The anisotropy of water diffusion in brain tissue is affected by both disease and development. This change can be detected using diffusion MRI and is often quantified by the fractional anisotropy (FA) derived from diffusion tensor imaging (DTI). Although FA is sensitive to anisotropic cell structures, such as axons, it is also sensitive to their orientation dispersion. This is a major limitation to the use of FA as a biomarker for “tissue integrity”, especially in regions of complex microarchitecture. In this work, we seek to circumvent this limitation by disentangling the effects of microscopic diffusion anisotropy from the orientation dispersion. The microscopic fractional anisotropy (μFA) and the order parameter (OP) were calculated from the contrast between signal prepared with directional and isotropic diffusion encoding, where the latter was achieved by magic angle spinning of the q-vector (qMAS). These parameters were quantified in healthy volunteers and in two patients; one patient with meningioma and one with glioblastoma. Finally, we used simulations to elucidate the relation between FA and μFA in various micro-architectures. Generally, μFA was high in the white matter and low in the gray matter. In the white matter, the largest differences between μFA and FA were found in crossing white matter and in interfaces between large white matter tracts, where μFA was high while FA was low. Both tumor types exhibited a low FA, in contrast to the μFA which was high in the meningioma and low in the glioblastoma, indicating that the meningioma contained disordered anisotropic structures, while the glioblastoma did not. This interpretation was confirmed by histological examination. We conclude that FA from DTI reflects both the amount of diffusion anisotropy and orientation dispersion. We suggest that the μFA and OP may complement FA by independently quantifying the microscopic anisotropy and the level of orientation coherence.

The structural heterogeneity of tumor tissue can be probed by diffusion MRI (dMRI) in terms of the variance of apparent diffusivities within a voxel. However, the link between the diffusional variance and the tissue heterogeneity is not well-established. To investigate this link we test the hypothesis that diffusional variance, caused by microscopic anisotropy and isotropic heterogeneity, is associated with variable cell eccentricity and cell density in brain tumors. We performed dMRI using a novel encoding scheme for diffusional variance decomposition (DIVIDE) in 7 meningiomas and 8 gliomas prior to surgery. The diffusional variance was quantified from dMRI in terms of the total mean kurtosis (MKT), and DIVIDE was used to decompose MKT into components caused by microscopic anisotropy (MKA) and isotropic heterogeneity (MKI). Diffusion anisotropy was evaluated in terms of the fractional anisotropy (FA) and microscopic fractional anisotropy (μFA). Quantitative microscopy was performed on the excised tumor tissue, where structural anisotropy and cell density were quantified by structure tensor analysis and cell nuclei segmentation, respectively. In order to validate the DIVIDE parameters they were correlated to the corresponding parameters derived from microscopy. We found an excellent agreement between the DIVIDE parameters and corresponding microscopy parameters; MKA correlated with cell eccentricity (r = 0.95, p < 10−7) and MKI with the cell density variance (r = 0.83, p < 10−3). The diffusion anisotropy correlated with structure tensor anisotropy on the voxel-scale (FA, r = 0.80, p < 10−3) and microscopic scale (μFA, r = 0.93, p < 10−6). A multiple regression analysis showed that the conventional MKT parameter reflects both variable cell eccentricity and cell density, and therefore lacks specificity in terms of microstructure characteristics. However, specificity was obtained by decomposing the two contributions; MKA was associated only to cell eccentricity, and MKI only to cell density variance. The variance in meningiomas was caused primarily by microscopic anisotropy (mean ± s.d.) MKA = 1.11 ± 0.33 vs MKI = 0.44 ± 0.20 (p < 10−3), whereas in the gliomas, it was mostly caused by isotropic heterogeneity MKI = 0.57 ± 0.30 vs MKA = 0.26 ± 0.11 (p < 0.05). In conclusion, DIVIDE allows noninvasive mapping of parameters that reflect variable cell eccentricity and density. These results constitute convincing evidence that a link exists between specific aspects of tissue heterogeneity and parameters from dMRI. Decomposing effects of microscopic anisotropy and isotropic heterogeneity facilitates an improved interpretation of tumor heterogeneity as well as diffusion anisotropy on both the microscopic and macroscopic scale.

