nach oben

Erschienen in:

17.08.2020 | Sp Iss: Experimental Advances in Cardiovascular Biomechanics

In Vivo Image-Based 4D Modeling of Competent and Regurgitant Mitral Valve Dynamics

verfasst von: A. H. Aly, A. H. Aly, E. K. Lai, N. Yushkevich, R. H. Stoffers, J. H. Gorman IV, A. T. Cheung, J. H. Gorman III, R. C. Gorman, P. A. Yushkevich, A. M. Pouch

Erschienen in: Experimental Mechanics | Ausgabe 1/2021

Einloggen

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config

KI-gestützte Suche

Aus

Abstract

Background

In vivo characterization of mitral valve dynamics relies on image analysis algorithms that accurately reconstruct valve morphology and motion from clinical images. The goal of such algorithms is to provide patient-specific descriptions of both competent and regurgitant mitral valves, which can be used as input to biomechanical analyses and provide insights into the pathophysiology of diseases like ischemic mitral regurgitation (IMR).

Objective

The goal is to generate accurate image-based representations of valve dynamics that visually and quantitatively capture normal and pathological valve function.

Methods

We present a novel framework for 4D segmentation and geometric modeling of the mitral valve in real-time 3D echocardiography (rt-3DE), an imaging modality used for pre-operative surgical planning of mitral interventions. The framework integrates groupwise multi-atlas label fusion and template-based medial modeling with Kalman filtering to generate quantitatively descriptive and temporally consistent models of valve dynamics.

Results

The algorithm is evaluated on rt-3DE data series from 28 patients: 14 with normal mitral valve morphology and 14 with severe IMR. In these 28 data series that total 613 individual 3DE images, each 3D mitral valve segmentation is validated against manual tracing, and temporal consistency between segmentations is demonstrated.

Conclusions

Automated 4D image analysis allows for reliable non-invasive modeling of the mitral valve over the cardiac cycle for comparison of annular and leaflet dynamics in pathological and normal mitral valves. Future studies can apply this algorithm to cardiovascular mechanics applications, including patient-specific strain estimation, fluid dynamics simulation, inverse finite element analysis, and risk stratification for surgical treatment.

Vorheriger Artikel A Novel Method for In Vitro 3D Imaging of Dissecting Pressurized Arterial Segments Using X-Ray Microtomography

Nächster Artikel Estimating Arterial Cyclic Strain from the Spacing of Endothelial Nuclei

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

über 102.000 Bücher
über 537 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Finance + Banking
Management + Führung
Marketing + Vertrieb
Maschinenbau + Werkstoffe
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 390 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Maschinenbau + Werkstoffe

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Nur mit Berechtigung zugänglich

Krishnamurthy G, Itoh A, Bothe W, Swanson JC, Kuhl E, Karlsson M, Craig Miller D, Ingels NB Jr (2009) Stress-strain behavior of mitral valve leaflets in the beating ovine heart. J Biomech 42(12):1909–1916. https://doi.org/10.1016/j.jbiomech.2009.05.018CrossRef

Gorman JH 3rd, Gupta KB, Streicher JT, Gorman RC, Jackson BM, Ratcliffe MB, Bogen DK, Edmunds LH Jr (1996) Dynamic three-dimensional imaging of the mitral valve and left ventricle by rapid sonomicrometry array localization. J Thorac Cardiovasc Surg 112(3):712–726CrossRef

Bothe W, Schubert H, Diab M, Faerber G, Bettag C, Jiang X, Fischer MS, Denzler J, Doenst T (2016) Fully automated tracking of cardiac structures using radiopaque markers and high-frequency videofluoroscopy in an in vivo ovine model: from three-dimensional marker coordinates to quantitative analyses. Springerplus 5:220. https://doi.org/10.1186/s40064-016-1868-3CrossRef

Zekry SB, Lawrie G, Little S, Zoghbi W, Freeman J, Jajoo A, Jain S, He J, Martynenko A, Azencott R (2012) Comparitive evaluation of mitral valve strain by deformation tracking in 3D-echocardiography. Cardiovasc Eng Technol 3(4):402–412CrossRef

