Use of magnetic resonance imaging for in vivo measurements of water content in human brain: method and normal values

Magnetic resonance fingerprinting-based myelin water fraction mapping for the assessment of white matter maturation and integrity in typical development and leukodystrophies

A quantitative biomarker for myelination, such as myelin water fraction (MWF), would boost the understanding of normative and pathological neurodevelopment, improving patients' diagnosis and follow-up. We quantified the fraction of a rapidly relaxing pool identified as MW using multicomponent three-dimensional (3D) magnetic resonance fingerprinting (MRF) to evaluate white matter (WM) maturation in typically developing (TD) children and alterations in leukodystrophies (LDs). We acquired DTI and 3D MRF-based R1, R2 and MWF data of 15 TD children and 17 LD patients (9 months-12.5 years old) at 1.5 T. We computed normative maturation curves in corpus callosum and corona radiata and performed WM tract profile analysis, comparing MWF with R1, R2 and fractional anisotropy (FA). Normative maturation curves demonstrated a steep increase for all tissue parameters in the first 3 years of age, followed by slower growth for MWF while R1, R2R2 and FA reached a plateau. Unlike FA, MWF values were similar for regions of interest (ROIs) with different degrees of axonal packing, suggesting independence from fiber bundle macro-organization and higher myelin specificity. Tract profile analysis indicated a specific spatial pattern of myelination in the major fiber bundles, consistent across subjects. LD were better distinguished from TD by MWF rather than FA, showing reduced MWF with respect to age-matched controls in both ROI-based and tract analysis. In conclusion, MRF-based MWF provides myelin-specific WM maturation curves and is sensitive to alteration due to LDs, suggesting its potential as a biomarker for WM disorders. As MRF allows fast simultaneous acquisition of relaxometry and MWF, it can represent a valuable diagnostic tool to study and follow up developmental WM disorders in children.

Strategically Acquired Gradient Echo (STAGE) Imaging, part IV: Constrained Reconstruction of White Noise (CROWN) Processing as a Means to Improve Signal-to-Noise in STAGE Imaging at 3 Tesla

Increasing the signal-to-noise ratio (SNR) has always been of critical importance for magnetic resonance imaging. Although increasing field strength provides a linear increase in SNR, it is more and more costly as field strength increases. Therefore, there is a major effort today to use signal processing methods to improve SNR since it is more efficient and economical. There are a variety of methods to improve SNR such as averaging the data at the expense of imaging time, or collecting the data with a lower resolution, all of these methods, including imaging processing methods, usually come at the expense of loss of image detail or image blurring. Therefore, we developed a new mathematical approach called CROWN (Constrained Reconstruction of White Noise) to enhance SNR without loss of structural detail and without affecting scanning time. In this study, we introduced and tested the concept behind CROWN specifically for STAGE (strategically acquired gradient echo) imaging. The concept itself is presented first, followed by simulations to demonstrate its theoretical effectiveness. Then the SNR improvement on proton spin density (PSD) and R2⁎ maps was investigated using brain STAGE data acquired from 10 healthy controls (HCs) and 10 patients with Parkinson's disease (PD). For the PSD and R2* maps, the SNR and CNR between white matter and gray matter were improved by a factor of 1.87 ± 0.50 and 1.72 ± 0.88, respectively. The white matter hyperintensity lesions in PD patients were more clearly defined after CROWN processing. Using these improved maps, simulated images for any repeat time, echo time or flip angle can be created with improved SNR. The potential applications of this technology are to trade off the increased SNR for higher resolution images and/or faster imaging.

Fast high-resolution electric properties tomography using three-dimensional quantitative transient-state imaging-based water fraction estimation

In this study, we aimed to develop a fast and robust high-resolution technique for clinically feasible electrical properties tomography based on water content maps (wEPT) using Quantitative Transient-state Imaging (QTI), a multiparametric transient state-based method that is similar to MR fingerprinting. Compared with the original wEPT implementation based on standard spin-echo acquisition, QTI provides robust electrical properties quantification towards B1 + inhomogeneities and full quantitative relaxometry data. To validate the proposed approach, 3D QTI data of 12 healthy volunteers were acquired on a 1.5 T scanner. QTI-provided T1 maps were used to compute water content maps of the tissues using an empirical relationship based on literature ex-vivo measurements. Assuming that electrical properties are modulated mainly by tissue water content, the water content maps were used to derive electrical conductivity and relative permittivity maps. The proposed technique was compared with a conventional phase-only Helmholtz EPT (HH-EPT) acquisition both within whole white matter, gray matter, and cerebrospinal fluid masks, and within different white and gray matter subregions. In addition, QTI-based wEPT was retrospectively applied to four multiple sclerosis adolescent and adult patients, compared with conventional contrast-weighted imaging in terms of lesion delineation, and quantitatively assessed by measuring the variation of electrical properties in lesions. Results obtained with the proposed approach agreed well with theoretical predictions and previous in vivo findings in both white and gray matter. The reconstructed maps showed greater anatomical detail and lower variability compared with standard phase-only HH-EPT. The technique can potentially improve delineation of pathology when compared with conventional contrast-weighted imaging and was able to detect significant variations in lesions with respect to normal-appearing tissues. In conclusion, QTI can reliably measure conductivity and relative permittivity of brain tissues within a short scan time, opening the way to the study of electric properties in clinical settings.

B1 mapping using pre-learned subspaces for quantitative brain imaging

PURPOSE

To develop a machine learning-based method for estimation of both transmitter and receiver B1 fields desired for correction of the B1 inhomogeneity effects in quantitative brain imaging.

THEORY AND METHODS

A subspace model-based machine learning method was proposed for estimation of B1t and B1r fields. Probabilistic subspace models were used to capture scan-dependent variations in the B1 fields; the subspace basis and coefficient distributions were learned from pre-scanned training data. Estimation of the B1 fields for new experimental data was achieved by solving a linear optimization problem with prior distribution constraints. We evaluated the performance of the proposed method for B1 inhomogeneity correction in quantitative brain imaging scenarios, including T1 and proton density (PD) mapping from variable-flip-angle spoiled gradient-echo (SPGR) data as well as neurometabolic mapping from MRSI data, using phantom, healthy subject and brain tumor patient data.

