Denoising High-field Multi-dimensional MRI with Local Complex PCA

Bazin, Pierre‐Louis; Alkemade, Anneke; Zwaag, Wietske van der; Caan, Matthan W.A.; Mulder, Martijn; Forstmann, Birte U.

doi:10.1101/606582

Cited by 8 publications

(13 citation statements)

References 23 publications

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“…However, local specificity and physiological noise reduction can also be optimized via specialized analysis techniques, which we did apply here. For instance, we controlled for physiological noise by including principle components of the time-course in the CSF as nuisance regressors in the GLM analysis 138 . Moreover, to enhance the regional specificity of our results, we also analyzed activity from LC-adjacent brainstem nuclei and by repeating our initial analyses for unsmoothed data from a smaller LC mask (1SD vs. 2SD).…”

Section: Discussionmentioning

confidence: 99%

Real-world stress resilience is associated with the responsivity of the locus coeruleus

et al. 2021

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Individuals may show different responses to stressful events. Here, we investigate the neurobiological basis of stress resilience, by showing that neural responsitivity of the noradrenergic locus coeruleus (LC-NE) and associated pupil responses are related to the subsequent change in measures of anxiety and depression in response to prolonged real-life stress. We acquired fMRI and pupillometry data during an emotional-conflict task in medical residents before they underwent stressful emergency-room internships known to be a risk factor for anxiety and depression. The LC-NE conflict response and its functional coupling with the amygdala was associated with stress-related symptom changes in response to the internship. A similar relationship was found for pupil-dilation, a potential marker of LC-NE firing. Our results provide insights into the noradrenergic basis of conflict generation, adaptation and stress resilience.

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Section: Discussionmentioning

confidence: 99%

Real-world stress resilience is associated with the responsivity of the locus coeruleus

et al. 2021

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“…Multi-contrast sequences may offer a novel alternative for eliminating the requirement of registration and resampling of separate scans while simultaneously reducing scan acquisition time ( Figure 2 ) [ 152 ]. A recently developed multiparametric imaging sequence is the Multi Echo (ME) MP2RAGE, which is largely unaffected by B1 inhomogeneities [ 153 , 154 , 155 , 156 , 157 , 158 , 159 , 160 ]. This allows for the acquisition of T2*-based contrasts from which subsequent SWI and quantitative susceptibility maps (QSM) can be created in the same space as the T1 images [ 158 , 160 ].…”

Section: Sequence Types and Contrastsmentioning

confidence: 99%

“…A recently developed multiparametric imaging sequence is the Multi Echo (ME) MP2RAGE, which is largely unaffected by B1 inhomogeneities [ 153 , 154 , 155 , 156 , 157 , 158 , 159 , 160 ]. This allows for the acquisition of T2*-based contrasts from which subsequent SWI and quantitative susceptibility maps (QSM) can be created in the same space as the T1 images [ 158 , 160 ]. Other benefits of multiple contrasts is that they contain complimentary information that can be used to jointly denoise and improve the SNR of the acquired images [ 161 , 162 , 163 ].…”

Section: Sequence Types and Contrastsmentioning

confidence: 99%

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Methodological Considerations for Neuroimaging in Deep Brain Stimulation of the Subthalamic Nucleus in Parkinson’s Disease Patients

Isaacs

Keuken

Alkemade

et al. 2020

JCM

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Deep brain stimulation (DBS) of the subthalamic nucleus is a neurosurgical intervention for Parkinson’s disease patients who no longer appropriately respond to drug treatments. A small fraction of patients will fail to respond to DBS, develop psychiatric and cognitive side-effects, or incur surgery-related complications such as infections and hemorrhagic events. In these cases, DBS may require recalibration, reimplantation, or removal. These negative responses to treatment can partly be attributed to suboptimal pre-operative planning procedures via direct targeting through low-field and low-resolution magnetic resonance imaging (MRI). One solution for increasing the success and efficacy of DBS is to optimize preoperative planning procedures via sophisticated neuroimaging techniques such as high-resolution MRI and higher field strengths to improve visualization of DBS targets and vasculature. We discuss targeting approaches, MRI acquisition, parameters, and post-acquisition analyses. Additionally, we highlight a number of approaches including the use of ultra-high field (UHF) MRI to overcome limitations of standard settings. There is a trade-off between spatial resolution, motion artifacts, and acquisition time, which could potentially be dissolved through the use of UHF-MRI. Image registration, correction, and post-processing techniques may require combined expertise of traditional radiologists, clinicians, and fundamental researchers. The optimization of pre-operative planning with MRI can therefore be best achieved through direct collaboration between researchers and clinicians.

