Background

Image-quality assessment is a fundamental step before clinical evaluation of magnetic resonance images. The aim of this study was to introduce a visual scoring system that provides a quality 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; and (2) artifact-based QC (aQC), evaluating image quality of the CBF map for the presence of common types of artifacts. Three raters evaluated cQC and aQC for 158 quantitative signal targeting with alternating radiofrequency labelling of arterial regions (QUASAR) ASL scans (CBF, T1 relaxation rate, arterial blood volume, and arterial transient 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 visual QC system with an automatic QC system.

中文翻译：

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用于临床动脉旋转标记图像的视觉质量控制量表。

背景

图像质量评估是磁共振图像临床评估之前的基本步骤。这项研究的目的是引入一种视觉评分系统，该评分系统为动脉旋转标记（ASL）提供质量控制标准，并且可以应用于脑血流（CBF）图以及辅助ASL图像。

方法

所提出的图像质量控制（QC）系统包含两个组件：（1）基于对比度的QC（cQC），用于描述解剖结构之间的视觉对比度；（2）基于伪影的质量控制（aQC），评估CBF图的图像质量是否存在常见伪影。三名评估者评估了158个定量信号目标的cQC和aQC，并交替使用了动脉区域的射频标记（QUASAR）ASL扫描（CBF，T1弛豫率，动脉血容量和动脉瞬时时间）。使用Spearman相关系数（r），组内相关系数（ICC）和接收机工作特性分析。

结果

内部/评估者之间的一致程度从中等到优秀；评估者之间的ICC对于cQC为0.72，对于aQC为0.60，对于组合QC（cQC + aQC）为0.74。cQC的评估者内部ICC为0.90；质量控制为0.80，综合质量控制为0.90。在aQC和CBF映射质量之间（r  = 0.75）以及在aQC和cQC之间（r  = 0.70）发现了很强的相关性。QC分数18是区分高品质和低品质临床扫描的最佳选择。

结论

拟议的QC系统提供了高重现性和可靠的阈值，可用于丢弃低质量的扫描。未来的研究应该将这种视觉质量控制系统与自动质量控制系统进行比较。