Clinical trials using cells derived from embryonic ventral mesencephalon have shown that transplanted dopaminergic neurons can survive and function in the long term, as demonstrated by in vivo brain imaging using 18F-fluorodopa and 11C-raclopride positron emission tomography. Here we report the postmortem analysis of a patient with Parkinson’s disease who 24 y earlier underwent unilateral transplantation of embryonic dopaminergic neurons in the putamen and subsequently exhibited major motor improvement and recovery of striatal dopaminergic function. Histopathological analysis showed that a dense, near-normal graft-derived dopaminergic reinnervation of the putamen can be maintained for a quarter of a century despite severe host brain pathology and with no evidence of immune response. In addition, ubiquitin- and α-synuclein–positive inclusions were seen, some with the appearance of typical Lewy bodies, in 11–12% of the grafted dopaminergic neurons, reflecting the spread of pathology from the host brain to the transplants. Because the clinical benefits induced by transplantation in this patient were gradually lost after 14 y posttransplantation, our findings provide the first reported evidence, to our knowledge, that even a viable dopaminergic graft giving rise to extensive striatal reinnervation may lose its efficacy if widespread degenerative changes develop in the host brain.

We present the first in vivo application of the filter-exchange imaging protocol for diffusion MRI. The protocol allows noninvasive mapping of the rate of water exchange between microenvironments with different self-diffusivities, such as the intracellular and extracellular spaces in tissue. Since diffusional water exchange across the cell membrane is a fundamental process in human physiology and pathophysiology, clinically feasible and noninvasive imaging of the water exchange rate would offer new means to diagnose disease and monitor treatment response in conditions such as cancer and edema. The in vivo use of filter-exchange imaging was demonstrated by studying the brain of five healthy volunteers and one intracranial tumor (meningioma). Apparent exchange rates in white matter range from 0.8±0.08 s(-1) in the internal capsule, to 1.6±0.11 s(-1) for frontal white matter, indicating that low values are associated with high myelination. Solid tumor displayed values of up to 2.9±0.8 s(-1). In white matter, the apparent exchange rate values suggest intra-axonal exchange times in the order of seconds, confirming the slow exchange assumption in the analysis of diffusion MRI data. We propose that filter-exchange imaging could be used clinically to map the water exchange rate in pathologies. Filter-exchange imaging may also be valuable for evaluating novel therapies targeting the function of aquaporins.

Water exchange through the cell membranes is an important feature of cells and tissues. The rate of exchange is determined by factors such as membrane lipid composition and organization, as well as the type and activity of aquaporins. A method for noninvasively estimating the rate of water exchange would be useful for characterizing pathological conditions, e.g., tumors, multiple sclerosis, and ischemic stroke, expected to be associated with a change of the membrane barrier properties. This study describes the filter exchange imaging method for determining the rate of water exchange between sites having different apparent diffusion coefficients. The method is based on the filter-exchange pulsed gradient spin-echo NMR spectroscopy experiment, which is here modified to be compatible with the constraints of clinical MR scanners. The data is analyzed using a modelfree approach yielding maps of the apparent exchange rate, here being introduced in analogy with the concept of the apparent diffusion coefficient. Proof-of-principle experiments are performed on microimaging and whole-body clinical scanners using yeast suspension phantoms. The limitations and appropriate experimental conditions are examined. The results demonstrate that filter exchange imaging is a fast and reliable method for characterizing exchange, and that it has the potential to become a powerful diagnostic tool. Magn Reson Med 66:356-365,

Many axons follow wave-like undulating courses. This is a general feature of extracranial nerve segments, but is also found in some intracranial nervous tissue. The importance of axonal undulation has previously been considered, for example, in the context of biomechanics, where it has been shown that posture affects undulation properties. However, the importance of axonal undulation in the context of diffusion MR measurements has not been investigated. Using an analytical model and Monte Carlo simulations of water diffusion, this study compared undulating and straight axons in terms of diffusion propagators, diffusion-weighted signal intensities and parameters derived from diffusion tensor imaging, such as the mean diffusivity (MD), the eigenvalues and the fractional anisotropy (FA). All parameters were strongly affected by the presence of undulation. The diffusivity perpendicular to the undulating axons increased with the undulation amplitude, thus resembling that of straight axons with larger diameters. Consequently, models assuming straight axons for the estimation of the axon diameter from diffusion MR measurements might overestimate the diameter if undulation is present. FA decreased from approximately 0.7 to 0.5 when axonal undulation was introduced into the simulation model structure. Our results indicate that axonal undulation may play a role in diffusion measurements when investigating, for example, the optic and sciatic nerves and the spinal cord. The simulations also demonstrate that the stretching or compression of neuronal tissue comprising undulating axons alters the observed water diffusivity, suggesting that posture may be of importance for the outcome of diffusion MRI measurements.

