Comparison of diffusion MRI and CLARITY fiber orientation estimates in both gray and white matter regions of human and primate brain.

Diffusion MRI (dMRI) represents one of the few methods for mapping brain fiber orientations non-invasively. Unfortunately, dMRI fiber mapping is an indirect method that relies on inference from measured diffusion patterns. Comparing dMRI results with other modalities is a way to improve the interpretation of dMRI data and help advance dMRI technologies. Here, we present methods for comparing dMRI fiber orientation estimates with optical imaging of fluorescently labeled neurofilaments and vasculature in 3D human and primate brain tissue cuboids cleared using CLARITY. The recent advancements in tissue clearing provide a new opportunity to histologically map fibers projecting in 3D, which represents a captivating complement to dMRI measurements. In this work, we demonstrate the capability to directly compare dMRI and CLARITY in the same human brain tissue and assess multiple approaches for extracting fiber orientation estimates from CLARITY data. We estimate the three-dimensional neuronal fiber and vasculature orientations from neurofilament and vasculature stained CLARITY images by calculating the tertiary eigenvector of structure tensors. We then extend CLARITY orientation estimates to an orientation distribution function (ODF) formalism by summing multiple sub-voxel structure tensor orientation estimates. In a sample containing part of the human thalamus, there is a mean angular difference of 19o±15o between the primary eigenvectors of the dMRI tensors and the tertiary eigenvectors from the CLARITY neurofilament stain. We also demonstrate evidence that vascular compartments do not affect the dMRI orientation estimates by showing an apparent lack of correspondence (mean angular difference = 49o±23o) between the orientation of the dMRI tensors and the structure tensors in the vasculature stained CLARITY images. In a macaque brain dataset, we examine how the CLARITY feature extraction depends on the chosen feature extraction parameters. By varying the volume of tissue over which the structure tensor estimates are derived, we show that orientation estimates are noisier with more spurious ODF peaks for sub-voxels below 30 µm3 and that, for our data, the optimal gray matter sub-voxel size is between 62.5 µm3 and 125 µm3. The example experiments presented here represent an important advancement towards robust multi-modal MRI-CLARITY comparisons.

Streamline density and lesion volume reveal a postero-anterior gradient of corpus callosum damage in multiple sclerosis.

BACKGROUND AND PURPOSE: Although interhemispheric disconnection significantly contributes to disability in multiple sclerosis (MS), the topography, timeline and relationship of callosal damage accrual with hemispheric damage are still unclear. METHODS: Streamline density and the presence of focal lesions in five callosal subregions were computed in 55 people with MS [13 relapsing-remitting (RRMS), 20 secondary progressive (SPMS), 22 primary progressive (PPMS)] and 24 healthy controls. RESULTS: Streamline density decrease was identified in SPMS in all corpus callosum (CC) subregions, in PPMS in the posterior CC and mid-posterior CC and in RRMS in the posterior CC. CC density was independently predicted by CC lesion volume and hemispheric lesion volume and independently predicted visuospatial memory, Expanded Disability Status Scale, manual dexterity and ambulation. CONCLUSIONS: The reduction in CC density across phenotypes suggests an earlier involvement of the posterior regions, followed only at a later stage by involvement of the anterior portions of the CC. Such interhemispheric disconnection seems to develop as a consequence of white matter macroscopic damage and exerts a relevant impact on motor and, to a lesser extent, cognitive disability.

A multi-contrast MRI study of microstructural brain damage in patients with mild cognitive impairment.

