MRI quality assurance based on 3D FLAIR brain images

被引:5
|
作者
Peltonen, Juha I. [1 ,2 ]
Makela, Teemu [1 ,3 ]
Salli, Eero [1 ]
机构
[1] Univ Helsinki, Helsinki Univ Hosp, HUS Med Imaging Ctr, Radiol, POB 340, FI-00029 Helsinki, Finland
[2] Aalto Univ, Sch Sci, Dept Neurosci & Biomed Engn, POB 12200, FI-00076 Espoo, Finland
[3] Univ Helsinki, Dept Phys, POB 64, FI-00014 Helsinki, Finland
关键词
Magnetic resonance imaging; Quality assurance; Quality control; Computer-assisted image analysis; MAGNETIC-RESONANCE IMAGES; SUBARACHNOID HEMORRHAGE; SPATIAL-RESOLUTION; SEQUENCES; OPTIMIZATION; SENSITIVITY; PREVALENCE; CONTRAST;
D O I
10.1007/s10334-018-0699-3
中图分类号
R8 [特种医学]; R445 [影像诊断学];
学科分类号
1002 ; 100207 ; 1009 ;
摘要
ObjectiveQuality assurance (QA) of magnetic resonance imaging (MRI) often relies on imaging phantoms with suitable structures and uniform regions. However, the connection between phantom measurements and actual clinical image quality is ambiguous. Thus, it is desirable to measure objective image quality directly from clinical images.Materials and methodsIn this work, four measurements suitable for clinical image QA were presented: image resolution, contrast-to-noise ratio, quality index and bias index. The methods were applied to a large cohort of clinical 3D FLAIR volumes over a test period of 9.5 months. The results were compared with phantom QA. Additionally, the effect of patient movement on the presented measures was studied.ResultsA connection between the presented clinical QA methods and scanner performance was observed: the values reacted to MRI equipment breakdowns that occurred during the study period. No apparent correlation with phantom QA results was found. The patient movement was found to have a significant effect on the resolution and contrast-to-noise ratio values.DiscussionQA based on clinical images provides a direct method for following MRI scanner performance. The methods could be used to detect problems, and potentially reduce scanner downtime. Furthermore, with the presented methodologies comparisons could be made between different sequences and imaging settings. In the future, an online QA system could recognize insufficient image quality and suggest an immediate re-scan.
引用
收藏
页码:689 / 699
页数:11
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