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A Comparison of Hyperelastic Warping of PET Images with Tagged MRI for the Analysis of Cardiac Deformation

DOI: 10.1155/2013/728624

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Abstract:

The objectives of the following research were to evaluate the utility of a deformable image registration technique known as hyperelastic warping for the measurement of local strains in the left ventricle through the analysis of clinical, gated PET image datasets. Two normal human male subjects were sequentially imaged with PET and tagged MRI imaging. Strain predictions were made for systolic contraction using warping analyses of the PET images and HARP based strain analyses of the MRI images. Coefficient of determination values were computed for the comparison of circumferential and radial strain predictions produced by each methodology. There was good correspondence between the methodologies, with values of 0.78 for the radial strains of both hearts and from an and for the circumferential strains. The strain predictions were not statistically different . A series of sensitivity results indicated that the methodology was relatively insensitive to alterations in image intensity, random image noise, and alterations in fiber structure. This study demonstrated that warping was able to provide strain predictions of systolic contraction of the LV consistent with those provided by tagged MRI Warping. 1. Introduction Diagnostic imaging technologies play a vital role in reducing the morbidity and mortality associated with heart failure, cardiac ischemia, and infarction. The assessment of regional left ventricular (LV) function is currently used as a major diagnostic and prognostic indicator in patients with cardiovascular disease [1–4]. Single photon emission computed tomography (SPECT) and positron emission tomography (PET) are commonly used for evaluation of cardiovascular disease and can allow for not only evaluation of perfusion, but with gated acquisitions these nuclear images can also be used to evaluate global cardiac function measures like ejection fraction (EF) and regional function measures such as wall motion and myocardial wall thickening. Local wall motion and thickening remain the most common methods used for evaluation of LV regional wall function in the clinical setting. They are, however, indirect measures of cardiac function. Deformation in the form of wall strain represents a direct measurement of tissue elongation and contraction. These measures provide more information on the functional health of cardiac tissue than regional wall motion [5–8], allowing for earlier and more exact diagnoses to be made. There has been growing interest in the use of deformable image registration methods for automated segmentation [9, 10] and deformation

