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理解弥散加权磁共振成像分析:良性乳腺病变队列中弥散模型的可重复性和性能。

Understanding diffusion-weighted MRI analysis: Repeatability and performance of diffusion models in a benign breast lesion cohort.

机构信息

Department of Circulation and Medical Imaging, Norwegian University of Science and Technology (NTNU), Trondheim, Norway.

Clinic of Radiology and Nuclear Medicine, St. Olavs Hospital, Trondheim, Norway.

出版信息

NMR Biomed. 2021 Jul;34(7):e4508. doi: 10.1002/nbm.4508. Epub 2021 Mar 18.

Abstract

Diffusion-weighted MRI (DWI) is an important tool for oncology research, with great clinical potential for the classification and monitoring of breast lesions. The utility of parameters derived from DWI, however, is influenced by specific analysis choices. The purpose of this study was to critically evaluate repeatability and curve-fitting performance of common DWI signal representations, for a prospective cohort of patients with benign breast lesions. Twenty informed, consented patients with confirmed benign breast lesions underwent repeated DWI (3 T) using: sagittal single-shot spin-echo echo planar imaging, bipolar encoding, TR/TE: 11,600/86 ms, FOV: 180 x 180 mm, matrix: 90 x 90, slices: 60 x 2.5 mm, iPAT: GRAPPA 2, fat suppression, and 13 b-values: 0-700 s/mm . A phase-reversed scan (b = 0 s/mm ) was acquired for distortion correction. Voxel-wise repeat-measures coefficients of variation (CoVs) were derived for monoexponential (apparent diffusion coefficient [ADC]), biexponential (intravoxel incoherent motion: f, D, D*) and stretched exponential (α, DDC) across the parameter histograms for lesion regions of interest (ROIs). Goodness-of-fit for each representation was assessed by Bayesian information criterion. The volume of interest (VOI) definition was repeatable (CoV 13.9%). Within lesions, and across both visits and the cohort, there was no dominant best-fit model, with all representations giving the best fit for a fraction of the voxels. Diffusivity measures from the signal representations (ADC, D, DDC) all showed good repeatability (CoV < 10%), whereas parameters associated with pseudodiffusion (f, D*) performed poorly (CoV > 50%). The stretching exponent α was repeatable (CoV < 12%). This pattern of repeatability was consistent over the central part of the parameter percentiles. Assumptions often made in diffusion studies about analysis choices will influence the detectability of changes, potentially obscuring useful information. No single signal representation prevails within or across lesions, or across repeated visits; parameter robustness is therefore a critical consideration. Our results suggest that stretched exponential representation is more repeatable than biexponential, with pseudodiffusion parameters unlikely to provide clinically useful biomarkers.

摘要

扩散加权磁共振成像(DWI)是肿瘤学研究的重要工具,在乳腺病变的分类和监测方面具有巨大的临床潜力。然而,来自 DWI 的参数的应用受到特定分析选择的影响。本研究的目的是批判性地评估常见 DWI 信号表示的可重复性和曲线拟合性能,该研究基于一组经证实的良性乳腺病变患者的前瞻性队列。二十名知情同意的良性乳腺病变患者接受了重复的 DWI(3 T)检查:矢状位单次激发自旋回波回波平面成像,双极编码,TR/TE:11,600/86 ms,FOV:180 x 180 mm,矩阵:90 x 90,切片:60 x 2.5 mm,iPAT:GRAPPA 2,脂肪抑制,以及 13 个 b 值:0-700 s/mm。采集相位反转扫描(b = 0 s/mm)用于失真校正。为了获取病变感兴趣区(ROI)的参数直方图的单指数(表观扩散系数 [ADC])、双指数(体素内不相干运动:f、D、D*)和拉伸指数(α、DDC)的重复测量系数变异(CoV)。通过贝叶斯信息准则评估每种表示的拟合优度。感兴趣区(VOI)的定义具有可重复性(CoV 13.9%)。在病变内,以及在两次就诊和整个队列中,没有主导的最佳拟合模型,所有表示都为一部分体素提供了最佳拟合。来自信号表示的扩散测量值(ADC、D、DDC)均表现出良好的可重复性(CoV < 10%),而与伪扩散相关的参数(f、D*)表现不佳(CoV > 50%)。拉伸指数 α 具有可重复性(CoV < 12%)。这种可重复性模式在参数百分位数的中心部分保持一致。扩散研究中关于分析选择的假设将影响变化的可检测性,可能会掩盖有用的信息。在病变内或病变之间,或在重复就诊时,没有一种单一的信号表示占主导地位;因此,参数稳健性是一个关键考虑因素。我们的结果表明,拉伸指数表示比双指数表示更具可重复性,伪扩散参数不太可能提供有临床价值的生物标志物。

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