RESULTS

In both phantom and healthy subject data, the proposed method produced high-quality B1 maps. B1 correction on SPGR data using the estimated B1 maps produced significantly improved T1 and PD maps. In brain tumor patients, the proposed method produced more accurate and robust B1 estimation and correction results than conventional methods. The B1 maps were also applied to MRSI data from tumor patients and produced improved neurometabolite maps, with better separation between pathological and normal tissues.

CONCLUSION

This work presents a novel method to estimate B1 variations using probabilistic subspace models and machine learning. The proposed method may make correction of B1 inhomogeneity effects more robust in practical applications.

Evaluation of Gliomas with Magnetic Resonance Fingerprinting with PET Correlation-A Comparative Study

OBJECTIVES

Advanced MR imaging of brain tumors is still mainly based on qualitative imaging. PET imaging offers additive metabolic information, and MR fingerprinting (MRF) offers a novel approach to quantitative data acquisition. The purpose of this study was to evaluate the ability of MRF to predict tumor regions and grading in combination with PET.

METHODS

Seventeen patients with histologically verified infiltrating gliomas and available amino-acid PET data were enrolled. ROIs for solid tumor parts (SPo), perifocal edema (ED1), and normal-appearing white matter (NAWM) were selected on conventional MRI sequences and aligned to the MRF and PET images. The predictability of gliomas by region and grading as well as intermodal correlations were assessed.

RESULTS

For MRF, we calculated an overall predictability by region (SPo, ED1, and NAWM) for all of the MRF parameters of 76.5%, 47.1%, and 94.1%, respectively. The overall ability to distinguish low- from high-grade gliomas using MRF was 88.9% for LGG and 75% for HGG, with an accuracy of 82.4%, a ppV of 85.71%, and an npV of 80%. PET positivity was found in 13/17 patients for solid tumor parts, and in 3/17 patients for the edema region. However, there was no significant difference in region-specific MRF values between PET positive and PET negative patients.

CONCLUSIONS

MRF and PET provide quantitative measurements of the tumor tissue characteristics of gliomas, with good predictability. Nonetheless, the results are dissimilar, reflecting the different underlying mechanisms of each method.

Primary Multiparametric Quantitative Brain MRI: State-of-the-Art Relaxometric and Proton Density Mapping Techniques

This review on brain multiparametric quantitative MRI (MP-qMRI) focuses on the primary subset of quantitative MRI (qMRI) parameters that represent the mobile ("free") and bound ("motion-restricted") proton pools. Such primary parameters are the proton densities, relaxation times, and magnetization transfer parameters. Diffusion qMRI is also included because of its wide implementation in complete clinical MP-qMRI application. MP-qMRI advances were reviewed over the past 2 decades, with substantial progress observed toward accelerating image acquisition and increasing mapping accuracy. Areas that need further investigation and refinement are identified as follows: (a) the biologic underpinnings of qMRI parameter values and their changes with age and/or disease and (b) the theoretical limitations implicitly built into most qMRI mapping algorithms that do not distinguish between the different spatial scales of voxels versus spin packets, the central physical object of the Bloch theory. With rapidly improving image processing techniques and continuous advances in computer hardware, MP-qMRI has the potential for implementation in a wide range of clinical applications. Currently, three emerging MP-qMRI applications are synthetic MRI, macrostructural qMRI, and microstructural tissue modeling.

An in vivo implementation of the MEX MRI for myelin fraction of mice brain

OBJECTIVE

Magnetization EXchange (MEX) sequence measures a signal linearly dependent on the myelin proton fraction by selective suppression of water magnetization and a recovery period. Varying the recovery period enables extraction of the percentile fraction of myelin bound protons. We aim to demonstrate the MEX sequence sensitivity to the fraction of protons associated with myelin in mice brain, in vivo.

METHODS

The cuprizone mouse model was used to manipulate the myelin content. Mice fed cuprizone (n = 15) and normal chow (n = 8) were imaged in vivo using MEX sequence. MR images were segmented into corpus callosum and internal capsule (white matter) and cortical gray matter, and fitted to the recovery equation. Results were analyzed with correlation to MWF and histopathology.

RESULTS

The extracted parameters show significant differences in the corpus callosum between the cuprizone and control groups. The cuprizone group exhibited reduced myelin fraction 26.5% (P < 0.01). The gray matter values were less affected, with 13.5% reduction (P < 0.05); no changes were detected in the internal capsule. Results were validated by MWF scans and good correlation to the histology analysis (R² = 0.685).

CONCLUSION

The results of this first in vivo implementation of the MEX sequence provide a quantitative measure of demyelination in brain white matter.

Central nervous system development of cats (Felis catus L. 1758)

The morphological similarities of vertebrates' embryonic development are used as a criterion for choosing animal models that can be used in biomedical research. This study describes the embryonic and fetal development of the domestic cat's central nervous system from 15 days after conception until birth. In total, fifty-seven samples of embryos and fetuses were carefully dissected and analyzed microscopically. The closure of the neural tube was observed between 14-15th days of gestation. The differentiation of the primordial cerebral vesicles was observed from the 17th day of gestation. On the 19th day of gestation, the formation of the choroid plexus began, and on the 20th day of gestation, the brain and brainstem were well-identified macroscopically. On the 24th day of gestation, four layers of cells from the cerebral cortex were described, and on the 60th day, six layers of cells were present. The cerebellar cortex had the three classic cortical layers at this stage. The morphological aspects of embryonic and fetal development in cats were very similar to the stages of development of the human nervous system. As such, this study provided relevant information that highlights the domestic cat as an animal model option for preclinical research on infectious and non-infectious neurological diseases in humans.

Current Applications and Future Development of Magnetic Resonance Fingerprinting in Diagnosis, Characterization, and Response Monitoring in Cancer

Magnetic resonance imaging (MRI) has enabled non-invasive cancer diagnosis, monitoring, and management in common clinical settings. However, inadequate quantitative analyses in MRI continue to limit its full potential and these often have an impact on clinicians' judgments. Magnetic resonance fingerprinting (MRF) has recently been introduced to acquire multiple quantitative parameters simultaneously in a reasonable timeframe. Initial retrospective studies have demonstrated the feasibility of using MRF for various cancer characterizations. Further trials with larger cohorts are still needed to explore the repeatability and reproducibility of the data acquired by MRF. At the moment, technical difficulties such as undesirable processing time or lack of motion robustness are limiting further implementations of MRF in clinical oncology. This review summarises the latest findings and technology developments for the use of MRF in cancer management and suggests possible future implications of MRF in characterizing tumour heterogeneity and response assessment.

