Wu Ziyue, Chen Weiyi, Nayak Krishna S
Ming Hsieh Department of Electrical Engineering, University of Southern California, Los Angeles, California, United States of America.
Department of Biomedical Engineering, University of Southern California, Los Angeles, California, United States of America.
PLoS One. 2016 May 2;11(5):e0154711. doi: 10.1371/journal.pone.0154711. eCollection 2016.
To develop and evaluate a framework for simulating low-field proton-density weighted MRI acquisitions based on high-field acquisitions, which could be used to predict the minimum B0 field strength requirements for MRI techniques. This framework would be particularly useful in the evaluation of de-noising and constrained reconstruction techniques.
Given MRI raw data, lower field MRI acquisitions can be simulated based on the signal and noise scaling with field strength. Certain assumptions are imposed for the simulation and their validity is discussed. A validation experiment was performed using a standard resolution phantom imaged at 0.35 T, 1.5 T, 3 T, and 7 T. This framework was then applied to two sample proton-density weighted MRI applications that demonstrated estimation of minimum field strength requirements: real-time upper airway imaging and liver proton-density fat fraction measurement.
The phantom experiment showed good agreement between simulated and measured images. The SNR difference between simulated and measured was ≤ 8% for the 1.5T, 3T, and 7T cases which utilized scanners with the same geometry and from the same vendor. The measured SNR at 0.35T was 1.8- to 2.5-fold less than predicted likely due to unaccounted differences in the RF receive chain. The predicted minimum field strength requirements for the two sample applications were 0.2 T and 0.3 T, respectively.
Under certain assumptions, low-field MRI acquisitions can be simulated from high-field MRI data. This enables prediction of the minimum field strength requirements for a broad range of MRI techniques.
开发并评估一种基于高场采集来模拟低场质子密度加权磁共振成像(MRI)采集的框架,该框架可用于预测MRI技术所需的最小B0场强。此框架在评估去噪和约束重建技术方面将特别有用。
给定MRI原始数据,可基于随场强变化的信号和噪声缩放来模拟低场MRI采集。为模拟设定了某些假设,并讨论了其有效性。使用在0.35T、1.5T、3T和7T下成像的标准分辨率体模进行了验证实验。然后将该框架应用于两个示例质子密度加权MRI应用,展示了对最小场强要求的估计:实时上呼吸道成像和肝脏质子密度脂肪分数测量。
体模实验表明模拟图像与测量图像之间具有良好的一致性。对于使用相同几何结构且来自同一供应商的扫描仪的1.5T、3T和7T情况,模拟与测量之间的信噪比(SNR)差异≤8%。0.35T时测量的SNR比预测值低1.8至2.5倍,这可能是由于射频接收链中未考虑的差异所致。两个示例应用预测的最小场强要求分别为0.2T和0.3T。
在某些假设下,可从高场MRI数据模拟低场MRI采集。这使得能够预测广泛的MRI技术所需的最小场强。