Cortical fibers orientation mapping using in-vivo whole brain 7 T diffusion MRI

AbstractWe present a whole-brain in vivo diffusion MRI (dMRI) dataset acquired at 760 μm isotropic resolution and sampled at 1260 q-space points across 9 two-hour sessions on a single healthy participant. The creation of this benchmark dataset is possible through the synergistic use of advanced acquisition hardware and software including the high-gradient-strength Connectom scanner, a custom-built 64-channel phased-array coil, a personalized motion-robust head stabilizer, a recently developed SNR-efficient dMRI acquisition method, and parallel imaging reconstruction with advanced ghost reduction algorithm. With its unprecedented resolution, SNR and image quality, we envision that this dataset will have a broad range of investigational, educational, and clinical applications that will advance the understanding of human brain structures and connectivity. This comprehensive dataset can also be used as a test bed for new modeling, sub-sampling strategies, denoising and processing algorithms, potentially providing a common testing platform for further development of in vivo high resolution dMRI techniques. Whole brain anatomical T1-weighted and T2-weighted images at submillimeter scale along with field maps are also made available.

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In vivo human whole-brain Connectom diffusion MRI dataset at 760 μm isotropic resolution

10.1101/2020.10.05.327395 ◽

2020 ◽

Author(s):

Fuyixue Wang ◽

Zijing Dong ◽

Qiyuan Tian ◽

Congyu Liao ◽

Qiuyun Fan ◽

...

Keyword(s):

Diffusion Mri ◽

Parallel Imaging ◽

Brain Structures ◽

Test Bed ◽

Whole Brain ◽

Isotropic Resolution ◽

Imaging Reconstruction ◽

Further Development ◽

Array Coil

AbstractWe present a whole-brain in vivo diffusion MRI (dMRI) dataset acquired at 760 μm isotropic resolution and sampled at 1260 q-space points across 9 two-hour sessions on a single healthy subject. The creation of this benchmark dataset is possible through the synergistic use of advanced acquisition hardware and software including the high-gradient-strength Connectom scanner, a custom-built 64-channel phased-array coil, a personalized motion-robust head stabilizer, a recently developed SNR-efficient dMRI acquisition method, and parallel imaging reconstruction with advanced ghost reduction algorithm. With its unprecedented resolution, SNR and image quality, we envision that this dataset will have a broad range of investigational, educational, and clinical applications that will advance the understanding of human brain structures and connectivity. This comprehensive dataset can also be used as a test bed for new modeling, sub-sampling strategies, denoising and processing algorithms, potentially providing a common testing platform for further development of in vivo high resolution dMRI techniques. Whole brain anatomical T1-weighted and T2-weighted images at submillimeter scale along with field maps are also made available.

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The role of whole‐brain diffusion MRI as a tool for studying human in vivo cortical segregation based on a measure of neurite density

Magnetic Resonance in Medicine ◽

10.1002/mrm.27150 ◽

2018 ◽

Vol 79 (5) ◽

Keyword(s):

Diffusion Mri ◽

Whole Brain ◽

Neurite Density

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Whole-brain 3D MR fingerprinting brain imaging: clinical validation and feasibility to patients with meningioma

Magnetic Resonance Materials in Physics Biology and Medicine ◽

10.1007/s10334-021-00924-1 ◽

2021 ◽

Author(s):

Thomaz R. Mostardeiro ◽

Ananya Panda ◽

Robert J. Witte ◽

Norbert G. Campeau ◽

Kiaran P. McGee ◽

...

Keyword(s):

White Matter ◽

Statistical Significance ◽

Relaxation Times ◽

Brain Structures ◽

Centrum Semiovale ◽

In Vivo Evaluation ◽

Whole Brain ◽

Mean Values ◽

Caudate Head

Abstract Purpose MR fingerprinting (MRF) is a MR technique that allows assessment of tissue relaxation times. The purpose of this study is to evaluate the clinical application of this technique in patients with meningioma. Materials and methods A whole-brain 3D isotropic 1mm3 acquisition under a 3.0T field strength was used to obtain MRF T1 and T2-based relaxometry values in 4:38 s. The accuracy of values was quantified by scanning a quantitative MR relaxometry phantom. In vivo evaluation was performed by applying the sequence to 20 subjects with 25 meningiomas. Regions of interest included the meningioma, caudate head, centrum semiovale, contralateral white matter and thalamus. For both phantom and subjects, mean values of both T1 and T2 estimates were obtained. Statistical significance of differences in mean values between the meningioma and other brain structures was tested using a Friedman’s ANOVA test. Results MR fingerprinting phantom data demonstrated a linear relationship between measured and reference relaxometry estimates for both T1 (r2 = 0.99) and T2 (r2 = 0.97). MRF T1 relaxation times were longer in meningioma (mean ± SD 1429 ± 202 ms) compared to thalamus (mean ± SD 1054 ± 58 ms; p = 0.004), centrum semiovale (mean ± SD 825 ± 42 ms; p < 0.001) and contralateral white matter (mean ± SD 799 ± 40 ms; p < 0.001). MRF T2 relaxation times were longer for meningioma (mean ± SD 69 ± 27 ms) as compared to thalamus (mean ± SD 27 ± 3 ms; p < 0.001), caudate head (mean ± SD 39 ± 5 ms; p < 0.001) and contralateral white matter (mean ± SD 35 ± 4 ms; p < 0.001) Conclusions Phantom measurements indicate that the proposed 3D-MRF sequence relaxometry estimations are valid and reproducible. For in vivo, entire brain coverage was obtained in clinically feasible time and allows quantitative assessment of meningioma in clinical practice.

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