Rego BV, Khalighi AH, Drach A, Lai EK, Pouch AM, Gorman RC, Gorman JH 3rd, Sacks MS (2018) A noninvasive method for the determination of in vivo mitral valve leaflet strains. Int J Numer Method Biomed Eng 34(12):e3142. https://doi.org/10.1002/cnm.3142CrossRef

Wang Q, Sun W (2013) Finite element modeling of mitral valve dynamic deformation using patient-specific multi-slices computed tomography scans. Ann Biomed Eng 41(1):142–153CrossRef

Choi A, Rim Y, Mun JS, Kim H (2014) A novel finite element-based patient-specific mitral valve repair: virtual ring annuloplasty. Biomed Mater Eng 24(1):341–347. https://doi.org/10.3233/BME-130816CrossRef

Hammer PE, Perrin DP, del Nido PJ, Howe RD (2008). Image-based mass-spring model of mitral valve closure for surgical planning. PRoceedings of SPIE medical imaging: visualization, image-guided procedures, and modeling 6918

Wenk JF, Zhang Z, Cheng G, Malhotra D, Acevedo-Bolton G, Burger M, Suzuki T, Saloner DA, Wallace AW, Guccione JM, Ratcliffe MB (2010) First finite element model of the left ventricle with mitral valve: insights into ischemic mitral regurgitation. Ann Thorac Surg 89(5):1546–1553. https://doi.org/10.1016/j.athoracsur.2010.02.036CrossRef

10.

Ge L, Morrel WG, Ward A, Mishra R, Zhang Z, Guccione JM, Grossi EA, Ratcliffe MB (2014) Measurement of mitral leaflet and annular geometry and stress after repair of posterior leaflet prolapse: virtual repair using a patient-specific finite element simulation. Ann Thorac Surg 97(5):1496–1503. https://doi.org/10.1016/j.athoracsur.2013.12.036CrossRef

11.

Mansi T, Voigt I, Georgescu B, Zheng X, Mengue EA, Hackl M, Ionasec RI, Noack T, Seeburger J, Comaniciu D (2012) An integrated framework for finite-element modeling of mitral valve biomechanics from medical images: application to MitralClip intervention planning. Med Image Anal 16:1330–1346. https://doi.org/10.1016/j.media.2012.05.009CrossRef

12.

Schneider RJ, Tenenholtz NA, Perrin DP, Marx GR, del Nido PJ, Howe RD (2011) Patient-specific mitral leaflet segmentation from 4D ultrasound. Med Image Comput Comput Assist Interv 14(Pt 3):520–527

13.

Ionasec RI, Voigt I, Georgescu B, Wang Y, Houle H, Vega-Higuera F, Navab N, Comaniciu D (2010) Patient-specific modeling and quantification of the aortic and mitral valves from 4-D cardiac CT and TEE. IEEE Trans Med Imaging 29(9):1636–1651. https://doi.org/10.1109/TMI.2010.2048756CrossRef

14.

Rausch MK, Famaey N, Shultz TO, Bothe W, Miller DC, Kuhl E (2012) Mechanics of the mitral valve : a critical review, an in vivo parameter identification, and the effect of prestrain. Biomech Model Mechanobiol 12:1053–1071. https://doi.org/10.1007/s10237-012-0462-zCrossRef

15.

Acker MA, Parides MK, Perrault LP, Moskowitz AJ, Gelijns AC, Voisine P, Smith PK, Hung JW, Blackstone EH, Puskas JD, Argenziano M, Gammie JS, Mack M, Ascheim DD, Bagiella E, Moquete EG, Ferguson TB, Horvath KA, Geller NL, Miller MA, Woo YJ, D'Alessandro DA, Ailawadi G, Dagenais F, Gardner TJ, O'Gara PT, Michler RE, Kron IL, Ctsn (2014) Mitral-valve repair versus replacement for severe ischemic mitral regurgitation. N Engl J Med 370(1):23–32. https://doi.org/10.1056/NEJMoa1312808CrossRef

16.

