Dataset Information

Papez Circuit Observed by in vivo Human Brain With 7.0T MRI Super-Resolution Track Density Imaging and Track Tracing.

ABSTRACT: The Papez circuit has been considered as an important anatomical substrate involved in emotional experience. However, the circuit remains difficult to elucidate in the human brain due to the resolution limit of current neuroimaging modalities. In this article, for the first time, we report the direct visualization of the Papez circuit with 7-Tesla super-resolution magnetic resonance tractography. Two healthy, young male subjects (aged 30 and 35 years) were recruited as volunteers following the guidelines of the institutional review board (IRB). Track density imaging (TDI) generation with track tracing was performed using MRtrix software package. With these tools, we were able to visualize the entire Papez circuit. We believe this is the first study to visualize the complete loop of the Papez circuit, including the perforant path (PP), thalamocortical fibers of the anterior nucleus (AN), and mammillothalamic tract (MTT), which were hitherto difficult to visualize by conventional imaging techniques.

SUBMITTER: Choi SH

PROVIDER: S-EPMC6387901 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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Papez Circuit Observed by <i>in vivo</i> Human Brain With 7.0T MRI Super-Resolution Track Density Imaging and Track Tracing.

Choi Sang-Han SH Kim Young-Bo YB Paek Sun-Ha SH Cho Zang-Hee ZH

Frontiers in neuroanatomy 20190218

The Papez circuit has been considered as an important anatomical substrate involved in emotional experience. However, the circuit remains difficult to elucidate in the human brain due to the resolution limit of current neuroimaging modalities. In this article, for the first time, we report the direct visualization of the Papez circuit with 7-Tesla super-resolution magnetic resonance tractography. Two healthy, young male subjects (aged 30 and 35 years) were recruited as volunteers following the g ...[more]

PMID: 30833891

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Project description:PurposeTo develop a super-resolution technique using convolutional neural networks for generating thin-slice knee MR images from thicker input slices, and compare this method with alternative through-plane interpolation methods.MethodsWe implemented a 3D convolutional neural network entitled DeepResolve to learn residual-based transformations between high-resolution thin-slice images and lower-resolution thick-slice images at the same center locations. DeepResolve was trained using 124 double echo in steady-state (DESS) data sets with 0.7-mm slice thickness and tested on 17 patients. Ground-truth images were compared with DeepResolve, clinically used tricubic interpolation, and Fourier interpolation methods, along with state-of-the-art single-image sparse-coding super-resolution. Comparisons were performed using structural similarity, peak SNR, and RMS error image quality metrics for a multitude of thin-slice downsampling factors. Two musculoskeletal radiologists ranked the 3 data sets and reviewed the diagnostic quality of the DeepResolve, tricubic interpolation, and ground-truth images for sharpness, contrast, artifacts, SNR, and overall diagnostic quality. Mann-Whitney U tests evaluated differences among the quantitative image metrics, reader scores, and rankings. Cohen's Kappa (κ) evaluated interreader reliability.ResultsDeepResolve had significantly better structural similarity, peak SNR, and RMS error than tricubic interpolation, Fourier interpolation, and sparse-coding super-resolution for all downsampling factors (p < .05, except 4 × and 8 × sparse-coding super-resolution downsampling factors). In the reader study, DeepResolve significantly outperformed (p < .01) tricubic interpolation in all image quality categories and overall image ranking. Both readers had substantial scoring agreement (κ = 0.73).ConclusionDeepResolve was capable of resolving high-resolution thin-slice knee MRI from lower-resolution thicker slices, achieving superior quantitative and qualitative diagnostic performance to both conventionally used and state-of-the-art methods.

Dataset Information

Papez Circuit Observed by in vivo Human Brain With 7.0T MRI Super-Resolution Track Density Imaging and Track Tracing.

Publications

Papez Circuit Observed by <i>in vivo</i> Human Brain With 7.0T MRI Super-Resolution Track Density Imaging and Track Tracing.

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