OBJECTIVES: The aim of this study was to investigate pathological mechanisms underlying brain tissue alterations in mild cognitive impairment (MCI) using multi-contrast 3 T magnetic resonance imaging (MRI). METHODS: Forty-two MCI patients and 77 healthy controls (HC) underwent T1/T2* relaxometry as well as Magnetization Transfer (MT) MRI. Between-groups comparisons in MRI metrics were performed using permutation-based tests. Using MRI data, a generalized linear model (GLM) was computed to predict clinical performance and a support-vector machine (SVM) classification was used to classify MCI and HC subjects. RESULTS: Multi-parametric MRI data showed microstructural brain alterations in MCI patients vs HC that might be interpreted as: (i) a broad loss of myelin/cellular proteins and tissue microstructure in the hippocampus (p ≤ 0.01) and global white matter (p < 0.05); and (ii) iron accumulation in the pallidus nucleus (p ≤ 0.05). MRI metrics accurately predicted memory and executive performances in patients (p ≤ 0.005). SVM classification reached an accuracy of 75% to separate MCI and HC, and performed best using both volumes and T1/T2*/MT metrics. CONCLUSION: Multi-contrast MRI appears to be a promising approach to infer pathophysiological mechanisms leading to brain tissue alterations in MCI. Likewise, parametric MRI data provide powerful correlates of cognitive deficits and improve automatic disease classification based on morphometric features.

Structured sparsity for spatially coherent fibre orientation estimation in diffusion MRI.

We propose a novel formulation to solve the problem of intra-voxel reconstruction of the fibre orientation distribution function (FOD) in each voxel of the white matter of the brain from diffusion MRI data. The majority of the state-of-the-art methods in the field perform the reconstruction on a voxel-by-voxel level, promoting sparsity of the orientation distribution. Recent methods have proposed a global denoising of the diffusion data using spatial information prior to reconstruction, while others promote spatial regularisation through an additional empirical prior on the diffusion image at each q-space point. Our approach reconciles voxelwise sparsity and spatial regularisation and defines a spatially structured FOD sparsity prior, where the structure originates from the spatial coherence of the fibre orientation between neighbour voxels. The method is shown, through both simulated and real data, to enable accurate FOD reconstruction from a much lower number of q-space samples than the state of the art, typically 15 samples, even for quite adverse noise conditions.

3D printing of rat salivary glands: The submandibular-sublingual complex.

The morphology and the functionality of the murid glandular complex, composed of the submandibular and sublingual salivary glands (SSC), were the object of several studies conducted mainly using magnetic resonance imaging (MRI). Using a 4.7 T scanner and a manganese-based contrast agent, we improved the signal-to-noise ratio of the SSC relating to the surrounding anatomical structures allowing to obtain high-contrast 3D images of the SSC. In the last few years, the large development in resin melting techniques opened the way for printing 3D objects starting from a 3D stack of images. Here, we demonstrate the feasibility of the 3D printing technique of soft tissues such as the SSC in the rat with the aim to improve the visualization of the organs. This approach is useful to preserve the real in vivo morphology of the SCC in living animals avoiding the anatomical shape changes due to the lack of relationships with the surrounding organs in case of extraction. It is also harmless, repeatable and can be applied to explore volumetric changes occurring during body growth, excretory duct obstruction, tumorigenesis and regeneration processes. 3D printing allows to obtain a solid object with the same shape of the organ of interest, which can be observed, freely rotated and manipulated. To increase the visibility of the details, it is possible to print the organs with a selected zoom factor, useful as in case of tiny organs in small mammalia. An immediate application of this technique is represented by educational classes.

Migraineurs without aura show microstructural abnormalities in the cerebellum and frontal lobe.

