Automatic vessel segmentation in MR angiography
Authors: Weiss K J , Mittmann N , Stehning C , Doeblin P , Beyer R , Hashemi D , Kelle S 
Published: June 2023

Abstract

Funding Acknowledgements
Type of funding sources: None.

Background
Vessel-to-background contrast (VBC), the ratio of signal intensities (SI) within a vessel segment compared to the surrounding tissue, is an essential objective parameter for assessing image quality in contrast-enhanced MR angiography (CE-MRA) of peripheral arteries. (1–3) Manual evaluation by the measurement of SIs within the vessel and in the surrounding area is labour-intensive and tedious. (2) An algorithm for automatic segmentation of the vessel lumen and background signal reduces the workload significantly. It has already been successfully applied to CE-MRA in peripheral arterial disease (PAD). (3) However, whether this algorithm is equal to a manual evaluation is not yet known.

Purpose
To compare the manual and automatic evaluation of VBC in CE-MRA in patients with PAD.

Methods
A patient with suspected peripheral arterial disease underwent first-pass subtraction MRA on a 3T scanner. Region-of-interests (ROIs) were drawn on predefined vessel segments (Figure 1), manually inside and outside the vessel lumen and additionally a comprehensive ROI with the vessel under investigation in the centre. The algorithm segmented the comprehensive ROI into the vessel and background by identifying a seed point for the vessel and then using a flood fill algorithm. The remaining vessel branches were removed in order to approximate the true background signal. SI of the manual and the automatic segmentation were compared to define the VBC using the formula SI lumen - SI background divided by the standard deviation (SD) of the background for both methods.

Results
43 vessel segments were evaluated. An example is given in Figure 2 with A) showing an axial view of the right thigh with a comprehensive ROI with the superficial femoral artery in the centre (green), and manual outlining of the lumen (red) and background (blue). Background signal (B1) and vessel lumen (B2) were used to evaluate the manuall values. Automated segmentation with C1) shows the ROI with the femoral artery in the centre. C2) shows the full extent of the vessel as identified by the flood-fill algorithm, and C3) the resulting mask. Background signal was calculated from SIs remaining in C4 after subtraction of the local maximas shown in C5). The mean SI in the vessel lumen was 4171 (standard deviation, SD 954) for the manual evaluation and 5014 (SD 830) for the automatic evaluation (p = 0.001) and in the background 601 (SD 542) for the manual evaluation and 493 (SD 229) for the automatic evaluation ((p = 0.231). The VBC was 10.3 (SD 5.9) for manual evaluation and 12.2 (SD 5.6) for automatic evaluation (p = 0.139).

Conclusion
Automatic segmentation of vessel lumen and background signal allows assessment of the VBC in CE-MRA in patients with PAD. The mean SI of the vessel lumen tends to be overestimated about 20% by the automatic algorithm. Higher patient numbers are required to further clarify the applicability of this algorithm for image quality evaluation.