Three-dimensional echocardiography for assessment of mitral valve regurgitation

3D echocardiography in mitral valve prolapse

Mitral valve prolapse (MVP) is the leading cause of mitral valve surgery. Echocardiography is the principal imaging modality used to diagnose MVP, assess the mitral valve morphology and mitral annulus dynamics, and quantify mitral regurgitation. Three-dimensional (3D) echocardiographic (3DE) imaging represents a consistent innovation in cardiovascular ultrasound in the last decades, and it has been implemented in routine clinical practice for the evaluation of mitral valve diseases. The focus of this review is the role and the advantages of 3DE in the comprehensive evaluation of MVP, intraoperative and intraprocedural monitoring.

Three-dimensional proximal flow convergence automatic calculation for determining mitral valve area in rheumatic mitral stenosis

PURPOSE

Management of patients with mitral stenosis (MS) depends heavily on the accurate quantification of mitral valve area (MVA) using echocardiography. All currently used two-dimensional (2D) methods have limitations. Estimation of MVA using the proximal isovelocity surface area (PISA) method with real time three-dimensional (3D) echocardiography may circumvent those limitations. We aimed to evaluate the accuracy of 3D direct measurement of PISA in the estimation of MVA.

METHODS

Twenty-seven consecutive patients (median age of 63 years; 77.8% females) with rheumatic MS were prospectively studied. Transthoracic and transesophageal echocardiography with 2D and 3D acquisitions were performed on the same day. The reference method for MVA quantification was valve planimetry after 3D-volume multiplanar reconstruction. A semi-automated software was used to calculate the 3D flow convergence volume.

RESULTS

Compared to MVA estimation using 3D planimetry, 3D PISA showed the best correlation (rho=0.78, P<.0001), followed by pressure half-time (PHT: rho=0.66, P<.001), continuity equation (CE: rho=0.61, P=.003), and 2D PISA (rho=0.26, P=.203). Bland-Altman analysis revealed a good agreement for MVA estimation with 3D PISA (mean difference -0.03 cm² ; limits of agreement (LOA) -0.40-0.35), in contrast to wider LOA for 2D methods: CE (mean difference 0.02 cm² , LOA -0.56-0.60); PHT (mean difference 0.31 cm² , LOA -0.32-0.95); 2D PISA (mean difference -0.03 cm² , LOA -0.92-0.86).

CONCLUSIONS

MVA estimation using 3D PISA was feasible and more accurate than 2D methods. Its introduction in daily clinical practice seems possible and may overcome technical limitations of 2D methods.

Three-Dimensional Echocardiography Compared With Computed Tomography to Determine Mitral Annulus Size Before Transcatheter Mitral Valve Implantation

BACKGROUND

Previously, through the use of computed tomography (CT), it has been proposed that D-shaped versus saddle-shaped mitral annulus (MA) segmentation is more biomechanically appropriate to determine transcatheter mitral valve implantation size and eligibility.

METHODS AND RESULTS

Forty-one patients with severe mitral regurgitation being considered for transcatheter mitral valve implantation who had undergone cardiac CT and 3-dimensional transesophageal echocardiography (3D-TEE) were retrospectively evaluated. A standardized segmentation protocol for the D-shaped MA was developed using Philips Q-Laboratory mitral valve quantification software. MA dimensions were compared using Spearman's rank correlation and Bland-Altman analysis. Inter- and intraobserver agreement was quantified by intraclass correlation coefficient and Bland-Altman analysis. Mean age was 77±14 years; 71% male (n=29); mitral regurgitation pathogenesis was functional in 54% (n=22) and myxomatous in 46% (n=19). Mean MA area and circumference by 3D-TEE and CT were 11.3±2.7 versus 11.4±3.0 (P=0.67) and 124.1±15.6 versus 123.9±15.5 (P=0.79), respectively, with excellent correlation between modalities (r=0.84 and r=0.86; P<0.0001) and no systematic bias (-0.20±1.8 cm(2) [-3.7 cm(2); 3.3 cm(2)], 0.37±9 mm [-18.0 mm; 17.27 mm]). Mean septal-to-lateral and inter-trigone distances by 3D-TEE and CT were 33.2±4.7 versus 32.5±4.4 (P=0.24) and 31.7±3.5 versus 32.6±3.6 (P=0.06), respectively, with good correlation (r=0.69 and r=0.71; P<0.0001) and no systematic bias (0.77±3.8 mm [-6.7 mm; 8.2 mm], -1.5±3.1 mm [-4.6 mm; 7.6 mm]). There was excellent intra- and interobserver agreement according to intraclass correlation coefficients >0.90 for all parameters.

