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Spatiotemporal maturation patterns of murine brain quantified by diffusion tensor MRI and deformation-based morphometry.

ABSTRACT: Highly heterogeneous spatiotemporal patterns of maturation of the murine brain during the first 80 postnatal days were examined by high-dimensional deformation-based morphometry applied to high-resolution diffusion tensor MRIs. The maturation profile revealed a sharp contrast between tissue anisotropy changes in the cortex and in major white-matter fibers. Radially oriented tissue anisotropy was measured during the first postnatal week in cortical regions, reflecting the underlying columnar organization of the cortex. Subsequently, tissue anisotropy reduced rapidly, potentially reflecting the growth of randomly oriented dendritic trees that reduce tissue coorientation. Distinct anisotropy patterns were also observed along layer I of the cortex and were attributed to thin fibers oriented parallel to the outer surface. Last, spatially complex patterns of maturation were measured in all major axonal pathways and in the hippocampus, caudate putamen, and cerebellum. This analysis provides a framework for quantifying normative maturation patterns against which phenotypes of mice of different genetic and environmental backgrounds can be contrasted.

SUBMITTER: Verma R

PROVIDER: S-EPMC1100736 | biostudies-literature | 2005 May

REPOSITORIES: biostudies-literature

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Spatiotemporal maturation patterns of murine brain quantified by diffusion tensor MRI and deformation-based morphometry.

Verma Ragini R Mori Susumu S Shen Dinggang D Yarowsky Paul P Zhang Jiangyang J Zhang Jiangyang J Davatzikos Christos C

Proceedings of the National Academy of Sciences of the United States of America 20050428 19

Highly heterogeneous spatiotemporal patterns of maturation of the murine brain during the first 80 postnatal days were examined by high-dimensional deformation-based morphometry applied to high-resolution diffusion tensor MRIs. The maturation profile revealed a sharp contrast between tissue anisotropy changes in the cortex and in major white-matter fibers. Radially oriented tissue anisotropy was measured during the first postnatal week in cortical regions, reflecting the underlying columnar orga ...[more]

PMID: 15860588

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Project description:BackgroundDynamic diffusion magnetic resonance imaging (ddMRI) metrics can assess transient microstructural alterations in tissue diffusivity but requires additional scan time hindering its clinical application.PurposeTo determine whether a diffusion gradient table can simultaneously acquire data to estimate dynamic and diffusion tensor imaging (DTI) metrics.Study typeProspective.SubjectsSeven healthy subjects, 39 epilepsy patients (15 female, 31 male, age ± 15).Field strength/sequenceTwo-dimensional diffusion MRI (b = 1000 s/mm2 ) at a field strength of 3 T. Sessions in healthy subjects-standard ddMRI (30 directions), standard DTI (15 and 30 directions), and nested cubes scans (15 and 30 directions). Sessions in epilepsy patients-two 30 direction (standard ddMRI, 10 nested cubes) or two 15 direction scans (standard DTI, 5 nested cubes).AssessmentFifteen direction DTI was repeated twice for within-session test-retest measurements in healthy subjects. Bland-Altman analysis computed bias and limits of agreement for DTI metrics using test-retest scans and standard 15 direction vs. 5 nested cubes scans. Intraclass correlation (ICC) analysis compared tensor metrics between 15 direction DTI scans (standard vs. 5 nested cubes) and the coefficients of variation (CoV) of trace and apparent diffusion coefficient (ADC) between 30 direction ddMRI scans (standard vs. 10 nested cubes).Statistical testsBland-Altman and ICC analysis using a P-value of 0.05 for statistical significance.ResultsCorrelations of mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD) were strong and significant in gray (ICC > 0.95) and white matter (ICC > 0.95) between standard vs. nested cubes DTI acquisitions. Correlation of white matter fractional anisotropy was also strong (ICC > 0.95) and significant. ICCs of the CoV of dynamic ADC measured using repeated cubes and nested cubes acquisitions were modest (ICC >0.60), but significant in gray matter.ConclusionA nested cubes diffusion gradient table produces tensor-based and dynamic diffusion measurements in a single acquisition.Level of evidence2 TECHNICAL EFFICACY: Stage 1.

Project description:ObjectivesMultiple b-value gas diffusion-weighted MRI (DW-MRI) enables non-invasive and quantitative assessment of lung morphometry, but its long acquisition time is not well-tolerated by patients. We aimed to accelerate multiple b-value gas DW-MRI for lung morphometry using deep learning.MethodsA deep cascade of residual dense network (DC-RDN) was developed to reconstruct high-quality DW images from highly undersampled k-space data. Hyperpolarized 129Xe lung ventilation images were acquired from 101 participants and were retrospectively collected to generate synthetic DW-MRI data to train the DC-RDN. Afterwards, the performance of the DC-RDN was evaluated on retrospectively and prospectively undersampled multiple b-value 129Xe MRI datasets.ResultsEach slice with size of 64 × 64 × 5 could be reconstructed within 7.2 ms. For the retrospective test data, the DC-RDN showed significant improvement on all quantitative metrics compared with the conventional reconstruction methods (p < 0.05). The apparent diffusion coefficient (ADC) and morphometry parameters were not significantly different between the fully sampled and DC-RDN reconstructed images (p > 0.05). For the prospectively accelerated acquisition, the required breath-holding time was reduced from 17.8 to 4.7 s with an acceleration factor of 4. Meanwhile, the prospectively reconstructed results showed good agreement with the fully sampled images, with a mean difference of -0.72% and -0.74% regarding global mean ADC and mean linear intercept (Lm) values.ConclusionsDC-RDN is effective in accelerating multiple b-value gas DW-MRI while maintaining accurate estimation of lung microstructural morphometry, facilitating the clinical potential of studying lung diseases with hyperpolarized DW-MRI.Key points• The deep cascade of residual dense network allowed fast and high-quality reconstruction of multiple b-value gas diffusion-weighted MRI at an acceleration factor of 4. • The apparent diffusion coefficient and morphometry parameters were not significantly different between the fully sampled images and the reconstructed results (p > 0.05). • The required breath-holding time was reduced from 17.8 to 4.7 s and each slice with size of 64 × 64 × 5 could be reconstructed within 7.2 ms.

Dataset Information

Spatiotemporal maturation patterns of murine brain quantified by diffusion tensor MRI and deformation-based morphometry.

Publications

Spatiotemporal maturation patterns of murine brain quantified by diffusion tensor MRI and deformation-based morphometry.

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