Accurate reconstruction of 3D cardiac geometry from coarsely-sliced MRI

Computer Methods and Programs in Biomedicine

Volumn 113, Issue 2, 2014, Pages 483-493

  Ringenberg, Jordan ^a   Deo, Makarand ^b   Devabhaktuni, Vijay ^a   Berenfeld, Omer ^c   Snyder, Brett ^a   Boyers, Pamela ^d   Gold, Jeffrey ^d  

^a The University of Toledo   (United States)

^b NORFOLK STATE UNIVERSITY   (United States)

^c UNIVERSITY OF MICHIGAN MEDICAL SCHOOL   (United States)

^d MEDICAL COLLEGE OF OHIO   (United States)

Author keywords

3D modeling; Cardiac MRI; Patient specific heart models; Variational implicit surfaces; Ventricular geometry

Indexed keywords

3D MODELING; GEOMETRY; HEART; IMAGE RECONSTRUCTION;

CARDIAC MRI; DIFFUSION TENSOR MRI; HEART MODEL; MODELING AND SIMULATION METHODS; SHORT AXIS IMAGES; VALIDATION ANALYSIS; VARIATIONAL IMPLICIT SURFACES; VENTRICULAR GEOMETRY;

THREE DIMENSIONAL COMPUTER GRAPHICS;

ANATOMIC LANDMARK; ANATOMICAL CONCEPTS; ANIMAL EXPERIMENT; ARTICLE; CARDIOVASCULAR MAGNETIC RESONANCE; CONTROLLED STUDY; DIFFUSION TENSOR IMAGING; GEOMETRY; HEART; HEART DISEASE; IN VIVO STUDY; INTERMETHOD COMPARISON; MALE; NONHUMAN; NUCLEAR MAGNETIC RESONANCE SCANNER; RADIOLOGICAL PARAMETERS; RADIOLOGICAL PROCEDURES; SIMULATION; THREE DIMENSIONAL IMAGING;

3D MODELING; CARDIAC MRI; PATIENT-SPECIFIC HEART MODELS; VARIATIONAL IMPLICIT SURFACES; VENTRICULAR GEOMETRY;

HEART; HUMANS; MAGNETIC RESONANCE IMAGING; MODELS, ANATOMIC;

EID: 84892809824     PISSN: 01692607     EISSN: 18727565     Source Type: Journal    
DOI: 10.1016/j.cmpb.2013.11.013     Document Type: Article

References (45)

