scholarly journals Avoiding Data Loss: Synthetic MRIs Generated from Diffusion Imaging Can Replace Corrupted Structural Acquisitions For Freesurfer-Seeded Tractography

2021 ◽  
Author(s):  
Jeremy Beaumont ◽  
Giulio Gambarota ◽  
Marita Prior ◽  
Jurgen Fripp ◽  
Lee B. Reid
Keyword(s):  
Magnetic Resonance ◽  
Diffusion Mri ◽  
Diffusion Imaging ◽  
Absolute Difference ◽  
List Type ◽  
Data Loss ◽  
Tissue Properties ◽  
Spherical Deconvolution ◽  
Tissue Contrast ◽  
Synthetic Images

1AbstractMagnetic Resonance Imaging (MRI) motion artefacts frequently complicate structural and diffusion MRI analyses. While diffusion imaging is easily ‘scrubbed’ of motion affected volumes, the same is not true for structural images. Structural images are critical to most diffusion-imaging pipelines thus their corruption can lead to disproportionate data loss. To enable diffusion-image processing when structural images have been corrupted, we propose a means by which synthetic structural images can be generated from diffusion MRI. This technique combines multi-tissue constrained spherical deconvolution, which is central to many existing diffusion analyses, with the Bloch equations which allow simulation of MRI intensities given scanner parameters and magnetic resonance (MR) tissue properties. We applied this technique to 32 scans, including those acquired on different scanners, with different protocols and with pathology present. The resulting synthetic T1w and T2w images were visually convincing and exhibited similar tissue contrast to acquired structural images. These were also of sufficient quality to drive a Freesurfer-based tractographic analysis. In this analysis, probabilistic tractography connecting the thalamus to the primary sensorimotor cortex was delineated with Freesurfer, using either real or synthetic structural images. Tractography for real and synthetic conditions was largely identical in terms of both voxels encountered (Dice 0.88 – 0.95) and mean fractional anisotropy (intrasubject absolute difference 0.00 – 0.02). We provide executables for the proposed technique in the hope that these may aid the community in analysing datasets where structural image corruption is common, such as studies of children or cognitively impaired persons.HighlightsWe propose a simple means of synthesizing T1w and T2w images from diffusion dataThe proposed method worked well for a variety of acquisitionsSynthetic images showed tissue contrast akin to acquired imagesSynthetic images were high enough quality to be used for Freesurfer seeded diffusion tractographyThis method enables analysis of datasets where motion has corrupted acquired structural MRIs

Optimization of T2-weighted imaging for shoulder magnetic resonance arthrography by synthetic magnetic resonance imaging

2017 ◽  
Vol 59 (8) ◽  
pp. 959-965
Author(s):  
Seung Hyun Lee ◽  
Young Han Lee ◽  
Seok Hahn ◽  
Jaemoon Yang ◽  
Ho-Taek Song ◽  
...  
Keyword(s):  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
Supraspinatus Tendon ◽  
Joint Fluid ◽  
Resonance Imaging ◽  
Mr Images ◽  
Diagnostic Agreement ◽  
Tissue Contrast ◽  
Synthetic Images ◽  
Synthetic Mri

Background Synthetic magnetic resonance imaging (MRI) allows reformatting of various synthetic images by adjustment of scanning parameters such as repetition time (TR) and echo time (TE). Optimized MR images can be reformatted from T1, T2, and proton density (PD) values to achieve maximum tissue contrast between joint fluid and adjacent soft tissue. Purpose To demonstrate the method for optimization of TR and TE by synthetic MRI and to validate the optimized images by comparison with conventional shoulder MR arthrography (MRA) images. Material and Methods Thirty-seven shoulder MRA images acquired by synthetic MRI were retrospectively evaluated for PD, T1, and T2 values at the joint fluid and glenoid labrum. Differences in signal intensity between the fluid and labrum were observed between TR of 500–6000 ms and TE of 80–300 ms in T2-weighted (T2W) images. Conventional T2W and synthetic images were analyzed for diagnostic agreement of supraspinatus tendon abnormalities (kappa statistics) and image quality scores (one-way analysis of variance with post-hoc analysis). Results Optimized mean values of TR and TE were 2724.7 ± 1634.7 and 80.1 ± 0.4, respectively. Diagnostic agreement for supraspinatus tendon abnormalities between conventional and synthetic MR images was excellent (κ = 0.882). The mean image quality score of the joint space in optimized synthetic images was significantly higher compared with those in conventional and synthetic images (2.861 ± 0.351 vs. 2.556 ± 0.607 vs. 2.750 ± 0.439; P < 0.05). Conclusion Synthetic MRI with optimized TR and TE for shoulder MRA enables optimization of soft-tissue contrast.

