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基于血管血氧水平依赖性功能磁共振成像(VASO)数据的北欧去噪法。

NORDIC denoising on VASO data.

作者信息

Knudsen Lasse, Vizioli Luca, De Martino Federico, Faes Lonike K, Handwerker Daniel A, Moeller Steen, Bandettini Peter A, Huber Laurentius

机构信息

Center of Functionally Integrative Neuroscience (CFIN), Aarhus University, Aarhus, Denmark.

Sino-Danish Center for Education and Research (SDC), University of Chinese Academy of Sciences, Beijing, China.

出版信息

Front Neurosci. 2025 Jan 6;18:1499762. doi: 10.3389/fnins.2024.1499762. eCollection 2024.

Abstract

The use of submillimeter resolution functional magnetic resonance imaging (fMRI) is increasing in popularity due to the prospect of studying human brain activation non-invasively at the scale of cortical layers and columns. This method, known as laminar fMRI, is inherently signal-to-noise ratio (SNR)-limited, especially at lower field strengths, with the dominant noise source being of thermal origin. Furthermore, laminar fMRI is challenged with signal displacements due to draining vein effects in conventional gradient-echo blood oxygen level-dependent (BOLD) imaging contrasts. fMRI contrasts such as cerebral blood volume (CBV)-sensitive vascular space occupancy (VASO) sequences have the potential to mitigate draining vein effects. However, VASO comes along with another reduction in detection sensitivity. NOise Reduction with DIstribution Corrected (NORDIC) PCA (principal component analysis) is a denoising technique specifically aimed at suppressing thermal noise, which has proven useful for increasing the SNR of high-resolution functional data. While NORDIC has been examined for BOLD acquisitions, its application to VASO data has been limited, which was the focus of the present study. We present a preliminary analysis to evaluate NORDIC's capability to suppress thermal noise while preserving the VASO signal across a wide parameter space at 3T. For the data presented here, with a proper set of parameters, NORDIC reduced thermal noise with minimal bias on the underlying signal and preserved spatial resolution. Denoising performance was found to vary with different implementation strategies and parameter choices, for which we provide recommendations. We conclude that when applied properly, NORDIC has the potential to overcome the sensitivity limitations of laminar-specific VASO fMRI. Since very few groups currently have 3T VASO data, by sharing our analysis and code, we can compile and compare the effects of NORDIC across a broader range of acquisition parameters and study designs. Such a communal effort will help develop robust recommendations that will increase the utility of laminar fMRI at lower field strengths.

摘要

由于有望在皮质层和柱状结构尺度上非侵入性地研究人类大脑激活,亚毫米分辨率功能磁共振成像(fMRI)的应用越来越广泛。这种方法被称为层流fMRI,其本质上受限于信噪比(SNR),尤其是在较低场强下,主要噪声源是热噪声。此外,在传统梯度回波血氧水平依赖(BOLD)成像对比中,层流fMRI还受到引流静脉效应导致的信号位移的挑战。诸如脑血容量(CBV)敏感的血管空间占据(VASO)序列等fMRI对比有减轻引流静脉效应的潜力。然而,VASO会带来检测灵敏度的另一种降低。分布校正降噪(NORDIC)主成分分析(PCA)是一种专门用于抑制热噪声的去噪技术,已被证明对提高高分辨率功能数据的SNR有用。虽然NORDIC已被用于BOLD采集,但它在VASO数据中的应用有限,这是本研究的重点。我们进行了一项初步分析,以评估NORDIC在3T下跨广泛参数空间抑制热噪声同时保留VASO信号的能力。对于此处呈现的数据,通过一组适当的参数,NORDIC降低了热噪声,对基础信号的偏差最小,并保留了空间分辨率。发现去噪性能因不同的实现策略和参数选择而有所不同,我们为此提供了建议。我们得出结论,当正确应用时,NORDIC有潜力克服层流特异性VASO fMRI的灵敏度限制。由于目前很少有研究小组拥有3T VASO数据,通过分享我们的分析和代码,我们可以汇总并比较NORDIC在更广泛的采集参数和研究设计中的效果。这样的共同努力将有助于制定强有力的建议,从而提高低场强下层流fMRI的效用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fc25/11743533/81b168c169b7/fnins-18-1499762-g001.jpg

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