Oscar Camara

Cardiac function estimation from MRI using a heart model and data assimilation: advances and difficulties.

In this paper, we present a framework to estimate local ventricular myocardium contractility using clinical MRI, a heart model and data assimilation. First, we build a generic anatomical model of the ventricles including muscle fibre orientations and anatomical subdivisions. Then, this model is deformed to fit a clinical MRI, using a semi-automatic fuzzy segmentation, an affine registration method and a local deformable biomechanical model. An electromechanical model of the heart is then presented and simulated. Finally, a data assimilation procedure is described, and applied to this model. Data assimilation makes it possible to estimate local contractility from given displacements. Presented results on fitting to patient-specific anatomy and assimilation with simulated data are very promising. Current work on model calibration and estimation of patient parameters opens up possibilities to apply this framework in a clinical environment.

Integration of fuzzy spatial relations in deformable models-Application to brain MRI segmentation

This paper presents a general framework to integrate a new type of constraints, based on spatial relations, in deformable models. In the proposed approach, spatial relations are represented as fuzzy subsets of the image space and incorporated in the deformable model as a new external force. Three methods to construct an external force from a fuzzy set representing a spatial relation are introduced and discussed. This framework is then used to segment brain subcortical structures in magnetic resonance images (MRI). A training step is proposed to estimate the main parameters defining the relations. The results demonstrate that the introduction of spatial relations in a deformable model can substantially improve the segmentation of structures with low contrast and ill-defined boundaries.

Temporal diffeomorphic free-form deformation: Application to motion and strain estimation from 3D echocardiography

This paper presents a new registration algorithm, called Temporal Diffeomorphic Free Form Deformation (TDFFD), and its application to motion and strain quantification from a sequence of 3D ultrasound (US) images. The originality of our approach resides in enforcing time consistency by representing the 4D velocity field as the sum of continuous spatiotemporal B-Spline kernels. The spatiotemporal displacement field is then recovered through forward Eulerian integration of the non-stationary velocity field. The strain tensor is computed locally using the spatial derivatives of the reconstructed displacement field. The energy functional considered in this paper weighs two terms: the image similarity and a regularization term. The image similarity metric is the sum of squared differences between the intensities of each frame and a reference one. Any frame in the sequence can be chosen as reference. The regularization term is based on the incompressibility of myocardial tissue. TDFFD was compared to pairwise 3D FFD and 3D+t FFD, both on displacement and velocity fields, on a set of synthetic 3D US images with different noise levels. TDFFD showed increased robustness to noise compared to these two state-of-the-art algorithms. TDFFD also proved to be more resistant to a reduced temporal resolution when decimating this synthetic sequence. Finally, this synthetic dataset was used to determine optimal settings of the TDFFD algorithm. Subsequently, TDFFD was applied to a database of cardiac 3D US images of the left ventricle acquired from 9 healthy volunteers and 13 patients treated by Cardiac Resynchronization Therapy (CRT). On healthy cases, uniform strain patterns were observed over all myocardial segments, as physiologically expected. On all CRT patients, the improvement in synchrony of regional longitudinal strain correlated with CRT clinical outcome as quantified by the reduction of end-systolic left ventricular volume at follow-up (6 and 12months), showing the potential of the proposed algorithm for the assessment of CRT.

Three-dimensional Architecture of Scar and Conducting Channels Based on High Resolution ce-CMR: Insights for Ventricular Tachycardia Ablation

Background—Conducting channels are the target for ventricular tachycardia (VT) ablation. Conducting channels could be identified with contrast enhanced–cardiac magnetic resonance (ce-CMR) as border zone (BZ) corridors. A 3-dimensional (3D) reconstruction of the ce-CMR could allow visualization of the 3D structure of these BZ channels. Methods and Results—We included 21 patients with healed myocardial infarction and VT. A 3D high-resolution 3T ce-CMR was performed before CARTO-guided VT ablation. The left ventricular wall was segmented and characterized using a pixel signal intensity algorithm at 5 layers (endocardium, 25%, 50%, 75%, epicardium). A 3D color-coded shell map was obtained for each layer to depict the scar core and BZ distribution. The presence/characteristics of BZ channels were registered for each layer. Scar area decreased progressively from endocardium to epicardium (scar area/left ventricular area: 34.0±17.4% at endocardium, 24.1±14.7% at 25%, 16.3±12.1% at 50%, 13.1±10.4 at 75%, 12.1±9.3% at epicardium; P<0.01). Forty-five BZ channels (2.1±1.0 per patient, 23.7±12.0 mm length, mean minimum width 2.5±1.5 mm) were identified, 85% between the endocardium and 50% shell and 76% present in ≥1 layer. The ce-CMR–defined BZ channels identified 74% of the critical isthmus of clinical VTs and 50% of all the conducting channels identified in electroanatomic maps. Conclusions—Scar area in patients with healed myocardial infarction decreases from the endocardium to the epicardium. BZ channels, more commonly seen in the endocardium, display a 3D structure within the myocardial wall that can be depicted with ce-CMR. The use of ce-CMR–derived maps to guide VT ablation warrants further investigation.

