Abstract
Assessing the left ventricular ejection fraction (LVEF) accurately requires 3D volumetric data of the LV. Cardiologists either have no access to 3D ultrasound (US) systems or prefer to visually estimate LVEF based on 2D US images. To facilitate the consistent estimation of the end-diastolic and end-systolic blood pool volume and LVEF based on 3D data without extensive complicated manual input, we propose a statistical shape model (SSM) based on 13 key anchor points—the LV apex (1), mitral valve hinges (6), and the midpoints of the endocardial contours (6)—identified from the LV endocardial contour of the tri-plane 2D US images. We use principal component analysis (PCA) to identify the principle modes of variation needed to represent the LV shapes, which enables us to estimate an incoming LV as a linear combination of the principle components (PC). For a new, incoming patient image, its 13 anchor points are projected onto the PC space; its shape is compared to each LV shape in the SSM based on Mahalanobis distance, which is normalized with respect to the LV size, as well as direct vector distance (i.e., PCA distance), without any size normalization. These distances are used to determine the weight each training shape in the SSM contributes to the description of the new patient LV shape. Finally, the new patient’s LV systolic and diastolic volumes are estimated as the weighted average of the training volumes in the SSM. To assess our proposed method, we compared the SSM-based estimates of diastolic, systolic, stroke volumes, and LVEF with those computed directly from 16 tri-plane 2D US imaging datasets using the GE Echo-Pac PC clinical platform. The estimated LVEF based on Mahalanobis distance and PCA distance were within 6.8% and 1.7% of the reference LVEF computed using the GE Echo-Pac PC clinical platform.
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References
Bruse, J.L., Ntsinjana, H., Capelli, C., Biglino, G., McLeod, K., Sermesant, M., Pennec, X., Hsia, T.Y., Schievano, S., Taylor, A.: CMR-based 3D statistical shape modelling reveals left ventricular morphological differences between healthy controls and arterial switch operation survivors. J. Cardiovasc. Magn. Reson. 18 (2016)
Dangi, S., Ben-Zikri, Y.K., Cahill, N., Schwarz, K.Q., Linte, C.A.: Endocardial left ventricle feature tracking and reconstruction from tri-plane trans-esophageal echocardiography data. In: Medical Imaging 2015: Image-Guided Procedures, Robotic Interventions, and Modeling, vol. 9415, p 941505 (2015)
Domingues, J.S., Vale, M.D.P., Martinez, C.B.: New mathematical model for the surface area of the left ventricle by the truncated prolate spheroid. Sci. World J. 2017, 6981515 (2017)
Dumesnil, J., Shoucri, R., Laurenceau, J., Turcot, J.: A mathematical model of the dynamic geometry of the intact left ventricle and its application to clinical data. Circulation 59, 1024–1034 (1979). https://doi.org/10.1161/01.cir.59.5.1024
Farrar, G., Suinesiaputra, A., Gilbert, K., Perry, J.C., Hegde, S., Marsden, A., Young, A.A., Omens, J.H., McCulloch, A.D.: Atlas-based ventricular shape analysis for understanding congenital heart disease. Prog. Pediatr. Cardiol. 43, 61–9 (2016)
Liu, D., Peck, I., Dangi, S., Schwarz, K., Linte, C.: Left ventricular ejection fraction: comparison between true volume-based measurements and area-based estimates. In: 2018 IEEE Western New York Image and Signal Processing Workshop (WNYISPW), pp. 1–5 (2018)
Liu, D., Peck, I., Dangi, S., Schwarz, K., Linte, C.: Left ventricular ejection fraction assessment: unraveling the bias between area- and volume-based estimates. In: Proceedings SPIE Medical Imaging - Ultrasonic Imaging and Tomography, vol. 10955, pp. 109550T–1–8 (2019)
Medrano-Gracia, P., Cowan, B.R., Ambale-Venkatesh, B., Bluemke, D.A., Eng, J., Finn, J.P., Fonseca, C.G., Lima, J.A., Suinesiaputra, A., Young, A.A.: Leftventricular shape variation in asymptomatic populations: the multi-ethnic study of atherosclerosis. J. Cardiovasc. Magn. Reson. 16, 56 (2014). https://doi.org/10.1186/s12968-014-0056-2
Medrano-Gracia, P., Cowan, B.R., Finn, J.P., Fonseca, C.G., Kadish, A.H., Lee, D.C., Tao, W., Young, A.A.: The cardiac atlas project: preliminary description of heart shape in patients with myocardial infarction. In: Camara, O., Pop, M., Rhode, K., Sermesant, M., Smith, N., Young, A. (eds.) Statistical Atlases and Computational Models of the Heart, pp. 46–53 (2010)
Piras, P., Teresi, L., Puddu, P., Concetta, T., Young, A., Suinesiaputra, A., Medrano-Gracia, P.: Morphologically normalized left ventricular motion indicators from MRI feature tracking characterize myocardial infarction. Sci. Rep. 7 (2017)
Remme, E.W., Young, A.A., Augenstein, K.F., Cowan, B., Hunter, P.J.: Extraction and quantification of left ventricular deformation modes. IEEE Trans. Biomed. Eng. 51, 1923–31 (2004)
Suinesiaputra, A., Ablin, P., Albà, X., Alessandrini, M., Allen, J., Bai, W., Cimen, S., Claes, P., Cowan, B., D’hooge, J., Duchateau, N., Ehrhardt, J., Frangi, A., Gooya, A., Grau, V., Lekadir, K., Lu, A., Mukhopadhyay, A., Oksuz, I., Medrano-Gracia, P.: Statistical shape modeling of the left ventricle: myocardial infarct classification challenge. IEEE J. Biomed. Health Inform. 22, 503–15 (2017)
Tejman-Yarden, S., Bratincsak, A., Bachner-Hinenzon, N., Khamis, H., Rzasa, C., Adam, D., Printz, B.F., Perry, J.C.: Left ventricular mechanical property changes during acute av synchronous right ventricular pacing in children. Pediatr. Cardiol. 37, 106–111 (2016)
Zhang, X., Cowan, B.R., Bluemke, D.A., Finn, J.P., Fonseca, C.G., Kadish, A.H., Lee, D.C., Lima, J.A.C., Suinesiaputra, A., Young, A.A., Medrano-Gracia, P.: Atlas-based quantification of cardiac remodeling due to myocardial infarction. PLOS ONE 9(10), 1–13 (2014)
Zhong, L., Su, Y., Yeo, S.Y., Tan, R.S., Ghista, D.N., Kassab, G.: Left ventricular regional wall curvedness and wall stress in patients with ischemic dilated cardiomyopathy. Am. J. Physiol.-Heart Circu. Physiol. 296, H573–84 (2009)
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This work was supported by the National Institutes of Health under Award No. R35GM128877 and by the National Science Foundation under Award No. 1808530.
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Liu, D., Peck, I., Dangi, S., Schwarz, K.Q., Linte, C.A. (2019). A Statistical Shape Model Approach for Computing Left Ventricle Volume and Ejection Fraction Using Multi-plane Ultrasound Images. In: Tavares, J., Natal Jorge, R. (eds) VipIMAGE 2019. VipIMAGE 2019. Lecture Notes in Computational Vision and Biomechanics, vol 34. Springer, Cham. https://doi.org/10.1007/978-3-030-32040-9_55
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DOI: https://doi.org/10.1007/978-3-030-32040-9_55
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