel accuracy and within a few minutes, which is a significant advance over the existing state of the art methods. To demonstrate its clinical utility, a generic cubic Hermite heart biventricular model is personalised to the anatomy of four patients, and the resulting mechanical stability of these customised meshes is successfully demonstrated.

Multiscale computational modelling of the heart

A computational framework is presented for integrating the electrical, mechanical and biochemical functions of the heart. Finite element techniques are used to solve the large-deformation soft tissue mechanics using orthotropic constitutive laws based in the measured fibre-sheet structure of myocardial (heart muscle) tissue. The reaction-diffusion equations governing electrical current flow in the heart are solved on a grid of deforming material points which access systems of ODEs representing the cellular processes underlying the cardiac action potential. Navier-Stokes equations are solved for coronary blood flow in a system of branching blood vessels embedded in the deforming myocardium and the delivery of oxygen and metabolites is coupled to the energy-dependent cellular processes. The framework presented here for modelling coupled physical conservation laws at the tissue and organ levels is also appropriate for other organ systems in the body and we briefly discuss applications to the lungs and the musculo-skeletal system. The computational framework is also designed to reach down to subcellular processes, including signal transduction cascades and metabolic pathways as well as ion channel electrophysiology, and we discuss the development of ontologies and markup language standards that will help link the tissue and organ level models to the vast array of gene and protein data that are now available in web-accessible databases.

Myocardial transversely isotropic material parameter estimation from in-silico measurements based on a reduced-order unscented Kalman filter

Parameter estimation from non-invasive measurements is a crucial step in patient-specific cardiac modeling. It also has the potential to provide significant assistance in the clinical diagnosis of cardiac diseases through the quantification of myocardial material heterogeneity. In this paper, we formulate a novel Reduced-order Unscented Kalman Filter (rUKF) applied to the left ventricular (LV) nonlinear mechanical model based on cubic-Hermite finite elements. Material parameters in the widely-employed transversely isotropic Gucciones constitutive law are successfully identified for both homogeneous and heterogeneous cases. We conclude that the four parameters in Gucciones law can be uniquely and correctly determined in-silico from noisy displacement measurements of material points located on the myocardial surfaces. The future application of this novel and effective approach to real clinical measurements is thus promising.

The estimation of patient-specific cardiac diastolic functions from clinical measurements

An unresolved issue in patients with diastolic dysfunction is that the estimation of myocardial stiffness cannot be decoupled from diastolic residual active tension (AT) because of the impaired ventricular relaxation during diastole. To address this problem, this paper presents a method for estimating diastolic mechanical parameters of the left ventricle (LV) from cine and tagged MRI measurements and LV cavity pressure recordings, separating the passive myocardial constitutive properties and diastolic residual AT. Dynamic C1-continuous meshes are automatically built from the anatomy and deformation captured from dynamic MRI sequences. Diastolic deformation is simulated using a mechanical model that combines passive and active material properties. The problem of non-uniqueness of constitutive parameter estimation using the well known Guccione law is characterized by reformulation of this law. Using this reformulated form, and by constraining the constitutive parameters to be constant across time points during diastole, we separate the effects of passive constitutive properties and the residual AT during diastolic relaxation. Finally, the method is applied to two clinical cases and one control, demonstrating that increased residual AT during diastole provides a potential novel index for delineating healthy and pathological cases.

Medical Imaging and Physiological Modelling: Linking Physics and Biology

Medical image analysis is increasingly providing a sophisticated set of tools for processing measurement inputs into clinically relevant outputs, although this is, on the whole, completed without consideration of the underlying physiology. In contrast, physiological modelling provides a predictive tool based on a physical and biological understanding of the underlying processes. In this editorial, we discuss the possibility of integrating physiological modelling data with medical images and measurements with the goal of providing new types of physiologically meaningful information with increased clinical relevance.

An automatic service for the personalization of ventricular cardiac meshes

Computational cardiac physiology has great potential to improve the management of cardiovascular diseases. One of the main bottlenecks in this field is the customization of the computational model to the anatomical and physiological status of the patient. We present a fully automatic service for the geometrical personalization of cardiac ventricular meshes with high-order interpolation from segmented images. The method is versatile (able to work with different species and disease conditions) and robust (fully automatic results fulfilling accuracy and quality requirements in 87% of 255 cases). Results also illustrate the capability to minimize the impact of segmentation errors, to overcome the sparse resolution of dynamic studies and to remove the sometimes unnecessary anatomical detail of papillary and trabecular structures. The smooth meshes produced can be used to simulate cardiac function, and in particular mechanics, or can be used as diagnostic descriptors of anatomical shape by cardiologists. This fully automatic service is deployed in a cloud infrastructure, and has been made available and accessible to the scientific community.

A finite-element approach to the direct computation of relative cardiovascular pressure from time-resolved MR velocity data

Graphical abstract Highlights ► Extraction of relative pressure from 4D MRI data sets. ► A novel workflow for determining relative cardiovascular pressure fields. ► Demonstration of the approach across a range of validation examples. ► Four subject specific cases showing agreement with published pressure differences.

Inter-Model Consistency and Complementarity: Learning from ex-vivo Imaging and Electrophysiological Data towards an Integrated Understanding of Cardiac Physiology

Computational models of the heart at various scales and levels of complexity have been independently developed, parameterised and validated using a wide range of experimental data for over four decades. However, despite remarkable progress, the lack of coordinated efforts to compare and combine these computational models has limited their impact on the numerous open questions in cardiac physiology. To address this issue, a comprehensive dataset has previously been made available to the community that contains the cardiac anatomy and fibre orientations from magnetic resonance imaging as well as epicardial transmembrane potentials from optical mapping measured on a perfused ex-vivo porcine heart. This data was used to develop and customize four models of cardiac electrophysiology with different level of details, including a personalized fast conduction Purkinje system, a maximum a posteriori estimation of the 3D distribution of transmembrane potential, the personalization of a simplified reaction-diffusion model, and a detailed biophysical model with generic conduction parameters. This study proposes the integration of these four models into a single modelling and simulation pipeline, after analyzing their common features and discrepancies. The proposed integrated pipeline demonstrates an increase prediction power of depolarization isochrones in different pacing conditions.