CONCLUSIONS

Similar to cardiac CT, 3D-TEE allows for D-shaped MA segmentation with no systematic difference in MA dimensions between modalities. This study supports the utilization of 3D-TEE as a complementary tool to CT assessment of the D-shaped MA to determine transcatheter mitral valve implantation size.

Dynamic Phenotypes of Degenerative Myxomatous Mitral Valve Disease

Background—

Fibro-elastic deficiency (FED) and diffuse myxomatous degeneration (DMD) are phenotypes of degenerative mitral valve disease defined morphologically. Whether physiological differences in annular and valvular dynamics exist between these phenotypes remains unknown.

Methods and Results—

We performed triple quantitation of cardiac remodeling and of mitral regurgitation severity and of annular and valvular dimensions by real-time 3-dimensional-transesophageal-echocardiography. Forty-nine patients with degenerative mitral valve disease classified as FED (n=31) and DMD (n=18) by surgical observation showed no difference in age (65±10 versus 59±13; P =0.5), body surface area (2.0±0.2 versus 2.0±0.2 m 2 ; P =0.5), left ventricular and atrial dimensions (all P >0.55), and mitral regurgitation regurgitant orifice ( P =0.62). On average, annular dimensions were larger in DMD versus FED, but height was similar resulting in lower saddle shape. Dynamically, annular DMD versus FED display poorer contraction and saddle-shape accentuation in early systole and abnormal enlargement, particularly intercommissural, in late-systole (all P <0.05). Valvular dynamics showed stable valvular area in systole in FED versus considerable systolic increased area in DMD ( P <0.001). Prolapse height and volume increased little throughout systole in FED versus marked increase in DMD ( P <0.001).

Conclusions—

Our novel observations show that FED and DMD, although both labeled myxomatous, display considerable physiological phenotypic differences. In DMD, the annular increased size and profoundly abnormal dynamics demonstrate DMD-specific annular degeneration compared with the enlarged but relatively normal FED annulus. DMD does not incur more severe mitral regurgitation, despite larger prolapse and valve redundancy, underscoring potential compensatory role of tissue redundancy of DMD (or aggravating role of tissue paucity of FED) on mitral regurgitation severity.

Accuracy of a mitral valve segmentation method using J-splines for real-time 3D echocardiography data

Patient-specific models of the heart's mitral valve (MV) exhibit potential for surgical planning. While advances in 3D echocardiography (3DE) have provided adequate resolution to extract MV leaflet geometry, no study has quantitatively assessed the accuracy of their modeled leaflets vs. a ground-truth standard for temporal frames beyond systolic closure or for differing valvular dysfunctions. The accuracy of a 3DE-based segmentation methodology based on J-splines was assessed for porcine MVs with known 4D leaflet coordinates within a pulsatile simulator during closure, peak closure, and opening for a control, prolapsed, and billowing MV model. For all time points, the mean distance error between the segmented models and ground-truth data were 0.40 ± 0.32 mm, 0.52 ± 0.51 mm, and 0.74 ± 0.69 mm for the control, flail, and billowing models. For all models and temporal frames, 95% of the distance errors were below 1.64 mm. When applied to a patient data set, segmentation was able to confirm a regurgitant orifice and post-operative improvements in coaptation. This study provides an experimental platform for assessing the accuracy of an MV segmentation methodology at phases beyond systolic closure and for differing MV dysfunctions. Results demonstrate the accuracy of a MV segmentation methodology for the development of future surgical planning tools.

