The Cardiac Atlas Project: Preliminary Description of Heart Shape in Patients with Myocardial Infarction

Medrano-Gracia, Pau; Cowan, Brett R.; Finn, J. Paul; Fonseca, Carissa G.; Kadish, Alan H.; Lee, Daniel; Tao, Wenchao; Young, Alistair A.

doi:10.1007/978-3-642-15835-3_5

Cited by 8 publications

(6 citation statements)

References 15 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The CAP was established as a worldwide consortium for pooling standardized analyses of cardiac images into a database for mapping heart shape and motion 5, 12, 14 . Cardiac MR datasets were obtained with informed consent compatible with data sharing, and data were contributed to the CAP database with the approval of the local institutional review board.…”

Section: Methodsmentioning

confidence: 99%

“…A statistical shape analysis in repaired tetralogy of Fallot patients uncovered significant correlations of RV dilatation, outflow tract bulging, and apical dilatation with the presence of pulmonary regurgitation 9 . A study of shape analysis in myocardial infarction showed that atlas-based shape parameters classified patients from asymptomatic controls with 94% specificity and 93% sensitivity 12, 14 . An MRI study using the same type of shape analysis techniques showed that young adults born pre-term had significant differences in LV mass, 3D geometry and regional wall motion that could predispose them to heart disease in later life 10 .…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Atlas-based ventricular shape analysis for understanding congenital heart disease

Farrar

Suinesiaputra

Gilbert

et al. 2016

Progress in Pediatric Cardiology

Self Cite

View full text Add to dashboard Cite

Congenital heart disease is associated with abnormal ventricular shape that can affect wall mechanics and may be predictive of long-term adverse outcomes. Atlas-based parametric shape analysis was used to analyze ventricular geometries of eight adolescent or adult single-ventricle CHD patients with tricuspid atresia and Fontans. These patients were compared with an “atlas” of non-congenital asymptomatic volunteers, resulting in a set of z-scores which quantify deviations from the control population distribution on a patient-by-patient basis. We examined the potential of these scores to: (1) quantify abnormalities of ventricular geometry in single ventricle physiologies relative to the normal population; (2) comprehensively quantify wall motion in CHD patients; and (3) identify possible relationships between ventricular shape and wall motion that may reflect underlying functional defects or remodeling in CHD patients. CHD ventricular geometries at end-diastole and end-systole were individually compared with statistical shape properties of an asymptomatic population from the Cardiac Atlas Project. Shape analysis-derived model properties, and myocardial wall motions between end-diastole and end-systole, were compared with physician observations of clinical functional parameters. Relationships between altered shape and altered function were evaluated via correlations between atlas-based shape and wall motion scores. Atlas-based shape analysis identified a diverse set of specific quantifiable abnormalities in ventricular geometry or myocardial wall motion in all subjects. Moreover, this initial cohort displayed significant relationships between specific shape abnormalities such as increased ventricular sphericity and functional defects in myocardial deformation, such as decreased long-axis wall motion. These findings suggest that atlas-based ventricular shape analysis may be a useful new tool in the management of patients with CHD who are at risk of impaired ventricular wall mechanics and chamber remodeling.

show abstract

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Atlas-based ventricular shape analysis for understanding congenital heart disease

Farrar

Suinesiaputra

Gilbert

et al. 2016

Progress in Pediatric Cardiology

Self Cite

View full text Add to dashboard Cite

show abstract

“…The construction of a statistical shape Preprint version accepted to appear in IEEE Transactions on Medical Imaging. Final version of this paper available at http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6362225 model of the left ventricle from part of this data (200 training shapes) was demonstrated in [13].…”

Section: Related Workmentioning

confidence: 99%

A High-Resolution Atlas and Statistical Model of the Human Heart From Multislice CT