scholarly journals Perivascular space fluid contributes to diffusion tensor imaging changes in white matter

2018 ◽  
Author(s):  
Farshid Sepehrband ◽  
Ryan P Cabeen ◽  
Jeiran Choupan ◽  
Giuseppe Barisano ◽  
Meng Law ◽  
...  
Keyword(s):  
Diffusion Tensor Imaging ◽  
White Matter ◽  
Fractional Anisotropy ◽  
Diffusion Mri ◽  
Diffusion Tensor ◽  
Diffusion Imaging ◽  
Mean Diffusivity ◽  
Brain Parenchyma ◽  
Perivascular Space ◽  
List Type

AbstractDiffusion tensor imaging (DTI) has been extensively used to map changes in brain tissue related to neurological disorders. Among the most widespread DTI findings are increased mean diffusivity and decreased fractional anisotropy of white matter tissue in neurodegenerative diseases. Here we utilize multi-shell diffusion imaging to separate diffusion signal of the brain parenchyma from fluid within the white matter. We show that unincorporated anisotropic water in perivascular space (PVS) significantly, and systematically, biases DTI measures, casting new light on the biological validity of many previously reported findings. Despite the challenge this poses for interpreting these past findings, our results suggest that multi-shell diffusion MRI provides a new opportunity for incorporating the PVS contribution, ultimately strengthening the clinical and scientific value of diffusion MRI.HighlightsPerivascular space (PVS) fluid significantly contributes to diffusion tensor imaging metricsIncreased PVS fluid results in increased mean diffusivity and decreased fractional anisotropyPVS contribution to diffusion signal is overlooked and demands further investigation

scholarly journals Spherical deconvolution with tissue-specific response functions and multi-shell diffusion MRI to estimate multiple fiber orientation distributions (mFODs)

2019 ◽  
Author(s):  
Alberto De Luca ◽  
Fenghua Guo ◽  
Martijn Froeling ◽  
Alexander Leemans
Keyword(s):  
Fiber Orientation ◽  
Diffusion Mri ◽  
Grey Matter ◽  
State Of The Art ◽  
List Type ◽  
Response Functions ◽  
Fiber Tractography ◽  
Tissue Specific ◽  
Spherical Deconvolution ◽  
Orientation Distributions

AbstractIn diffusion MRI, spherical deconvolution approaches can estimate local white matter (WM) fiber orientation distributions (FOD) which can be used to produce fiber tractography reconstructions. The applicability of spherical deconvolution to grey matter (GM), however, is still limited, despite its critical role as start/endpoint of WM fiber pathways. The advent of multi-shell diffusion MRI data offers additional contrast to model the GM signal but, to date, only isotropic models have been applied to GM. Evidence from both histology and high-resolution diffusion MRI studies suggests a marked anisotropic character of the diffusion process in GM, which could be exploited to improve the description of the cortical organization. In this study, we investigated whether performing spherical deconvolution with tissue specific models of both WM and GM can improve the characterization of the latter while retaining state-of-the-art performances in WM. To this end, we developed a framework able to simultaneously accommodate multiple anisotropic response functions to estimate multiple, tissue-specific, fiber orientation distributions (mFODs). As proof of principle, we used the diffusion kurtosis imaging model to represent the WM signal, and the neurite orientation dispersion and density imaging (NODDI) model to represent the GM signal. The feasibility of the proposed approach is shown with numerical simulations and with data from the Human Connectome Project (HCP). The performance of our method is compared to the current state of the art, multi-shell constrained spherical deconvolution (MSCSD). The simulations show that with our new method we can accurately estimate a mixture of two FODs at SNR≥50. With HCP data, the proposed method was able to reconstruct both tangentially and radially oriented FODs in GM, and performed comparably well to MSCSD in computing FODs in WM. When performing fiber tractography, the trajectories reconstructed with mFODs reached the cortex with more spatial continuity and for a longer distance as compared to MSCSD and allowed to reconstruct short trajectories tangential to the cortical folding. In conclusion, we demonstrated that our proposed method allows to perform spherical deconvolution of multiple anisotropic response functions, specifically improving the performances of spherical deconvolution in GM tissue.HighlightsWe introduce a novel framework to perform spherical deconvolution with multiple anisotropic response functions (mFOD)We show that the proposed framework can be used to improve the FOD estimation in the cortical grey matterFiber tractography performed with mFOD reaches the cortical GM with more coverage and contiguity than with previous methodsThe proposed framework is a first step towards GM to GM fiber tractography

