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. 2011 Aug 15;27(16):2288-95.
doi: 10.1093/bioinformatics/btr360. Epub 2011 Jul 6.

The Cardiac Atlas Project--an Imaging Database for Computational Modeling and Statistical Atlases of the Heart

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Free PMC article

The Cardiac Atlas Project--an Imaging Database for Computational Modeling and Statistical Atlases of the Heart

Carissa G Fonseca et al. Bioinformatics. .
Free PMC article

Abstract

Motivation: Integrative mathematical and statistical models of cardiac anatomy and physiology can play a vital role in understanding cardiac disease phenotype and planning therapeutic strategies. However, the accuracy and predictive power of such models is dependent upon the breadth and depth of noninvasive imaging datasets. The Cardiac Atlas Project (CAP) has established a large-scale database of cardiac imaging examinations and associated clinical data in order to develop a shareable, web-accessible, structural and functional atlas of the normal and pathological heart for clinical, research and educational purposes. A goal of CAP is to facilitate collaborative statistical analysis of regional heart shape and wall motion and characterize cardiac function among and within population groups.

Results: Three main open-source software components were developed: (i) a database with web-interface; (ii) a modeling client for 3D + time visualization and parametric description of shape and motion; and (iii) open data formats for semantic characterization of models and annotations. The database was implemented using a three-tier architecture utilizing MySQL, JBoss and Dcm4chee, in compliance with the DICOM standard to provide compatibility with existing clinical networks and devices. Parts of Dcm4chee were extended to access image specific attributes as search parameters. To date, approximately 3000 de-identified cardiac imaging examinations are available in the database. All software components developed by the CAP are open source and are freely available under the Mozilla Public License Version 1.1 (http://www.mozilla.org/MPL/MPL-1.1.txt).

Availability: http://www.cardiacatlas.org

Contact: a.young@auckland.ac.nz

Supplementary information: Supplementary data are available at Bioinformatics online.

Figures

Fig. 1.
Fig. 1.
Cine MRI short- (top) and long-axis (bottom) images, at end-diastole (end of ventricular filling, left), and end-systole (end of ejection, right). Contours show inner (green) and outer (blue) boundaries of the left ventricle, and the position of the mitral valve (red).
Fig. 2.
Fig. 2.
CAP workflow. Step 1: data ACQUISITION; Step 2: data processing; Step 3: data analysis and Step 4: public data access.
Fig. 3.
Fig. 3.
Screenshot of the CAP Client running on Mac OS X. One short axis and one long axis MRI image are visible, togther with the inner and outer surfaces of the LV model (green and red lines, respectively).
Fig. 4.
Fig. 4.
First three modes of shape variation in principal component analysis of a subset of the DETERMINE cohort (n=200). Mode 1: size; Mode 2: sphericity; Mode 3: mitral geometry.
Fig. 5.
Fig. 5.
In order to store volumetric models generated with the CAP client application, an XML schema has been designed representing the elements associated with volumetric shape model creation and curation. This includes input parameters, such as images, contours and markers, calculated output parameters, mesh files representing the model geometry, and provenance information.
Fig. 6.
Fig. 6.
Three-tier architecture of the CAP model implementation based on Dcm4chee. Blue boxes represent basic Dcm4chee classes, and yellow boxes represent CAP specific model extensions.

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