Investigating microstructural changes between in vivo and perfused ex vivo marmoset brains using oscillating gradient and b-tensor encoded diffusion MRI at 9.4 T.

PURPOSE: To investigate microstructural alterations induced by perfusion fixation in brain tissues using advanced diffusion MRI techniques and estimate their potential impact on the application of ex vivo models to in vivo microstructure. METHODS: We used oscillating gradient spin echo (OGSE) and b-tensor encoding diffusion MRI to examine in vivo and ex vivo microstructural differences in the marmoset brain. OGSE was used to shorten effective diffusion times, whereas b-tensor encoding allowed for the differentiation of isotropic and anisotropic kurtosis. Additionally, we performed Monte Carlo simulations to estimate the potential microstructural changes in the tissues. RESULTS: We report large changes (˜50%-60%) in kurtosis frequency dispersion (OGSE) and in both anisotropic and isotropic kurtosis (b-tensor encoding) after perfusion fixation. Structural MRI showed an average volume reduction of about 10%. Monte Carlo simulations indicated that these alterations could likely be attributed to extracellular fluid loss possibly combined with axon beading and increased dot compartment signal fraction. Little evidence was observed for reductions in axonal caliber. CONCLUSION: Our findings shed light on advanced MRI parameter changes that are induced by perfusion fixation and potential microstructural sources for these changes. This work also suggests that caution should be exercised when applying ex vivo models to infer in vivo tissue microstructure, as significant differences may arise.

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.

High-resolution quantitative acoustic microscopy of cutaneous carcinoma and melanoma: Comparison with histology.

BACKGROUND: The increased incidence rate of skin cancers during the last decades is alarming. One of the significant difficulties in the histopathology of skin cancers is appearance variability due to the heterogeneity of diseases or tissue preparation and staining process. This study aims to investigate whether the high-resolution acoustic microscopy has the potential for identifying and quantitatively classifying skin cancers. MATERIAL/METHODS: Unstained standard formalin-fixed skin tissue samples were used for ultrasonic examination. The high-frequency acoustic microscope equipped with the 320 MHz transducer was utilized to visualize skin structure. Fourier transform was performed to calculate the sound speed and attenuation in the tissue. RESULTS: The acoustic images demonstrate good concordance with the traditional histology images. All histological features in the tumour were easily identifiable on acoustic images. Each skin cancer type has its combination of ultrasonic properties significantly different from the healthy skin. CONCLUSIONS: High-resolution acoustic imaging strengthened with quantitative analysis shows a potential to work as an auxiliary imaging modality assisting pathologists to lean to the particular decision in doubtful cases. The method can also assist surgeon to ensure the complete resection of a tumour.

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 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.

Rosai Dorfman disease.

We report an unusual presentation of sinus histiocytosis with massive lymphadenopathy (SHML), also called Rosai Dorfman disease. The child presented with bilateral proptosis with massive cervical lymphadenopathy. The patient had fair response to steroid therapy but relapsed during the course of the disease.