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1.
Nature ; 604(7907): 697-707, 2022 04.
Artigo em Inglês | MEDLINE | ID: mdl-35255491

RESUMO

There is strong evidence of brain-related abnormalities in COVID-191-13. However, it remains unknown whether the impact of SARS-CoV-2 infection can be detected in milder cases, and whether this can reveal possible mechanisms contributing to brain pathology. Here we investigated brain changes in 785 participants of UK Biobank (aged 51-81 years) who were imaged twice using magnetic resonance imaging, including 401 cases who tested positive for infection with SARS-CoV-2 between their two scans-with 141 days on average separating their diagnosis and the second scan-as well as 384 controls. The availability of pre-infection imaging data reduces the likelihood of pre-existing risk factors being misinterpreted as disease effects. We identified significant longitudinal effects when comparing the two groups, including (1) a greater reduction in grey matter thickness and tissue contrast in the orbitofrontal cortex and parahippocampal gyrus; (2) greater changes in markers of tissue damage in regions that are functionally connected to the primary olfactory cortex; and (3) a greater reduction in global brain size in the SARS-CoV-2 cases. The participants who were infected with SARS-CoV-2 also showed on average a greater cognitive decline between the two time points. Importantly, these imaging and cognitive longitudinal effects were still observed after excluding the 15 patients who had been hospitalised. These mainly limbic brain imaging results may be the in vivo hallmarks of a degenerative spread of the disease through olfactory pathways, of neuroinflammatory events, or of the loss of sensory input due to anosmia. Whether this deleterious effect can be partially reversed, or whether these effects will persist in the long term, remains to be investigated with additional follow-up.


Assuntos
Encéfalo , COVID-19 , Idoso , Idoso de 80 Anos ou mais , Bancos de Espécimes Biológicos , Encéfalo/diagnóstico por imagem , Encéfalo/virologia , COVID-19/patologia , Humanos , Imageamento por Ressonância Magnética , Pessoa de Meia-Idade , SARS-CoV-2 , Olfato , Reino Unido/epidemiologia
2.
Magn Reson Med ; 90(4): 1484-1501, 2023 10.
Artigo em Inglês | MEDLINE | ID: mdl-37317708

RESUMO

PURPOSE: To develop a new method for high-fidelity, high-resolution 3D multi-slab diffusion MRI with minimal distortion and boundary slice aliasing. METHODS: Our method modifies 3D multi-slab imaging to integrate blip-reversed acquisitions for distortion correction and oversampling in the slice direction (kz ) for reducing boundary slice aliasing. Our aim is to achieve robust acceleration to keep the scan time the same as conventional 3D multi-slab acquisitions, in which data are acquired with a single direction of blip traversal and without kz -oversampling. We employ a two-stage reconstruction. In the first stage, the blip-up/down images are respectively reconstructed and analyzed to produce a field map for each diffusion direction. In the second stage, the blip-reversed data and the field map are incorporated into a joint reconstruction to produce images that are corrected for distortion and boundary slice aliasing. RESULTS: We conducted experiments at 7T in six healthy subjects. Stage 1 reconstruction produces images from highly under-sampled data (R = 7.2) with sufficient quality to provide accurate field map estimation. Stage 2 joint reconstruction substantially reduces distortion artifacts with comparable quality to fully-sampled blip-reversed results (2.4× scan time). Whole-brain in-vivo results acquired at 1.22 mm and 1.05 mm isotropic resolutions demonstrate improved anatomical fidelity compared to conventional 3D multi-slab imaging. Data demonstrate good reliability and reproducibility of the proposed method over multiple subjects. CONCLUSION: The proposed acquisition and reconstruction framework provide major reductions in distortion and boundary slice aliasing for 3D multi-slab diffusion MRI without increasing the scan time, which can potentially produce high-quality, high-resolution diffusion MRI.