References

[1]  K. G. Morris, S. T. Palmeri, and R. M. Califf, “Value of radionuclide angiography for predicting specific cardiac events after acute myocardial infarction,” American Journal of Cardiology, vol. 55, no. 4, pp. 318–324, 1985.
[2]  L. J. Shaw, S. K. Heinle, S. Borges-Neto, K. Kesler, R. E. Coleman, and R. H. Jones, “Prognosis by measurements of left ventricular function during exercise,” Journal of Nuclear Medicine, vol. 39, no. 1, pp. 140–146, 1998.
[3]  H. D. White, R. M. Norris, and M. A. Brown, “Left ventricular end-systolic volume as the major determinant of survival after recovery from myocardial infarction,” Circulation, vol. 76, no. 1, pp. 44–51, 1987.
[4]  S. H. Johnson, C. Bigelow, K. L. Lee, D. B. Pryor, and R. H. Jones, “Prediction of death and myocardial infarction by radionuclide angiocardiography in patients with suspected coronary artery disease,” American Journal of Cardiology, vol. 67, no. 11, pp. 919–926, 1991.
[5]  H. Fujimoto, H. Honma, T. Ohno, K. Mizuno, and S. Kumita, “Longitudinal doppler strain measurement for assessment of damaged and/or hibernating myocardium by dobutamine stress echocardiography in patients with old myocardial infarction,” Journal of Cardiology, vol. 55, no. 3, pp. 309–316, 2010.
[6]  C. Schneider, K. Jaquet, S. Geidel et al., “Regional diastolic and systolic function by strain rate imaging for the detection of intramural viability during dobutamine stress echocardiography in a porcine model of myocardial infarction,” Echocardiography, vol. 27, no. 5, pp. 552–562, 2010.
[7]  F. Weidemann, C. Dommke, B. Bijnens et al., “Defining the transmurality of a chronic myocardial infarction by ultrasonic strain-rate imaging: Implications for identifying intramural viability—an experimental study,” Circulation, vol. 107, no. 6, pp. 883–888, 2003.
[8]  J. Garot, J. A. C. Lima, B. L. Gerber et al., “Spatially resolved imaging of myocardial function with strain-encoded MR: comparison with delayed contrast-enhanced MR imaging after myocardial infarction,” Radiology, vol. 233, no. 2, pp. 596–602, 2004.
[9]  J. Montagnat, M. Sermesant, H. Delingette, G. Malandain, and N. Ayache, “Anisotropic filtering for model-based segmentation of 4D cylindrical echocardiographic images,” Pattern Recognition Letters, vol. 24, no. 4-5, pp. 815–825, 2003.
[10]  M. Sermesant, Y. Coudiere, H. Delingette, and N. Ayache, “Progress towards an electro-mechanical model of the heart for cardiac image analysis,” in Proceedings of the IEEE International Symposium on Biomedical Imaging (ISBI '02), 2002.
[11]  M. Sermesant, C. Forest, X. Pennec, H. Delingette, and N. Ayache, “Deformable biomechanical models: application to 4D cardiac image analysis,” Medical Image Analysis, vol. 7, no. 4, pp. 475–488, 2003.
[12]  A. Sitek, G. J. Klein, G. T. Gullberg, and R. H. Huesman, “Deformable model of the heart with fiber structure,” IEEE Transactions on Nuclear Science, vol. 49, no. 3, pp. 789–793, 2002.
[13]  S. M. Choi, Y. K. Lee, and M. H. Kim, “Quantitative analysis of gated SPECT images using an efficient physical deformation model,” Computers in Biology and Medicine, vol. 34, no. 1, pp. 15–33, 2004.
[14]  N. S. Phatak, S. A. Maas, A. I. Veress, N. A. Pack, E. V. R. Di Bella, and J. A. Weiss, “Strain measurement in the left ventricle during systole with deformable image registration,” Medical Image Analysis, vol. 13, no. 2, pp. 354–361, 2009.
[15]  N. S. Phatak, Q. Sun, S. E. Kim et al., “Noninvasive determination of ligament strain with deformable image registration,” Annals of Biomedical Engineering, vol. 35, no. 7, pp. 1175–1187, 2007.
[16]  A. I. Veress, J. A. Weiss, G. T. Gullberg, D. G. Vince, and R. D. Rabbitt, “Strain measurement in coronary arteries using intravascular ultrasound and deformable images,” Journal of Biomechanical Engineering, vol. 124, no. 6, pp. 734–741, 2002.
[17]  A. I. Veress, J. A. Weiss, R. H. Huesman et al., “Measuring regional changes in the diastolic deformation of the left ventricle of SHR rats using microPET technology and hyperelastic warping,” Annals of Biomedical Engineering, vol. 36, no. 7, pp. 1104–1117, 2008.
[18]  G. E. Christensen, R. D. Rabbitti, and M. I. Miller, “3D brain mapping using a deformable neuroanatomy,” Physics in Medicine and Biology, vol. 39, no. 3, pp. 609–618, 1994.
