Denoising of diffusion MRI in the cervical spinal cord - effects of denoising strategy and acquisition on intra-cord contrast, signal modeling, and feature conspicuity.
Denoising of diffusion MRI in the cervical spinal cord - effects of denoising strategy and acquisition on intra-cord contrast, signal modeling, and feature conspicuity.
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DOI：
10.1016/j.neuroimage.2022.119826
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发表时间：
2023-02-01
期刊：
影响因子：
5.7
通讯作者：
O'Grady KP
中科院分区：
文献类型：
--
作者：
Schilling KG;Fadnavis S;Batson J;Visagie M;Combes AJE;By S;McKnight CD;Bagnato F;Garyfallidis E;Landman BA;Smith SA;O'Grady KP
定量扩散MRI（dMRI）是一种很有前途的技术，用于评估脊髓在健康和疾病。然而，低信噪比（SNR）可能会妨碍这些图像的解释和量化。本研究的目的是评估几种dMRI去噪方法提高脊髓定量扩散MRI质量、可靠性和准确性的能力。我们评估了三种去噪方法（非局部均值、Marchenko-Pastur PCA和新提出的Patch 2Self算法），并进行五项实验以验证临床质量和常用dMRI采集的去噪性能：1）评估去噪误差和偏倚的体模实验; 2）用于噪声残差定性和定量评估的多供应商、多采集开放实验; 3）估计参数图的不确定性的自举实验; 4）多发性硬化组中脊髓病变显著性的评估;以及5）用于高级参数多室建模的去噪的评估。我们发现，所有方法都提高了单个扩散加权图像（DWI）中MS病变的信噪比和显著性，但MPPCA和Patch 2Self擅长提高扩散加权图像的质量和脊髓内对比度-消除由于热噪声引起的信号波动，同时提高扩散参数估计的精度，即使使用很少的DWI（即，16-32）典型的临床采集。这些去噪方法有望促进脊髓中可靠的扩散观察和测量，以研究生物和病理过程。
Quantitative diffusion MRI (dMRI) is a promising technique for evaluating the spinal cord in health and disease. However, low signal-to-noise ratio (SNR) can impede interpretation and quantification of these images. The purpose of this study is to evaluate several dMRI denoising approaches on their ability to improve the quality, reliability, and accuracy of quantitative diffusion MRI of the spinal cord. We evaluate three denoising approaches (Non-Local Means, Marchenko-Pastur PCA, and a newly proposed Patch2Self algorithm) and conduct five experiments to validate the denoising performance on clinical-quality and commonly-acquired dMRI acquisitions: 1) a phantom experiment to assess denoising error and bias; 2) a multi-vendor, multi-acquisition open experiment for both qualitative and quantitative evaluation of noise residuals; 3) a bootstrapping experiment to estimate uncertainty of parametric maps; 4) an assessment of spinal cord lesion conspicuity in a multiple sclerosis group; and 5) an evaluation of denoising for advanced parametric multi-compartment modeling. We find that all methods improve signal-to-noise ratio and conspicuity of MS lesions in individual diffusion weighted images (DWIs), but MPPCA and Patch2Self excel at improving the quality and intra-cord contrast of diffusion weighted images – removing signal fluctuations due to thermal noise while improving precision of estimation of diffusion parameters even with very few DWIs (i.e., 16–32) typical of clinical acquisitions. These denoising approaches hold promise for facilitating reliable diffusion observations and measurements in the spinal cord to investigate biological and pathological processes.
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影响因子：
3.5
作者：
Garyfallidis E;Brett M;Amirbekian B;Rokem A;van der Walt S;Descoteaux M;Nimmo-Smith I;Dipy Contributors
通讯作者：
Dipy Contributors
影响因子：
3.3
作者：
Grussu F;Ianuş A;Tur C;Prados F;Schneider T;Kaden E;Ourselin S;Drobnjak I;Zhang H;Alexander DC;Gandini Wheeler-Kingshott CAM
通讯作者：
Gandini Wheeler-Kingshott CAM
影响因子：
4
作者：
RUDIN, LI;OSHER, S;FATEMI, E
通讯作者：
FATEMI, E
影响因子：
3
作者：
Grussu, Francesco;Schneidera, Torben;Alexander, Daniel C.
通讯作者：
Alexander, Daniel C.
影响因子：
5.7
作者：
Cohen-Adad, J.
通讯作者：
Cohen-Adad, J.