The involvement of the cerebellum in migraine pathophysiology is not well understood. We used a biparametric approach at high-field MRI (3 T) to assess the structural integrity of the cerebellum in 15 migraineurs with aura (MWA), 23 migraineurs without aura (MWoA), and 20 healthy controls (HC). High-resolution T1 relaxation maps were acquired together with magnetization transfer images in order to probe microstructural and myelin integrity. Clusterwise analysis was performed on T1 and magnetization transfer ratio (MTR) maps of the cerebellum of MWA, MWoA, and HC using an ANOVA and a non-parametric clusterwise permutation F test, with age and gender as covariates and correction for familywise error rate. In addition, mean MTR and T1 in frontal regions known to be highly connected to the cerebellum were computed. Clusterwise comparison among groups showed a cluster of lower MTR in the right Crus I of MWoA patients vs. HC and MWA subjects (p = 0.04). Univariate and bivariate analysis on T1 and MTR contrasts showed that MWoA patients had longer T1 and lower MTR in the right and left pars orbitalis compared to MWA (p < 0.01 and 0.05, respectively), but no differences were found with HC. Lower MTR and longer T1 point at a loss of macromolecules and/or micro-edema in Crus I and pars orbitalis in MWoA patients vs. HC and vs. MWA. The pathophysiological implications of these findings are discussed in light of recent literature.

A multi-center study: intra-scan and inter-scan variability of diffusion spectrum imaging.

The objective of this study was to investigate whether it is possible to pool together diffusion spectrum imaging data from four different scanners, located at three different sites. Two of the scanners had identical configuration whereas two did not. To measure the variability, we extracted three scalar maps (ADC, FA and GFA) from the DSI and utilized a region and a tract-based analysis. Additionally, a phantom study was performed to rule out some potential factors arising from the scanner performance in case some systematic bias occurred in the subject study. This work was split into three experiments: intra-scanner reproducibility, reproducibility with twin-scanner settings and reproducibility with other configurations. Overall for the intra-scanner and twin-scanner experiments, the region-based analysis coefficient of variation (CV) was in a range of 1%-4.2% and below 3% for almost every bundle for the tract-based analysis. The uncinate fasciculus showed the worst reproducibility, especially for FA and GFA values (CV 3.7-6%). For the GFA and FA maps, an ICC value of 0.7 and above is observed in almost all the regions/tracts. Looking at the last experiment, it was found that there is a very high similarity of the outcomes from the two scanners with identical setting. However, this was not the case for the two other imagers. Given the fact that the overall variation in our study is low for the imagers with identical settings, our findings support the feasibility of cross-site pooling of DSI data from identical scanners.

Experimental protocol for activation-induced manganese-enhanced MRI (AIM-MRI) based on quantitative determination of Mn content in rat brain by fast T1 mapping.

In activation-induced manganese-enhanced MRI (AIM-MRI) experiments, differential accumulation of Mn in activated and silent brain areas is generally assessed using T(1)-weighted images and quantified by the enhancement of signal intensity (SI), calculated with reference to SI before Mn administration or to SI of brain regions unaffected by the specific stimulus. However, SI enhancement can be unreliable when animals are removed from and reinserted into the magnet. We have developed an experimental protocol based on repeated intraperitoneal (i.p.) injections of Mn, quantitative determination of T(1), and coregistration of images to a rat brain atlas that allows absolute quantification of Mn concentration in selected brain areas. Results showed that interanimal variability of postcontrast T(1) values was very low (compared to the experimental error in T(1) determinations) allowing detection of differential regional Mn uptake in stimulated and unstimulated animals. In addition we have determined in vivo relaxivity of Mn in brain tissue and its frequency dependence.

DCE-MRI data analysis for cancer area classification.

OBJECTIVES: The paper aims at improving the support of medical researchers in the context of in-vivo cancer imaging. Morphological and functional parameters obtained by dynamic contrast-enhanced MRI (DCE-MRI) techniques are analyzed, which aim at investigating the development of tumor microvessels. The main contribution consists in proposing a machine learning methodology to segment automatically these MRI data, by isolating tumor areas with different meaning, in a histological sense. METHODS: The proposed approach is based on a three-step procedure: i) robust feature extraction from raw time-intensity curves, ii) voxel segmentation, and iii) voxel classification based on a learning-by-example approach. In the first step, few robust features that compactly represent the response of the tissue to the DCE-MRI analysis are computed. The second step provides a segmentation based on the mean shift (MS) paradigm, which has recently shown to be robust and useful for different and heterogeneous clustering tasks. Finally, in the third step, a support vector machine (SVM) is trained to classify voxels according to the labels obtained by the clustering phase (i.e., each class corresponds to a cluster). Indeed, the SVM is able to classify new unseen subjects with the same kind of tumor. RESULTS: Experiments on different subjects affected by the same kind of tumor evidence that the extracted regions by both the MS clustering and the SVM classifier exhibit a precise medical meaning, as carefully validated by the medical researchers. Moreover, our approach is more stable and robust than methods based on quantification of DCE-MRI data by means of pharmacokinetic models. CONCLUSIONS: The proposed method allows to analyze the DCE-MRI data more precisely and faster than previous automated or manual approaches.

