Quo vadis cardiovascular informatics?

In spite of the advancement and proliferation of cardiovascular imaging, the rate of deaths due to unpredicted heart attack remains high. Thus, it becomes imperative to develop novel computational tools to mine quantitative parameters from the imaging data for early detection of asymptomatic cardiovascular disease. Coronary calcification burden has been reported to be a significant and independent predictor of the atherosclerosis disease, and is associated with future cardiac events. Additionally, increased neovascularization of the plaque has been identified as a common feature of coronary plaque inflammation and has been defined as a plaque vulnerability index. In this paper, we present methods to extract and quantify coronary calcifications in the non-contrast cardiac CT scans and to detect neovascularization in the coronary vessels using contrast-enhanced intra-vascular ultrasound imaging.

[1]  Antonio Colombo,et al.  From vulnerable plaque to vulnerable patient: a call for new definitions and risk assessment strategies: Part II. , 2003, Circulation.

[2]  Fuhui Long,et al.  Feature selection based on mutual information criteria of max-dependency, max-relevance, and min-redundancy , 2003, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[3]  N. Obuchowski,et al.  Assessing spectral algorithms to predict atherosclerotic plaque composition with normalized and raw intravascular ultrasound data. , 2001, Ultrasound in Medicine and Biology.

[4]  Federico Girosi,et al.  Support Vector Machines: Training and Applications , 1997 .

[5]  Federico Girosi,et al.  Training support vector machines: an application to face detection , 1997, Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[6]  E. Boerwinkle,et al.  From vulnerable plaque to vulnerable patient: a call for new definitions and risk assessment strategies: Part I. , 2003, Circulation.

[7]  K. Laws Textured Image Segmentation , 1980 .

[8]  Nico de Jong,et al.  Nonlinear intravascular ultrasound contrast imaging. , 2006, Ultrasound in medicine & biology.

[9]  E L Ritman,et al.  Impact of coronary vasa vasorum functional structure on coronary vessel wall perfusion distribution. , 2003, American journal of physiology. Heart and circulatory physiology.

[10]  Irwin Feuerstein,et al.  Coronary calcium independently predicts incident premature coronary heart disease over measured cardiovascular risk factors: mean three-year outcomes in the Prospective Army Coronary Calcium (PACC) project. , 2005, Journal of the American College of Cardiology.

[11]  Ioannis A. Kakadiaris,et al.  Intravascular Ultrasound-Based Imaging of Vasa Vasorum for the Detection of Vulnerable Atherosclerotic Plaque , 2005, MICCAI.

[12]  E. Tuzcu,et al.  Coronary Plaque Classification With Intravascular Ultrasound Radiofrequency Data Analysis , 2002, Circulation.

[13]  Khawar Gul,et al.  Vasa vasorum imaging: A new window to the clinical detection of vulnerable atherosclerotic plaques , 2005, Current atherosclerosis reports.

[14]  Nico de Jong,et al.  Subharmonic contrast intravascular ultrasound for vasa vasorum imaging. , 2007, Ultrasound in medicine & biology.

[15]  Ioannis A. Kakadiaris,et al.  One-Class Acoustic Characterization Applied to Blood Detection in IVUS , 2007, MICCAI.

[16]  Nico de Jong,et al.  Contrast Harmonic Intravascular Ultrasound: A Feasibility Study for Vasa Vasorum Imaging , 2006, Investigative radiology.

[17]  Uday Kurkure Computational methods for non-invasive cardiovascular image analysis , 2008 .