Assuntos
Encéfalo , Imagem de Difusão por Ressonância Magnética , Humanos , Reprodutibilidade dos Testes , Imagem de Difusão por Ressonância Magnética/métodos , Encéfalo/diagnóstico por imagem , Artefatos , Aceleração , Processamento de Imagem Assistida por Computador/métodos , Imagem Ecoplanar/métodos , Algoritmos
3.
Cereb Cortex ; 32(8): 1608-1624, 2022 04 05.
Artigo em Inglês | MEDLINE | ID: mdl-34518890

RESUMO

Comparative neuroimaging has been used to identify changes in white matter architecture across primate species phylogenetically close to humans, but few have compared the phylogenetically distant species. Here, we acquired postmortem diffusion imaging data from ring-tailed lemurs (Lemur catta), black-capped squirrel monkeys (Saimiri boliviensis), and rhesus macaques (Macaca mulatta). We were able to establish templates and surfaces allowing us to investigate sulcal, cortical, and white matter anatomy. The results demonstrate an expansion of the frontal projections of the superior longitudinal fasciculus complex in squirrel monkeys and rhesus macaques compared to ring-tailed lemurs, which correlates with sulcal anatomy and the lemur's smaller prefrontal granular cortex. The connectivity of the ventral pathway in the parietal region is also comparatively reduced in ring-tailed lemurs, with the posterior projections of the inferior longitudinal fasciculus not extending toward parietal cortical areas as in the other species. In the squirrel monkeys we note a very specific occipito-parietal anatomy that is apparent in their surface anatomy and the expansion of the posterior projections of the optical radiation. Our study supports the hypothesis that the connectivity of the prefrontal-parietal regions became relatively elaborated in the simian lineage after divergence from the prosimian lineage.


Assuntos
Substância Branca , Animais , Mapeamento Encefálico/métodos , Macaca mulatta , Vias Neurais/anatomia & histologia , Vias Neurais/diagnóstico por imagem , Lobo Parietal , Substância Branca/anatomia & histologia , Substância Branca/diagnóstico por imagem
4.
Neuroimage ; 264: 119701, 2022 12 01.
Artigo em Inglês | MEDLINE | ID: mdl-36283542

RESUMO

Accurate spatial alignment of MRI data acquired across multiple contrasts in the same subject is often crucial for data analysis and interpretation, but can be challenging in the presence of geometric distortions that differ between acquisitions. It is well known that single-shot echo-planar imaging (EPI) acquisitions suffer from distortion in the phase-encoding direction due to B0 field inhomogeneities arising from tissue magnetic susceptibility differences and other sources, however there can be distortion in other encoding directions as well in the presence of strong field inhomogeneities. High-resolution ultrahigh-field MRI typically uses low bandwidth in the slice-encoding direction to acquire thin slices and, when combined with the pronounced B0 inhomogeneities, is prone to an additional geometric distortion in the slice direction as well. Here we demonstrate the presence of this slice distortion in high-resolution 7T EPI acquired with a novel pulse sequence allowing for the reversal of the slice-encoding gradient polarity that enables the acquisition of pairs of images with equal magnitudes of distortion in the slice direction but with opposing polarities. We also show that the slice-direction distortion can be corrected using gradient reversal-based method applying the same software used for conventional corrections of phase-encoding direction distortion.


Assuntos
Imagem Ecoplanar , Imageamento por Ressonância Magnética , Humanos , Imagem Ecoplanar/métodos , Imageamento por Ressonância Magnética/métodos , Processamento de Imagem Assistida por Computador/métodos , Artefatos , Algoritmos , Encéfalo/diagnóstico por imagem
5.
Neuroimage ; 224: 117002, 2021 01 01.
Artigo em Inglês | MEDLINE | ID: mdl-32502668

RESUMO

Dealing with confounds is an essential step in large cohort studies to address problems such as unexplained variance and spurious correlations. UK Biobank is a powerful resource for studying associations between imaging and non-imaging measures such as lifestyle factors and health outcomes, in part because of the large subject numbers. However, the resulting high statistical power also raises the sensitivity to confound effects, which therefore have to be carefully considered. In this work we describe a set of possible confounds (including non-linear effects and interactions that researchers may wish to consider for their studies using such data). We include descriptions of how we can estimate the confounds, and study the extent to which each of these confounds affects the data, and the spurious correlations that may arise if they are not controlled. Finally, we discuss several issues that future studies should consider when dealing with confounds.


