A visual quality control scale for clinical arterial spin labeling images

Background: Image-quality assessment is a fundamental step before c linical evaluation of mag netic resonance images. The aim of this study was to introduce a vi sual scoring system that provides a qual ity control standard for arterial spin labeling (ASL) and that can be applied to cerebral blood flow (CBF) maps, as well as to ancillary ASL images. Methods: The proposed image quality control (QC) system had two components: (1) contrast-based QC (cQC), describing the visual contrast between anatomical structures; a nd (2) artifact-based QC (aQC), evaluating image quality of theCBFmapforthepresenceofcommontypesofartifacts. Three raters evaluated cQC an d aQC for 158 quantitative signal targeting with alternating radiofrequency labelling o f arterial regions (QUASAR) ASL scans (CBF, T1 relaxation rate, arterial blood volume, and arterial transie nt time). Spearman correlation coefficient ( r ), intraclass correlation coefficients (ICC), and receiver operating characteristic analysis were used. Results: Intra/inter-rater agreement ranged from moderate to excellent; inter-rater ICC was 0.72 for cQC, 0.60 for aQC, and 0.74 for the combined QC (cQC + aQC). Intra-rater ICC was 0.90 for cQC; 0.80 for aQC, and 0.90 for the combined QC. Strong correlations were found between aQC and CBF maps quality ( r = 0.75), and between aQC and cQC ( r = 0.70). A QC score of 18 was optimal to discriminate between high and low quality clinical scans. Conclusions: The proposed QC system provided high reproducibility and a reliable threshold for discarding low quality scans. Future research should compare this v isualQCsystemwithanautomaticQCsystem.