Accelerated noncontrast‐enhanced 4‐dimensional intracranial MR angiography using golden‐angle stack‐of‐stars trajectory and compressed sensing with magnitude subtraction

Purpose To evaluate the feasibility and performance of compressed sensing (CS) with magnitude subtraction regularization in accelerating non–contrast-enhanced dynamic intracranial MR angiography (NCE-dMRA). Methods A CS algorithm was introduced in NCE-dMRA by exploiting the sparsity of the magnitude difference of the control and label images. The NCE-dMRA data were acquired using golden-angle stack-of-stars trajectory on six healthy volunteers and one patient with arteriovenous fistula. Images were reconstructed using (i) the proposed magnitude-subtraction CS (MS-CS); (ii) complex-subtraction CS; (iii) independent CS; and (iv) view-sharing with k-space weighted image contrast (KWIC). The dMRA image quality was compared across the four reconstruction strategies. The proposed MS-CS method was further compared with KWIC for temporal fidelity of depicting dynamic flow. Results The proposed MS-CS method was able to reconstruct NCE-dMRA images with detailed vascular structures and clean background. It provided better subjective image quality than the other two CS strategies (P < 0.05). Compared with KWIC, MS-CS showed similar image quality, but reduced temporal blurring in delineating the fine distal arteries. Conclusions The MS-CS method is a promising CS technique for accelerating NCE-dMRA acquisition without compromising image quality and temporal fidelity. Magn Reson Med, 2017. © 2017 International Society for Magnetic Resonance in Medicine.