Assuntos
Bancos de Espécimes Biológicos , Encéfalo , Neuroimagem , Processamento Eletrônico de Dados , Cabeça , Humanos , Neuroimagem/métodos , Fatores de Tempo , Reino Unido
6.
Neuroimage ; 244: 118543, 2021 12 01.
Artigo em Inglês | MEDLINE | ID: mdl-34508893

RESUMO

The Human Connectome Project (HCP) was launched in 2010 as an ambitious effort to accelerate advances in human neuroimaging, particularly for measures of brain connectivity; apply these advances to study a large number of healthy young adults; and freely share the data and tools with the scientific community. NIH awarded grants to two consortia; this retrospective focuses on the "WU-Minn-Ox" HCP consortium centered at Washington University, the University of Minnesota, and University of Oxford. In just over 6 years, the WU-Minn-Ox consortium succeeded in its core objectives by: 1) improving MR scanner hardware, pulse sequence design, and image reconstruction methods, 2) acquiring and analyzing multimodal MRI and MEG data of unprecedented quality together with behavioral measures from more than 1100 HCP participants, and 3) freely sharing the data (via the ConnectomeDB database) and associated analysis and visualization tools. To date, more than 27 Petabytes of data have been shared, and 1538 papers acknowledging HCP data use have been published. The "HCP-style" neuroimaging paradigm has emerged as a set of best-practice strategies for optimizing data acquisition and analysis. This article reviews the history of the HCP, including comments on key events and decisions associated with major project components. We discuss several scientific advances using HCP data, including improved cortical parcellations, analyses of connectivity based on functional and diffusion MRI, and analyses of brain-behavior relationships. We also touch upon our efforts to develop and share a variety of associated data processing and analysis tools along with detailed documentation, tutorials, and an educational course to train the next generation of neuroimagers. We conclude with a look forward at opportunities and challenges facing the human neuroimaging field from the perspective of the HCP consortium.


Assuntos
Conectoma/história , Encéfalo/diagnóstico por imagem , Bases de Dados Factuais , Imagem de Difusão por Ressonância Magnética , Feminino , História do Século XXI , Humanos , Processamento de Imagem Assistida por Computador , Masculino , Neuroimagem , Estudos Retrospectivos
7.
Cereb Cortex ; 30(3): 1159-1170, 2020 03 14.
Artigo em Inglês | MEDLINE | ID: mdl-31504269

RESUMO

The brain operates at a critical point that is balanced between order and disorder. Even during rest, unstable periods of random behavior are interspersed with stable periods of balanced activity patterns that support optimal information processing. Being born preterm may cause deviations from this normal pattern of development. We compared 33 extremely preterm (EPT) children born at < 27 weeks of gestation and 28 full-term controls. Two approaches were adopted in both groups, when they were 10 years of age, using structural and functional brain magnetic resonance imaging data. The first was using a novel intrinsic ignition analysis to study the ability of the areas of the brain to propagate neural activity. The second was a whole-brain Hopf model, to define the level of stability, desynchronization, or criticality of the brain. EPT-born children exhibited fewer intrinsic ignition events than controls; nodes were related to less sophisticated aspects of cognitive control, and there was a different hierarchy pattern in the propagation of information and suboptimal synchronicity and criticality. The largest differences were found in brain nodes belonging to the rich-club architecture. These results provide important insights into the neural substrates underlying brain reorganization and neurodevelopmental impairments related to prematurity.