OpenCMISS: A multi-physics & multi-scale computational infrastructure for the VPH/Physiome project

The VPH/Physiome Project is developing the model encoding standards CellML (cellml.org) and FieldML (fieldml.org) as well as web-accessible model repositories based on these standards (models.physiome.org). Freely available open source computational modelling software is also being developed to solve the partial differential equations described by the models and to visualise results. The OpenCMISS code (opencmiss.org), described here, has been developed by the authors over the last six years to replace the CMISS code that has supported a number of organ system Physiome projects. OpenCMISS is designed to encompass multiple sets of physical equations and to link subcellular and tissue-level biophysical processes into organ-level processes. In the Heart Physiome project, for example, the large deformation mechanics of the myocardial wall need to be coupled to both ventricular flow and embedded coronary flow, and the reaction-diffusion equations that govern the propagation of electrical waves through myocardial tissue need to be coupled with equations that describe the ion channel currents that flow through the cardiac cell membranes. In this paper we discuss the design principles and distributed memory architecture behind the OpenCMISS code. We also discuss the design of the interfaces that link the sets of physical equations across common boundaries (such as fluid-structure coupling), or between spatial fields over the same domain (such as coupled electromechanics), and the concepts behind CellML and FieldML that are embodied in the OpenCMISS data structures. We show how all of these provide a flexible infrastructure for combining models developed across the VPH/Physiome community.

Simulation of cardiac pathologies using an electromechanical biventricular model and XMR interventional imaging

Simulating cardiac electromechanical activity is of great interest for a better understanding of pathologies and for therapy planning. Design and validation of such models is difficult due to the lack of clinical data. XMR systems are a new type of interventional facility in which patients can be rapidly transferred between X-ray and MR systems. Our goal is to design and validate an electromechanical model of the myocardium using XMR imaging. The proposed model is computationally fast and uses clinically observable parameters. We present the integration of anatomy, electrophysiology, and motion from patient data. Pathologies are introduced in the model and simulations are compared to measured data. Initial qualitative comparison on the two clinical cases presented is encouraging. Once fully validated, these models will make it possible to simulate different interventional strategies.

Relationship between endocardial activation sequences defined by high-density mapping to early septal contraction (septal flash) in patients with left bundle branch block undergoing cardiac resynchronization therapy

AIMS Early inward motion and thickening/thinning of the ventricular septum associated with left bundle branch block is known as the septal flash (SF). Correction of SF corresponds to response to cardiac resynchronization therapy (CRT). We hypothesized that SF was associated with a specific left ventricular (LV) activation pattern predicting a favourable response to CRT. We sought to characterize the spatio-temporal relationship between electrical and mechanical events by directly comparing non-contact mapping (NCM), acute haemodynamics, and echocardiography. METHODS AND RESULTS Thirteen patients (63 ± 10 years, 10 men) with severe heart failure (ejection fraction 22.8 ± 5.8%) awaiting CRT underwent echocardiography and NCM pre-implant. Presence and extent of SF defined visually and with M-mode was fused with NCM bulls eye plots of endocardial activation patterns. LV-dP/dt(max) was measured during different pacing modes. Five patients had a large SF, four small SF, and four no SF. Large SF patients had areas of conduction block in non-infarcted regions, whereas those with small or no SF did not. Patients with large SF had greater acute response to LV and biventricular (BIV) pacing vs. those with small/no SF (% increase dP/dt 28 ± 14 vs. 11 ± 19% for LV pacing and 42 ± 28 vs. 22 ± 21% for BIV pacing) (P < 0.05). This translated into a more favourable chronic response to CRT. The lines of conduction block disappeared with LV/BIV pacing while remaining with right ventricle pacing. CONCLUSION A strong association exists between electrical activation and mechanical deformation of the septum. Correction of both mechanical synchrony and the functional conduction block by CRT may explain the favourable response in patients with SF.