[19]  G. E. Christensen, R. D. Rabbitt, and M. I. Miller, “Deformable templates using large deformation kinematics,” IEEE Transactions on Image Processing, vol. 5, no. 10, pp. 1435–1447, 1996.
[20]  J. E. Marsden and T. J. R. Hughes, Mathematical Foundations of Elasticity, Minneola, NY, USA, 1994.
[21]  A. I. Veress, N. Phatak, and J. A. Weiss, “Deformable image registration with hyperelastic warping,” in The Handbook of Medical Image Analysis: Segmentation and Registration Models, vol. 3, Marcel Dekker, New York, NY, USA, 2005.
[22]  A. E. Bowden, R. D. Rabbitt, and J. A. Weiss, “Anatomical registration and segmentation by Warping template finite element models,” in Laser-Tissue Interaction IX, vol. 3254 of Proceedings of SPIE, pp. 469–476, January 1998.
[23]  J. A. Weiss, R. D. Rabbitt, A. E. Bowden, and B. N. Maker, “Incorporation of medical image data in finite element models to track strain in soft tissues,” in Laser-Tissue Interaction IX, vol. 3254 of Proceedings of SPIE, pp. 477–484, January 1998.
[24]  A. I. Veress, G. T. Gullberg, and J. A. Weiss, “Measurement of strain in the left ventricle during diastole with cine-mri and deformable image registration,” Journal of Biomechanical Engineering, vol. 127, pp. 1195–1207, 2005.
[25]  J. A. Weiss, B. N. Maker, and S. Govindjee, “Finite element implementation of incompressible, transversely isotropic hyperelasticity,” Computer Methods in Applied Mechanics and Engineering, vol. 135, no. 1-2, pp. 107–128, 1996.
[26]  A. I. Veress, W. P. Segars, B. M. W. Tsui, and G. T. Gullberg, “Incorporation of a left ventricle finite element model defining infarction into the XCAT imaging phantom,” IEEE Transactions on Medical Imaging, vol. 30, no. 4, pp. 915–927, 2011.
[27]  J. D. Humphrey, Cardiovascular Solid Mechanics Cells, Tissues and Organs, Springer, New York, NY, USA, 2002.
[28]  J. M. Guccione and A. D. McCulloch, “Mechanics of active contraction in cardiac muscle: part I-constitutive relations for fiber stress that describe deactivation,” Journal of Biomechanical Engineering, vol. 115, no. 1, pp. 72–81, 1993.
[29]  J. M. Guccione and A. D. McCulloch, “Mechanics of active contraction in cardiac muscle: part II-constitutive relations for fiber stress that describe deactivation,” Journal of Biomechanical Engineering, vol. 115, pp. 82–90, 1993.
[30]  G. J. Klein and R. H. Huesman, “Four-dimensional processing of deformable cardiac PET data,” Medical Image Analysis, vol. 6, no. 1, pp. 29–46, 2002.
[31]  A. I. Veress, J. A. Weiss, R. D. Rabbitt, J. N. Lee, and G. T. Gullberg, “Measurement of 3D left ventricular strains during diastole using image warping and untagged MRI images,” in Proceedings of the IEEE Computer in Cardiology, pp. 165–168, September 2001.
[32]  A. I. Veress, W. P. Segars, J. A. Weiss, B. M. W. Tsui, and G. T. Gullberg, “Normal and pathological NCAT image and phantom data based on physiologically realistic left ventricle finite-element models,” IEEE Transactions on Medical Imaging, vol. 25, no. 12, pp. 1604–1616, 2006.
[33]  G. Buckberg, J. I. E. Hoffman, A. Mahajan, S. Saleh, and C. Coghlan, “Cardiac mechanics revisited: the relationship of cardiac architecture to ventricular function,” Circulation, vol. 118, no. 24, pp. 2571–2587, 2008.
[34]  A. I. Veress, J. A. Weiss, G. J. Klein, and G. T. Gullberg, “Quantification of 3D left ventricular deformation using hyperelastic warping: comparisons between MRI and PET imaging,” in Computers in Cardiology 2002, pp. 709–712, September 2002.
[35]  R. C. Gonzalez and R. E. Woods, Digital Image Processing, Addison-Wesley, 1992.
[36]  N. S. Phatak, S. A. Maas, A. I. Veress, N. A. Pack, E. V. R. Di Bella, and J. A. Weiss, “Strain measurement in the left ventricle during systole with deformable image registration,” Medical Image Analysis, vol. 13, no. 2, pp. 354–361, 2009.
[37]  A. I. Veress, G. Fung, B. M. Tsui, W. P. Segars, and G. T. Gullberg, “Incorporation of perfusion information into a finite element model of the left ventricle,” in Proceedings of the ASME Summer Bioengineering Conference, Farmington, Pa, USA, June 2011.
[38]  C. C. Watson, M. E. Casey, B. Bendriem et al., “Optimizing injected dose in clinical PET by accurately modeling the counting-rate response functions specific to individual patient scans,” Journal of Nuclear Medicine, vol. 46, no. 11, pp. 1825–1834, 2005.

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