Fast Femoral Artery Segmentation from Black-Blood MRI

With the prevalence of about 3% in the general Chinese population, peripheral arterial disease (PAD) has become a serious health issue. To address this issue, vessel wall imaging techniques have been introduced to assess the burden of PAD in terms of vessel wall thickness, area or volume. Recent advances in a 3D black-blood MRI sequence known as the 3D MSDE prepared rapid gradient echo sequence (3D MERGE) have allowed the acquisition of vessel wall images with up to 50 cm coverage, facilitating noninvasive and detailed PAD assessment. This work introduces an algorithm that combines 2D slice-based segmentation and 3D user editing to allow for efficient plaque burden analysis of 3D MERGE femoral artery images. The 2D slice-based segmentation approach is based on propagating segmentation results of contiguous 2D slices. The 3D image volume was then reformatted using the curved planar reformation (CPR) technique. User editing of the segmented contours was performed on the CPR views taken at different angles. The method was evaluated on 6 femoral artery images. Lumen and outer wall boundaries segmented using the proposed algorithm were assessed by comparison with manual segmentation. The Mean Absolute Difference (MAD) between the semi automatically segmented lumen boundaries and the manually segmented boundaries was 0.23 ±0.20mm and the MAD between the semi automatically segmented wall boundaries and the manually segmented boundaries was 0.25 ± 0.14 mm. The time required for the entire semi automated segmentation process was only 1-2% of the time required for manual segmentation.