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数量与质量:规范性开放获取神经影像学数据库。

Quantity and quality: Normative open-access neuroimaging databases.

机构信息

Integrative Model-Based Cognitive Neuroscience Research Unit, University of Amsterdam, Amsterdam, The Netherlands.

Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany.

出版信息

PLoS One. 2021 Mar 11;16(3):e0248341. doi: 10.1371/journal.pone.0248341. eCollection 2021.

Abstract

The focus of this article is to compare twenty normative and open-access neuroimaging databases based on quantitative measures of image quality, namely, signal-to-noise (SNR) and contrast-to-noise ratios (CNR). We further the analysis through discussing to what extent these databases can be used for the visualization of deeper regions of the brain, such as the subcortex, as well as provide an overview of the types of inferences that can be drawn. A quantitative comparison of contrasts including T1-weighted (T1w) and T2-weighted (T2w) images are summarized, providing evidence for the benefit of ultra-high field MRI. Our analysis suggests a decline in SNR in the caudate nuclei with increasing age, in T1w, T2w, qT1 and qT2* contrasts, potentially indicative of complex structural age-dependent changes. A similar decline was found in the corpus callosum of the T1w, qT1 and qT2* contrasts, though this relationship is not as extensive as within the caudate nuclei. These declines were accompanied by a declining CNR over age in all image contrasts. A positive correlation was found between scan time and the estimated SNR as well as a negative correlation between scan time and spatial resolution. Image quality as well as the number and types of contrasts acquired by these databases are important factors to take into account when selecting structural data for reuse. This article highlights the opportunities and pitfalls associated with sampling existing databases, and provides a quantitative backing for their usage.

摘要

本文的重点是比较二十个规范的和开放获取的神经影像学数据库,基于图像质量的定量测量,即信噪比(SNR)和对比噪声比(CNR)。我们通过讨论这些数据库在多大程度上可以用于可视化大脑的更深区域,如皮质下区域,以及提供可以得出的推断类型的概述,进一步分析。对包括 T1 加权(T1w)和 T2 加权(T2w)图像在内的对比度进行了定量比较,为超高场 MRI 的优势提供了证据。我们的分析表明,在 T1w、T2w、qT1 和 qT2对比度中,尾状核的 SNR 随着年龄的增长而下降,这可能表明复杂的结构与年龄相关的变化。在 T1w、qT1 和 qT2对比度中,胼胝体也发现了类似的下降趋势,但这种关系不如尾状核广泛。所有图像对比度的 SNR 随年龄的下降都伴随着 CNR 的下降。在估计 SNR 时,扫描时间与 SNR 呈正相关,而在空间分辨率时,扫描时间与 SNR 呈负相关。在选择可重复使用的结构数据时,图像质量以及这些数据库中获取的对比度的数量和类型是需要考虑的重要因素。本文强调了从现有数据库中采样所涉及的机会和陷阱,并为其使用提供了定量支持。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bc85/7951909/4c4f78d0c827/pone.0248341.g001.jpg

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