Peltonen Juha I, Mäkelä Teemu, Kuusela Linda, Salli Eero, Kangasniemi Marko
HUS Diagnostic Center, Department of Radiology, University of Helsinki and Helsinki University Hospital, P.O. Box 340, FI-00029 HUS, Helsinki, Finland.
MAGMA. 2025 Sep 3. doi: 10.1007/s10334-025-01292-w.
Magnetic resonance imaging (MRI) is a complex medical imaging method where multiple technical and physiological factors may lead to undesired changes in image quality. The quality control methods utilizing test objects are useful in measuring technical performance, but they may not fully detect all factors present in clinical imaging. In this study, we developed methodologies to quantify observer-based image quality and to compare these observations with technical quality control (QC) parameters.
We analysed 150 brain MRI 3D-FLAIR volumes from 15 scanners, measuring image quality both quantitatively and by visually ranking the images using forced-choice comparison.
Significant differences were found between different scanners based on the forced choice comparison. In imaging study-specific analysis, a weak correlation was observed with contrast-to-noise ratio (CNR) (R = 0.17) and brain white matter-gray matter (WM/GM) contrast (R = 0.14). With device-specific median correlation, the CNR and WM/GM contrast R were 0.21 and 0.34, respectively. Additionally, using device-specific median values, a correlation was found with image quality index (QI) (R = 0.21) and some modulation transfer function (MTF) based resolution-specific parameters (MTF10 FH, R = 0.19; MTF10 AP, R = 0.20; MTF50 AP, R = 0.17).
The forced choice comparison can be effectively utilized to rank image quality across multiple MRI scanners. Technical image quality parameters, directly analysed from anatomical image volumes, can offer prospective maintenance value. Additionally, the quality of clinical image volumes can be assessed using both forced choice comparison and calculational image analysis methods.
磁共振成像(MRI)是一种复杂的医学成像方法,多种技术和生理因素可能导致图像质量出现不理想的变化。利用测试对象的质量控制方法有助于测量技术性能,但可能无法完全检测出临床成像中存在的所有因素。在本研究中,我们开发了方法来量化基于观察者的图像质量,并将这些观察结果与技术质量控制(QC)参数进行比较。
我们分析了来自15台扫描仪的150个脑部MRI 3D-FLAIR容积,通过定量测量以及使用强制选择比较对图像进行视觉排序来评估图像质量。
基于强制选择比较发现不同扫描仪之间存在显著差异。在成像研究特定分析中,观察到与对比度噪声比(CNR)(R = 0.17)和脑白质-灰质(WM/GM)对比度(R = 0.14)存在弱相关性。对于特定设备的中位数相关性,CNR和WM/GM对比度R分别为0.21和0.34。此外,使用特定设备的中位数,发现与图像质量指数(QI)(R = 0.21)以及一些基于调制传递函数(MTF)的分辨率特定参数(MTF10 FH,R = 0.19;MTF10 AP,R = 0.20;MTF50 AP,R = 0.17)存在相关性。
强制选择比较可有效地用于对多个MRI扫描仪的图像质量进行排名。直接从解剖图像容积分析的技术图像质量参数可提供前瞻性的维护价值。此外,临床图像容积的质量可使用强制选择比较和计算图像分析方法进行评估。