Assuntos
Mapeamento Encefálico/métodos , Encéfalo/fisiologia , Encéfalo/crescimento & desenvolvimento , Criança , Desenvolvimento Infantil/fisiologia , Interpretação Estatística de Dados , Feminino , Idade Gestacional , Humanos , Lactente Extremamente Prematuro , Recém-Nascido , Imageamento por Ressonância Magnética , Masculino
8.
Neuroimage ; 219: 116962, 2020 10 01.
Artigo em Inglês | MEDLINE | ID: mdl-32497785

RESUMO

Nonlinear registration is critical to many aspects of Neuroimaging research. It facilitates averaging and comparisons across multiple subjects, as well as reporting of data in a common anatomical frame of reference. It is, however, a fundamentally ill-posed problem, with many possible solutions which minimise a given dissimilarity metric equally well. We present a regularisation method capable of selectively driving solutions towards those which would be considered anatomically plausible by penalising unlikely lineal, areal and volumetric deformations. This penalty is symmetric in the sense that geometric expansions and contractions are penalised equally, which encourages inverse-consistency. We demonstrate that this method is able to significantly reduce local volume changes and shape distortions compared to state-of-the-art elastic (FNIRT) and plastic (ANTs) registration frameworks. Crucially, this is achieved whilst simultaneously matching or exceeding the registration quality of these methods, as measured by overlap scores of labelled cortical regions. Extensive leveraging of GPU parallelisation has allowed us to solve this highly computationally intensive optimisation problem while maintaining reasonable run times of under half an hour.


Assuntos
Encéfalo/diagnóstico por imagem , Processamento de Imagem Assistida por Computador/métodos , Neuroimagem/métodos , Algoritmos , Humanos
9.
Neuroimage ; 184: 801-812, 2019 01 01.
Artigo em Inglês | MEDLINE | ID: mdl-30267859

RESUMO

Diffusion MRI data can be affected by hardware and subject-related artefacts that can adversely affect downstream analyses. Therefore, automated quality control (QC) is of great importance, especially in large population studies where visual QC is not practical. In this work, we introduce an automated diffusion MRI QC framework for single subject and group studies. The QC is based on a comprehensive, non-parametric approach for movement and distortion correction: FSL EDDY, which allows us to extract a rich set of QC metrics that are both sensitive and specific to different types of artefacts. Two different tools are presented: QUAD (QUality Assessment for DMRI), for single subject QC and SQUAD (Study-wise QUality Assessment for DMRI), which is designed to enable group QC and facilitate cross-studies harmonisation efforts.


Assuntos
Mapeamento Encefálico/métodos , Encéfalo/anatomia & histologia , Imagem de Difusão por Ressonância Magnética , Processamento de Imagem Assistida por Computador/métodos , Artefatos , Imagem de Tensor de Difusão , Feminino , Humanos , Masculino , Controle de Qualidade , Reprodutibilidade dos Testes , Razão Sinal-Ruído
10.
Neuroimage ; 185: 750-763, 2019 01 15.
Artigo em Inglês | MEDLINE | ID: mdl-29852283

RESUMO

The developing Human Connectome Project is set to create and make available to the scientific community a 4-dimensional map of functional and structural cerebral connectivity from 20 to 44 weeks post-menstrual age, to allow exploration of the genetic and environmental influences on brain development, and the relation between connectivity and neurocognitive function. A large set of multi-modal MRI data from fetuses and newborn infants is currently being acquired, along with genetic, clinical and developmental information. In this overview, we describe the neonatal diffusion MRI (dMRI) image processing pipeline and the structural connectivity aspect of the project. Neonatal dMRI data poses specific challenges, and standard analysis techniques used for adult data are not directly applicable. We have developed a processing pipeline that deals directly with neonatal-specific issues, such as severe motion and motion-related artefacts, small brain sizes, high brain water content and reduced anisotropy. This pipeline allows automated analysis of in-vivo dMRI data, probes tissue microstructure, reconstructs a number of major white matter tracts, and includes an automated quality control framework that identifies processing issues or inconsistencies. We here describe the pipeline and present an exemplar analysis of data from 140 infants imaged at 38-44 weeks post-menstrual age.