Conductivity Tensor Imaging of the Human Brain Using Water Mapping Techniques

Conductivity tensor imaging (CTI) has been recently proposed to map the conductivity tensor in 3D using magnetic resonance imaging (MRI) at the frequency range of the brain at rest, i.e., low-frequencies. Conventional CTI mapping methods process the trans-receiver phase of the MRI signal using the MR electric properties tomography (MR-EPT) technique, which in turn involves the application of the Laplace operator. This results in CTI maps with a low signal-to-noise ratio (SNR), artifacts at tissue boundaries and a limited spatial resolution. In order to improve on these aspects, a methodology independent from the MR-EPT method is proposed. This relies on the strong assumption for which electrical conductivity is univocally pre-determined by water concentration. In particular, CTI maps are calculated by combining high-frequency conductivity derived from water maps and multi b-value diffusion tensor imaging (DTI) data. Following the implementation of a pipeline to optimize the pre-processing of diffusion data and the fitting routine of a multi-compartment diffusivity model, reconstructed conductivity images were evaluated in terms of the achieved spatial resolution in five healthy subjects scanned at rest. We found that the pre-processing of diffusion data and the optimization of the fitting procedure improve the quality of conductivity maps. We achieve reproducible measurements across healthy participants and, in particular, we report conductivity values across subjects of 0.55 ± 0.01Sm, 0.3 ± 0.01Sm and 2.15 ± 0.02Sm for gray matter (GM), white matter (WM), and cerebrospinal fluid (CSF), respectively. By attaining an actual spatial resolution of the conductivity tensor close to 1 mm in-plane isotropic, partial volume effects are reduced leading to good discrimination of tissues with similar conductivity values, such as GM and WM. The application of the proposed framework may contribute to a better definition of the head tissue compartments in electroencephalograpy/magnetoencephalography (EEG/MEG) source imaging and be used as biomarker for assessing conductivity changes in pathological conditions, such as stroke and brain tumors.

Diffuse correlation spectroscopy measurements of blood flow using 1064 nm light

SIGNIFICANCE

Diffuse correlation spectroscopy (DCS) is an established optical modality that enables noninvasive measurements of blood flow in deep tissue by quantifying the temporal light intensity fluctuations generated by dynamic scattering of moving red blood cells. Compared with near-infrared spectroscopy, DCS is hampered by a limited signal-to-noise ratio (SNR) due to the need to use small detection apertures to preserve speckle contrast. However, DCS is a dynamic light scattering technique and does not rely on hemoglobin contrast; thus, there are significant SNR advantages to using longer wavelengths (>1000  nm) for the DCS measurement due to a variety of biophysical and regulatory factors.

AIM

We offer a quantitative assessment of the benefits and challenges of operating DCS at 1064 nm versus the typical 765 to 850 nm wavelength through simulations and experimental demonstrations.

APPROACH

We evaluate the photon budget, depth sensitivity, and SNR for detecting blood flow changes using numerical simulations. We discuss continuous wave (CW) and time-domain (TD) DCS hardware considerations for 1064 nm operation. We report proof-of-concept measurements in tissue-like phantoms and healthy adult volunteers.

RESULTS

DCS at 1064 nm offers higher intrinsic sensitivity to deep tissue compared with DCS measurements at the typically used wavelength range (765 to 850 nm) due to increased photon counts and a slower autocorrelation decay. These advantages are explored using simulations and are demonstrated using phantom and in vivo measurements. We show the first high-speed (cardiac pulsation-resolved), high-SNR measurements at large source-detector separation (3 cm) for CW-DCS and late temporal gates (1 ns) for TD-DCS.

CONCLUSIONS

DCS at 1064 nm offers a leap forward in the ability to monitor deep tissue blood flow and could be especially useful in increasing the reliability of cerebral blood flow monitoring in adults.

Statistical analysis of the accuracy of water content-based electrical properties tomography

Water content-based electrical properties tomography (wEPT) can retrieve electrical properties (EPs) from water content maps, thereby eliminating the need for B₁ field measurement in the traditional magnetic resonance electrical properties tomography method. The wEPT is performed by conventional MR scanning, such as T₁ -weighted spin-echo imaging, and thus can be directly applied to clinical settings. However, the random noise propagation involved in wEPT causes inaccuracy in EP mapping. To guarantee the EP estimates desired for clinical practice, this study statically investigates the noise-specific uncertainty of wEPT through probability density function models. We calculated the probability distribution of EP maps with different noise levels and examined the effects of scan parameters on reconstruction accuracy with various flip angles (FAs) and repetition time (TR) settings. The theoretical derivation was validated by Monte Carlo simulations and human imaging experiment at 3 T. Results showed that a serious deviation could occur in tissues with large conductivity value at a low signal-to-noise ratio and quantitatively demonstrate that such deviation could be mitigated by increased FAs or TRs. This study provided useful information for the setup of scan parameters, evaluation of accuracy of the wEPT under specific SNR levels, and promote its clinical applications.

Application of Cytokines of the Bone Morphogenetic Protein (BMP) Family in Spinal Fusion - Effects on the Bone, Intervertebral Disc and Mesenchymal Stromal Cells

Low back pain is a prevalent socio-economic burden and is often associated with damaged or degenerated intervertebral discs (IVDs). When conservative therapy fails, removal of the IVD (discectomy), followed by intersomatic spinal fusion, is currently the standard practice in clinics. The remaining space is filled with an intersomatic device (cage) and with bone substitutes to achieve disc height compensation and bone fusion. As a complication, in up to 30% of cases, spinal non-fusions result in a painful pseudoarthrosis. Bone morphogenetic proteins (BMPs) have been clinically applied with varied outcomes. Several members of the BMP family, such as BMP2, BMP4, BMP6, BMP7, and BMP9, are known to induce osteogenesis. Questions remain on why hyper-physiological doses of BMPs do not show beneficial effects in certain patients. In this respect, BMP antagonists secreted by mesenchymal cells, which might interfere with or block the action of BMPs, have drawn research attention as possible targets for the enhancement of spinal fusion or the prevention of non-unions. Examples of these antagonists are noggin, gremlin1 and 2, chordin, follistatin, BMP3, and twisted gastrulation. In this review, we discuss current evidence of the osteogenic effects of several members of the BMP family on osteoblasts, IVD cells, and mesenchymal stromal cells. We consider in vitro and in vivo studies performed in human, mouse, rat, and rabbit related to BMP and BMP antagonists in the last two decades. We give insights into the effects that BMP have on the ossification of the spine. Furthermore, the benefits, pitfalls, and possible safety concerns using these cytokines for the improvement of spinal fusion are discussed.

