Fast plaque burden assessment of the femoral artery using 3D black-blood MRI and automated segmentation

Abstract

Purpose: Vessel wall imaging techniques have been introduced to assess the burden of peripheral arterial disease (PAD) in terms of vessel wall thickness, area or volume. Recent advances in a 3D black-blood MRI sequence known as the 3D motion-sensitized driven equilibrium (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 assessment of PAD. This work introduces an algorithm that combines 2D slice-based segmentation and 3D user editing to allow for efficient plaque burden analysis of the femoral artery images acquired using 3D MERGE. Methods: 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 six femoral artery images. Vessel wall thickness and area obtained before and after editing on the CPR views were assessed by comparison with manual segmentation. Difference between semiautomatically and manually segmented contours were compared with the difference of the corresponding measurements between two repeated manual segmentations. Results: The root-mean-square (RMS) errors of the mean wall thickness (t mean ) and the wall area (WA) of the edited contours were 0.35 mm and 7.1 mm 2 , respectively, which are close to the RMS difference between two repeated manual segmentations (RMSE: 0.33 mm in t mean , 6.6 mm 2 in WA). The time required for the entire semiautomated segmentation process was only 1%-2% of the time required for manual segmentation. Conclusions: The difference between the boundaries generated by the proposed algorithm and the manually segmented boundary is close to the difference between repeated manual segmentations. The proposed method provides accurate plaque burden measurements, while considerably reducing the analysis time compared to manual review.

MRI in Lower Extremity Peripheral Arterial Disease: Recent Advancements

“…Better blood suppression will be required however since the current spatial saturation did not always provide for adequate delineation of the vessel wall. Another option for more rapid assessment of femoral artery plaque using CMR uses an automated segmentation and a 3-D black blood sequence 40 (3-D motion-sensitized driven equilibrium prepared rapid gradient echo sequence, called 3-D MERGE) to image up to 50 cm of the femoral artery wall. Although performed in only 6 participants, results were encouraging with similar vessel wall measurements for the manual and semi-automated segmentation, with only 1–2% of the usual time necessary for segmentation.…”

Fast segmentation of the femoral arteries from 3D MR images: A tool for rapid assessment of peripheral arterial disease

“…14 The extended coverage afforded by 3D black-blood sequences, however, has posed a challenge in image analysis required for vessel wall and plaque burden quantification. In our experience in generating surrogate ground truth to validate the semiautomated vessel-wall-plus-plaque quantification of the current and a previous study, 15 70-80 min were required to segment arterial lumen and outer wall on 30 axial image slices per artery with 10 mm interslice distance (ISD). The reason of choosing a large interslice distance was to allow the manual segmentation to be completed within a reasonable time frame.…”

“…To the best of our knowledge, only two prior semiautomatic algorithms 15,16 have been described to segment the lumen and outer wall boundaries from 3D black-blood MR images of the femoral artery with extended coverage. Our group has developed a 2D slice-based deformable segmentation approach, 15 in which a user initialized the boundary on the first axial image. The second axial slice was then registered with the first slice using an optical flow registration algorithm.…”

“…After the lumen surface is obtained, the initial outer wall surface is constructed by expanding the optimized lumen surface; the outer wall surface is subsequently optimized by the 3D deformable model. The accuracy of the segmented surfaces was evaluated using the same metrics described in Chiu et al 15 Based on these metrics, we address the two major issues regarding our algorithm: (a) How much is the accuracy of outer wall, lumen, and the vessel-wall-plus-plaque measurements improved after the introduction of the adjustment operators? (b) Are the segmentation results sensitive to the ISD with which lumen centers are manually located?…”

Vessel-wall imaging and quantification of flow-mediated dilation using water-selective 3D SSFP-echo

“…In comparison only a few studies exist targeting peripheral arteries at 3 T, e.g. common femoral and popliteal arteries [5,6]. In patients with peripheral artery disease (PAD) the image-based evaluation can be crucial, especially when revascularization is being considered.…”