Assuntos
Encéfalo/diagnóstico por imagem , Conectoma/métodos , Processamento de Imagem Assistida por Computador/métodos , Recém-Nascido , Encéfalo/crescimento & desenvolvimento , Imagem de Difusão por Ressonância Magnética/métodos , Feminino , Humanos , Masculino
11.
Magn Reson Med ; 82(1): 107-125, 2019 07.
Artigo em Inglês | MEDLINE | ID: mdl-30825243

RESUMO

PURPOSE: Image acceleration provides multiple benefits to diffusion MRI, with in-plane acceleration reducing distortion and slice-wise acceleration increasing the number of directions that can be acquired in a given scan time. However, as acceleration factors increase, the reconstruction problem becomes ill-conditioned, particularly when using both in-plane acceleration and simultaneous multislice imaging. In this work, we develop a novel reconstruction method for in vivo MRI acquisition that provides acceleration beyond what conventional techniques can achieve. THEORY AND METHODS: We propose to constrain the reconstruction in the spatial (k) domain by incorporating information from the angular (q) domain. This approach exploits smoothness of the signal in q-space using Gaussian processes, as has previously been exploited in post-reconstruction analysis. We demonstrate in-plane undersampling exceeding the theoretical parallel imaging limits, and simultaneous multislice combined with in-plane undersampling at a total factor of 12. This reconstruction is cast within a Bayesian framework that incorporates estimation of smoothness hyper-parameters, with no need for manual tuning. RESULTS: Simulations and in vivo results demonstrate superior performance of the proposed method compared with conventional parallel imaging methods. These improvements are achieved without loss of spatial or angular resolution and require only a minor modification to standard pulse sequences. CONCLUSION: The proposed method provides improvements over existing methods for diffusion acceleration, particularly for high simultaneous multislice acceleration with in-plane undersampling.


Assuntos
Imagem de Tensor de Difusão/métodos , Processamento de Imagem Assistida por Computador/métodos , Processamento de Sinais Assistido por Computador , Algoritmos , Encéfalo/diagnóstico por imagem , Simulação por Computador , Humanos , Distribuição Normal
12.
Neuroimage ; 171: 277-295, 2018 05 01.
Artigo em Inglês | MEDLINE | ID: mdl-29277648

RESUMO

Because of their low bandwidth in the phase-encode (PE) direction, the susceptibility-induced off-resonance field causes distortions in echo planar imaging (EPI) images. It is therefore crucial to correct for susceptibility-induced distortions when performing diffusion studies using EPI. The susceptibility-induced field is caused by the object (head) disrupting the field and it is typically assumed that it remains constant within a framework defined by the object, (i.e. it follows the object as it moves in the scanner). However, this is only approximately true. When a non-spherical object rotates around an axis other than that parallel with the magnetic flux (the z-axis) it changes the way it disrupts the field, leading to different distortions. Hence, if using a single field to correct for distortions there will be residual distortions in the volumes where the object orientation is substantially different to that when the field was measured. In this paper we present a post-processing method for estimating the field as it changes with motion during the course of an experiment. It only requires a single measured field and knowledge of the orientation of the subject when that field was acquired. The volume-to-volume changes of the field as a consequence of subject movement are estimated directly from the diffusion data without the need for any additional or special acquisitions. It uses a generative model that predicts how each volume would look predicated on field change and inverts that model to yield an estimate of the field changes. It has been validated on both simulations and experimental data. The results show that we are able to track the field with high accuracy and that we are able to correct the data for the adverse effects of the changing field.


Assuntos
Artefatos , Mapeamento Encefálico/métodos , Imagem Ecoplanar/métodos , Processamento de Imagem Assistida por Computador/métodos , Algoritmos , Movimentos da Cabeça , Humanos , Movimento (Física)
13.
Neuroimage ; 166: 400-424, 2018 02 01.
Artigo em Inglês | MEDLINE | ID: mdl-29079522

RESUMO

UK Biobank is a large-scale prospective epidemiological study with all data accessible to researchers worldwide. It is currently in the process of bringing back 100,000 of the original participants for brain, heart and body MRI, carotid ultrasound and low-dose bone/fat x-ray. The brain imaging component covers 6 modalities (T1, T2 FLAIR, susceptibility weighted MRI, Resting fMRI, Task fMRI and Diffusion MRI). Raw and processed data from the first 10,000 imaged subjects has recently been released for general research access. To help convert this data into useful summary information we have developed an automated processing and QC (Quality Control) pipeline that is available for use by other researchers. In this paper we describe the pipeline in detail, following a brief overview of UK Biobank brain imaging and the acquisition protocol. We also describe several quantitative investigations carried out as part of the development of both the imaging protocol and the processing pipeline.