A Single-Scan, Rapid Whole-Brain Protocol for Quantitative Water Content Mapping With Neurobiological Implications

Water concentration is tightly regulated in the healthy human brain and changes only slightly with age and gender in healthy subjects. Consequently, changes in water content are important for the characterization of disease. MRI can be used to measure changes in brain water content, but as these changes are usually in the low percentage range, highly accurate and precise methods are required for detection. The method proposed here is based on a long-TR (10 s) multiple-echo gradient-echo measurement with an acquisition time of 7:21 min. Using such a long TR ensures that there is no T₁ weighting, meaning that the image intensity at zero echo time is only proportional to the water content, the transmit field, and to the receive field. The receive and transmit corrections, which are increasingly large at higher field strengths and for highly segmented coil arrays, are multiplicative and can be approached heuristically using a bias field correction. The method was tested on 21 healthy volunteers at 3T field strength. Calibration using cerebral-spinal fluid values (~100% water content) resulted in mean values and standard deviations of the water content distribution in white matter and gray matter of 69.1% (1.7%) and 83.7% (1.2%), respectively. Measured distributions were coil-independent, as seen by using either a 12-channel receiver coil or a 32-channel receiver coil. In a test-retest investigation using 12 scans on one volunteer, the variation in the mean value of water content for different tissue types was ~0.3% and the mean voxel variability was ~1%. Robustness against reduced SNR was assessed by comparing results for 5 additional volunteers at 1.5T and 3T. Furthermore, water content distribution in gray matter is investigated and regional contrast reported for the first time. Clinical applicability is illustrated with data from one stroke patient and one brain tumor patient. It is anticipated that this fast, stable, easy-to-use, high-quality mapping method will facilitate routine quantitative MR imaging of water content.

hMRI - A toolbox for quantitative MRI in neuroscience and clinical research

Neuroscience and clinical researchers are increasingly interested in quantitative magnetic resonance imaging (qMRI) due to its sensitivity to micro-structural properties of brain tissue such as axon, myelin, iron and water concentration. We introduce the hMRI-toolbox, an open-source, easy-to-use tool available on GitHub, for qMRI data handling and processing, presented together with a tutorial and example dataset. This toolbox allows the estimation of high-quality multi-parameter qMRI maps (longitudinal and effective transverse relaxation rates R1 and R2⋆, proton density PD and magnetisation transfer MT saturation) that can be used for quantitative parameter analysis and accurate delineation of subcortical brain structures. The qMRI maps generated by the toolbox are key input parameters for biophysical models designed to estimate tissue microstructure properties such as the MR g-ratio and to derive standard and novel MRI biomarkers. Thus, the current version of the toolbox is a first step towards in vivo histology using MRI (hMRI) and is being extended further in this direction. Embedded in the Statistical Parametric Mapping (SPM) framework, it benefits from the extensive range of established SPM tools for high-accuracy spatial registration and statistical inferences and can be readily combined with existing SPM toolboxes for estimating diffusion MRI parameter maps. From a user's perspective, the hMRI-toolbox is an efficient, robust and simple framework for investigating qMRI data in neuroscience and clinical research.

Partial volume mapping using magnetic resonance fingerprinting

Magnetic resonance fingerprinting (MRF) is a quantitative imaging technique that maps multiple tissue properties through pseudorandom signal excitation and dictionary-based reconstruction. The aim of this study is to estimate and validate partial volumes from MRF signal evolutions (PV-MRF), and to characterize possible sources of error. Partial volume model inversion (pseudoinverse) and dictionary-matching approaches to calculate brain tissue fractions (cerebrospinal fluid, gray matter, white matter) were compared in a numerical phantom and seven healthy subjects scanned at 3 T. Results were validated by comparison with ground truth in simulations and ROI analysis in vivo. Simulations investigated tissue fraction errors arising from noise, undersampling artifacts, and model errors. An expanded partial volume model was investigated in a brain tumor patient. PV-MRF with dictionary matching is robust to noise, and estimated tissue fractions are sensitive to model errors. A 6% error in pure tissue T₁ resulted in average absolute tissue fraction error of 4% or less. A partial volume model within these accuracy limits could be semi-automatically constructed in vivo using k-means clustering of MRF-mapped relaxation times. Dictionary-based PV-MRF robustly identifies pure white matter, gray matter and cerebrospinal fluid, and partial volumes in subcortical structures. PV-MRF could also estimate partial volumes of solid tumor and peritumoral edema. We conclude that PV-MRF can attribute subtle changes in relaxation times to altered tissue composition, allowing for quantification of specific tissues which occupy a fraction of a voxel.

Flexible proton density (PD) mapping using multi-contrast variable flip angle (VFA) data