Bouma W, Lai EK, Levack MM, Shang EK, Pouch AM, Eperjesi TJ, Plappert TJ, Yushkevich PA, Mariani MA, Khabbaz KR, Gleason TG, Mahmood F, Acker MA, Woo YJ, Cheung AT, Jackson BM, Gorman JH 3rd, Gorman RC (2016) Preoperative three-dimensional valve analysis predicts recurrent ischemic mitral regurgitation after mitral Annuloplasty. Ann Thorac Surg 101(2):567–575; discussion 575. https://doi.org/10.1016/j.athoracsur.2015.09.076CrossRef

17.

Pouch AM, Aly AH, Lai EK, Yushkevich N, Stoffers RH, Gorman JH, Cheung AT, Gorman JH 3rd, Gorman RC, Yushkevich PA (2017) Spatiotemporal segmentation and modeling of the mitral valve in real-time 3D echocardiographic images. Med Image Comput Comput Assist Interv 10433:746–754. https://doi.org/10.1007/978-3-319-66182-7_85CrossRef

18.

Yushkevich PA, Piven J, Hazlett HC, Smith RG, Ho S, Gee JC, Gerig G (2006) User-guided 3D active contour segmentation of anatomical structures: significantly improved efficiency and reliability. Neuroimage 31(3):1116–1128. https://doi.org/10.1016/j.neuroimage.2006.01.015CrossRef

19.

Pouch AM, Yushkevich PA, Jackson BM, Jassar AS, Vergnat M, Gorman JH, Gorman RC, Sehgal CM (2012) Development of a semi-automated method for mitral valve modeling with medial axis representation using 3D ultrasound. Med Phys 39(2):933–950CrossRef

20.

Carnahan P, Ginty O, Moore J, Lasso A, Jolley MA, Herz C, Eskandari M, Bainbridge D, Peters TM (2019). Interactive-automatic segmentation and modelling of the mitral valve. In: International Conference on Functional Imaging and Modeling of the Heart. Springer, pp 397–404

21.

van Zon M, Veta M, Li S (2019). Automatic cardiac landmark localization by a recurrent neural network. In: Medical Imaging 2019: Image Processing. International Society for Optics and Photonics, p 1094916

22.

Avants BB, Epstein CL, Grossman M, Gee JC (2008) Symmetric diffeomorphic image registration with cross-correlation: evaluating automated labeling of elderly and neurodegenerative brain. Med Image Anal 12(1):26–41. https://doi.org/10.1016/j.media.2007.06.004CrossRef

23.

Wang H, Suh JW, Das SR, Pluta JB, Craige C, Yushkevich PA (2012) Multi-atlas segmentation with joint label fusion. IEEE Trans Pattern Anal Mach Intell 35(3):611–623CrossRef

24.

Wang H, Yushkevich PA (2013). Multi-atlas segmentation without registration: a supervoxel-based approach. Paper presented at the Medical Image Computing and Computer Assisted Intervention,

25.

Wang H, Yushkevich PA (2013). Groupwise segmentaiton with multi-atlas joint label fusion. Paper presented at the Medical Image Computing and Computer Assisted Intervention

26.

Yushkevich PA, Zhang H, Gee JC (2006) Continuous medial representation for anatomical structures. IEEE Trans Med Imaging 25(12):1547–1564CrossRef

27.

Pouch AM, Tian S, Takebe M, Yuan J, Gorman R Jr, Cheung AT, Wang H, Jackson BM, Gorman JH 3rd, Gorman RC, Yushkevich PA (2015) Medially constrained deformable modeling for segmentation of branching medial structures: application to aortic valve segmentation and morphometry. Med Image Anal 26(1):217–231. https://doi.org/10.1016/j.media.2015.09.003CrossRef

28.

Pouch AM, Wang H, Takabe M, Jackson BM, Gorman JH 3rd, Gorman RC, Yushkevich PA, Sehgal CM (2014) Fully automatic segmentation of the mitral leaflets in 3D transesophageal echocardiographic images using multi-atlas joint label fusion and deformable medial modeling. Med Image Anal 18(1):118–129. https://doi.org/10.1016/j.media.2013.10.001CrossRef

29.

Kalman RE (1960) A new approach to linear filtering and prediction problems. J basic Eng 82(series D):35–45MathSciNetCrossRef

30.