Computational modeling of thoracic and abdominal anatomy using spatial relationships for image segmentation

This paper presents an original hierarchical segmentation approach of several thoracic and abdominal structures in CT and emission PET images. Segmentation results will be used to initialize a non-linear registration procedure between these complementary imaging modalities. Therefore, structures involved in the segmentation system must be visible in both CT and emission PET images in order to compute a spatial transformation between them. Thus, the chosen structures include lungs, kidneys and liver (skin and skeleton are also segmented as support structures). In the hierarchical segmentation procedure, the extraction of a given structure is driven by information derived from a simpler one. This information is composed of spatial constraints inferred from the previously segmented structures and expressed by means of Regions Of Interest (ROI) in which the search for new structures will take place. The segmentation of each structure follows a two-phase process: a first stage is composed of automatic thresholding and other low-level operations in the ROI defined by previously segmented objects; a second stage employs a 3D deformable model to refine and regularize results provided by the former step. Visual inspection by medical experts has stated that the proposed segmentation approach provides results which are accurate enough to guide a subsequent non-linear registration procedure.

Generalised overlap measures for assessment of pairwise and groupwise image registration and segmentation

Effective validation techniques are an essential pre-requisite for segmentation and non-rigid registration techniques to enter clinical use. These algorithms can be evaluated by calculating the overlap of corresponding test and gold-standard regions. Common overlap measures compare pairs of binary labels but it is now common for multiple labels to exist and for fractional (partial volume) labels to be used to describe multiple tissue types contributing to a single voxel. Evaluation studies may involve multiple image pairs. In this paper we use results from fuzzy set theory and fuzzy morphology to extend the definitions of existing overlap measures to accommodate multiple fractional labels. Simple formulas are provided which define single figures of merit to quantify the total overlap for ensembles of pairwise or groupwise label comparisons. A quantitative link between overlap and registration error is established by defining the overlap tolerance. Experiments are performed on publicly available labeled brain data to demonstrate the new measures in a comparison of pairwise and groupwise registration.

Accuracy assessment of global and local atrophy measurement techniques with realistic simulated longitudinal Alzheimer's disease images

The evaluation of atrophy quantification methods based on magnetic resonance imaging have been usually hindered by the lack of realistic gold standard data against which to judge these methods or to help refine them. Recently [Camara, O., Schweiger, M., Scahill, R., Crum, W., Sneller, B., Schnabel, J., Ridgway, G., Cash, D., Hill, D., Fox, N., 2006. Phenomenological model of diffuse global and regional atrophy using finite-element methods. IEEE Trans. Med.l Imaging 25, 1417-1430], we presented a technique in which atrophy is realistically simulated in different tissue compartments or neuroanatomical structures with a phenomenological model. In this study, we have generated a cohort of realistic simulated Alzheimers disease (AD) images with known amounts of atrophy, mimicking a set of 19 real controls and 27 probable AD subjects, with an improved version of our atrophy simulation methodology. This database was then used to assess the accuracy of several well-known computational anatomy methods which provide global (BSI and SIENA) or local (Jacobian integration) estimates of longitudinal atrophy in brain structures using MR images. SIENA and BSI results correlated very well with gold standard data (Pearson coefficient of 0.962 and 0.969 respectively), achieving small mean absolute differences with respect to the gold standard (percentage change from baseline volume): BSI of 0.23%+/-0.26%; SIENA of 0.22%+/-0.28%. Jacobian integration was guided by both fluid and FFD-based registration techniques and resulting deformation fields and associated Jacobians were compared, region by region, with gold standard ones. The FFD-based technique outperformed the fluid one in all evaluated structures (mean absolute differences from the gold standard in percentage change from baseline volume): whole brain, FFD=0.31%, fluid=0.58%; lateral ventricles, FFD=0.79%; fluid=1.45%; left hippocampus, FFD=0.82%; fluid=1.42%; right hippocampus, FFD=0.95%; fluid=1.62%. The largest errors for both local techniques occurred in the sulcal CSF (FFD=2.27%; fluid=3.55%) regions. For large structures such as the whole brain, these mean absolute differences, relative to the applied atrophy, represented similar percentages for the BSI, SIENA and FFD techniques (controls/patients): BSI, 51.99%/16.36%; SIENA, 62.34%/21.59%; FFD, 41.02%/24.95%. For small structures such as the hippocampi, these percentages were larger, especially for controls where errors were approximately equal to the small applied changes (controls/patients): FFD, 92.82%/43.61%. However, these apparently large relative errors have not prevented the global or hippocampal measures from finding significant group separation in our study. The evaluation framework presented here will help in quantifying whether the accuracy of future methodological developments is sufficient for analysing change in smaller or less atrophied local brain regions. Results obtained in our experiments with realistic simulated data confirm previously published estimates of accuracy for both evaluated global techniques. Regarding Jacobian Integration methods, the FFD-based one demonstrated promising results and potential for being used in clinical studies alongside (or in place of) the more common global methods. The generated gold standard data has also allowed us to identify some stages and sets of parameters in the evaluated techniques--the brain extraction step in the global techniques and the number of multi-resolution levels and the stopping criteria in the registration-based methods--that are critical for their accuracy.