Suppr超能文献

用于校正临床扩散加权磁共振成像中伪扩散体积分数的TE依赖性的扩展T2-IVIM模型。

Extended T2-IVIM model for correction of TE dependence of pseudo-diffusion volume fraction in clinical diffusion-weighted magnetic resonance imaging.

作者信息

Jerome N P, d'Arcy J A, Feiweier T, Koh D-M, Leach M O, Collins D J, Orton M R

机构信息

Cancer Research UK Cancer Imaging Centre, Division of Radiotherapy & Imaging, The Institute of Cancer Research, London, SM2 5NG, UK.

出版信息

Phys Med Biol. 2016 Dec 21;61(24):N667-N680. doi: 10.1088/1361-6560/61/24/N667. Epub 2016 Nov 28.

Abstract

The bi-exponential intravoxel-incoherent-motion (IVIM) model for diffusion-weighted MRI (DWI) fails to account for differential T s in the model compartments, resulting in overestimation of pseudodiffusion fraction f. An extended model, T2-IVIM, allows removal of the confounding echo-time (TE) dependence of f, and provides direct compartment T estimates. Two consented healthy volunteer cohorts (n  =  5, 6) underwent DWI comprising multiple TE/b-value combinations (Protocol 1: TE  =  62-102 ms, b  =  0-250 mms, 30 combinations. Protocol 2: 8 b-values 0-800 mms at TE  =  62 ms, with 3 additional b-values 0-50 mms at TE  =  80, 100 ms; scanned twice). Data from liver ROIs were fitted with IVIM at individual TEs, and with the T2-IVIM model using all data. Repeat-measures coefficients of variation were assessed for Protocol 2. Conventional IVIM modelling at individual TEs (Protocol 1) demonstrated apparent f increasing with longer TE: 22.4  ±  7% (TE  =  62 ms) to 30.7  ±  11% (TE  =  102 ms); T2-IVIM model fitting accounted for all data variation. Fitting of Protocol 2 data using T2-IVIM yielded reduced f estimates (IVIM: 27.9  ±  6%, T2-IVIM: 18.3  ±  7%), as well as T   =  42.1  ±  7 ms, 77.6  ±  30 ms for true and pseudodiffusion compartments, respectively. A reduced Protocol 2 dataset yielded comparable results in a clinical time frame (11 min). The confounding dependence of IVIM f on TE can be accounted for using additional b/TE images and the extended T2-IVIM model.

摘要

用于扩散加权磁共振成像(DWI)的双指数体素内不相干运动(IVIM)模型未考虑模型各部分的不同T值,导致伪扩散分数f被高估。一种扩展模型T2-IVIM,能够消除f对回波时间(TE)的混淆依赖性,并提供各部分T值的直接估计。两组经同意的健康志愿者队列(n = 5, 6)接受了包含多个TE/b值组合的DWI检查(方案1:TE = 62 - 102 ms,b = 0 - 250 mms²,30种组合。方案2:在TE = 62 ms时8个b值0 - 800 mms²,在TE = 80、100 ms时另有3个b值0 - 50 mms²;扫描两次)。肝脏感兴趣区(ROI)的数据在各个TE值下用IVIM进行拟合,并使用所有数据用T2-IVIM模型进行拟合。对方案2评估了重复测量变异系数。在各个TE值下进行传统IVIM建模(方案1)显示,随着TE延长,表观f增加:从22.4 ± 7%(TE = 62 ms)到30.7 ± 11%(TE = 102 ms);T2-IVIM模型拟合解释了所有数据变异。使用T2-IVIM对方案2的数据进行拟合得到的f估计值降低(IVIM:27.9 ± 6%,T2-IVIM:18.3 ± 7%),真实扩散和伪扩散部分的T值分别为42.1 ± 7 ms、77.6 ± 30 ms。一个缩减的方案2数据集在临床时间范围内(11分钟)产生了可比的结果。IVIM的f对TE的混淆依赖性可以通过额外的b/TE图像和扩展的T2-IVIM模型来解释。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7b23/5952260/3b1f9244b5bf/pmbaa4af3f01_hr.jpg

相似文献

3
Echo time dependence of biexponential and triexponential intravoxel incoherent motion parameters in the liver.
Magn Reson Med. 2022 Feb;87(2):859-871. doi: 10.1002/mrm.28996. Epub 2021 Aug 28.
4
Effects of Echo Time on IVIM Quantification of the Normal Prostate.
Sci Rep. 2018 Feb 7;8(1):2572. doi: 10.1038/s41598-018-19150-2.
6
On the Field Strength Dependence of Bi- and Triexponential Intravoxel Incoherent Motion (IVIM) Parameters in the Liver.
J Magn Reson Imaging. 2019 Dec;50(6):1883-1892. doi: 10.1002/jmri.26730. Epub 2019 Apr 3.
8
Bayesian intravoxel incoherent motion parameter mapping in the human heart.
J Cardiovasc Magn Reson. 2017 Nov 6;19(1):85. doi: 10.1186/s12968-017-0391-1.
9
Stroke assessment with intravoxel incoherent motion diffusion-weighted MRI.
NMR Biomed. 2016 Mar;29(3):320-8. doi: 10.1002/nbm.3467. Epub 2016 Jan 8.

引用本文的文献

2
Toward optimized intravoxel incoherent motion (IVIM) and compartmental T2 mapping in abdominal organs.
medRxiv. 2025 Jul 15:2025.07.14.25331475. doi: 10.1101/2025.07.14.25331475.
4
Effect of inaccurate b-values from imaging gradients on intravoxel incoherent motion.
Magn Reson Med. 2025 Oct;94(4):1514-1528. doi: 10.1002/mrm.30579. Epub 2025 Jun 2.
7
An explanation for the triphasic dependency of apparent diffusion coefficient (ADC) on T2 relaxation time: the multiple T2 compartments model.
Quant Imaging Med Surg. 2025 Apr 1;15(4):3779-3791. doi: 10.21037/qims-2025-195. Epub 2025 Mar 5.
9
MRI signal simulation of liver (diffusion derived 'vessel density') with multiple compartments diffusion model.
Quant Imaging Med Surg. 2025 Feb 1;15(2):1710-1718. doi: 10.21037/qims-2024-2693. Epub 2025 Jan 21.

本文引用的文献

1
3
T2 relaxation time is related to liver fibrosis severity.
Quant Imaging Med Surg. 2016 Apr;6(2):103-14. doi: 10.21037/qims.2016.03.02.
5
Body diffusion kurtosis imaging: Basic principles, applications, and considerations for clinical practice.
J Magn Reson Imaging. 2015 Nov;42(5):1190-202. doi: 10.1002/jmri.24985. Epub 2015 Jun 26.
6
Modelling DW-MRI data from primary and metastatic ovarian tumours.
Eur Radiol. 2015 Jul;25(7):2033-40. doi: 10.1007/s00330-014-3573-3. Epub 2015 Jan 21.
8
Optimization of intra-voxel incoherent motion imaging at 3.0 Tesla for fast liver examination.
J Magn Reson Imaging. 2015 May;41(5):1209-17. doi: 10.1002/jmri.24693. Epub 2014 Jul 11.
9
Optimization of b-value distribution for biexponential diffusion-weighted MR imaging of normal prostate.
J Magn Reson Imaging. 2014 May;39(5):1213-22. doi: 10.1002/jmri.24271. Epub 2013 Oct 11.
10
Diffusion-weighted MRI and optimal b-value for characterization of liver lesions.
Acta Radiol. 2014 Jun;55(5):532-42. doi: 10.1177/0284185113502017. Epub 2013 Aug 27.

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验