摘要
目的:评估磁共振成像(MRI)设备的性能状态,实施MRI设备的质量保证和质量控制方案,为诊断疾病提供优质的图像。方法:将模糊数学和信息熵方法引入MRI设备的性能分析中,通过分析MRI设备的图像质量综合评价指标数据,建立多参数的MRI设备性能评估模型。选择医院门诊楼内MRI设备(MRI设备-1)和医技楼MRI设备(MRI设备-2),利用熵权模糊评价方法分别将采集的头线圈和体线圈成像两组参数处理成为MRI设备性能状态指标,并对两组6个月内检测的状态指标数据进行信噪比(SNR)、均匀度、层厚、高对比度空间分辨率和几何畸变率5项性能指标一致性检验,验证质量控制方案的有效性。结果:头线圈和体线圈成像两组数据的一致性较高,验证了质量控制方案的有效性;两组6个月内的测试样本对模型分析结果与实际维修情况一致。结论:建立的多指标参数的评估模型,可为系统基于状态的维护(CBM)决策过程夯实基础,并可提高MRI设备性能状态评估的准确性,有助于制定最优MRI设备维护维修计划,提高MRI设备故障排除和维护的水平,为临床诊断的准确性提供保障。
Objective:To assess the performance states of magnetic resonance imaging(MRI)equipment and implement the schemes of quality assurance and quality control of MRI equipment so as to provide the images with high quality for the diagnosis of disease.Methods:The methods of fuzzy mathematics and the information entropy were introduced into the performance analysis of MRI equipment to establish performance assessment mode of MRI equipment with multi-parameter through analyze the data of comprehensive evaluation indicator of image quality of MRI equipment.The MRI equipment(MRI equipment-1)in outpatient build and that(MRI equipment-2)in medical technique build of hospital were selected respectively.The entropy weight fuzzy evaluation was adopted to process the selected parameters of two groups included head coil and body coil as the indicators of performance states of MRI equipment,respectively.And the data of the tested state indicators of two groups within 6 months were used to implement consistency check for 5 performance indicators included signal-noise ratio(SNR),evenness,layer thickness,high contrast spatial resolution and geometric distortion rate,so as to verify the validity of the scheme of quality control.Results:The consistencies of the two groups of data of head coil and body coil imaging were higher,and the validity of the QC scheme was verified.The tested samples of two groups within 6 months were consistent with the analysis results of mode and the condition of actual maintenance.Conclusion:The established evaluation mode with multi-parameter can lay a solid foundation for the decision-making process of condition-based maintenance(CBM)of system,and it can improve the accuracy of performance condition assessment of MRI equipment.It is contribute to formulate the optimal maintenance schedule for MRI equipment,and enhance the levels of trouble removal and maintenance for MRI equipment,and provide guarantee for the accuracy of clinical diagnosis.
作者
储呈晨
季智勇
李斌
CHU Cheng-chen;JI Zhi-yong;LI Bin(Department of Medical Equipment,Shanghai Sixth People’s Hospital Affiliated to Shanghai Jiao Tong University,Shanghai 201306,China;Institute for Hospital Management,Academy for Development and Research of Hospital in China,Shanghai Jiao Tong University,Shanghai 200233,China;不详)
出处
《中国医学装备》
2022年第2期40-45,共6页
China Medical Equipment
基金
国家重点研发计划(2019YFC0121805)“大数据分析和战略规划支撑应用研究”
国家重点研发计划(2016YFC0106803)“工程性能评价”。
关键词
磁共振成像设备
性能评估
信息熵
质量控制(QC)
Magnetic resonance imaging(MRI)
Performance assessment
Information entropy
Quality control(QC)