Quantitative proton density (PD) maps measure the amount of free water, which is important for non-invasive tissue characterization in pathology and across lifespan. PD mapping requires the estimation and subsequent removal of factors influencing the signal intensity other than PD. These factors include the T1, T2* relaxation effects, transmit field inhomogeneities, receiver coil sensitivity profile (RP) and the spatially invariant factor that is required to scale the data. While the transmit field can be reliably measured, the RP estimation is usually based on image post-processing techniques due to limitations of its measurement at magnetic fields higher than 1.5 T. The post-processing methods are based on unified bias-field/tissue segmentation, fitting the sensitivity profile from images obtained with different coils, or on the linear relationship between T1 and PD. The scaling factor is derived from the signal within a specific tissue compartment or reference object. However, these approaches for calculating the RP and scaling factor have limitations particularly in severe pathology or over a wide age range, restricting their application. We propose a new approach for PD mapping based on a multi-contrast variable flip angle acquisition protocol and a data-driven estimation method for the RP correction and map scaling. By combining all the multi-contrast data acquired at different echo times, we are able to fully correct the MRI signal for T2* relaxation effects and to decrease the variance and the entropy of PD values within tissue class of the final map. The RP is determined from the corrected data applying a non-parametric bias estimation, and the scaling factor is based on the median intensity of an external calibration object. Finally, we compare the signal intensity and homogeneity of the multi-contrast PD map with the well-established effective PD (PD*) mapping, for which the RP is based on concurrent bias field estimation and tissue classification, and the scaling factor is estimated from the mean white matter signal. The multi-contrast PD values homogeneity and accuracy within the cerebrospinal fluid (CSF) and deep brain structures are increased beyond that obtained using PD* maps. We demonstrate that the multi-contrast RP approach is insensitive to anatomical or a priori tissue information by applying it in a patient with extensive brain abnormalities and for whole body PD mapping in post-mortem foetal imaging.

White matter intercompartmental water exchange rates determined from detailed modeling of the myelin sheath

PURPOSE

Magnetization exchange (ME) between hydrogen protons of water and large molecules (semisolids [SS]) in lipid bilayers is an important factor in MRI signal generation and can be exploited to study white matter pathology. Current models used to quantify ME in white matter generally consider water to reside in 1 or 2 distinct compartments, ignoring the complexities of the myelin sheath's multicompartment structure of alternating myelin SS and myelin water (MW) layers. Here, we investigated the effect of this by fitting ME data obtained from human brain at 7 T with a multilayer model of myelin.

METHODS

A multi-echo acquisition for a T₂ ^* -based separation of MW from other water signals was combined with various preparation pulses to change the (relative) state of the SS and water pools and analyzed by fitting with a multilayer exchange model.

RESULTS

The estimated lifetime within a single MW layer was 260 µs, corresponding to a lipid bilayer permeability of 6.7 µm/s. The magnetization lifetime of the aggregate of all MW was estimated at 13 ms, shorter than previously reported values in the range of 40 to 140 ms.

CONCLUSION

Contrary to expectations and previous reports, ME between protons in myelin SS and water is not limited by the myelin sheath but rather by the exchange between SS and water protons. The analysis of ME contrast should account for the relatively short MW lifetime and affects the interpretation of tissue compartmentalization from MRI contrasts such as T₁ - and diffusion-weighting.

Myelin water imaging to detect demyelination and remyelination and its validation in pathology

Damage to myelin is a key feature of multiple sclerosis (MS) pathology. Magnetic resonance imaging (MRI) has revolutionized our ability to detect and monitor MS pathology in vivo. Proton density, T1 and T2 can provide qualitative contrast weightings that yield superb in vivo visualization of central nervous system tissue and have proved invaluable as diagnostic and patient management tools in MS. However, standard clinical MR methods are not specific to the types of tissue damage they visualize, and they cannot detect subtle abnormalities in tissue that appears otherwise normal on conventional MRIs. Myelin water imaging is an MR method that provides in vivo measurement of myelin. Histological validation work in both human brain and spinal cord tissue demonstrates a strong correlation between myelin water and staining for myelin, validating myelin water as a marker for myelin. Myelin water varies throughout the brain and spinal cord in healthy controls, and shows good intra- and inter-site reproducibility. MS plaques show variably decreased myelin water fraction, with older lesions demonstrating the greatest myelin loss. Longitudinal study of myelin water can provide insights into the dynamics of demyelination and remyelination in plaques. Normal appearing brain and spinal cord tissues show reduced myelin water, an abnormality which becomes progressively more evident over a timescale of years. Diffusely abnormal white matter, which is evident in 20%-25% of MS patients, also shows reduced myelin water both in vivo and postmortem, and appears to originate from a primary lipid abnormality with relative preservation of myelin proteins. Active research is ongoing in the quest to refine our ability to image myelin and its perturbations in MS and other disorders of the myelin sheath.

A 3D two-point method for whole-brain water content and relaxation time mapping: Comparison with gold standard methods

Quantitative imaging of the human brain is of great interest in clinical research as it enables the identification of a range of MR biomarkers useful in diagnosis, treatment and prognosis of a wide spectrum of diseases. Here, a 3D two-point method for water content and relaxation time mapping is presented and compared to established gold standard methods. The method determines free water content, H2O, and the longitudinal relaxation time, T1, quantitatively from a two-point fit to the signal equation including corrections of the transmit and receive fields. In addition, the effective transverse relaxation time, T2*, is obtained from an exponential fit to the multi-echo signal train and its influence on H2O values is corrected. The phantom results obtained with the proposed method show good agreement for H2O and T1 values with known and spectroscopically measured values, respectively. The method is compared in vivo to already established gold standard quantitative methods. For H2O and T2* mapping, the 3D two-point results were compared to a measurement conducted with a multiple-echo GRE with long TR and T1 is compared to results from a Look-Locker method, TAPIR. In vivo results show good overall agreement between the methods, but some systematic deviations are present. Besides an expected dependence of T2* on voxel size, T1 values are systematically larger in the 3D approach than those obtained with the gold standard method. This behaviour might be due to imperfect spoiling, influencing each method differently. Results for H2O differ due to differences in the saturation of cerebrospinal fluid and partial volume effects. In addition, ground truth values of in vivo studies are unknown, even when comparing to in vivo gold standard methods. A detailed region-of-interest analysis for H2O and T1 matches well published literature values.

The role of magnetization transfer in the observed contrast in T1 weighted imaging under clinical setups

In T₁ weighted magnetic resonance imaging of brain and spinal cord in the clinical setting, the white matter (WM) appears with greater intensity than the gray matter (GM). This contrast has been assigned to differences in T₁ values. In these experiments the RF pulses are too long to excite both the water and the species with restricted motion of the protons (SRMP). In in vitro studies using short RF pulses, the contrast is reversed, with greater intensity for the GM. These results raise the question of whether magnetization transfer (MT) plays a role in the contrast observed in the T₁ weighting experiments. In the present work we implemented selective saturation recovery alone and together with the conventional magnetization transfer contrast (MTC) method. The results confirm that a major factor that determines the characteristic WM/GM averaged intensity ratio observed in T₁ weighted imaging under clinical conditions is MT between the SRMP and water. When selective saturation recovery is combined with MTC, the SRMP yields spectral widths ranging from a few to tens of kilohertz, indicating that more than one type of SRMP is involved in the MT. The z-spectrum obtained with this combination is free of the effect of direct saturation of the water peak. Selective saturation recovery enables an independent measurement of the exchange time and T₁ , while the combination with MTC with complete saturation of the SRMP enables measurement of T₁ without the effect of MT. The latter measurement can be carried out on a timescale much shorter than T_1.

