Literature DB >> 20879234

Complete valvular heart apparatus model from 4D cardiac CT.

Sasa Grbić1, Razvan Ionasec, Dime Vitanovski, Ingmar Voigt, Yang Wang, Bogdan Georgescu, Nassir Navab, Dorin Comaniciu.   

Abstract

The cardiac valvular apparatus, composed of the aortic, mitral, pulmonary and tricuspid valve, is an essential part of the anatomical, functional and hemodynamic mechanism of the heart and the cardiovascular system as a whole. Valvular heart diseases often involve multiple dysfunctions and require joint assessment and therapy of the valves. In this paper, we propose a complete and modular patient-specific model of the cardiac valvular apparatus estimated from 4D cardiac CT data. A new constrained Multi-linear Shape Model (cMSM), conditioned by anatomical measurements, is introduced to represent the complex spatiotemporal variation of the heart valves. The cMSM is exploited within a learning-based framework to efficiently estimate the patient-specific valve parameters from cine images. Experiments on 64 4D cardiac CT studies demonstrate the performance and clinical potential of the proposed method. To the best of our knowledge, it is the first time cardiologists and cardiac surgeons can benefit from an automatic quantitative evaluation of the complete valvular apparatus based on non-invasive imaging techniques. In conjunction with existent patient-specific chamber models, the presented valvular model enables personalized computation modeling and realistic simulation of the entire cardiac system.

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Year:  2010        PMID: 20879234     DOI: 10.1007/978-3-642-15705-9_27

Source DB:  PubMed          Journal:  Med Image Comput Comput Assist Interv


  4 in total

Review 1.  In vivo imaging and computational analysis of the aortic root. Application in clinical research and design of transcatheter aortic valve systems.

Authors:  Paul Schoenhagen; Alexander Hill; Tim Kelley; Zoran Popovic; Sandra S Halliburton
Journal:  J Cardiovasc Transl Res       Date:  2011-04-12       Impact factor: 4.132

Review 2.  Artificial Intelligence in Cardiovascular Imaging: JACC State-of-the-Art Review.

Authors:  Damini Dey; Piotr J Slomka; Paul Leeson; Dorin Comaniciu; Sirish Shrestha; Partho P Sengupta; Thomas H Marwick
Journal:  J Am Coll Cardiol       Date:  2019-03-26       Impact factor: 24.094

3.  Feasibility of in vivo human aortic valve modeling using real-time three-dimensional echocardiography.

Authors:  Arminder S Jassar; Melissa M Levack; Ricardo D Solorzano; Alison M Pouch; Giovanni Ferrari; Albert T Cheung; Victor A Ferrari; Joseph H Gorman; Robert C Gorman; Benjamin M Jackson
Journal:  Ann Thorac Surg       Date:  2014-02-08       Impact factor: 4.330

4.  Position paper of the EACVI and EANM on artificial intelligence applications in multimodality cardiovascular imaging using SPECT/CT, PET/CT, and cardiac CT.

Authors:  Riemer H J A Slart; Michelle C Williams; Luis Eduardo Juarez-Orozco; Christoph Rischpler; Marc R Dweck; Andor W J M Glaudemans; Alessia Gimelli; Panagiotis Georgoulias; Olivier Gheysens; Oliver Gaemperli; Gilbert Habib; Roland Hustinx; Bernard Cosyns; Hein J Verberne; Fabien Hyafil; Paola A Erba; Mark Lubberink; Piotr Slomka; Ivana Išgum; Dimitris Visvikis; Márton Kolossváry; Antti Saraste
Journal:  Eur J Nucl Med Mol Imaging       Date:  2021-04-17       Impact factor: 9.236

  4 in total

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