Using a shape prior for robust modeling of the mitral annulus on 4D ultrasound data

Over 40,000 annuloplasty rings are implanted each year in the USA to treat mitral regurgitation. However, the used measuring techniques to select a suitable annuloplasty ring are imprecise and highly depending on the expert's experience. This can cause a re-occurrence of the mitral regurgitation or an annuloplasty ring dehiscence, and thus the necessity of a re-operation. We propose a method to create a 4D model of the mitral annulus from ultrasound data to enable precise measurement and patient-specific implant planning.

An initial mitral annulus model is placed interactively in the 4D image data by defining commissure points and the annulus plane for one time step in diastole and systole. The model is automatically optimized using distinct image features. A shape and pose prior of the mitral annulus is used to compensate for artifacts and to enforce a plausible anatomical morphology, while a temporal alignment ensures a natural motion of the 4D model.

Ground truth data were created for 4D images of 42 patients with varying image quality. A parameter and shape prior training was performed on a third of the ground truth data, while the rest was used to validate the method. The average error of the resulting mitral annulus models was computed as 2.25 ( +/-0.38 ) mm. The average expert standard deviation was determined as 1.86 (+/-0.32 ) mm.

The proposed method enables the 4D modeling of mitral annuli based on ultrasound data in less than 2 min. The resulting models are comparable to manually delineated models and can be used for measurements of annular geometries and patient-specific annuloplasty treatment planning.