scholarly journals Q -ball imaging of macaque white matter architecture

2005 ◽  
Vol 360 (1457) ◽  
pp. 869-879 ◽  
Author(s):  
David S Tuch ◽  
Jonathan J Wisco ◽  
Mark H Khachaturian ◽  
Leeland B Ekstrom ◽  
Rolf Kötter ◽  
...  
Keyword(s):  
White Matter ◽  
Magnetic Resonance ◽  
Diffusion Imaging ◽  
Large Body ◽  
Macaque Monkey ◽  
High Angular Resolution ◽  
Imaging Method ◽  
Diffusion Tractography ◽  
Axonal Projections ◽  
Histological Validation

Diffusion-weighted magnetic resonance imaging holds substantial promise as a technique for non-invasive imaging of white matter (WM) axonal projections. For diffusion imaging to be capable of providing new insight into the connectional neuroanatomy of the human brain, it will be necessary to histologically validate the technique against established tracer methods such as horseradish peroxidase and biocytin histochemistry. The macaque monkey provides an ideal model for histological validation of the diffusion imaging method due to the phylogenetic proximity between humans and macaques, the gyrencephalic structure of the macaque cortex, the large body of knowledge on the neuroanatomic connectivity of the macaque brain and the ability to use comparable magnetic resonance acquisition protocols in both species. Recently, it has been shown that high angular resolution diffusion imaging (HARDI) can resolve multiple axon orientations within an individual imaging voxel in human WM. This capability promises to boost the accuracy of tract reconstructions from diffusion imaging. If the macaque is to serve as a model for histological validation of the diffusion tractography method, it will be necessary to show that HARDI can also resolve intravoxel architecture in macaque WM. The present study therefore sought to test whether the technique can resolve intravoxel structure in macaque WM. Using a HARDI method called q -ball imaging (QBI) it was possible to resolve composite intravoxel architecture in a number of anatomic regions. QBI resolved intravoxel structure in, for example, the dorsolateral convexity, the pontine decussation, the pulvinar and temporal subcortical WM. The paper concludes by reviewing remaining challenges for the diffusion tractography project.

Imaging Usual Addictions: Tobacco, Canabis and Alcohol

2009 ◽  
Vol 24 (S1) ◽  
pp. 1-1
Author(s):  
C. Leroy ◽  
S. Chanraud ◽  
E. Artiges ◽  
C. Martelli ◽  
A. Cachia ◽  
...  
Keyword(s):  
White Matter ◽  
Psychosocial Functioning ◽  
Grey Matter ◽  
Diffusion Imaging ◽  
Temporal Cortex ◽  
List Type ◽  
Dopamine Level ◽  
Type Number ◽  
Positron Emission ◽  
Brain Microstructure