A new algebraic method for quantitative proton density mapping using multi-channel coil data

A difficult problem in quantitative MRI is the accurate determination of the proton density, which is an important quantity in measuring brain tissue organization. Recent progress in estimating proton density in vivo has been based on using the inverse linear relationship between the longitudinal relaxation rate T₁ and proton density. In this study, the same type of relationship is being used, however, in a more general framework by constructing 3D basis functions to model the receiver bias field. The novelty of this method is that the basis functions developed are suitable to cover an entire range of inverse linearities between T₁ and proton density. The method is applied by parcellating the human brain into small cubes with size 30mm x 30mm x 30mm. In each cube the optimal set of basis functions is determined to model the receiver coil sensitivities using multi-channel (32 element) coil data. For validation, we use arbitrary data from a numerical phantom where the data satisfy the conventional MR signal equations. Using added noise of different magnitude and realizations, we show that the proton densities obtained have a bias close to zero and also low noise sensitivity. The obtained root-mean-square-error rate is less than 0.2% for the estimated proton density in a realistic 3D simulation. As an application, the method is used in a small cohort of MS patients, and proton density values for specific brain structures are determined.

Modeling white matter microstructure

Quantitative magnetic resonance imaging can be combined with advanced biophysical models to measure microstructural features of white matter. Non-invasive microstructural imaging has the potential to revolutionize neuroscience, and acquiring these measures in clinically feasible times would greatly improve patient monitoring and clinical studies of drug efficacy. However, a good understanding of microstructural imaging techniques is essential to set realistic expectations and to prevent over-interpretation of results. This review explains the methodology behind microstructural modeling and imaging, and gives an overview of the breakthroughs and challenges associated with it.

Magnetic Resonance of Myelin Water: An in vivo Marker for Myelin

Myelin is critical for healthy brain function. An accurate in vivo measure of myelin content has important implications for understanding brain plasticity and neurodegenerative diseases. Myelin water imaging is a magnetic resonance imaging method which can be used to visualize myelination in the brain and spinal cord in vivo. This review presents an overview of myelin water imaging data acquisition and analysis, post-mortem validation work, findings in both animal and human studies and a brief discussion about other MR techniques purported to provide in vivo myelin content. Multi-echo T₂ relaxation approaches continue to undergo development and whole-brain imaging time now takes less than 10 minutes; the standard analysis method for this type of data acquisition is a non-negative least squares approach. Alternate methods including the multi-flip angle gradient echo mcDESPOT are also being used for myelin water imaging. Histological validation studies in animal and human brain and spinal cord tissue demonstrate high specificity of myelin water imaging for myelin. Potential confounding factors for in vivo myelin water fraction measurement include the presence of myelin debris and magnetization exchange processes. Myelin water imaging has successfully been used to study animal models of injury, applied in healthy human controls and can be used to assess damage and injury in conditions such as multiple sclerosis, neuromyelitis optica, schizophrenia, phenylketonuria, neurofibromatosis, niemann pick’s disease, stroke and concussion. Other quantitative magnetic resonance approaches that are sensitive to, but not specific for, myelin exist including magnetization transfer, diffusion tensor imaging and T₁ weighted imaging.

Can MRI T1 be used to detect early changes in 5xFAD Alzheimer's mouse brain?

OBJECTIVES

In the present study, we have tested whether MRI T₁ relaxation time is a sensitive marker to detect early stages of amyloidosis and gliosis in the young 5xFAD transgenic mouse, a well-established animal model for Alzheimer's disease.

MATERIALS AND METHODS

5xFAD and wild-type mice were imaged in a 4.7 T Varian horizontal bore MRI system to generate T₁ quantitative maps using the spin-echo multi-slice sequence. Following immunostaining for glial fibrillary acidic protein, Iba-1, and amyloid-β, T₁ and area fraction of staining were quantified in the posterior parietal and primary somatosensory cortex and corpus callosum.

RESULTS

In comparison with age-matched wild-type mice, we observed first signs of amyloidosis in 2.5-month-old 5xFAD mice, and development of gliosis in 5-month-old 5xFAD mice. In contrast, MRI T₁ relaxation times of young, i.e., 2.5- and 5-month-old, 5xFAD mice were not significantly different to those of age-matched wild-type controls. Furthermore, although disease progression was detectable by increased amyloid-β load in the brain of 5-month-old 5xFAD mice compared with 2.5-month-old 5xFAD mice, MRI T₁ relaxation time did not change.

CONCLUSIONS

In summary, our data suggest that MRI T₁ relaxation time is neither a sensitive measure of disease onset nor progression at early stages in the 5xFAD mouse transgenic mouse model.

Simultaneous Quantitative Imaging of Electrical Properties and Proton Density From B1 Maps Using MRI

Electrical conductivity and permittivity of biological tissues are important diagnostic parameters and are useful for calculating subject-specific specific absorption rate distribution. On the other hand, water proton density also has clinical relevance for diagnosis purposes. These two kinds of tissue properties are inevitably associated in the technique of electrical properties tomography (EPT), which can be used to map in vivo electrical properties based on the measured B1 field distribution at Larmor frequency using magnetic resonance imaging (MRI). The signal magnitude in MR images is locally proportional to both the proton density of tissue and the receive B1 field; this is a source of artifact in receive B1-based EPT reconstruction because these two quantities cannot easily be disentangled. In this study, a new method was proposed for simultaneously extracting quantitative conductivity, permittivity and proton density from the measured magnitude of transmit B1 field, proton density-weighted receive B1 field, and transceiver phase, in a multi-channel radiofrequency (RF) coil using MRI, without specific assumptions to derive the proton density distribution. We evaluated the spatial resolution, sensitivity to contrast, and accuracy of the method using numerical simulations of B1 field in a phantom and in a realistic human head model. Using the proposed method, conductivity, permittivity and proton density were then experimentally obtained ex vivo in a pork tissue sample on a 7T MRI scanner equipped with a 16-channel microstrip transceiver RF coil.