Assuntos
Encéfalo/diagnóstico por imagem , Bases de Dados Factuais , Conjuntos de Dados como Assunto , Processamento de Imagem Assistida por Computador/métodos , Aprendizado de Máquina , Imageamento por Ressonância Magnética/métodos , Neuroimagem/métodos , Controle de Qualidade , Bases de Dados Factuais/normas , Conjuntos de Dados como Assunto/normas , Humanos , Processamento de Imagem Assistida por Computador/normas , Aprendizado de Máquina/normas , Imageamento por Ressonância Magnética/normas , Neuroimagem/normas , Reino Unido
14.
Neuroimage ; 152: 450-466, 2017 05 15.
Artigo em Inglês | MEDLINE | ID: mdl-28284799

RESUMO

Most motion correction methods work by aligning a set of volumes together, or to a volume that represents a reference location. These are based on an implicit assumption that the subject remains motionless during the several seconds it takes to acquire all slices in a volume, and that any movement occurs in the brief moment between acquiring the last slice of one volume and the first slice of the next. This is clearly an approximation that can be more or less good depending on how long it takes to acquire one volume and in how rapidly the subject moves. In this paper we present a method that increases the temporal resolution of the motion correction by modelling movement as a piecewise continous function over time. This intra-volume movement correction is implemented within a previously presented framework that simultaneously estimates distortions, movement and movement-induced signal dropout. We validate the method on highly realistic simulated data containing all of these effects. It is demonstrated that we can estimate the true movement with high accuracy, and that scalar parameters derived from the data, such as fractional anisotropy, are estimated with greater fidelity when data has been corrected for intra-volume movement. Importantly, we also show that the difference in fidelity between data affected by different amounts of movement is much reduced when taking intra-volume movement into account. Additional validation was performed on data from a healthy volunteer scanned when lying still and when performing deliberate movements. We show an increased correspondence between the "still" and the "movement" data when the latter is corrected for intra-volume movement. Finally we demonstrate a big reduction in the telltale signs of intra-volume movement in data acquired on elderly subjects.


Assuntos
Mapeamento Encefálico/métodos , Encéfalo/anatomia & histologia , Imagem de Difusão por Ressonância Magnética/métodos , Aumento da Imagem/métodos , Artefatos , Simulação por Computador , Humanos , Movimento , Reprodutibilidade dos Testes
15.
Neuroimage ; 125: 1063-1078, 2016 Jan 15.
Artigo em Inglês | MEDLINE | ID: mdl-26481672

RESUMO

In this paper we describe a method for retrospective estimation and correction of eddy current (EC)-induced distortions and subject movement in diffusion imaging. In addition a susceptibility-induced field can be supplied and will be incorporated into the calculations in a way that accurately reflects that the two fields (susceptibility- and EC-induced) behave differently in the presence of subject movement. The method is based on registering the individual volumes to a model free prediction of what each volume should look like, thereby enabling its use on high b-value data where the contrast is vastly different in different volumes. In addition we show that the linear EC-model commonly used is insufficient for the data used in the present paper (high spatial and angular resolution data acquired with Stejskal-Tanner gradients on a 3T Siemens Verio, a 3T Siemens Connectome Skyra or a 7T Siemens Magnetome scanner) and that a higher order model performs significantly better. The method is already in extensive practical use and is used by four major projects (the WU-UMinn HCP, the MGH HCP, the UK Biobank and the Whitehall studies) to correct for distortions and subject movement.