1. Go A.S., Mozaffarian D., Roger V.L., Benjamin E.J., Berry J.D., Borden W.B., et al. Heart disease and stroke statistics - 2013 update: a report from the American Heart Association. Circulation 2012, 127:e6-e245.
2. Heidenreich P.A., Trogdon J.G., Khavjou O.A., Butler J., Dracup K., Ezekowitz M.D., et al. Forecasting the future of cardiovascular disease in the United States: a policy statement from the American Heart Association. Circulation 2011, 123:933-944.
3. World Health Organization The Top 10 Causes of Death (Fact Sheet No. 317) 2011.
4. Roger V.L., Go A.S., Lloyd-Jones D.M., Adams R.J., Berry J.D., Brown T.M., et al. Heart disease and stroke statistics - 2011 update: a report from the American Heart Association. Circulation 2011, 123:e18-e209.
5. Petitjean C., Dacher J.-N. A review of segmentation methods in short axis cardiac MR images. Medical Image Analysis 2011, 15:169-184.
6. Sermesant M., Peyrat J.-M., Chinchapatnam P., Billet F., Mansi T., Rhode K., et al. Toward patient-specific myocardial models of the heart. Heart Failure Clinics 2008, 4:289-301.
7. Ringenberg J., Deo M., Devabhaktuni V., Filgueiras-Rama G., Pizarro D., Ibañez B., Berenfeld O., et al. Automated segmentation and reconstruction of patient-specific cardiac anatomy and pathology from in vivo MRI. Measurement Science and Technology 2012, 23:125405.
8. Wang L., Dawoud F., Wong K.C.L., Zhang H., Liu H., Lardo A.C., et al. Transmural electrophysiologic and scar imaging on porcine heart with chronic infarction. Statistical Atlases and Computational Models of the Heart: Imaging and Modelling Challenges 2012, 23-32.
9. Bartz D., Botha C.P., Hornegger J., Machiraju R., Wiebel A., Preim B. Interactive real time simulation of cardiac radio-frequency ablation. Eurographics Workshop on Visual Computing for Biology and Medicine 2010, 91-98.
10. Crampin M., Halstead E.J., Hunter M., Nielsen P., Noble P., Smith D., Tawhai N. Computational physiology and the physiome project. Experimental Physiology 2004, 89:1-26.
11. Hunter P., Nielsen P. A strategy for integrative computational physiology. Physiology 2005, 20:316-325.
12. Kerckhoffs R.C., Narayan S.M., Omens J.H., Mulligan L.J., McCulloch A.D. Computational modeling for bedside application. Heart Failure Clinics 2008, 4:371-378.
13. Sermesant M., Chabiniok R., Chinchapatnam P., Mansi T., Billet F., Moireau P., et al. Patient-specific electromechanical models of the heart for the prediction of pacing acute effects in CRT: a preliminary clinical validation. Medical Image Analysis 2012, 16:201-215.
14. Wong K.C.L., Billet F., Mansi T., Chabiniok R., Sermesant M., Delingette H., et al. Cardiac motion estimation using a proactive deformable model: evaluation and sensitivity analysis. Statistical Atlases and Computational Models of the Heart 2010, 154-163.
15. McLeod K., Prakosa A., Mansi T., Pennec X. An incompressible log-domain demons algorithm for tracking heart tissue. Statistical Atlases and Computational Models of the Heart: Imaging and Modelling Challenges 2012, 55-67.
16. Akhbardeh A., Tavakolian K., Gurev V., Lee T., New W., Kaminska B., et al. Comparative analysis of three different modalities for characterization of the seismocardiogram. IEEE Engineering in Medicine and Biology Society 2009, 2899-2903.
17. Toussaint N., Mansi T., Delingette H., Ayache N., Sermesant M. An integrated platform for dynamic cardiac simulation and image processing: application to personalised tetralogy of Fallot simulation. Proc. Eurographics Workshop on Visual Computing for Biomedicine (VCBM) 2008, 21-28.
18. Turk G., O'Brien J.F. Variational Implicit Surfaces. Technical Report 1999, Georgia Institute of Technology.
19. Vadakkumpadan F., Arevalo H., Prassl A.J., Chen J., Kickinger F., Kohl P., et al. Image-based models of cardiac structure in health and disease. Wiley Interdisciplinary Reviews: Systems Biology and Medicine 2010, 2:489-506.
20. Peyrat J.-M., Sermesant M., Pennec X., Delingette H., Xu C., McVeigh E.R., et al. A computational framework for the statistical analysis of cardiac diffusion tensors: application to a small database of canine hearts. IEEE Transactions on Medical Imaging 2007, 26:1500-1514.
21. Vázquez M., Arís R., Houzeaux G., Aubry R., Villar P., Garcia-Barnés J., et al. A massively parallel computational electrophysiology model of the heart. International Journal for Numerical Methods in Biomedical Engineering 2011, 27:1911-1929.
22. Helm P.A., Tseng H.-J., Younes L., McVeigh E.R., Winslow R.L. Ex vivo 3D diffusion tensor imaging and quantification of cardiac laminar structure. Magnetic Resonance in Medicine 2005, 54:850-859.
