Person:

Marx, Gerald

Segmenting the mitral valve during closure and throughout a cardiac cycle from four dimensional ultrasound (4DUS) is important for creation and validation of mechanical models and for improved visualization and understanding of mitral valve behavior. Current methods of segmenting the valve from 4DUS either require extensive user interaction and initialization, do not maintain the valve geometry across a cardiac cycle, or are incapable of producing a detailed coaptation line and surface. We present a method of segmenting the mitral valve annulus and leaflets from 4DUS such that a detailed, patient-specific annulus and leaflets are tracked throughout mitral valve closure, resulting in a detailed coaptation region. The method requires only the selection of two frames from a sequence indicating the start and end of valve closure and a single point near a closed valve. The annulus and leaflets are first found through direct segmentation in the appropriate frames and then by tracking the known geometry to the remaining frames. We compared the automatically segmented meshes to expert manual tracings for both a normal and diseased mitral valve, and found an average difference of 0.59 ± 0.49mm, which is on the order of the spatial resolution of the ultrasound volumes (0.5–1.0mm/voxel).

Objectives: Although mitral valve repair is rarely required in neonates, this population is considered to be at high risk for adverse outcomes. The aim of this study was to review the indications for surgery, mechanisms, repair techniques, and mid-term outcomes of neonatal mitral valve repair. Methods: The demographic, procedural, and outcome data were obtained for all neonates who underwent mitral valve repair from 2005 to 2012. The primary endpoints included mortality, transplantation, and mitral valve reoperation. Results: Twenty patients were included during the study period. Median age at operation was 11 days (range: 3–25). Eleven patients (55%) presented with mitral stenosis, three had regurgitation (15%), and six had mixed mitral disease (30%). Nineteen of 20 patients had mild or less regurgitation on immediate postoperative imaging. During a median follow-up of 5 months (1 month–4.8 years), six patients died at a median of 33 months (7–41 months) from repair and one patient required orthotopic heart transplantation. Six patients required mitral valve reoperation, five for mitral valve re-repair, and one for mitral valve replacement. Freedom from death, transplantation, or mitral valve replacement was 84.2 ± 8.4% at 1 month, 71.3 ± 11% at 6 months, 64.1 ± 12% at 1 year, and 51.3 ± 15% at 2 years and was worse for patients presenting with mitral regurgitation compared to stenosis or mixed mitral valve disease. Conclusion: Although mitral valve repair can be performed with acceptable immediate postoperative result, this procedure carries a high burden of late death and mitral valve reoperations.

An accurate and reproducible segmentation of the mitral valve annulus from 3D ultrasound is useful to clinicians and researchers in applications such as pathology diagnosis and mitral valve modeling. Current segmentation methods, however, are based on 2D information, resulting in inaccuracies and a lack of spatial coherence. We present a segmentation algorithm which, given a single user-specified point near the center of the valve, uses maxflow and active contour methods to delineate the annulus geometry in 3D. Preliminary comparisons to manual segmentations and a sensitivity study show the algorithm is both accurate and robust.

The geometry of the mitral leaflets, most commonly viewed using three-dimensional ultrasound, is an important input for mechanical models predicting valve closure. Current methods for leaflet modeling from ultrasound either require extensive user interaction, rely on inaccurate assumptions, or produce generic results. The presented method for modeling the mitral leaflets from three-dimensional ultrasound of an open mitral valve is automatic and able to capture patient specific geometry. The method requires as an input the location of the mitral annulus, which we generate semi-automatically using our previously designed method. No additional user interaction is required. The leaflet modeling algorithm operates by first constructing an extended surface at the location of the leaflets which extends beyond the leaflet edges into the blood pool, and then trims the surface to the observed length of the leaflets. Preliminary results suggest the leaflet modeling method, combined with our previous method for annulus segmentation, generates accurate patient-specific mitral valve models.