Assuntos
Artefatos , Interpretação de Imagem Assistida por Computador/métodos , Algoritmos , Imagem de Difusão por Ressonância Magnética/métodos , Humanos , Movimento
16.
Neuroimage ; 141: 556-572, 2016 Nov 01.
Artigo em Inglês | MEDLINE | ID: mdl-27393418

RESUMO

Despite its great potential in studying brain anatomy and structure, diffusion magnetic resonance imaging (dMRI) is marred by artefacts more than any other commonly used MRI technique. In this paper we present a non-parametric framework for detecting and correcting dMRI outliers (signal loss) caused by subject motion. Signal loss (dropout) affecting a whole slice, or a large connected region of a slice, is frequently observed in diffusion weighted images, leading to a set of unusable measurements. This is caused by bulk (subject or physiological) motion during the diffusion encoding part of the imaging sequence. We suggest a method to detect slices affected by signal loss and replace them by a non-parametric prediction, in order to minimise their impact on subsequent analysis. The outlier detection and replacement, as well as correction of other dMRI distortions (susceptibility-induced distortions, eddy currents (EC) and subject motion) are performed within a single framework, allowing the use of an integrated approach for distortion correction. Highly realistic simulations have been used to evaluate the method with respect to its ability to detect outliers (types 1 and 2 errors), the impact of outliers on retrospective correction of movement and distortion and the impact on estimation of commonly used diffusion tensor metrics, such as fractional anisotropy (FA) and mean diffusivity (MD). Data from a large imaging project studying older adults (the Whitehall Imaging sub-study) was used to demonstrate the utility of the method when applied to datasets with severe subject movement. The results indicate high sensitivity and specificity for detecting outliers and that their deleterious effects on FA and MD can be almost completely corrected.


Assuntos
Algoritmos , Artefatos , Encéfalo/anatomia & histologia , Imagem de Difusão por Ressonância Magnética/métodos , Aumento da Imagem/métodos , Interpretação de Imagem Assistida por Computador/métodos , Reconhecimento Automatizado de Padrão/métodos , Humanos , Movimento (Física) , Reprodutibilidade dos Testes , Sensibilidade e Especificidade
17.
Neuroimage ; 122: 166-76, 2015 Nov 15.
Artigo em Inglês | MEDLINE | ID: mdl-26236030

RESUMO

Diffusion MRI offers great potential in studying the human brain microstructure and connectivity. However, diffusion images are marred by technical problems, such as image distortions and spurious signal loss. Correcting for these problems is non-trivial and relies on having a mechanism that predicts what to expect. In this paper we describe a novel way to represent and make predictions about diffusion MRI data. It is based on a Gaussian process on one or several spheres similar to the Geostatistical method of "Kriging". We present a choice of covariance function that allows us to accurately predict the signal even from voxels with complex fibre patterns. For multi-shell data (multiple non-zero b-values) the covariance function extends across the shells which means that data from one shell is used when making predictions for another shell.


Assuntos
Encéfalo/anatomia & histologia , Encéfalo/fisiologia , Imagem de Difusão por Ressonância Magnética/métodos , Imagem de Tensor de Difusão/métodos , Modelos Neurológicos , Artefatos , Interpretação Estatística de Dados , Difusão , Humanos , Processamento de Imagem Assistida por Computador/métodos , Distribuição Normal , Processamento de Sinais Assistido por Computador
18.
Neuroimage ; 76: 400-11, 2013 Aug 01.
Artigo em Inglês | MEDLINE | ID: mdl-23523807

RESUMO

Anatomical alignment in neuroimaging studies is of such importance that considerable effort is put into improving the registration used to establish spatial correspondence. Tract-based spatial statistics (TBSS) is a popular method for comparing diffusion characteristics across subjects. TBSS establishes spatial correspondence using a combination of nonlinear registration and a "skeleton projection" that may break topological consistency of the transformed brain images. We therefore investigated feasibility of replacing the two-stage registration-projection procedure in TBSS with a single, regularized, high-dimensional registration. To optimize registration parameters and to evaluate registration performance in diffusion MRI, we designed an evaluation framework that uses native space probabilistic tractography for 23 white matter tracts, and quantifies tract similarity across subjects in standard space. We optimized parameters for two registration algorithms on two diffusion datasets of different quality. We investigated reproducibility of the evaluation framework, and of the optimized registration algorithms. Next, we compared registration performance of the regularized registration methods and TBSS. Finally, feasibility and effect of incorporating the improved registration in TBSS were evaluated in an example study. The evaluation framework was highly reproducible for both algorithms (R(2) 0.993; 0.931). The optimal registration parameters depended on the quality of the dataset in a graded and predictable manner. At optimal parameters, both algorithms outperformed the registration of TBSS, showing feasibility of adopting such approaches in TBSS. This was further confirmed in the example experiment.


