Cai Leon Y, Yang Qi, Hansen Colin B, Nath Vishwesh, Ramadass Karthik, Johnson Graham W, Conrad Benjamin N, Boyd Brian D, Begnoche John P, Beason-Held Lori L, Shafer Andrea T, Resnick Susan M, Taylor Warren D, Price Gavin R, Morgan Victoria L, Rogers Baxter P, Schilling Kurt G, Landman Bennett A
Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, USA.
Department of Electrical Engineering and Computer Science, Vanderbilt University, Nashville, TN, USA.
Magn Reson Med. 2021 Jul;86(1):456-470. doi: 10.1002/mrm.28678. Epub 2021 Feb 3.
Diffusion weighted MRI imaging (DWI) is often subject to low signal-to-noise ratios (SNRs) and artifacts. Recent work has produced software tools that can correct individual problems, but these tools have not been combined with each other and with quality assurance (QA). A single integrated pipeline is proposed to perform DWI preprocessing with a spectrum of tools and produce an intuitive QA document.
The proposed pipeline, built around the FSL, MRTrix3, and ANTs software packages, performs DWI denoising; inter-scan intensity normalization; susceptibility-, eddy current-, and motion-induced artifact correction; and slice-wise signal drop-out imputation. To perform QA on the raw and preprocessed data and each preprocessing operation, the pipeline documents qualitative visualizations, quantitative plots, gradient verifications, and tensor goodness-of-fit and fractional anisotropy analyses.
Raw DWI data were preprocessed and quality checked with the proposed pipeline and demonstrated improved SNRs; physiologic intensity ratios; corrected susceptibility-, eddy current-, and motion-induced artifacts; imputed signal-lost slices; and improved tensor fits. The pipeline identified incorrect gradient configurations and file-type conversion errors and was shown to be effective on externally available datasets.
The proposed pipeline is a single integrated pipeline that combines established diffusion preprocessing tools from major MRI-focused software packages with intuitive QA.
扩散加权磁共振成像（DWI）常常存在低信噪比（SNR）和伪影问题。近期的工作开发出了能够纠正个别问题的软件工具，但这些工具尚未相互结合，也未与质量保证（QA）相结合。本文提出了一个单一的集成流程，利用一系列工具进行DWI预处理，并生成一份直观的QA文档。
所提出的流程围绕FSL、MRTrix3和ANTs软件包构建，可进行DWI去噪；扫描间强度归一化；对由磁化率、涡流和运动引起的伪影进行校正；以及对切片方向的信号丢失进行插补。为了对原始数据和预处理后的数据以及每个预处理操作进行QA，该流程记录了定性可视化、定量绘图、梯度验证以及张量拟合优度和分数各向异性分析。
利用所提出的流程对原始DWI数据进行了预处理和质量检查，结果显示信噪比有所提高；生理强度比得到改善；对由磁化率、涡流和运动引起的伪影进行了校正；对信号丢失的切片进行了插补；张量拟合得到改善。该流程识别出了错误的梯度配置和文件类型转换错误，并在外部可用数据集上证明是有效的。
所提出的流程是一个单一的集成流程，它将来自主要专注于MRI的软件包中已有的扩散预处理工具与直观的QA相结合。
