Quantitative Mitral Valve Modeling Using Real-Time Three-Dimensional Echocardiography: Technique and Repeatability

Jassar, Arminder S.; Brinster, Clayton J.; Vergnat, Mathieu; Robb, J. Daniel; Eperjesi, Thomas J.; Pouch, Alison M.; Cheung, Albert T.; Weiss, Stuart J.; Acker, Michael A.; Gorman, Joseph H.; Gorman, Robert C.; Jackson, Benjamin M.

doi:10.1016/j.athoracsur.2010.10.034

Cited by 57 publications

(48 citation statements)

References 25 publications

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“…Moreover, the results of this study demonstrate that user-initialized 3D US image analysis provides a quantitative valve assessment that is consistent with manual delineation. The errors and biases in our measurements are within the range of interobserver variability in manual image analysis presented by Jassar et al 9 and are within the range of error in annular measurements presented by Ionasec et al, 18 who use an automated image analysis technique. While the average percent difference in total tenting volume between manual and semi-automated image analysis is high (26.2%), the average percent difference in the contribution of the anterior leaflet to the total tenting volume is lower (12.2%).…”

Section: Discussion Iva Contributionsmentioning

confidence: 49%

“…Specifically, the anterior annular points are defined as points on the anterior leaflet cm-rep boundary mapped to medial manifold edges that are not contained within the convex hull of the posterior leaflet. The anterior and posterior commissures are identified as points on the annular curve where the anterior and posterior leaflets meet, a definition that is consistent with the protocol described by Jassar et al 9 and Vergnat et al 8 An alternative definition of the commissures is described by Carpentier et al, 46 wherein several millimeters of valve tissue separates the free edge of the commissures from the annulus. Sometimes the commissures exist as separate leaflet segments, but more often the area is a subtle structure.…”

Section: Iid Feature Extractionmentioning

confidence: 97%

“…Sometimes the commissures exist as separate leaflet segments, but more often the area is a subtle structure. Given that commissures and=or commissural leaflets are difficult to define when the valve is closed, the commissural definition of Jassar et al 9 and Vergnat et al 8 is used in this work.…”

Section: Iid Feature Extractionmentioning

confidence: 99%

“…The biharmonic PDE is a bijective mapping that transforms points from a vector space, parameterized by {m,q,s}, into the set of all radial fields R defined over m that satisfy Eq. (9). In this framework, the curve forming the boundary of the medial manifold, @m, is parameterized by the arclength s: cðsÞ : ½0; LÞ !…”

Section: Iib2 Deformable Medial Modelingmentioning

confidence: 99%

“…Here, it is assumed that interobserver variability in the measurement of annular diameter is within 10%, which has been previously confirmed. 9 For each displacement value, the average percent difference in the ROA measurement was computed. Percent difference was defined as the difference between the manual and automated measurement, divided by the average of the two measurements, multiplied by 100.…”

Section: Iig Roa Sensitivity Analysismentioning

confidence: 99%

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Development of a semi-automated method for mitral valve modeling with medial axis representation using 3D ultrasound

Pouch¹,

Yushkevich²,

Jackson³

et al. 2012

Med. Phys.

