Targeted vessel reconstruction in non‐contrast‐enhanced steady‐state free precession angiography. (8th February 2016)

• Record Type: Journal Article
• Authors: Ilicak, Efe; Cetin, Suheyla; Bulut, Elif; Oguz, Kader Karli; Saritas, Emine Ulku; Unal, Gozde; Çukur, Tolga
• Is Part Of: NMR in biomedicine. Volume 29:Number 5(2016:May)
• Page Start: 532
• Page End: 544
• Publication Date: 2016-02-08
• Subjects: sparsity -- regularization -- angiography -- segmentation -- vasculature -- compressed sensing; Nuclear magnetic resonance -- Periodicals; Magnetic Resonance Spectroscopy -- Periodicals; 574
• DOI: 10.1002/nbm.3497
• Languages: English
• ISSNs: 0952-3480

Abstract

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. Copyright © 2016 John Wiley & Sons, Ltd. Abstract : In this work we propose a two‐stage strategy for improved reconstruction of non‐contrast‐enhanced angiograms. We employ a tractographic segmentation to create three‐dimensional vasculature maps from undersampled data and apply spatially adaptive penalty terms based on the morphological information obtained. The proposed strategy effectively suppresses aliasing artefacts and background signals, while achieving superior depiction of blood vessels compared with conventional methods.