Comparison of two quantitative proton density mapping methods in multiple sclerosis

OBJECTIVE

Proton density (PD) mapping requires correction for the receive profile (RP), which is frequently performed via bias-field correction. An alternative RP-mapping method utilizes a comparison of uncorrected PD-maps and a value ρ(T1) directly derived from T1-maps via the Fatouros equation. This may be problematic in multiple sclerosis (MS), if respective parameters are only valid for healthy brain tissue. We aimed to investigate whether the alternative method yields correct PD values in MS patients.

MATERIALS/METHODS

PD mapping was performed on 27 patients with relapsing-remitting MS and 27 healthy controls, utilizing both methods, yielding reference PD values (PD_ref, bias-field method) and PD_alt (alternative method).

RESULTS

PD_alt-values closely matched PD_ref, both for patients and controls. In contrast, ρ(T1) differed by up to 3 % from PD_ref, and the voxel-wise correlation between PD_ref and ρ(T1) was reduced in a patient subgroup with a higher degree of disability. Still, discrepancies between ρ(T1) and PD_ref were almost identical across different tissue types, thus translating into a scaling factor, which cancelled out during normalization to 100 % in CSF, yielding a good agreement between PD_alt and PD_ref.

CONCLUSION

RP correction utilizing the auxiliary parameter ρ(T1) derived via the Fatouros equation provides accurate PD results in MS patients, in spite of discrepancies between ρ(T1) and actual PD values.

Refined modelling of the short-T2 signal component and ensuing detection of glutamate and glutamine in short-TE, localised, (1) H MR spectra of human glioma measured at 3 T

Short-TE (1) H MRS has great potential for brain cancer diagnostics. A major difficulty in the analysis of the spectra is the contribution from short-T2 signal components, mainly coming from mobile lipids. This complicates the accurate estimation of the spectral parameters of the resonance lines from metabolites, so that a qualitative to semi-quantitative interpretation of the spectra dominates in practice. One solution to overcome this difficulty is to measure and estimate the short-T2 signal component and to subtract it from the total signal, thus leaving only the metabolite signals. The technique works well when applied to spectra obtained from healthy individuals, but requires some optimisation during data acquisition. In the clinical setting, time constraints hardly allow this. Here, we propose an iterative estimation of the short-T2 signal component, acquired in a single acquisition after measurement of the full spectrum. The method is based on QUEST (quantitation based on quantum estimation) and allows the refinement of the estimate of the short-T2 signal component after measurement. Thus, acquisition protocols used on healthy volunteers can also be used on patients without further optimisation. The aim is to improve metabolite detection and, ultimately, to enable the estimation of the glutamine and glutamate signals distinctly. These two metabolites are of great interest in the characterisation of brain cancer, gliomas in particular. When applied to spectra from healthy volunteers, the new algorithm yields similar results to QUEST and direct subtraction of the short-T2 signal component. With patients, up to 12 metabolites and, at least, seven can be quantified in each individual brain tumour spectrum, depending on the metabolic state of the tumour. The refinement of the short-T2 signal component significantly improves the fitting procedure and produces a separate short-T2 signal component that can be used for the analysis of mobile lipid resonances. Thus, in brain tumour spectra, distinct estimates of signals from glutamate and glutamine are possible. Copyright © 2016 John Wiley & Sons, Ltd.

Rapid measurement of brain macromolecular proton fraction with transient saturation transfer MRI

PURPOSE

To develop an efficient MRI approach to estimate the nonwater proton fraction (f) in human brain.

METHODS

We implement a brief, efficient magnetization transfer (MT) pulse that selectively saturates the magnetization of the (semi-) solid protons, and monitor the transfer of this saturation to the water protons as a function of delay after saturation.

RESULTS

Analysis of the transient MT effect with two-pool model allowed robust extraction of f at both 3 and 7 T. This required estimating the longitudinal relaxation rate constant (R_1,MP and R_1,WP ) for both proton pools, which was achieved with the assumption of uniform R_1,MP and R_1,WP across brain tissues. Resulting values of f were approximately 50% higher than reported previously, which is partly attributed to MT-pulse efficiency and R_1,MP being higher than assumed previously.

CONCLUSION

Experiments performed on human brain in vivo at 3 and 7 T demonstrate the ability of the method to robustly determine f in a scan time of approximately 5 min. Magn Reson Med 77:2174-2185, 2017. © 2016 International Society for Magnetic Resonance in Medicine.

Evaluating quantitative proton-density-mapping methods

Quantitative magnetic resonance imaging (qMRI) aims to quantify tissue parameters by eliminating instrumental bias. We describe qMRI theory, simulations, and software designed to estimate proton density (PD), the apparent local concentration of water protons in the living human brain. First, we show that, in the absence of noise, multichannel coil data contain enough information to separate PD and coil sensitivity, a limiting instrumental bias. Second, we show that, in the presence of noise, regularization by a constraint on the relationship between T1 and PD produces accurate coil sensitivity and PD maps. The ability to measure PD quantitatively has applications in the analysis of in-vivo human brain tissue and enables multisite comparisons between individuals and across instruments. Hum Brain Mapp 37:3623-3635, 2016. © 2016 Wiley Periodicals, Inc.

Electrical conductivity and permittivity maps of brain tissues derived from water content based on T1 -weighted acquisition

PURPOSE

To develop an electrical properties tomography (EPT) technique that can provide in vivo electrical conductivity and permittivity images of biological tissue without performing complex-valued radiofrequency field measurements.

THEORY AND METHODS

Electrical conductivity and permittivity images are modeled as a monotonic function of tissues' water content (W) under the principle of Maxwell's mixture theory. Water content maps are estimated from two spin-echo images having different repetition times (TRs). For the modeling functions, physically measured parameters (electrical properties, water content, and T₁ ) of brain cerebrospinal fluid (CSF), gray matter, and white matter are used as landmark literature references. The formulations are validated by a developed electrolyte-protein phantom and by human brain studies at 3 Tesla (T).

