Comparative Study of Left Ventricular Low Wall Motion with Scar Tissue Using 4D Left Ventricular Cardiac Images
Keywords:Left ventricular remodeling, myocardial wall motion, Cardiac imaging, Fibrotic tissue, Noninvasive cardiac evaluation
Myocardial contraction affects the cardiovascular pumping system, and helps in the early phase to detect abnormalities of wall motion noninvasively. In this research, we designed a program to characterize regional abnormalities because scar tissue is very difficult to identify in normal cardiac CT images. We created 10 frames of a 3D heart model that contains the long axis as reference for predicting the left ventricular wall motion. We tested our 4D cardiac model with scar tissue using non invasive cardiac CT images. Here, four subjects (patients) were involved in this study. Subject 1 and 4 are matching the low motion of surgical area with scar tissue area. Subject 2 found fibrous tissue regions (about 40%), compared with the 2SD (Standard Deviation) region. The fibrotic area is completely overlapped with a low-motion region which indicates the fibrotic area has a significant correlation with the low wall motion region. This research evaluates low wall motion of the left ventricle and detection of fibrosis regions.
(1) J. Areeda, E. Garcia, K.Vantrain, D. Brown, A. Waxman and D. Berman. A comprehensive method for automatic analysis of rest/exercise ventricular function from radionuclide angiography. Digital Imaging: Clinical Advances in NuclearMedicine,1982.
(2) E. L. Bolson et al. Left ventricular segmental wall motion - A new method using local direction information. The computer in Cardiology, 1980.
(3) I. Clayton et al. The characteristic sequence for the onset of contraction in the normal left ventricle. Circulation,1979, 59:671.
(4) H. Gelberg et al. Quantitative left ventricular wall motion analysis: A comparison of area, chord, and radical methods. Circulation,1979,59:991-1000.
(5) C. Slager et al. Quantitative assessment of regional left ventricular motion using endocardial landmarks. JA CC, 1986.
(6) D. Zisserman et al. Cardiac catheterization and angiographic analysis computer applications. Progress in Cardiovascular Diseases,1983.
(7) S. Song and R. Leahy. Computation of 3D velocity fields from 3D cine CT images. IEEE Transactionson Medical Imaging,1991.
(8) C. Kambhamettu and D. Goldgof. Point correspondence recovery in non-rigid motion. IEEEComputer Vision and Pattern Recognition,1992, 222- 227.
(9) A. Pentland and B. Horowitz. Recovery of nonrigid motion and structure. IEEE Transactions onPattern Analysis and Machine Intelligence,1991.
(10) D. Terzopoulos and D. Metaxas. Dynamic 3D models with local and global deformations: deformable superquadrics. IEEE Transactions onPattern Analysis and Machine Intelligence,1991
(11) N. J. Pelc, A. Shimakawaand G. H. Glover. Phase contrast cine MRI. Proceedings of the 8th AnnualSMRM,1989.
(12) J. van Wedeen, G. Holmvang, H. Kantor and T. J. Brady. Measurement of myocardial strain with phase sensitive MR. Proceedings of 2h.e 9th AnnualSMRM,1990.
(13) W. J. Richard S., "OpenGL Super Bible," 1996.
(14) Monga and N. Ayache. From voxel to curvature. IEEE Computer Vision and Pattern Recognition, 1991, 644-649.
(15) P. T. Sander and S. W. Zucker. Inferring surface trace and differential structure from 3D images. IEEE Transactions on Pattern Analysis and MachineIntelligence, 1990, 12(9):833-854.
(16) J. Park, D. Metaxas, A. A. Young, and L. Axel, "Deformable models with parameter functions for cardiac motion analysis from tagged MRI data, “IEEE Transactions on Medical Imaging, 1996.
(17) J. Huang, D. Abendschein, V. G. Davila-Roman, and A. A. Amini, "Spatio-temporal tracking of myocardial deformations with a 4-D B-spline model from tagged MRI," IEEE Transactions on Medical Imaging, 1999.
(18) M. F. Smith, "The effect of contraction and twist on myocardial PET and SPECT image resolution: a mathematical phantom study," IEEE transactions on nuclear science, 2000.
(19) L. H. Staib and J. S. Duncan. Deformable Fourier models for surface finding in 3D images. SPIEVol. 1808: Visualization a Biomedical Computing, 1992.
(20) Fearmonti, R., Bond, J., Erdmann, D., & Levinson, H. A review of scar scales and scar measuring devices. Eplasty, 2010.
Razi, T., Niknami, M., & Ghazani, F. A. Relationship between Hounsfield unit in CT scan and grayscale in CBCT. Journal of dental research, dental clinics, dental prospects, 2014.