23. Helm P. A Novel Technique for Quantifying Variability of Cardiac Anatomy: Application to the Dyssynchronous Failing Heart 2005, Johns Hopkins University, (Ph.D. Dissertation).
24. Scollan D.F., Holmes A., Zhang J., Winslow R.L. Reconstruction of cardiac ventricular geometry and fiber orientation using magnetic resonance imaging. Annals of Biomedical Engineering 2000, 28:934-944.
25. Turk G., O'Brien J. Shape transformation using variational implicit functions. SIGGRAPH'99: Proceedings of the 26th Annual Conference on Computer Graphics and Interactive Techniques 1999, 335-342.
26. Wendland H. Scattered data approximation. Cambridge Monographs on Applied and Computational Mathematics 2005, 41-42. Cambridge University Press, Cambridge. C.U. Press (Ed.).
27. Mansi T. Modèles physiologiques et statistiques du cœur guidés par imagerie médicale: application à la tétralogie de Fallot 2010, École Nationale Supérieure des Mines de Paris, (Ph.D. Dissertation).
28. Dinh H.Q., Turk G., Slabaugh G. Reconstructing surfaces using anisotropic basis functions. Proceedings of the Eighth IEEE International Conference on Computer Vision, 2001 (ICCV 2001) 2001, 606-613.
29. Morse B.S., Yoo T.S., Rheingans P., Chen D.T., Subramanian K.R. Interpolating implicit surfaces from scattered surface data using compactly supported radial basis functions. ACM SIGGRAPH 2005, 78.
30. Lorensen W.E., Cline H.E. Marching cubes: a high resolution 3D surface construction algorithm. ACM Siggraph Computer Graphics 1987, 21:163-169.
31. Cocosco C., Niessen W.J., Netsch T., Vonken E.-J.P., Lund G., Stork A., et al. Automatic image-driven segmentation of the ventricles in cardiac cine MRI. Journal of Magnetic Resonance Imaging: JMRI 2008, 28:366-374.
32. Lynch M., Ghita O., Whelan P.F. Automatic segmentation of the left ventricle cavity and myocardium in MRI data. Computers in Biology and Medicine 2006, 36:389-407.
33. Sun H., Frangi A.F., Wang H., Sukno F.M., Tobon-Gomez C., Yushkevich P.A. Automatic cardiac MRI segmentation using a biventricular deformable medial model. Medical Image Computing and Computer-Assisted Intervention (MICCAI) 2010, 468-475.
34. Senegas J., Netsch T., Cocosco C.A., Lund G., Stork A. Segmentation of medical images with a shape and motion model: a Bayesian perspective. Computer Vision and Mathematical Methods in Medical and Biomedical Image Analysis 2004, 157-168.
35. Lynch M., Ghita O., Whelan P.F. Segmentation of the left ventricle of the heart in 3-D+t MRI data using an optimized nonrigid temporal model. IEEE Transactions on Medical Imaging 2008, 27:195-203.
36. Jolly M.-P., Guetter C., Lu X., Xue H., Guehring J. Automatic segmentation of the myocardium in cine MR images using deformable registration. Statistical Atlases and Computational Models of the Heart: Imaging and Modelling Challenges 2012, 98-108.
37. Margeta A., Geremia J., Criminisi E., Ayache N. Layered spatio-temporal forests for left ventricle segmentation from 4D cardiac MRI data. Statistical Atlases and Computational Models of the Heart: Imaging and Modelling Challenges 2012, 109-119.
38. Costa K.D., Takayama Y., McCulloch A.D., Covell J.W. Laminar fiber architecture and three-dimensional systolic mechanics in canine ventricular myocardium. American Journal of Physiology: Heart and Circulatory Physiology 1999, 276:H595-H607.
39. Costa K.D., Holmes J.W., McCulloch A.D. Modelling cardiac mechanical properties in three dimensions. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 2001, 359:1233-1250.
40. Tusscher T., Kirsten H., Panfilov A.V. Organization of ventricular fibrillation in the human heart. Circulation Research 2007, 100:e87-e101.
41. Bayer J.D., Blake R.C., Plank G., Trayanova N.A. A novel rule-based algorithm for assigning myocardial fiber orientation to computational heart models. Annals of Biomedical Engineering 2012, 1-12.
42. Aguado-Sierra J., Krishnamurthy A., Villongco C., Chuang J., Howard E., Gonzales M.J., et al. Patient-specific modeling of dyssynchronous heart failure: a case study. Progress in Biophysics and Molecular Biology 2011, 107:147-155.
43. Lötjönen J., Kivistö S., Koikkalainen J., Smutek D., Lauerma K. Statistical shape model of atria, ventricles and epicardium from short- and long-axis MR images. Medical Image Analysis 2004, 8:371-386.
44. Young A.A., Medway D.J., Lygate C.A., Neubauer S., Schneider J.E. Accelerating global left-ventricular function assessment in mice using reduced slice acquisition and three-dimensional guide-point modelling. Journal of Magnetic Resonance Imaging: JMRI 2011, 13.
45. Young A.A., Barnes H., Davison D., Neubauer S., Schneider J.E. Fast left ventricular mass and volume assessment in mice with three-dimensional guide-point modeling. Journal of Magnetic Resonance Imaging: JMRI 2009, 30:514-520.