Hoogendoorn

Duchateau

Sánchez‐Quintana

et al. 2013

IEEE Trans. Med. Imaging

View full text Add to dashboard Cite

Atlases and statistical models play important roles in the personalization and simulation of cardiac physiology. For the study of the heart, however, the construction of comprehensive atlases and spatio-temporal models is faced with a number of challenges, in particular the need to handle large and highly variable image datasets, the multi-region nature of the heart, and the presence of complex as well as small cardiovascular structures. In this paper, we present a detailed atlas and spatio-temporal statistical model of the human heart based on a large population of 3D+time multi-slice computed tomography sequences, and the framework for its construction. It uses spatial normalization based on nonrigid image registration to synthesize a population mean image and establish the spatial relationships between the mean and the subjects in the population. Temporal image registration is then applied to resolve each subject-specific cardiac motion and the resulting transformations are used to warp a surface mesh representation of the atlas to fit the images of the remaining cardiac phases in each subject. Subsequently, we demonstrate the construction of a spatio-temporal statistical model of shape such that the inter-subject and dynamic sources of variation are suitably separated. The framework is applied to a 3D+time data set of 138 subjects. The data is drawn from a variety of pathologies, which benefits its generalization to new subjects and physiological studies. The obtained level of detail and the extendability of the atlas present an advantage over most cardiac models published previously.

show abstract

“…The PCA-based method also allows the usage of only a few modes of variation, and yet maintains an acceptable accuracy in the LVEF estimation. As pointed out by other researchers, 7,13 the first three to five PCs describe the majority of the shape variances in SSM. In our case, the first three and five PCs describe 71.4% and 86.5%, respectively, of the overall variances in our SSM.…”

Section: Discussion Conclusion and Future Workmentioning

confidence: 62%

Combining statistical shape model and principal component analysis to estimate left ventricular volume and ejection fraction

Liu

Dangi

Schwarz

et al. 2020

Medical Imaging 2020: Ultrasonic Imaging and Tomography

View full text Add to dashboard Cite

Left ventricular ejection fraction (LVEF) assessment is instrumental for cardiac health diagnosis, patient management, and patient eligibility for participation in clinical studies. Due to its noninvasiveness and low operational cost, ultrasound (US) imaging is the most commonly used imaging modality to image the heart and assess LVEF. Even though 3D US imaging technology is becoming more available, cardiologists dominantly use 2D US imaging to visualize the LV blood pool and interpret its area changes between end-systole and end-diastole. Our previous work showed that LVEF estimates based on area changes are significantly lower than the true volumebased estimates by as much as 13%, 1 which could lead to unnecessary and costly therapeutic decisions. Acquiring volumetric information about the LV blood pool necessitates either timeconsuming 3D reconstruction or 3D US image acquisition. Here, we propose a method that leverages on a statistical shape model (SSM) constructed from 13 landmarks depicting the LV endocardial border to estimate a new patient's LV volume and LVEF. Two methods to estimate the 3D LV geometry with and without size normalization were employed. The SSM was built using the 13 landmarks from 50 training patient image datasets. Subsequently, the Mahalanobis distance (with size normalization) or the vector distance (without size normalization) between an incoming patient's LV landmarks and each shape in the SSM were used to determine the weights each training patient contributed to describing the new, incoming patient's LV geometry and associated blood pool volume. We tested the proposed method to estimate the LV volumes and LVEF for 16 new test patients. The estimated LVEFs based on Mahalanobis distance and vector distance were within 2.9% and 1.1%, respectively, of the ground truth LVEFs calculated from the 3D reconstructed LV volumes. Furthermore, the viability of using fewer principal components (PCs) to estimate the LV volume was explored by reducing the number of PCs retained when projecting landmarks onto PCA space. LVEF estimated based on 3 PCs, 5 PCs, and 10 PCs are within 6.6%, 5.4%, and 3.3%, respectively, of LVEF estimates using the full set of 39 PCs.

show abstract

The Cardiac Atlas Project: Preliminary Description of Heart Shape in Patients with Myocardial Infarction

Cited by 8 publications

References 15 publications

Atlas-based ventricular shape analysis for understanding congenital heart disease

Atlas-based ventricular shape analysis for understanding congenital heart disease

A High-Resolution Atlas and Statistical Model of the Human Heart From Multislice CT

Combining statistical shape model and principal component analysis to estimate left ventricular volume and ejection fraction

Contact Info

Product

Resources

About