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Bloch 模型能够使用来自不同供应商和站点的回顾性质子密度和 T2 加权图像进行稳健的 T2 映射。

Bloch modelling enables robust T2 mapping using retrospective proton density and T2-weighted images from different vendors and sites.

机构信息

Department of Biomedical Engineering, University of Alberta, 1098 RTF, Edmonton, AB T6G 2V2, Canada.

Department of Physics, University of Alberta, 4-181 CCIS, Edmonton, AB T6G 2E1, Canada.

出版信息

Neuroimage. 2021 Aug 15;237:118116. doi: 10.1016/j.neuroimage.2021.118116. Epub 2021 May 1.

Abstract

T2 quantification is commonly attempted by applying an exponential fit to proton density (PD) and transverse relaxation (T2)-weighted fast spin echo (FSE) images. However, inter-site studies have noted systematic differences between vendors in T2 maps computed via standard exponential fitting due to imperfect slice refocusing, different refocusing angles and transmit field (B1) inhomogeneity. We examine T2 mapping at 3T across 13 sites and two vendors in healthy volunteers from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database using both a standard exponential and a Bloch modelling approach. The standard exponential approach resulted in highly variable T2 values across different sites and vendors. The two-echo fitting method based on Bloch equation modelling of the pulse sequence with prior knowledge of the nominal refocusing angles, slice profiles, and estimated B1 maps yielded similar T2 values across sites and vendors by accounting for the effects of indirect and stimulated echoes. By modelling the actual refocusing angles used, T2 quantification from PD and T2-weighted images can be applied in studies across multiple sites and vendors.

摘要

T2 定量通常通过对质子密度(PD)和横向弛豫(T2)加权快速自旋回波(FSE)图像应用指数拟合来尝试。然而,由于切片重聚焦不完美、不同的重聚焦角度和发射场(B1)不均匀性,不同站点的研究已经注意到通过标准指数拟合计算的 T2 图谱之间存在系统差异。我们使用标准指数和布洛赫建模方法在阿尔茨海默病神经影像学倡议(ADNI)数据库中的 13 个站点和两个供应商的健康志愿者中检查了 3T 处的 T2 映射。标准指数方法导致不同站点和供应商的 T2 值变化很大。基于脉冲序列的布洛赫方程建模的双回波拟合方法,具有标称重聚焦角度、切片轮廓和估计的 B1 图谱的先验知识,通过考虑间接和受激回波的影响,在站点和供应商之间产生了相似的 T2 值。通过对实际使用的重聚焦角度进行建模,可以在多个站点和供应商的研究中应用 PD 和 T2 加权图像的 T2 定量。

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