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“…One category of denoising methods incorporate these priors, such as sparseness 52,[55][56][57][58] and low rank 59-64 , during the formation of MR images. Another category of denoising methods are designed to be applied to the reconstructed images, with numerous algorithms proposed for processing 2-dimensional images (e.g., total variation denoising 65 , anisotropic diffusion filtering 66,67 , bilateral filtering 68 , non-local means (NLM) filtering 69 , block-matching and 3-dimentional filtering (BM3D) 70 and K-SVD denoising 71 ) and 3dimensional medical imaging data [72][73][74][75][76] . As a stand-alone processing step, these methods only take in reconstructed images from the MRI scanner as inputs, without any need to intervene in the current MRI workflow, and can be directly incorporated into the existing surface reconstruction software packages.…”

Section: Introductionmentioning

confidence: 99%

Improved cortical surface reconstruction using sub-millimeter resolution MPRAGE by image denoising

Tian

Zaretskaya

Fan

et al. 2020

Preprint

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Automatic cerebral cortical surface reconstruction is a useful tool for cortical anatomy quantification, analysis and visualization. Recently, the Human Connectome Project and several studies have shown the advantages of using T1-weighted magnetic resonance (MR) images with sub-millimeter isotropic spatial resolution instead of the standard 1-millimeter isotropic resolution for improved accuracy of cortical surface positioning and thickness estimation. Nonetheless, sub-millimeter resolution images are noisy by nature and require averaging multiple repetitions to increase the signal-to-noise ratio for precisely delineating the cortical boundary. The prolonged acquisition time and potential motion artifacts pose significant barriers to the wide adoption of cortical surface reconstruction at sub-millimeter resolution for a broad range of neuroscientific and clinical applications. We address this challenge by evaluating the cortical surface reconstruction resulting from denoised single-repetition sub-millimeter T1-weighted images. We systematically characterized the effects of image denoising on empirical data acquired at 0.6 mm isotropic resolution using three classical denoising methods, including denoising convolutional neural network (DnCNN), block-matching and 4-dimensional filtering (BM4D) and adaptive optimized non-local means (AONLM). The denoised single-repetition images were found to be highly similar to 6-repetition averaged images, with a low whole-brain averaged mean absolute difference of ∼0.016, high whole-brain averaged peak signal-to-noise ratio of ∼33.5 dB and structural similarity index of 0.92, and minimal gray matter–white matter contrast loss (2% to 9%). The whole-brain mean absolute discrepancies in gray–white surface placement, gray–CSF surface placement and cortical thickness estimation were lower than 165 μm, 155 μm and 145 μm—sufficiently accurate for most applications. The denoising performance is equivalent to averaging ∼2.5 repetitions of the data in terms of image similarity, and 1.6–2.2 repetitions in terms of the cortical surface placement accuracy. The scan-rescan precision of the cortical surface positioning and thickness estimation was lower than 170 μm. Our unique dataset and systematic characterization support the use of denoising methods for improved cortical surface reconstruction sub-millimeter resolution.

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Denoising High-field Multi-dimensional MRI with Local Complex PCA

Cited by 8 publications

References 23 publications

Real-world stress resilience is associated with the responsivity of the locus coeruleus

Real-world stress resilience is associated with the responsivity of the locus coeruleus

Methodological Considerations for Neuroimaging in Deep Brain Stimulation of the Subthalamic Nucleus in Parkinson’s Disease Patients

Improved cortical surface reconstruction using sub-millimeter resolution MPRAGE by image denoising

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