Test-retest reproducibility of in vivo oscillating gradient and microscopic anisotropy diffusion MRI in mice at 9.4 Tesla

Standardization of a silver stain to reveal mesoscale myelin in histological preparations of the mammalian brain

BACKGROUND

The brain is built of neurons supported by myelin, a fatty substance that improves cellular communication. Noninvasive magnetic resonance imaging (MRI) is now able to measure brain structure like myelin and requires histological validation.

NEW METHOD

Here we present work in small and large biomedical model mammals to standardize a silver impregnation method as a high-throughput histological myelin visualization procedure. Specifically, we built a new staining well plate to increase batch size, and then systematically varied the staining and clearing cycles to describe the staining response curve across taxa and conditions. We compared tissues fixed by immersion or perfusion, mounted versus free-floating, and cut as thicker or thinner slices, with two-weeks of post-fixation.

RESULTS

The staining response curves show optimal staining with a single exposure across taxa when incubation and clearing epochs are held to within 3-9 min. We show that clearing was slower in mounted vs free-floating tissue, and that staining was faster and caused fracturing earlier in thinner sliced and smaller volumes of tissue.

COMPARISON WITH EXISTING METHODS

We developed a batch processing approach to increase throughput while ensuring reproducibility and demonstrate the optimal conditions for fine myelinated fiber morphology visualization with short cycles (<9 minutes).

CONCLUSIONS

We present our optimized protocol to reveal mesoscale neuroanatomical myelin content in histology across mammals. This standard staining procedure will facilitate multiscale analyses of myelin content across development as well as in the presence of injury or disease.

A longitudinal microstructural MRI dataset in healthy C57Bl/6 mice at 9.4 Tesla

Multimodal microstructural MRI has shown increased sensitivity and specificity to changes in various brain disease and injury models in the preclinical setting. Here, we present an in vivo longitudinal dataset, including a subset of ex vivo data, acquired as control data and to investigate microstructural changes in the healthy mouse brain. The dataset consists of structural T2-weighted imaging, magnetization transfer ratio and saturation imaging, and advanced quantitative diffusion MRI (dMRI) methods. The dMRI methods include oscillating gradient spin echo (OGSE) dMRI and microscopic anisotropy (μA) dMRI, which provide additional insight by increasing sensitivity to smaller spatial scales and disentangling fiber orientation dispersion from true microstructural changes, respectively. The technical skills required to analyze microstructural MRI data are complex and include MRI sequence development, acquisition, and computational neuroimaging expertise. Here, we share unprocessed and preprocessed data, and scalar maps of quantitative MRI metrics. We envision utility of this dataset in the microstructural MRI field to develop and test biophysical models, methods that model temporal brain dynamics, and registration and preprocessing pipelines.

Test-Retest Reproducibility of In Vivo Magnetization Transfer Ratio and Saturation Index in Mice at 9.4 Tesla

BACKGROUND

Magnetization transfer saturation (MTsat) imaging was developed to reduce T1 dependence and improve specificity to myelin, compared to the widely used MT ratio (MTR) approach, while maintaining a feasible scan time. As MTsat imaging is an emerging technique, the reproducibility of MTsat compared to MTR must be evaluated.

PURPOSE

To assess the test-retest reproducibility of MTR and MTsat in the mouse brain at 9.4 T and calculate sample sizes potentially required to detect effect sizes ranging from 6% to 14%.

STUDY TYPE

Prospective.

SUBJECTS

Twelve healthy C57Bl/6 mice.

FIELD STRENGTH/SEQUENCE

9.4 T; magnetization transfer imaging using FLASH-3D Gradient Echo; T2-weighted TurboRARE spin echo.

ASSESSMENT

All mice were scanned at two timepoints (5 days apart). MTR and MTsat maps were analyzed using mean region-of-interest (ROIs: corpus callosum [CC], internal capsule [IC], hippocampus [HC], cortex [CX], and thalamus [TH]), and whole brain voxel-wise analysis.

STATISTICAL TESTS

Bland-Altman plots were used to assess biases between test-retest measurements. Test-retest reproducibility was evaluated via between and within-subject coefficients of variation (bsCV and wsCV, respectively). Sample sizes required were calculated (significance level: 95%; power: 80%), given effect sizes ranging from 6% to 14%, using both between and within-subject approaches. Results were considered statistically significant at P ≤ 0.05.

RESULTS

Bland-Altman plots showed negligible biases between test-retest sessions (MTR: 0.0009; MTsat: 0). ROI-based and voxel-wise CVs revealed high reproducibility for both MTR (ROI-bsCV/wsCV: CC-4.5/2.8%; IC-6.1/5.2%; HC-5.7/4.6%; CX-5.1/2.3%; TH-7.4/4.9%) and MTsat (ROI-bsCV/wsCV: CC-6.3/4.8%; IC-7.3/5.1%; HC-9.5/6.4%; CX-6.7/6.5%; TH-7.2/5.3%). With a sample size of 6, changes on the order of 15% could be detected in MTR and MTsat, both between and within subjects, while smaller changes (6%-8%) required sample sizes of 10-15 for MTR, and 15-20 for MTsat.

DATA CONCLUSION

MTsat exhibited comparable reproducibility to MTR, while providing sensitivity to myelin with less T1 dependence than MTR. EVIDENCE LEVEL: 2 TECHNICAL EFFICACY: Stage 1.

Test-retest reproducibility of in vivo oscillating gradient and microscopic anisotropy diffusion MRI in mice at 9.4 Tesla

BACKGROUND AND PURPOSE

Microstructure imaging with advanced diffusion MRI (dMRI) techniques have shown increased sensitivity and specificity to microstructural changes in various disease and injury models. Oscillating gradient spin echo (OGSE) dMRI, implemented by varying the oscillating gradient frequency, and microscopic anisotropy (μA) dMRI, implemented via tensor valued diffusion encoding, may provide additional insight by increasing sensitivity to smaller spatial scales and disentangling fiber orientation dispersion from true microstructural changes, respectively. The aims of this study were to characterize the test-retest reproducibility of in vivo OGSE and μA dMRI metrics in the mouse brain at 9.4 Tesla and provide estimates of required sample sizes for future investigations.

METHODS

Twelve adult C57Bl/6 mice were scanned twice (5 days apart). Each imaging session consisted of multifrequency OGSE and μA dMRI protocols. Metrics investigated included μA, linear diffusion kurtosis, isotropic diffusion kurtosis, and the diffusion dispersion rate (Λ), which explores the power-law frequency dependence of mean diffusivity. The dMRI metric maps were analyzed with mean region-of-interest (ROI) and whole brain voxel-wise analysis. Bland-Altman plots and coefficients of variation (CV) were used to assess the reproducibility of OGSE and μA metrics. Furthermore, we estimated sample sizes required to detect a variety of effect sizes.

RESULTS

Bland-Altman plots showed negligible biases between test and retest sessions. ROI-based CVs revealed high reproducibility for most metrics (CVs < 15%). Voxel-wise CV maps revealed high reproducibility for μA (CVs ~ 10%), but low reproducibility for OGSE metrics (CVs ~ 50%).

CONCLUSION

Most of the μA dMRI metrics are reproducible in both ROI-based and voxel-wise analysis, while the OGSE dMRI metrics are only reproducible in ROI-based analysis. Given feasible sample sizes (10-15), μA metrics and OGSE metrics may provide sensitivity to subtle microstructural changes (4-8%) and moderate changes (> 6%), respectively.