Quantification of mitral valve regurgitation with color flow Doppler using baseline shift

Vena contracta width (VCW) and effective regurgitant orifice area (EROA) are well established methods for evaluating mitral regurgitation using transesophageal echocardiography (TEE). For color-flow Doppler (CF) measurements Nyquist limit of 50-60 cm/s is recommended. Aim of the study was to investigate the effectiveness of a baseline shift of the Nyquist limit for these measurements. After a comprehensive 2-dimensional (2D) TEE examination, the mitral regurgitation jet was acquired with a Nyquist limit of 50 cm/s (NL50) along with a baseline shift to 37.5 cm/s (NL37.5) using CF. Moreover a real time 3-dimensional (RT 3D) color complete volume dataset was stored with a Nyquist limit of 50 cm/s (NL50) and 37.5 cm/s (NL37.5). Vena contracta width (VCW) as well as proximal isovelocity surface area (PISA) derived EROA were measured based on 2D TEE and compared to RT 3D echo measurements for vena contracta area (VCA) using planimetry method. Correlation between VCA 3D NL50 and VCW NL50 was 0.29 (p < 0.05) compared to 0.6 (p < 0.05) using NL37.5. Correlation between VCA 3D NL50 and EROA 2D NL50 was 0.46 (p < 0.05) vs. 0.6 (p < 0.05) EROA 2D NL37.5. Correlation between VCA 3D NL37.5 and VCW NL50 was 0.45 (p < 0.05) compared to 0.65 (p < 0.05) using VCW NL37.5. Correlation between VCA 3D NL37.5 and EROA 2D NL50 was 0.41 (p < 0.05) vs. 0.53 (p < 0.05) using EROA 2D NL37.5. Baseline shift of the NL to 37.5 cm/s improves the correlation for VCW and EROA when compared to RT 3D NL50 planimetry of the vena contracta area. Baseline shift in RT 3D to a NL of 37.5 cm/s shows similar results like NL50.

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

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 user-identification 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.

Semi-automated mitral valve morphometry and computational stress analysis using 3D ultrasound

In vivo human mitral valves (MV) were imaged using real-time 3D transesophageal echocardiography (rt-3DTEE), and volumetric images of the MV at mid-systole were analyzed by user-initialized segmentation and 3D deformable modeling with continuous medial representation, a compact representation of shape. The resulting MV models were loaded with physiologic pressures using finite element analysis (FEA). We present the regional leaflet stress distributions predicted in normal and diseased (regurgitant) MVs. Rt-3DTEE, semi-automated leaflet segmentation, 3D deformable modeling, and FEA modeling of the in vivo human MV is tenable and useful for evaluation of MV pathology.

Quantitative mitral valve modeling using real-time three-dimensional echocardiography: technique and repeatability

BACKGROUND

Real-time three-dimensional (3D) echocardiography has the ability to construct quantitative models of the mitral valve (MV). Imaging and modeling algorithms rely on operator interpretation of raw images and may be subject to observer-dependent variability. We describe a comprehensive analysis technique to generate high-resolution 3D MV models and examine interoperator and intraoperator repeatability in humans.

METHODS

Patients with normal MVs were imaged using intraoperative transesophageal real-time 3D echocardiography. The annulus and leaflets were manually segmented using a TomTec Echo-View workstation. The resultant annular and leaflet point cloud was used to generate fully quantitative 3D MV models using custom Matlab algorithms. Eight images were subjected to analysis by two independent observers. Two sequential images were acquired for 6 patients and analyzed by the same observer. Each pair of annular tracings was compared with respect to conventional variables and by calculating the mean absolute distance between paired renderings. To compare leaflets, MV models were aligned so as to minimize their sum of squares difference, and their mean absolute difference was measured.

RESULTS

Mean absolute annular and leaflet distance was 2.4±0.8 and 0.6±0.2 mm for the interobserver and 1.5±0.6 and 0.5±0.2 mm for the intraobserver comparisons, respectively. There was less than 10% variation in annular variables between comparisons.

CONCLUSIONS

These techniques generate high-resolution, quantitative 3D models of the MV and can be used consistently to image the human MV with very small interoperator and intraoperator variability. These data lay the framework for reliable and comprehensive noninvasive modeling of the normal and diseased MV.