Background:Brain models of drug addiction are being tackled in humans, using PET and MRI.Results:1.Whereas tobacco and cannabis do not interact directly with dopamine sites, positron emission tomography detected lower availability in sites regulating the catecholamines homeostasis, notably in dopamine transporter sites in striatal and in extrastriatal regions. This further supports repeated and long term substance use progress towards an adaptative diminished basal dopamine level that would contribute to the switch to an addicted brain.2.Alcohol: abnormalities in brain macro- and micro- structure were searched in detoxified alcohol-dependents with preserved psychosocial functioning:-Brain function (fMRI): fronto-cerebellar overactivation detected during an auditory language task in alcohol-dependents may reflect the compensatory effort required for patients to maintain the same level of performance as controls.-Brain macrostructure (MRI). Widespread lower white matter volumes, and lower grey matter volumes in the frontal lobe, insula, hippocampus, thalami and cerebellum, were detected. Poorer neuropsychological performance correlated with smaller grey matter volumes in these regions and with lower white matter volume in the brainstem.-Brain microstructure (DTI): tractography of white matter fiber bundles revealed that brainstem bundles alteration may contribute to cognitive flexibility impairment. Regression analyses showed memory scores were related to brain microstructure in parahippocampal areas, frontal cortex, and left temporal cortex. This suggest diffusion imaging (DTI) is a useful probe to early alcohol-induced brain alterations.Conclusion:While indices of dopamine down-regulation are consistency detected in several drug addictions, even “socially-adapted” alcohol dependence may induce change in brain structure.Psychol Med. 1998 28:1039-48.Neuropsychopharmacology. 2007 32:429-38.IEEE Trans Med Imaging. 2007 26:553-65J Nucl Med. 2007 48:538-46.Neuropsychopharmacology (Chanraud S et al., 2008 Jul 9. [Epub ahead of print]).J Clin Psychopharmacol (Leroy C et al, in press).

The Potential for Quantifying Regional Distributions of Radial and Shear Strain in the Thoracic and Abdominal Aortic Wall Using Spiral Cine DENSE Magnetic Resonance Imaging

2021 ◽  
Vol 143 (6) ◽  
Author(s):  
Patrick A. Jones ◽  
John S. Wilson
Keyword(s):  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
Shear Strain ◽  
Aortic Wall ◽  
Strain Tensor ◽  
Clinical Diagnostics ◽  
Absolute Difference ◽  
Resonance Imaging ◽  
Minimal Impact ◽  
2D Strain

Abstract Aortic displacement encoding with stimulated echoes (DENSE) magnetic resonance imaging (MRI) was recently developed to assess heterogeneities in aortic wall circumferential strain (CS). However, previous studies neglected potential radial and shear strain (RSS) distributions. Herein, we present an improved aortic DENSE MRI postprocessing method to assess the feasibility of quantifying all components of the two-dimensional (2D) strain tensor. 32 previously acquired 2D DENSE scans from three distinct aortic locations were re-analyzed. Contrasting previous studies, displacements of the inner and outer aortic wall layers were processed separately to preserve RSS. Differences in regional strain between the new and old postprocessing methods were evaluated, along with interobserver, intraobserver, and interscan repeatability for all strain components. The new postprocessing method revealed an overall mean absolute difference in regional CS of 0.01 ± 0.01 compared to the prior method, with minimal impact on CS repeatability. Mean absolute magnitudes of regional RSS increased significantly compared to changes in CS (radial 0.04 ± 0.05, p &lt; 0.001; shear 0.04 ± 0.04, p = 0.02). Most repeatability metrics for RSS were significantly worse than for CS. The unique distributions of RSS for each axial location associated well with local periaortic structures and mean aortic displacement. The new postprocessing method captures heterogeneous distributions of nonzero RSS which may provide new information for improving clinical diagnostics and computational modeling of heterogeneous aortic wall mechanics. However, future studies are required to improve the repeatability of RSS and assess the influence of partial volume effects.

Diffusion imaging perspectives on brain development in childhood and adolescence

2021 ◽  
Author(s):  
Bryce L. Geeraert ◽  
Jess E. Reynolds ◽  
Catherine Lebel
Keyword(s):  
White Matter ◽  
Brain Development ◽  
Diffusion Imaging ◽  
Childhood And Adolescence ◽  
Tissue Properties ◽  
Versatile Tool ◽  
P Diffusion ◽  
White Matter Development ◽  
Brain Microstructure ◽  
Development Trajectories

Diffusion magnetic resonance imaging (dMRI) is a versatile tool which can be applied to investigate brain microstructure. This chapter outlines brain development trajectories from infancy to adulthood as described by dMRI. The chapter focuses on white matter development, as dMRI is particularly well suited to describing white matter tissue properties. The chapter also discusses sources of individual variation which are simultaneously fascinating and confounding to research efforts. Next, the chapter discusses links between white matter development and cognition, with specific examples drawn from reading research. Additional techniques which may complement future diffusion-based research are introduced in the chapter’s final section.

Sign in / Sign up

Export Citation Format

Share Document