Assuntos
Algoritmos , Mapeamento Encefálico/métodos , Imagem de Tensor de Difusão/métodos , Interpretação de Imagem Assistida por Computador/métodos , Humanos
19.
Neuroimage ; 80: 80-104, 2013 Oct 15.
Artigo em Inglês | MEDLINE | ID: mdl-23702417

RESUMO

The Human Connectome Project (HCP) relies primarily on three complementary magnetic resonance (MR) methods. These are: 1) resting state functional MR imaging (rfMRI) which uses correlations in the temporal fluctuations in an fMRI time series to deduce 'functional connectivity'; 2) diffusion imaging (dMRI), which provides the input for tractography algorithms used for the reconstruction of the complex axonal fiber architecture; and 3) task based fMRI (tfMRI), which is employed to identify functional parcellation in the human brain in order to assist analyses of data obtained with the first two methods. We describe technical improvements and optimization of these methods as well as instrumental choices that impact speed of acquisition of fMRI and dMRI images at 3T, leading to whole brain coverage with 2 mm isotropic resolution in 0.7 s for fMRI, and 1.25 mm isotropic resolution dMRI data for tractography analysis with three-fold reduction in total dMRI data acquisition time. Ongoing technical developments and optimization for acquisition of similar data at 7 T magnetic field are also presented, targeting higher spatial resolution, enhanced specificity of functional imaging signals, mitigation of the inhomogeneous radio frequency (RF) fields, and reduced power deposition. Results demonstrate that overall, these approaches represent a significant advance in MR imaging of the human brain to investigate brain function and structure.


Assuntos
Encéfalo/anatomia & histologia , Encéfalo/fisiologia , Conectoma/métodos , Imagem de Difusão por Ressonância Magnética/métodos , Modelos Neurológicos , Rede Nervosa/anatomia & histologia , Rede Nervosa/fisiologia , Animais , Humanos , Aumento da Imagem/métodos , Modelos Anatômicos , Análise Espaço-Temporal
20.
bioRxiv ; 2023 Nov 02.
Artigo em Inglês | MEDLINE | ID: mdl-37546835

RESUMO

Development of diffusion MRI (dMRI) denoising approaches has experienced considerable growth over the last years. As noise can inherently reduce accuracy and precision in measurements, its effects have been well characterised both in terms of uncertainty increase in dMRI-derived features and in terms of biases caused by the noise floor, the smallest measurable signal given the noise level. However, gaps in our knowledge still exist in objectively characterising dMRI denoising approaches in terms of both of these effects and assessing their efficacy. In this work, we reconsider what a denoising method should and should not do and we accordingly define criteria to characterise the performance. We propose a comprehensive set of evaluations, including i) benefits in improving signal quality and reducing noise variance, ii) gains in reducing biases and the noise floor and improving, iii) preservation of spatial resolution, iv) agreement of denoised data against a gold standard, v) gains in downstream parameter estimation (precision and accuracy), vi) efficacy in enabling noise-prone applications, such as ultra-high-resolution imaging. We further provide newly acquired complex datasets (magnitude and phase) with multiple repeats that sample different SNR regimes to highlight performance differences under different scenarios. Without loss of generality, we subsequently apply a number of exemplar patch-based denoising algorithms to these datasets, including Non-Local Means, Marchenko-Pastur PCA (MPPCA) in the magnitude and complex domain and NORDIC, and compare them with respect to the above criteria and against a gold standard complex average of multiple repeats. We demonstrate that all tested denoising approaches reduce noise-related variance, but not always biases from the elevated noise floor. They all induce a spatial resolution penalty, but its extent can vary depending on the method and the implementation. Some denoising approaches agree with the gold standard more than others and we demonstrate challenges in even defining such a standard. Overall, we show that dMRI denoising performed in the complex domain is advantageous to magnitude domain denoising with respect to all the above criteria.

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