Sinogram-based coil selection for streak artifact reduction in undersampled radial real-time magnetic resonance imaging

Abstract

Background: Streak artifacts are a common problem in radial magnetic resonance imaging (MRI). We therefore developed a method for automatically excluding receiver coil elements which lead to these artifacts. Methods:The proposed coil selection relates to real-time MRI data based on highly undersampled radial acquisitions. It exploits differences between high-and low-resolution sinograms reconstructed from datasets acquired during preparatory scans. Apart from phantom validations, the performance was assessed for realtime MRI studies of different human organ systems in vivo.Results: The algorithm greatly reduces streak artifact strength without compromising image quality in other parts of the image. It is robust with respect to different experimental settings and fast to be included in the online reconstruction pipeline for real-time MRI. Conclusions:The proposed method enables a fast reduction of streak artifacts in radial real-time MRI.

Free‐breathing fat and R2* quantification in the liver using a stack‐of‐stars multi‐echo acquisition with respiratory‐resolved model‐based reconstruction

“…Since reliable NAFLD assessment requires high measurement accuracy for small fat fraction values, future work should focus on improving the PDFF value accuracy for small PDFF values, for example, by exploring various strategies for reducing streaking artifacts. For example, streaking suppression can be achieved by automatically excluding certain coils containing high levels of streaking during reconstruction 51‐53 …”

“…For example, streaking suppression can be achieved by automatically excluding certain coils containing high levels of streaking during reconstruction. [51][52][53] F I G U R E 3 PDFF (top) and R * 2 (bottom) maps of a 25-year old patient (male, BMI: 24.6 kg m −2 ) from (A) the breath-held Cartesianeference scan, and (B)-(E) the free-breathing stack-of-stars acquisition (end-expiratory frame). The radial dataset was reconstructed (B) using motiongating (25% acceptance rate) followed by NUFFT and image-based water-fat separation, (C) using motion-gating (50% acceptance rate) followed by NUFFT and image-based water-fat separation, (D) using motion-gating (25% acceptance rate) followed by model-based water-fat separation ("Motion-resolved XD" with W = F = R * 2 = 0), and (D) using motion-resolved XD reconstruction.…”

Radial streak artifact reduction using phased array beamforming

“…Manual identification of problematic coils can be quite laborious as trading artifact reduction vs signal‐to‐noise ratio (SNR) loss is nontrivial. Recently, automated coil pruning strategies which attempt to select the optimal set of coils to prune with little to no user intervention have emerged . Hybrid approaches that weight the k‐space coil data instead of full coil removal have also been proposed .…”

RACER‐GRASP: Respiratory‐weighted, aortic contrast enhancement‐guided and coil‐unstreaking golden‐angle radial sparse MRI

“…Several attempts have been made during the past few years to address some of these challenges. Examples of these approaches include (i) contrast bolus tracking using the center of k‐space ; (ii) extension of GRASP to eXtra‐Dimensional GRASP (XD‐GRASP) to reduce residual motion effects by reconstructing a multidimensional respiratory motion‐resolved image set ; and (iii) exclusion of “poor” coil elements containing a high level of streaking artifacts before image reconstruction . Although these methods can partially solve some challenges, they all have various limitations.…”