Institute for Circulation and Diagnostic Imaging, Norwegian University of Science and Technology (NTNU), Trondheim, Norway.
Department of Radiology and Nuclear Medicine, St. Olav's University Hospital, Trondheim, Norway.
Methods Mol Biol. 2021;2216:611-635. doi: 10.1007/978-1-0716-0978-1_37.
Analysis of renal diffusion-weighted imaging (DWI) data to derive markers of tissue properties requires careful consideration of the type, extent, and limitations of the acquired data. Alongside data quality and general suitability for quantitative analysis, choice of diffusion model, fitting algorithm, and processing steps can have consequences for the precision, accuracy, and reliability of derived diffusion parameters. Here we introduce and discuss important steps for diffusion-weighted image processing, and in particular give example analysis protocols and pseudo-code for analysis using the apparent diffusion coefficient (ADC) and intravoxel incoherent motion (IVIM) models. Following an overview of general principles, we provide details of optional steps, and steps for validation of results. Illustrative examples are provided, together with extensive notes discussing wider context of individual steps, and notes on potential pitfalls.This publication is based upon work from the COST Action PARENCHIMA, a community-driven network funded by the European Cooperation in Science and Technology (COST) program of the European Union, which aims to improve the reproducibility and standardization of renal MRI biomarkers. This analysis protocol chapter is complemented by two separate chapters describing the basic concepts and experimental procedure.
分析肾脏扩散加权成像（DWI）数据以得出组织特性标志物，需要仔细考虑所获取数据的类型、程度和局限性。除了数据质量和一般适合定量分析外，扩散模型、拟合算法和处理步骤的选择也会对得出的扩散参数的精度、准确性和可靠性产生影响。在这里，我们介绍并讨论了扩散加权图像处理的重要步骤，特别是给出了使用表观扩散系数（ADC）和体素内不相干运动（IVIM）模型进行分析的示例分析方案和伪代码。在概述一般原则之后，我们提供了可选步骤的详细信息，以及验证结果的步骤。提供了说明性示例，并附有关于各个步骤的更广泛背景的详细说明，以及关于潜在陷阱的说明。本出版物基于 COST 行动 PARENCHIMA 的工作，该行动是一个由社区驱动的网络，由欧盟的欧洲科学与技术合作组织（COST）计划资助，旨在提高肾脏 MRI 生物标志物的重现性和标准化。本分析方案章节由另外两个章节补充，描述了基本概念和实验程序。