Inhibition of tyrosine kinase receptors by SU6668 promotes abnormal stromal development at the periphery of carcinomas.

Dynamic contrast-enhanced (albumin-Gd-DTPA) magnetic resonance imaging, performed during 2 weeks of daily administration of an inhibitor of tyrosine kinase receptors (SU6668) in an HT-29 colon carcinoma model, revealed the onset of a hyper-enhancing rim, not observed in untreated tumours. To account for tissue heterogeneity in the quantitative analysis, we segmented tumours into three subunits automatically identified by cluster analysis of the enhancement curves using a k-means algorithm. Transendothelial permeability (Kps) and fractional plasma volume (fPV) were calculated in each subunit. An avascular and necrotic region, an intermediate zone and a well-vascularised periphery were reliably identified. During untreated tumour growth, the identified sub-regions did not substantially change their enhancement pattern. Treatment with SU6668 induced major changes at tumour periphery where a significant increase of Kps and fPV was observed with respect to control tumours. Histology revealed a sub-capsular layer composed of hyper-dense viable tumour cells in the periphery of untreated tumours. The rim of viable neoplastic cells was reduced in treated tumours, and replaced by loose connective tissue characterised by numerous vessels, which explains the observed hyper-enhancement. The present data show a peripheral abnormal development of cancer-associated stroma, indicative of an adaptive response to anti-angiogenic treatment.

Synthesis and characterization of polyethylenimine-based iron oxide composites as novel contrast agents for MRI.

OBJECT: Use of polyethylenimines (PEIs) of different molecular weight and selected carboxylated-PEI derivatives (PEI-COOH) in the synthesis and stabilization of iron oxide nanoparticles, to obtain possible multifunctional contrast agents. MATERIALS AND METHODS: Oxidation of Fe(II) at slightly elevated pH and temperature resulted in the formation of highly soluble and stable nanocomposites of iron oxides and polymer. Composites were characterized and studied by atomic force microscopy (AFM), transmission electron microscopy (TEM), X-ray diffractometry, AC and DC magnetometry, NMR relaxometry and magnetic resonance imaging (MRI). RESULTS: From AFM the dimensions of the aggregates were found to be in the ~150-250 nm size region; the mean diameter of the magnetic core of the compounds named PEI-25, PEI-500 and PEI-COOH60 resulted d approximately 20 +/- 5 nm for PEI-25, d approximately 9.5 +/- 1.0 nm for PEI-500 and d approximately 6.8 +/- 1.0 nm for PEI-COOH60. In PEI-COOH60 TEM and X-ray diffractometry revealed small assemblies of mineral magnetic cores with clear indications that the main constituents are maghemite and/or magnetite as confirmed by AC and DC SQUID magnetometry. For PEI-COOH60, the study of NMR-dispersion profiles revealed r (1) and r (2) relaxivities comparable to superparamagnetic iron-oxide commercial compounds in the whole investigated frequency range 7 < or = nu < or = 212 MHz. CONCLUSION: PEI-25 was studied as possible MRI contrast agent (CA) to map the cerebral blood volume (CBV) and cerebral blood flow (CBF) in an animal model obtaining promising results. The reported compounds may be further functionalized to afford novel multifunctional systems for biomedical applications.