Biophysical models that describe the outcome of white matter diffusion MRI experiments have various degrees of complexity. While the simplest models assume equal-sized and parallel axons, more elaborate ones may include distributions of axon diameters and axonal orientation dispersions. These microstructural features can be inferred from diffusion-weighted signal attenuation curves by solving an inverse problem, validated in several Monte Carlo simulation studies. Model development has been paralleled by microscopy studies of the microstructure of excised and fixed nerves, confirming that axon diameter estimates from diffusion measurements agree with those from microscopy. However, results obtained in vivo are less conclusive. For example, the amount of slowly diffusing water is lower than expected, and the diffusion-encoded signal is apparently insensitive to diffusion time variations, contrary to what may be expected. Recent understandings of the resolution limit in diffusion MRI, the rate of water exchange, and the presence of microscopic axonal undulation and axonal orientation dispersions may, however, explain such apparent contradictions. Knowledge of the effects of biophysical mechanisms on water diffusion in tissue can be used to predict the outcome of diffusion tensor imaging (DTI) and of diffusion kurtosis imaging (DKI) studies. Alterations of DTI or DKI parameters found in studies of pathologies such as ischemic stroke can thus be compared with those predicted by modelling. Observations in agreement with the predictions strengthen the credibility of biophysical models; those in disagreement could provide clues of how to improve them. DKI is particularly suited for this purpose; it is performed using higher b-values than DTI, and thus carries more information about the tissue microstructure. The purpose of this review is to provide an update on the current understanding of how various properties of the tissue microstructure and the rate of water exchange between microenvironments are reflected in diffusion MRI measurements. We focus on the use of biophysical models for extracting tissue-specific parameters from data obtained with single PGSE sequences on clinical MRI scanners, but results obtained with animal MRI scanners are also considered. While modelling of white matter is the central theme, experiments on model systems that highlight important aspects of the biophysical models are also reviewed.

The purpose of this study was to develop multimodality SPECT/ MRI contrast agents for sentinel lymph node (SLN) mapping in vivo. Methods: Nanoparticles with a solid iron oxide core and a polyethylene glycol coating were labeled with 99m Tc. The labeling efficiency was determined with instant thin-layer chromatography and magnetic separation. The stability of the radiolabeled superparamagnetic iron oxide nanoparticles (SPIONs) was verified in both sterile water and human serum at room temperature 6 and 24 h after labeling. Five Wistar rats were injected subcutaneously in the right hind paw with 99m Tc-SPIONs (25-50 MBq, ;0.2 mg of Fe) and sacrificed 4 h after injection. Two animals were imaged with SPECT/MRI. All 5 rats were dissected; the lymph nodes, liver, kidneys, spleen, and hind paw containing the injection site were removed and weighed; and activity in the samples was measured. The microdistribution within the lymph nodes was studied with digital autoradiography. Results: The efficiency of labeling of the SPIONs was 99% 6 h after labeling in both water and human serum. The labeling yield was 98% in water and 97% in human serum 24 h after labeling. The SLN could be identified in vivo with SPECT/MRI. The accumulation of 99m Tc-SPIONs (as the percentage injected dose/g [%ID/g]) in the SLN was 100 % ID/g, whereas in the liver and spleen it was less than 2 %ID/g. Digital autoradiography images revealed a nonhomogeneous distribution of 99m Tc-SPIONs within the lymph nodes; nanoparticles were found in the cortical, subcapsular, and medullary sinuses. Conclusion: This study revealed the feasibility of labeling SPIONs with 99m Tc. The accumulation of 99m Tc-SPIONs in lymph nodes after subcutaneous injection in animals, verified by SPECT/MRI, is encouraging for applications in breast cancer and malignant melanoma. The sentinel lymph node (SLN) is defined as the first regional lymph node receiving lymphatic drainage from a malignant tumor (1) and the first node to which metastatic cells are likely to anchor. Therefore, accurate detection and characterization of the SLN is of major importance for cancer staging and for the choice of therapy in patients with breast cancer and malignant melanoma. The current gold standard relies on lymphoscintigraphy after intradermal injection of radiolabeled colloids and blue dye to intraoperatively identify the SLN by dissection and histopathologic examination (2). The radiopharmaceuticals most frequently used for SLN imaging are 99m Tc-labeled colloids and macromolecules such as trisulfide, dextran, and human serum albumin (3-5). The current technique, however, is limited because of the nonspecificity of the tracer and the lack of anatomic information in scintigraphic images. Preoperative planning and identification of the SLN often rely on the experience of the surgeon.We propose combining information from high-resolution MRI and high-sensitivity SPECT images to provide more accurate and less invasive identification of the SLN before surgery. The use of radioactivity would help to ...