Abstract
Imaging of the heart during exercise can improve detection and treatment of heart diseases but is challenging using current clinically applied cardiac MRI (cMRI) techniques. Real-time (RT) imaging strategies have recently been proposed for exercise cMRI, but respiratory motion and unreliable cardiac gating introduce significant errors in quantification of cardiac function. Self-navigated cMRI sequences are currently not routinely available in a clinical environment. We aim to establish a method for cardiac and respiratory gated cine exercise cMRI that can be applied in a clinical cMRI setting. We developed a retrospective, image-based cardiac and respiratory gating and reconstruction framework based on widely available highly accelerated dynamic imaging. From the acquired dynamic images, respiratory motion was estimated using manifold learning. Cardiac periodicity was obtained by identifying local maxima in the temporal frequency spectrum of the spatial means of the images. We then binned the dynamic images in respiratory and cardiac phases and subsequently registered and averaged them to reconstruct a respiratory and cardiac gated cine stack. We evaluated our method in healthy volunteers and patients with heart diseases and demonstrate good agreement with existing RT acquisitions (R = .82). We show that our reconstruction pipeline yields better image quality and has lower inter- and intra-observer variability compared to RT imaging. Subsequently, we demonstrate that our method is able to detect a pathological response to exercise in patients with heart diseases, illustrating its potential benefit in cardiac diagnostic and prognostic assessment.
Keywords
- Exercise MRI
- Cardiac imaging
- Image-based motion correction
- Manifold learning
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van Amerom, J., Lloyd, D., Price, A., Kuklisova Murgasova, M., Aljabar, P., Malik, S., Lohezic, M., Rutherford, M., Pushparajah, K., Razavi, R., et al.: Fetal cardiac cine imaging using highly accelerated dynamic MRI with retrospective motion correction and outlier rejection. Magn. Reson. Med. (2017)
Cahalin, L., Chase, P., Arena, R., Myers, J., Bensimhon, D., Peberdy, M., Ashley, E., West, E., Forman, D., Pinkstaff, S., et al.: A meta-analysis of the prognostic significance of cardiopulmonary exercise testing in patients with heart failure. Heart Fail. Rev. 18(1), 79–94 (2013)
Claessen, G., Claus, P., Delcroix, M., Bogaert, J., La Gerche, A., Heidbuchel, H.: Interaction between respiration and right versus left ventricular volumes at rest and during exercise: a real-time cardiac magnetic resonance study. Am. J. Physiol. Heart Circ. Physiol. 306(6), H816–H824 (2014)
Crowe, M., Larson, A., Zhang, Q., Carr, J., White, R., Li, D., Simonetti, O.: Automated rectilinear self-gated cardiac cine imaging. Magn. Reson. Med. 52(4), 782–788 (2004)
Feng, L., Axel, L., Chandarana, H., Block, K.T., Sodickson, D.K., Otazo, R.: XD-GRASP: golden-angle radial MRI with reconstruction of extra motion-state dimensions using compressed sensing. Magn. Reson. Med. 75(2), 775–788 (2016)
Fratz, S., Chung, T., Greil, G., Samyn, M., Taylor, A., Buechel, E., Yoo, S.J., Powell, A.: Guidelines and protocols for cardiovascular magnetic resonance in children and adults with congenital heart disease: SCMR expert consensus group on congenital heart disease. J. Cardiovasc. Magn. Reson. 15(1), 51 (2013)
Han, F., Zhou, Z., Han, E., Gao, Y., Nguyen, K.L., Finn, J., Hu, P.: Self-gated 4D multiphase, steady-state imaging with contrast enhancement (MUSIC) using rotating cartesian K-space (ROCK): validation in children with congenital heart disease. Magn. Reson. Med. (2016)
Hansen, M., Sørensen, T., Arai, A., Kellman, P.: Retrospective reconstruction of high temporal resolution cine images from real-time MRI using iterative motion correction. Magn. Reson. Med. 68(3), 741–750 (2012)
Kim, W., Mun, C., Kim, D., Cho, Z.: Extraction of cardiac and respiratory motion cycles by use of projection data and its applications to nmr imaging. Magn. Reson. Med. 13(1), 25–37 (1990)
La Gerche, A., Claessen, G., Van de Bruaene, A., Pattyn, N., Van Cleemput, J., Gewillig, M., Bogaert, J., Dymarkowski, S., Claus, P., Heidbuchel, H.: Cardiac MRI: a new gold standard for ventricular volume quantification during high-intensity exercise. Circ. Cardiovasc. Imaging 6(2), 329–338 (2013)
Larson, A., White, R., Laub, G., McVeigh, E., Li, D., Simonetti, O.: Self-gated cardiac cine MRI. Magn. Reson. Med. 51(1), 93–102 (2004)
Liu, C., Bammer, R., Kim, D.H., Moseley, M.: Self-navigated interleaved spiral (SNAILS): application to high-resolution diffusion tensor imaging. Magn. Reson. Med. 52(6), 1388–1396 (2004)
Lurz, P., Muthurangu, V., Schievano, S., Nordmeyer, J., Bonhoeffer, P., Taylor, A., Hansen, M.: Feasibility and reproducibility of biventricular volumetric assessment of cardiac function during exercise using real-time radial k-t SENSE magnetic resonance imaging. J. Magn. Reson. Imaging 29(5), 1062–1070 (2009)
Paul, J., Divkovic, E., Wundrak, S., Bernhardt, P., Rottbauer, W., Neumann, H., Rasche, V.: High-resolution respiratory self-gated golden angle cardiac MRI: comparison of self-gating methods in combination with k-t SPARSE SENSE. Magn. Reson. Med. 73(1), 292–298 (2015)
Peters, D.C., Nezafat, R., Eggers, H., Stehning, C., Manning, W.J.: 2D free-breathing dual navigator-gated cardiac function validated against the 2D breath-hold acquisition. J. Magn. Reson. Imaging 28(3), 773–777 (2008)
Thirion, J.P.: Image matching as a diffusion process: an analogy with Maxwell’s demons. Med. Image Anal. 2(3), 243–260 (1998)
Usman, M., Atkinson, D., Kolbitsch, C., Schaeffter, T., Prieto, C.: Manifold learning based ECG-free free-breathing cardiac CINE MRI. J. Magn. Reson. Imaging 41(6), 1521–1527 (2015)
Yoon, H., Kim, K., Kim, D., Bresler, Y., Ye, J.: Motion adaptive patch-based low-rank approach for compressed sensing cardiac cine MRI. IEEE Trans. Med. Imaging 33(11), 2069–2085 (2014)
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Ruijsink, B. et al. (2017). Semi-automatic Cardiac and Respiratory Gated MRI for Cardiac Assessment During Exercise. In: , et al. Molecular Imaging, Reconstruction and Analysis of Moving Body Organs, and Stroke Imaging and Treatment. RAMBO CMMI SWITCH 2017 2017 2017. Lecture Notes in Computer Science(), vol 10555. Springer, Cham. https://doi.org/10.1007/978-3-319-67564-0_9
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DOI: https://doi.org/10.1007/978-3-319-67564-0_9
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