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用于临床磁共振成像的体素内不相干运动(IVIM)衍生灌注分数的快速测量。

Rapid measurement of intravoxel incoherent motion (IVIM) derived perfusion fraction for clinical magnetic resonance imaging.

作者信息

Meeus Emma M, Novak Jan, Dehghani Hamid, Peet Andrew C

机构信息

Physical Sciences of Imaging in Biomedical Sciences (PSIBS) Doctoral Training Centre, University of Birmingham, Birmingham, B15 2TT, UK.

Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, B15 2TT, UK.

出版信息

MAGMA. 2018 Apr;31(2):269-283. doi: 10.1007/s10334-017-0656-6. Epub 2017 Oct 26.

DOI:10.1007/s10334-017-0656-6
PMID:29075909
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5871652/
Abstract

OBJECTIVE

This study aimed to investigate the reliability of intravoxel incoherent motion (IVIM) model derived parameters D and f and their dependence on b value distributions with a rapid three b value acquisition protocol.

MATERIALS AND METHODS

Diffusion models for brain, kidney, and liver were assessed for bias, error, and reproducibility for the estimated IVIM parameters using b values 0 and 1000, and a b value between 200 and 900, at signal-to-noise ratios (SNR) 40, 55, and 80. Relative errors were used to estimate optimal b value distributions for each tissue scenario. Sixteen volunteers underwent brain DW-MRI, for which bias and coefficient of variation were determined in the grey matter.

RESULTS

Bias had a large influence in the estimation of D and f for the low-perfused brain model, particularly at lower b values, with the same trends being confirmed by in vivo imaging. Significant differences were demonstrated in vivo for estimation of D (P = 0.029) and f (P < 0.001) with [300,1000] and [500,1000] distributions. The effect of bias was considerably lower for the high-perfused models. The optimal b value distributions were estimated to be brain, kidney, and liver.

CONCLUSION

IVIM parameters can be estimated using a rapid DW-MRI protocol, where the optimal b value distribution depends on tissue characteristics and compromise between bias and variability.

摘要

目的

本研究旨在通过快速三b值采集协议,研究体素内不相干运动(IVIM)模型导出参数D和f的可靠性及其对b值分布的依赖性。

材料与方法

使用b值0和1000以及200至900之间的b值,在信噪比(SNR)为40、55和80的情况下,评估脑、肾和肝的扩散模型在估计IVIM参数时的偏差、误差和可重复性。使用相对误差来估计每种组织情况下的最佳b值分布。16名志愿者接受了脑部扩散加权磁共振成像(DW-MRI),并在灰质中确定了偏差和变异系数。

结果

对于低灌注脑模型,偏差对D和f的估计有很大影响,尤其是在较低的b值时,并在体内成像中得到了相同趋势的证实。在体内,使用[300,1000]和[500,1000]分布估计D(P = 0.029)和f(P < 0.001)时存在显著差异。对于高灌注模型,偏差的影响要低得多。估计的最佳b值分布分别为脑、肾和肝。

结论

可以使用快速DW-MRI协议估计IVIM参数,其中最佳b值分布取决于组织特征以及偏差和变异性之间的折衷。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d8ca/5871652/eb2b331021ef/10334_2017_656_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d8ca/5871652/069f9c97b592/10334_2017_656_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d8ca/5871652/593f49cac246/10334_2017_656_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d8ca/5871652/6aa354da78a0/10334_2017_656_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d8ca/5871652/064bc4428032/10334_2017_656_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d8ca/5871652/e772b418906e/10334_2017_656_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d8ca/5871652/b90b9260bfa1/10334_2017_656_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d8ca/5871652/237660cce861/10334_2017_656_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d8ca/5871652/eb2b331021ef/10334_2017_656_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d8ca/5871652/069f9c97b592/10334_2017_656_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d8ca/5871652/593f49cac246/10334_2017_656_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d8ca/5871652/6aa354da78a0/10334_2017_656_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d8ca/5871652/064bc4428032/10334_2017_656_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d8ca/5871652/e772b418906e/10334_2017_656_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d8ca/5871652/b90b9260bfa1/10334_2017_656_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d8ca/5871652/237660cce861/10334_2017_656_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d8ca/5871652/eb2b331021ef/10334_2017_656_Fig8_HTML.jpg

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