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估计和考虑 MRI 扫描仪变化对纵向全脑容量变化测量的影响。

Estimating and accounting for the effect of MRI scanner changes on longitudinal whole-brain volume change measurements.

机构信息

Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada.

Lerner Research Institute, Cleveland Clinic, Cleveland, OH, USA.

出版信息

Neuroimage. 2019 Jan 1;184:555-565. doi: 10.1016/j.neuroimage.2018.09.062. Epub 2018 Sep 22.

DOI:10.1016/j.neuroimage.2018.09.062
PMID:30253207
Abstract

OBJECTIVE

Longitudinal MRI studies are often subjected to mid-study scanner changes, which may alter image characteristics such as contrast, signal-to-noise ratio, contrast-to-noise ratio, intensity non-uniformity and geometric distortion. Measuring brain volume loss under these conditions can render the results potentially unreliable across the timepoint of the change. Estimating and accounting for this effect may improve the reliability of estimates of brain atrophy rates.

METHODS

We analyzed 237 subjects who were scanned at 1.5 T for the Alzheimer's Disease Neuroimaging Initiative (ADNI) study and were subject to intra-vendor or inter-vendor scanner changes during follow-up (up to 8 years). Sixty-three subjects scanned on GE Signa HDx and HDxt platforms were also subject to a T1-weighted sequence change from Magnetization Prepared Rapid Gradient Echo (MP-RAGE) to Fast Spoiled Gradient Echo with IR Preparation (IR-FSPGR), as part of the transition from ADNI-1 to ADNI-2/GO. Two-timepoint percentage brain volume changes (PBVCs) between the baseline "screening" and the follow-up scans were calculated using SIENA. A linear mixed-effects model with subject-specific random slopes and intercepts was applied to estimate the fixed effects of scanner hardware changes on the PBVC measures. The same model also included a term to estimate the fixed effects of the T1-weighted sequence change.

RESULTS

Different hardware upgrade or change combinations led to different offsets in the PBVC (SE; p): Philips Intera to Siemens Avanto, -1.81% (0.30; p < 0.0001); GE Genesis Signa to Philips Intera, 0.99% (0.47, p = 0.042); GE Signa Excite to Signa HDx, 0.33% (0.095, p = 0.0005); GE Signa Excite to Signa HDxt, -0.023% (0.23, p = 0.92); GE Signa Excite to Signa HDx to Signa HDxt, 0.25% (0.095, p = 0.010) and 0.27% (0.16, p = 0.098), respectively; GE Signa HDx to Signa HDxt, -0.24% (0.25, p = 0.34); Siemens Symphony to Symphony TIM, -0.39% (0.16; p = 0.019). The sequence change from MP-RAGE to IR-SPGR was associated with an average -1.63% (0.12; p < 0.0001) change.

CONCLUSION

Inter-vendor scanner changes generally led to greater effects on PBVC measurements than did intra-vendor scanner upgrades. The effect of T1-weighted sequence change was comparable to that of the inter-vendor scanner changes. Inclusion of the corrective fixed-effects terms for the scanner hardware and T1-weighted sequence changes yielded better model goodness-of-fits, and thus, potentially more reliable estimates of whole-brain atrophy rates.

摘要

目的

纵向 MRI 研究经常会受到研究中期扫描仪变化的影响,这可能会改变对比度、信噪比、对比噪声比、强度不均匀性和几何变形等图像特征。在这些条件下测量脑体积损失可能会导致在变化的时间点上结果不可靠。估计和考虑这种影响可能会提高脑萎缩率估计的可靠性。

方法

我们分析了 237 名在 ADNI 研究中以 1.5T 扫描的受试者,他们在随访期间(最长 8 年)经历了内部供应商或外部供应商的扫描仪变化。63 名在 GE Signa HDx 和 HDxt 平台上扫描的受试者也经历了从磁化准备快速梯度回波(MP-RAGE)到带 IR 准备的快速扰相梯度回波(IR-FSPGR)的 T1 加权序列变化,这是从 ADNI-1 到 ADNI-2/GO 的过渡的一部分。使用 SIENA 计算基线“筛选”和随访扫描之间的两次脑容量百分比变化(PBVC)。应用具有个体随机斜率和截距的线性混合效应模型来估计扫描仪硬件变化对 PBVC 测量的固定影响。相同的模型还包括一个用于估计 T1 加权序列变化的固定影响的项。

结果

不同的硬件升级或变化组合导致 PBVC 出现不同的偏移量(SE;p):飞利浦 Intera 到西门子 Avanto,-1.81%(0.30;p<0.0001);GE Genesis Signa 到飞利浦 Intera,0.99%(0.47,p=0.042);GE Signa Excite 到 Signa HDx,0.33%(0.095,p=0.0005);GE Signa Excite 到 Signa HDxt,-0.023%(0.23,p=0.92);GE Signa Excite 到 Signa HDx 到 Signa HDxt,0.25%(0.095,p=0.010)和 0.27%(0.16,p=0.098);GE Signa HDx 到 Signa HDxt,-0.24%(0.25,p=0.34);西门子 Symphony 到 Symphony TIM,-0.39%(0.16;p=0.019)。从 MP-RAGE 到 IR-SPGR 的序列变化与平均-1.63%(0.12;p<0.0001)的变化相关。

结论

与内部供应商扫描仪升级相比,外部供应商扫描仪变化通常会对 PBVC 测量产生更大的影响。T1 加权序列变化的影响与外部供应商扫描仪变化相当。包括扫描仪硬件和 T1 加权序列变化的校正固定效应项可提高模型拟合优度,从而更可靠地估计全脑萎缩率。

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