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采用MPnRAGE的三维运动校正T弛豫测量法。

Three-dimensional motion-corrected T relaxometry with MPnRAGE.

作者信息

Kecskemeti Steven, Alexander Andrew L

机构信息

Waisman Center, University of Wisconsin, Madison, WI, USA.

Department of Radiology, University of Wisconsin, Madison, WI, USA.

出版信息

Magn Reson Med. 2020 Nov;84(5):2400-2411. doi: 10.1002/mrm.28283. Epub 2020 Apr 17.

Abstract

PURPOSE

To test the performance of the MPnRAGE motion-correction algorithm on quantitative relaxometry estimates.

METHODS

Twelve children (9.4 ± 2.6 years, min = 6.5 years, max = 13.8 years) were imaged 3 times in a session without sedation. Stabilization padding was not used for the second and third scans. Quantitative T values were estimated in each voxel on images reconstructed with and without motion correction. Mean T values were assessed in various regions determined from automated segmentation algorithms. Statistical tests were performed on mean values and the coefficient of variation across the measurements. Accuracy of T estimates were determined by scanning the High Precision Devices (Boulder, CO) MRI system phantom with the same protocol.

RESULTS

The T values obtained with MPnRAGE agreed within 4% of the reference values of the High Precision Devices phantom. The best fit line was T (MPnRAGE) = 1.02 T (reference)-0.9 ms, R  = 0.9999. For in vivo studies, motion correction reduced the coefficients of variation of mean T values in whole-brain tissue regions determined by FSL FAST by 74% ± 7%, and subcortical regions determined by FIRST and FreeSurfer by 32% ± 21% and 33% ± 26%, respectively. Across all participants, the mean coefficients of variation ranged from 0.8% to 2.0% for subcortical regions and 0.6% ± 0.5% for cortical regions when motion correction was applied.

CONCLUSION

The MPnRAGE technique demonstrated highly accurate values in phantom measurements. When combined with retrospective motion correction, MPnRAGE demonstrated highly reproducible T values, even in participants who moved during the acquisition.

摘要

目的

测试MPnRAGE运动校正算法在定量弛豫测量估计中的性能。

方法

12名儿童(9.4±2.6岁,最小6.5岁,最大13.8岁)在未使用镇静剂的情况下,在一次检查中接受了3次成像。第二次和第三次扫描未使用稳定衬垫。在有和没有运动校正重建的图像上,估计每个体素的定量T值。在通过自动分割算法确定的各个区域中评估平均T值。对测量的平均值和变异系数进行统计检验。通过使用相同协议扫描高精度设备(科罗拉多州博尔德)MRI系统模型来确定T估计的准确性。

结果

用MPnRAGE获得的T值与高精度设备模型的参考值在4%以内相符。最佳拟合线为T(MPnRAGE)=1.02T(参考值)-0.9毫秒,R=0.9999。对于体内研究,运动校正使FSL FAST确定的全脑组织区域中平均T值的变异系数降低了74%±7%,FIRST和FreeSurfer确定的皮质下区域中平均T值的变异系数分别降低了32%±21%和33%±26%。在所有参与者中,应用运动校正时,皮质下区域的平均变异系数范围为0.8%至2.0%,皮质区域为0.6%±0.5%。

结论

MPnRAGE技术在模型测量中显示出高度准确的值。当与回顾性运动校正相结合时,MPnRAGE显示出高度可重复的T值,即使在采集过程中移动的参与者中也是如此。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1350/7396302/9619cd098484/nihms-1587567-f0001.jpg

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