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Purpose: Precise 3D modeling of the mitral valve has the potential to improve our understanding of valve morphology, particularly in the setting of mitral regurgitation (MR). Toward this goal, the authors have developed a user-initialized algorithm for reconstructing valve geometry from transesophageal 3D ultrasound (3D US) image data. Methods: Semi-automated image analysis was performed on transesophageal 3D US images obtained from 14 subjects with MR ranging from trace to severe. Image analysis of the mitral valve at midsystole had two stages: user-initialized segmentation and 3D deformable modeling with continuous medial representation (cm-rep). Semi-automated segmentation began with useridentification of valve location in 2D projection images generated from 3D US data. The mitral leaflets were then automatically segmented in 3D using the level set method. Second, a bileaflet deformable medial model was fitted to the binary valve segmentation by Bayesian optimization. The resulting cm-rep provided a visual reconstruction of the mitral valve, from which localized measurements of valve morphology were automatically derived. The features extracted from the fitted cm-rep included annular area, annular circumference, annular height, intercommissural width, septolateral length, total tenting volume, and percent anterior tenting volume. These measurements were compared to those obtained by expert manual tracing. Regurgitant orifice area (ROA) measurements were compared to qualitative assessments of MR severity. The accuracy of valve shape representation with cm-rep was evaluated in terms of the Dice overlap between the fitted cm-rep and its target segmentation. Results: The morphological features and anatomic ROA derived from semi-automated image analysis were consistent with manual tracing of 3D US image data and with qualitative assessments of MR severity made on clinical radiology. The fitted cm-reps accurately captured valve shape and demonstrated patient-specific differences in valve morphology among subjects with varying degrees of MR severity. Minimal variation in the Dice overlap and morphological measurements was observed when different cm-rep templates were used to initialize model fitting. Conclusions: This study demonstrates the use of deformable medial modeling for semi-automated 3D reconstruction of mitral valve geometry using transesophageal 3D US. The proposed algorithm provides a parametric geometrical representation of the mitral leaflets, which can be used to evaluate valve morphology in clinical ultrasound images.

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Section: Discussion Iva Contributionsmentioning

confidence: 49%

Section: Iid Feature Extractionmentioning

confidence: 97%

Section: Iid Feature Extractionmentioning

confidence: 99%

Section: Iib2 Deformable Medial Modelingmentioning

confidence: 99%

Section: Iig Roa Sensitivity Analysismentioning

confidence: 99%

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Development of a semi-automated method for mitral valve modeling with medial axis representation using 3D ultrasound

Pouch¹,

Yushkevich²,

Jackson³

et al. 2012

Med. Phys.

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A noninvasive method for the determination of in vivo mitral valve leaflet strains

Rego

Khalighi

Drach

et al. 2018

Numer Methods Biomed Eng

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Assessment of mitral valve (MV) function is important in many diagnostic, prognostic, and surgical planning applications for treatment of MV disease. Yet, to date, there are no accepted noninvasive methods for determination of MV leaflet deformation, which is a critical metric of MV function. In this study, we present a novel, completely noninvasive computational method to estimate MV leaflet in-plane strains from clinical-quality real-time three-dimensional echocardiography (rt-3DE) images. The images were first segmented to produce meshed medial-surface leaflet geometries of the open and closed states. To establish material point correspondence between the two states, an image-based morphing pipeline was implemented within a finite element (FE) modeling framework in which MV closure was simulated by pressurizing the open-state geometry, and local corrective loads were applied to enforce the actual MV closed shape. This resulted in a complete map of local systolic leaflet membrane strains, obtained from the final FE mesh configuration. To validate the method, we utilized an extant in vitro database of fiducially labeled MVs, imaged in conditions mimicking both the healthy and diseased states. Our method estimated local anisotropic in vivo strains with less than 10% error and proved to be robust to changes in boundary conditions similar to those observed in ischemic MV disease. Next, we applied our methodology to ovine MVs imaged in vivo with rt-3DE and compared our results to previously published findings of in vivo MV strains in the same type of animal as measured using surgically sutured fiducial marker arrays. In regions encompassed by fiducial markers, we found no significant differences in circumferential(P = 0.240) or radial (P = 0.808) strain estimates between the marker-based measurements and our novel noninvasive method. This method can thus be used for model validation as well as for studies of MV disease and repair.

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Towards Patient-Specific Mitral Valve Surgical Simulations

Khalighi

Rego

Drach

et al. 2018

Advances in Heart Valve Biomechanics

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Quantitative Mitral Valve Modeling Using Real-Time Three-Dimensional Echocardiography: Technique and Repeatability

Cited by 57 publications

References 25 publications

Development of a semi-automated method for mitral valve modeling with medial axis representation using 3D ultrasound

Development of a semi-automated method for mitral valve modeling with medial axis representation using 3D ultrasound

A noninvasive method for the determination of in vivo mitral valve leaflet strains

Towards Patient-Specific Mitral Valve Surgical Simulations

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