title: Targeted vessel reconstruction in non-contrast-enhanced steady-state free precession angiography.
abstract: Image quality in non-contrast-enhanced (NCE) angiograms is often limited by scan time constraints. An effective solution is to undersample angiographic acquisitions and to recover vessel images with penalized reconstructions. However, conventional methods leverage penalty terms with uniform spatial weighting, which typically yield insufficient suppression of aliasing interference and suboptimal blood/background contrast. Here we propose a two-stage strategy where a tractographic segmentation is employed to auto-extract vasculature maps from undersampled data. These maps are then used to incur spatially adaptive sparsity penalties on vascular and background regions. In vivo steady-state free precession angiograms were acquired in the hand, lower leg and foot. Compared with regular non-adaptive compressed sensing (CS) reconstructions (CSlow ), the proposed strategy improves blood/background contrast by 71.3 ± 28.9% in the hand (mean ± s.d. across acceleration factors 1-8), 30.6 ± 11.3% in the lower leg and 28.1 ± 7.0% in the foot (signed-rank test, P < 0.05 at each acceleration). The proposed targeted reconstruction can relax trade-offs between image contrast, resolution and scan efficiency without compromising vessel depiction.
authors: Department of Electrical and Electronics Engineering and the National Magnetic Resonance Research Center, Bilkent University, Ankara, Turkey.
authors: Efe
authors: E
authors: Ilicak
authors: Faculty of Engineering and Natural Sciences, Sabanci University, Istanbul, Turkey.
authors: Suheyla
authors: S
authors: Cetin
authors: Hacettepe University Faculty of Medicine, Ankara, Turkey.
authors: Elif
authors: E
authors: Bulut
authors: Hacettepe University Faculty of Medicine, Ankara, Turkey.
authors: Kader Karli
authors: KK
authors: Oguz
authors: Department of Electrical and Electronics Engineering and the National Magnetic Resonance Research Center, Bilkent University, Ankara, Turkey.
authors: Emine Ulku
authors: EU
authors: Saritas
authors: Department of Computer Engineering, Istanbul Technical University, Istanbul, Turkey.
authors: Gozde
authors: G
authors: Unal
authors: Department of Electrical and Electronics Engineering and the National Magnetic Resonance Research Center, Bilkent University, Ankara, Turkey.
authors: Tolga
authors: T
authors: Çukur
mesh_terms: D001808:Blood Vessels / Q000033:anatomy & histology*; D003198:Computer Simulation; D003287:Contrast Media / Q000737:chemistry*; D006801:Humans; D007090:Image Interpretation, Computer-Assisted; D007866:Leg / Q000098:blood supply; D018810:Magnetic Resonance Angiography / Q000379:methods*; D019047:Phantoms, Imaging
chemical_list: D003287:Contrast Media
keywords: angiography; compressed sensing; regularization; segmentation; sparsity; vasculature