Siefert AW, Icenogle DA, Rabbah JP, Saikrishnan N, Rossignac J, Lerakis S, Yoganathan AP (2013) Accuracy of a mitral valve segmentation method using J-splines for real-time 3D echocardiography data. Ann Biomed Eng 41(6):1258–1268. https://doi.org/10.1007/s10439-013-0784-8CrossRef

31.

Gorman JH III, Gupta KB, Streicher JT, Gorman RC, Jackson BM, Ratcliffe MB, Bogen DK, Edmunds LH Jr (1996) Dynamic three-dimensional imaging of the mitral valve and left ventricle by rapid sonomicrometry array localization. J Thorac Cardiovasc Surg 112(3):712–724CrossRef

32.

Krishnamurthy G, Itoh A, Swanson JC, Bothe W, Karlsson M, Kuhl E, Miller DC, Ingels NB Jr (2009) Regional stiffening of the mitral valve anterior leaflet in the beating ovine heart. J Biomech 42(16):2697–2701CrossRef

33.

Bavo A, Pouch AM, Degroote J, Vierendeels J, Gorman JH, Gorman RC, Segers P (2017) Patient-specific CFD models for intraventricular flow analysis from 3D ultrasound imaging: comparison of three clinical cases. J Biomech 50:144–150CrossRef

34.

Falahatpisheh A, Pahlevan NM, Kheradvar A (2015) Effect of the mitral valve’s anterior leaflet on axisymmetry of transmitral vortex ring. Ann Biomed Eng 43(10):2349–2360CrossRef

35.

Caballero A, Mao W, McKay R, Hahn RT, Sun W (2020). A comprehensive engineering analysis of left heart dynamics after MitraClip in a functional mitral regurgitation patient. Front Physiol 11

36.

Jeyhani M, Shahriari S, Labrosse M (2018) Experimental investigation of left ventricular flow patterns after percutaneous edge-to-edge mitral valve repair. Artif Organs 42(5):516–524CrossRef

37.

Du D, Jiang S, Wang Z, Hu Y, He Z (2014) Effects of suture position on left ventricular fluid mechanics under mitral valve edge-to-edge repair. Biomed Mater Eng 24(1):155–161

Titel: In Vivo Image-Based 4D Modeling of Competent and Regurgitant Mitral Valve Dynamics
verfasst von: A. H. Aly
A. H. Aly
E. K. Lai
N. Yushkevich
R. H. Stoffers
J. H. Gorman IV
A. T. Cheung
J. H. Gorman III
R. C. Gorman
P. A. Yushkevich
A. M. Pouch
Publikationsdatum: 17.08.2020
Verlag: Springer US
Erschienen in: Experimental Mechanics / Ausgabe 1/2021
Print ISSN: 0014-4851
Elektronische ISSN: 1741-2765
DOI: https://doi.org/10.1007/s11340-020-00656-8

Premium Partner

Marktübersichten

Die im Laufe eines Jahres in der „adhäsion“ veröffentlichten Marktübersichten helfen Anwendern verschiedenster Branchen, sich einen gezielten Überblick über Lieferantenangebote zu verschaffen.

Zur Marktübersicht

Springer Professional

Abstract

Background

Objective

Methods

Results

Conclusions

Bitte loggen Sie sich ein, um Zugang zu Ihrer Lizenz zu erhalten.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Springer Professional "Technik"

Weitere Artikel der Ausgabe 1/2021

Radiofrequency Ablation Alters the Microstructural Organization of Healthy and Enzymatically Digested Porcine Mitral Valves

Effect of Macro-calcification on the Failure Mechanics of Intracranial Aneurysmal Wall Tissue

Pentagalloyl Glucose (PGG) Partially Prevents Arterial Mechanical Changes Due to Elastin Degradation

Nanoindentation of Calcified and Non-calcified Components of Atherosclerotic Tissues

Myocardial Laminar Organization Is Retained in Angiotensin-Converting Enzyme Inhibitor Treated SHRs

Special Issue on Advances in Cardiovascular Biomechanics

Premium Partner

Marktübersichten