A B-spline Based Cardiac Feature Extraction Method

Objectives The interventricular sulcus (IS) is the line of intersection between the left ventricle (LV) and right ventricle (RV) of a human heart. As an anatomical feature, it follows the movement of the heart especially its twisting motion. The goal of this research is to develop and evaluate a new feature extraction method to track the motion of the IS from 4D gated cardiac PET images for use in quantitative cardiac motion estimation.

Methods The challenge of extracting IS from cardiac PET images is the blurring of the image due to the low system resolution and image noise. Instead of identifying the IS directly from the blurred intersection of the LV and RV from the PET images, we developed an extraction method for the IS by the intersection of the estimated boundaries of the LV and LV using B-spline fitting. The first step of the IS extraction method was to identify and separate the boundary of the LV and the RV from the short-axis slice images of the 3D cardiac PET image at each cardiac-gated frame. An estimate of the inner boundary of the RV was obtained by segmenting the blood pool (BP) within the RV using the 3D region growing method. The shape of the extracted BP was concave at the septal wall side and convex at the lateral side. By subtracting the BP from its convex hull, the central part of the septal side of the BP boundary was identified as a segment of the useful outer LV boundary within the RV. We then identified segments of the LV boundary outside and on the anterior and posterior sides of the RV. The three extracted outer LV segments were fitted with a B-spline curve that passed through the IS intersection points of the short-axis image slice. The segment of the BP boundary on the lateral side of the RV minus the area adjacent to the IS intersection points was identified. It was then extrapolated using B-spline fitting to determine the two crossings with the fitted outer LV boundary as the anterior and posterior IS intersection points. The procedures were repeated for all short-axis image slices of the 3D cardiac PET image at each cardiac-gated frame to obtained the anterior and posterior segments of the IS over the entire heart. To evaluate the IS extraction method, we generated noise-free 4D projection datasets from the 4D XCAT phantom with 4 cardiac gated frames modeling PET system resolution from 0.6 to 4.5 mm. The STIR software package was used to reconstruct the projection dataset at each system resolution and each cardiac-gated frame using the iterative OS-EM algorithm. The IS extraction method was implemented and applied to each reconstructed image for evaluation.

Results The proposed method was capable of extracting both the anterior and posterior IS from the simulated 4D gated cardiac PET images of all system resolution. The location estimation error of the posterior IS was less than 1.8mm, for system resolution up to ~3 mm and increase with further resolution degradation especially the anterior IS due to its local geometric properties.

Conclusions A new cardiac feature extraction method based on B-spline curve fitting, interpolation and extrapolation techniques of identifiable left and right ventricle boundary information, was proposed for extraction of the IS of the heart. The method provides improved extraction accuracy of the IS and allow its use to track its motion for aid in cardiac motion estimate from 4D gated cardiac PET images with continuing improving resolution.