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利用分段体素内不相干运动模型拟合优化扩散系数和灌注分数的 b 值方案。

Optimization of b-value schemes for estimation of the diffusion coefficient and the perfusion fraction with segmented intravoxel incoherent motion model fitting.

机构信息

Department of Radiation Physics, Institute of Clinical Sciences, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.

Department of Medical Physics and Biomedical Engineering, Sahlgrenska University Hospital, Gothenburg, Sweden.

出版信息

Magn Reson Med. 2019 Oct;82(4):1541-1552. doi: 10.1002/mrm.27826. Epub 2019 May 31.

Abstract

PURPOSE

Intravoxel incoherent motion (IVIM) modeling for estimation of the diffusion coefficient (D) and perfusion fraction (f) is increasingly popular, but no consensus on standard protocols exists. This study provides a framework for optimization of b-value schemes for reduced estimation uncertainty of D and f from segmented model fitting.

THEORY

Analytical expressions for uncertainties of D and f from segmented model fitting were derived as Cramer-Rao lower bounds (CRLBs).

METHODS

Optimized b-value schemes were obtained for 3 to 12 acquisitions and in the limit of infinitely many acquisitions through constrained minimization of the CRLBs, with b-values constrained to be 0 or 200 to 800 s/mm . The optimized b-value scheme with eight acquisitions was compared with b-values linearly distributed in the allowed range using simulations and in vivo liver data from seven healthy volunteers.

RESULTS

All optimized b-value schemes contained exactly three unique b-values regardless of the total number of acquisitions (0, 200, and 800 s/mm ) with repeated acquisitions distributed approximately as 1:2:2. Compared with linearly distributed b-values, the variability of estimates of D and f was reduced by approximately 30% as seen both in simulations and in repeated in vivo measurements.

CONCLUSION

The uncertainty of IVIM D and f estimates can be reduced by the use of optimized b-value schemes.

摘要

目的

体素内不相干运动(IVIM)模型用于估计扩散系数(D)和灌注分数(f)越来越受欢迎,但目前尚无关于标准方案的共识。本研究提供了一个框架,用于优化分段模型拟合中 D 和 f 的估计不确定性的 b 值方案。

理论

从分段模型拟合中推导出 D 和 f 的不确定度的解析表达式,作为克拉美-罗下限(CRLB)。

方法

通过对 CRLB 的约束最小化,获得了 3 到 12 次采集以及在无限次采集的极限情况下的优化 b 值方案,其中 b 值被约束为 0 或 200 到 800 s/mm 。使用模拟和来自 7 名健康志愿者的体内肝脏数据,比较了具有 8 次采集的优化 b 值方案和在线性允许范围内分布的 b 值方案。

结果

所有优化的 b 值方案无论总采集次数(0、200 和 800 s/mm )如何,都包含完全相同的三个唯一 b 值,重复采集的分布大致为 1:2:2。与线性分布的 b 值相比,D 和 f 的估计值的可变性在模拟和重复体内测量中都降低了约 30%。

结论

通过使用优化的 b 值方案,可以降低 IVIM D 和 f 估计的不确定性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3245/6772171/fbe90dea5580/MRM-82-1541-g001.jpg

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