title: 3D undersampled golden-radial phase encoding for DCE-MRA using inherently regularized iterative SENSE.
abstract: One of the current limitations of dynamic contrast-enhanced MR angiography is the requirement of both high spatial and high temporal resolution. Several undersampling techniques have been proposed to overcome this problem. However, in most of these methods the tradeoff between spatial and temporal resolution is constant for all the time frames and needs to be specified prior to data collection. This is not optimal for dynamic contrast-enhanced MR angiography where the dynamics of the process are difficult to predict and the image quality requirements are changing during the bolus passage. Here, we propose a new highly undersampled approach that allows the retrospective adaptation of the spatial and temporal resolution. The method combines a three-dimensional radial phase encoding trajectory with the golden angle profile order and non-Cartesian Sensitivity Encoding (SENSE) reconstruction. Different regularization images, obtained from the same acquired data, are used to stabilize the non-Cartesian SENSE reconstruction for the different phases of the bolus passage. The feasibility of the proposed method was demonstrated on a numerical phantom and in three-dimensional intracranial dynamic contrast-enhanced MR angiography of healthy volunteers. The acquired data were reconstructed retrospectively with temporal resolutions from 1.2 sec to 8.1 sec, providing a good depiction of small vessels, as well as distinction of different temporal phases.
authors.affiliation: King's College London, Division of Imaging Sciences, NIHR Biomedical Research Centre at Guy's & St Thomas' Foundation Trust London, United Kingdom. claudia.prieto@kcl.ac.uk
authors.forename: Claudia
authors.initials: C
authors.lastname: Prieto
authors.forename: Sergio
authors.initials: S
authors.lastname: Uribe
authors.forename: Reza
authors.initials: R
authors.lastname: Razavi
authors.forename: David
authors.initials: D
authors.lastname: Atkinson
authors.forename: Tobias
authors.initials: T
authors.lastname: Schaeffter
mesh_terms: D000465:Algorithms; D002536:Cerebral Arteries / Q000033:anatomy & histology*; D003627:Data Interpretation, Statistical; D005240:Feasibility Studies; D006801:Humans; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D018810:Magnetic Resonance Angiography / Q000379:methods*; D015203:Reproducibility of Results; D018401:Sample Size; D012680:Sensitivity and Specificity; D012815:Signal Processing, Computer-Assisted