Cerebral artery segmentation based on magnetization-prepared two rapid acquisition gradient echo multi-contrast images in 7 Tesla magnetic resonance imaging

Uk-Su Choi; Hirokazu Kawaguchi; Ikuhiro Kida

doi:10.1016/j.neuroimage.2020.117259

Cerebral artery segmentation based on magnetization-prepared two rapid acquisition gradient echo multi-contrast images in 7 Tesla magnetic resonance imaging

Neuroimage. 2020 Nov 15:222:117259. doi: 10.1016/j.neuroimage.2020.117259. Epub 2020 Aug 13.

Authors

Uk-Su Choi¹, Hirokazu Kawaguchi², Ikuhiro Kida³

Affiliations

¹ Center for Information and Neural Networks, National Institute of Information and Communications Technology, 1-4 Yamadaoka, Suita, Osaka 565-0871, Japan; Graduate School of Frontier Biosciences, Osaka University, Suita, Osaka 565-0871, Japan.
² Siemens Healthcare K.K., Shinagawa, Tokyo 141-8644, Japan.
³ Center for Information and Neural Networks, National Institute of Information and Communications Technology, 1-4 Yamadaoka, Suita, Osaka 565-0871, Japan; Graduate School of Frontier Biosciences, Osaka University, Suita, Osaka 565-0871, Japan. Electronic address: ikuhiro.kida@nict.go.jp.

PMID: 32798680
DOI: 10.1016/j.neuroimage.2020.117259

Abstract

Cerebral artery segmentation plays an important role in the direct visualization of the human brain to obtain vascular system information. On ultra-high field magnetic resonance imaging, cerebral arteries appearing hyperintense on T1 weighted (T1w) images could be segmented from brain tissues such as gray and white matter. In this study, we propose an automated method to segment the cerebral arteries using multi-contrast images including T1w images of a magnetization-prepared two rapid acquisition gradient echo (MP2RAGE) sequence at 7 T. The proposed method, termed MP2rase-CA (MP2rage based RApid SEgmentation Cerebral Artery), employed a seed-based region-growing strategy and Frangi filtering as well as our brain tissue segmentation (MP2rase Brain Tissue). Time-of-flight (TOF) magnetic resonance angiography (MRA) images were obtained as a reference to evaluate the MP2rase-CA. We successfully performed vessel segmentations, from T1w MP2RAGE images, which mostly overlapped with the segmentations of large cerebral arteries from the TOF-MRA. We also investigated the effect of the large cerebral arteries on spatial transformation of anatomical images to standard coordinate space using vessel segmentation by MP2rase-CA. As a result, the T1w image without the cerebral arteries by MP2rase-CA showed better agreement with the standard atlas compared with the T1w image containing the arteries. In addition, voxel-based morphology showed significant differences between T1w images with and without cerebral arteries in brain areas nearby large arteries. Thus, because MP2rase-CA using MP2RAGE images can obtain brain tissue anatomical information as well as relatively large cerebral artery information without need for additional structure acquisition, it is useful and time saving for functional and structural studies.

Keywords: Automated segmentation; Cerebral artery; MP2RAGE; Spatial normalization; Time-of-flight; VBM; Vessel segmentation; Voxel-based morphology.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Adult
Brain / anatomy & histology
Brain / blood supply*
Cerebral Arteries / pathology*
Female
Humans
Image Enhancement / methods
Image Interpretation, Computer-Assisted* / methods
Image Processing, Computer-Assisted / methods
Imaging, Three-Dimensional / methods
Magnetic Resonance Imaging* / methods
Male