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首页> 外文期刊>Medical Imaging, IEEE Transactions on >Robustness of Quantitative Compressive Sensing MRI: The Effect of Random Undersampling Patterns on Derived Parameters for DCE- and DSC-MRI
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Robustness of Quantitative Compressive Sensing MRI: The Effect of Random Undersampling Patterns on Derived Parameters for DCE- and DSC-MRI

机译：定量压敏MRI的鲁棒性：随机欠采样模式对DCE-和DSC-MRI派生参数的影响

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摘要

Compressive sensing (CS) in Cartesian magnetic resonance imaging (MRI) involves random partial Fourier acquisitions. The random nature of these acquisitions can lead to variance in reconstruction errors. In quantitative MRI, variance in the reconstructed images translates to an uncertainty in the derived quantitative maps. We show that for a spatially regularized 2 $times$-accelerated human breast CS DCE-MRI acquisition with a 192$^{2}$ matrix size, the coefficients of variation (CoVs) in voxel-level parameters due to the random acquisition are 1.1%, 0.96%, and 1.5% for the tissue parameters $K^{rm trans}$, $v_{rm e}$, and $v_{rm p}$, with an average error in the mean of $-$2.5%, $-$2.0%, and $-$3.7%, respectively. Only 5% of the acquisition schemes had a systematic underestimation larger than than 4.2%, 3.7%, and 6.1%, respectively. For a 2$times$ -accelerated rat brain CS DSC-MRI study with a $64^{2}$ matrix size, the CoVs due to the random acquisition were 19%, 9.5%, and 15% for the cerebral blood flow and blood volume and mean transit time, respectively, and the average errors in the tumor mean were 9.2%, 0.49%, and $-$7.0%, respectively. Across 11 $thinspace$000 different -nS reconstructions, we saw no outliers in the distribution of parameters, suggesting that, despite the random undersampling schemes, CS accelerated quantitative MRI may have a predictable level of performance.
机译：笛卡尔磁共振成像（MRI）中的压缩感测（CS）涉及随机的部分傅里叶采集。这些采集的随机性可能导致重建误差的变化。在定量MRI中，重建图像中的方差转化为导出的定量图中的不确定性。我们显示，对于具有192 $ ^ {2} $矩阵大小的空间正规化2次×倍加速的人乳房CS DCE-MRI采集，由于随机采集而导致的体素级参数的变异系数（CoV）为组织参数$ K ^ {rm trans} $，$ v_ {rm e} $和$ v_ {rm p} $的组织参数分别为1.1％，0.96％和1.5％，平均误差为$-$ 2.5 ％，$-$ 2.0％和$-$ 3.7％。只有5％的收购方案的系统低估分别超过4.2％，3.7％和6.1％。对于矩阵大小为64 ^ {2} $的2倍加速的大鼠脑CS DSC-MRI研究，由于随机采集而产生的CoV分别为脑血流量和血液的19％，9.5％和15％肿瘤的平均体积和平均通过时间分别为9.2％，0.49％和$-$ 7.0％。在11个$ thinspace $ 000不同的-nS重构中，我们没有看到参数分布方面的异常值，这表明，尽管采用了随机的欠采样方案，CS加速定量MRI的性能仍可预测。

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