A bi-ventricular cardiac atlas built from 1000+ high resolution MR images of healthy subjects and an analysis of shape and motion

Bai, Wenjia; Shi, Wenzhe; Marvao, Antonio de; Dawes, Timothy J W; O’Regan, Declan P; Cook, Stuart A.; Rueckert, Daniel

doi:10.1016/j.media.2015.08.009

Cited by 123 publications

(123 citation statements)

References 69 publications

(106 reference statements)

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“…To complement our 2D studies we collected an independent dataset of high-resolution, single-breath hold 3D CMR images and, blinded to genotype, performed atlas- and machine-based analyses of LV geometry with respect to TTNtv status41,42. The 3D data show that TTNtv were associated with eccentric cardiac remodeling in healthy individuals.…”

Section: Resultsmentioning

confidence: 99%

Titin-truncating variants affect heart function in disease cohorts and the general population

et al. 2016

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Titin truncating variants (TTNtv) commonly cause dilated cardiomyopathy (DCM). TTNtv are also encountered in ~1% of the general population where they may be silent, perhaps reflecting allelic factors. To better understand TTNtv we integrated TTN allelic series, cardiac imaging and genomic data in humans and studied rat models with disparate TTNtv. In patients with DCM, TTNtv throughout TTN were significantly associated with DCM. Ribosomal profiling in rat revealed the translational footprint of premature stop codons in Ttn, TTNtv position-independent nonsense-mediated degradation of the mutant allele and a signature of perturbed cardiac metabolism. Heart physiology in rats with TTNtv was unremarkable at baseline but became impaired during cardiac stress. In healthy humans, machine-based analysis of high-resolution cardiac scans showed TTNtv to be associated with eccentric cardiac remodelling. These data show that TTNtv have molecular and physiological effects on the heart across species, with a continuum of expressivity in health and disease.

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Section: Resultsmentioning

confidence: 99%

Titin-truncating variants affect heart function in disease cohorts and the general population

et al. 2016

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“…The optimal scale and number of dimensions for prediction of CRT response and identification of LBBB was selected as the combination of V s and D j that maximised the classification accuracy from the RSCV. Given the small size of the patient cohort (34 subjects), only up to the first 5 PCA dimensions were assessed to avoid over-fitting, specifically D j ∈ [2,3,4,5]. Accuracies, sensitivities and specificities are visualised in grids with respect to V s (y-axis) and D j (x-axis), as shown in Figure 3.…”

Section: Experiments and Resultsmentioning

confidence: 99%

“…The segmentations from the SA and LA images were subsequently fused and manually smoothed at a 2mm isotropic resolution. Following the identification of anatomical landmarks, a statistical shape model (SSM) was optimised to fit to the endocardial and epicardial surfaces of the LV binary segmentation [2], providing point-correspondence between patient hearts. The overlap of the SSM with each patient's LV geometry was visually assessed and the above process refined if necessary to ensure suitable overlap for subsequent motion tracking.…”

Section: Spatio-temporal Motion Atlasmentioning

confidence: 99%

Learning Optimal Spatial Scales for Cardiac Strain Analysis Using a Motion Atlas

Sinclair

Peressutti

Puyol‐Antón

et al. 2017

Statistical Atlases and Computational Models of the Heart. Imaging and Modelling Challenges

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“…Synthetic data were generated through the use of a statistical shape model (SSM) obtained from [24,25] and is available online (http://wp.doc.ic.ac.uk/ wbai/data/). Using the modes of variation, different plausible heart-like shapes were generated and used in our experiments.…”

Section: Synthetic and Real Datamentioning

confidence: 99%

Surface Mesh Reconstruction from Cardiac MRI Contours

2018

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Abstract:We introduce a tool to build a surface mesh able to deal with sparse, heterogeneous, non-parallel, cross-sectional, non-coincidental contours and show its application to reconstruct surfaces of the heart. In recent years, much research has looked at creating personalised 3D anatomical models of the heart. These models usually incorporate a geometrical reconstruction of the anatomy in order to better understand cardiovascular functions as well as predict different cardiac processes. As MRIs are becoming the standard for cardiac medical imaging, we tested our methodology on cardiac MRI data from standard acquisitions. However, the ability to accurately reconstruct heart anatomy in three dimensions commonly comes with fundamental challenges-notably, the trade-off between data fitting and expected visual appearance. Most current techniques can either require contours from parallel slices or, if multiple slice orientations are used, require an exact match between these contours. In addition, some methods introduce a bias by the use of prior shape models or by trade-offs between the data matching terms and the smoothing terms. Our approach uses a composition of smooth approximations towards the maximization of the data fitting, ensuring a good matching to the input data as well as pleasant interpolation characteristics. To assess our method in the task of cardiac mesh generations, we evaluated its performance on synthetic data obtained from a cardiac statistical shape model as well as on real data. Using a statistical shape model, we simulated standard cardiac MRI acquisitions planes and contour data. We performed a multi-parameter evaluation study using plausible cardiac shapes generated from the model. We also show that long axes contours as well as the most extremal slices (basal and apical) contain the most amount of structural information, and thus should be taken into account when generating anatomically relevant geometrical cardiovascular surfaces. Our method is both used on epicardial and endocardial left ventricle surfaces as well as on the right ventricle.

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A bi-ventricular cardiac atlas built from 1000+ high resolution MR images of healthy subjects and an analysis of shape and motion

Cited by 123 publications

References 69 publications

Titin-truncating variants affect heart function in disease cohorts and the general population

Titin-truncating variants affect heart function in disease cohorts and the general population

Learning Optimal Spatial Scales for Cardiac Strain Analysis Using a Motion Atlas

Surface Mesh Reconstruction from Cardiac MRI Contours

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