RESULTS

The electrical properties (EPs) of the phantom estimated by the proposed method match well with the values measured on the bench. The conductivity and permittivity maps from all experiments show uncompromised spatial resolution without boundary artifacts and higher contrast when compared with water content maps.

CONCLUSIONS

Human brain and phantom EP images suggest that water content is a dominating factor in determining the electrical properties of tissues. Despite possible literature inaccuracies, the proposed method offers EP maps that can provide complementary information to current approaches, to facilitate EPT scans in clinical applications. Magn Reson Med 77:1094-1103, 2017. © 2016 International Society for Magnetic Resonance in Medicine.

Quantitative T1 and proton density mapping with direct calculation of radiofrequency coil transmit and receive profiles from two-point variable flip angle data

Quantitative T1 mapping of brain tissue is frequently based on the variable flip angle (VFA) method, acquiring spoiled gradient echo (GE) datasets at different excitation angles. However, accurate T1 calculation requires a knowledge of the sensitivity profile B1 of the radiofrequency (RF) transmit coil. For an additional derivation of proton density (PD) maps, the receive coil sensitivity profile (RP) must also be known. Mapping of B1 and RP increases the experiment duration, which may be critical when investigating patients. In this work, a method is presented for the direct calculation of B1 and RP from VFA data. Thus, quantitative maps of T1 , PD, B1 and RP can be obtained from only two spoiled GE datasets. The method is based on: (1) the exploitation of the linear relationship between 1/PD and 1/T1 in brain tissue and (2) the assumption of smoothly varying B1 and RP, so that a large number of data points can be fitted across small volume elements where B1 and RP are approximately constant. The method is tested and optimized on healthy subjects. Copyright © 2016 John Wiley & Sons, Ltd.

Effects of magnetization transfer on T1 contrast in human brain white matter

MRI based on T1 relaxation contrast is increasingly being used to study brain morphology and myelination. Although it provides for excellent distinction between the major tissue types of gray matter, white matter, and CSF, reproducible quantification of T1 relaxation rates is difficult due to the complexity of the contrast mechanism and dependence on experimental details. In this work, we perform simulations and inversion-recovery MRI measurements at 3T and 7T to show that substantial measurement variability results from unintended and uncontrolled perturbation of the magnetization of MRI-invisible (1)H protons of lipids and macromolecules. This results in bi-exponential relaxation, with a fast component whose relative contribution under practical conditions can reach 20%. This phenomenon can strongly affect apparent relaxation rates, affect contrast between tissue types, and result in contrast variations over the brain. Based on this novel understanding, ways are proposed to minimize this experimental variability and its effect on T1 contrast, quantification accuracy and reproducibility.

Modeling T(1) and T(2) relaxation in bovine white matter

The fundamental basis of T1 and T2 contrast in brain MRI is not well understood; recent literature contains conflicting views on the nature of relaxation in white matter (WM). We investigated the effects of inversion pulse bandwidth on measurements of T1 and T2 in WM. Hybrid inversion-recovery/Carr-Purcell-Meiboom-Gill experiments with broad or narrow bandwidth inversion pulses were applied to bovine WM in vitro. Data were analysed with the commonly used 1D-non-negative least squares (NNLS) algorithm, a 2D-NNLS algorithm, and a four-pool model which was based upon microscopically distinguishable WM compartments (myelin non-aqueous protons, myelin water, non-myelin non-aqueous protons and intra/extracellular water) and incorporated magnetization exchange between adjacent compartments. 1D-NNLS showed that different T2 components had different T1 behaviours and yielded dissimilar results for the two inversion conditions. 2D-NNLS revealed significantly more complicated T1/T2 distributions for narrow bandwidth than for broad bandwidth inversion pulses. The four-pool model fits allow physical interpretation of the parameters, fit better than the NNLS techniques, and fits results from both inversion conditions using the same parameters. The results demonstrate that exchange cannot be neglected when analysing experimental inversion recovery data from WM, in part because it can introduce exponential components having negative amplitude coefficients that cannot be correctly modeled with nonnegative fitting techniques. While assignment of an individual T1 to one particular pool is not possible, the results suggest that under carefully controlled experimental conditions the amplitude of an apparent short T1 component might be used to quantify myelin water.

Improved visibility of brain tumors in synthetic MP-RAGE anatomies with pure T1 weighting

Conventional MRI for brain tumor diagnosis employs T2 -weighted and contrast-enhanced T1 -weighted sequences. Non-enhanced T1 -weighted images provide improved anatomical details for precise tumor location, but reduced tumor-to-background contrast as elevated T1 and proton density (PD) values in tumor tissue affect the signal inversely. Radiofrequency (RF) coil inhomogeneities may further mask tumor and edema outlines. To overcome this problem, the aims of this work were to employ quantitative MRI techniques to create purely T1 -weighted synthetic anatomies which can be expected to yield improved tissue and tumor-to-background contrasts, to compare the quality of conventional and synthetic anatomies, and to investigate optical contrast and visibility of brain tumors and edema in synthetic anatomies. Conventional magnetization-prepared rapid acquisition of gradient echoes (MP-RAGE) anatomies and maps of T1 , PD and RF coil profiles were acquired in comparable and clinically feasible times. Three synthetic MP-RAGE anatomies (PD T1 weighting both with and without RF bias; pure T1 weighting) were calculated for healthy subjects and 32 patients with brain tumors. In healthy subjects, the PD T1 -weighted synthetic anatomies with RF bias precisely matched the conventional anatomies, yielding high signal-to-noise (SNR) and contrast-to-noise (CNR) ratios. Pure T1 weighting yielded lower SNR, but high CNR, because of increased optical contrasts. In patients with brain tumors, synthetic anatomies with pure T1 weighting yielded significant increases in optical contrast and improved visibility of tumor and edema in comparison with anatomies reflecting conventional T1 contrasts. In summary, the optimized purely T1 -weighted synthetic anatomy with an isotropic resolution of 1 mm, as proposed in this work, considerably enhances optical contrast and visibility of brain tumors and edema.

Tumor T1 Relaxation Time for Assessing Response to Bevacizumab Anti-Angiogenic Therapy in a Mouse Ovarian Cancer Model

Purpose

To assess whether T₁ relaxation time of tumors may be used to assess response to bevacizumab anti-angiogenic therapy. Procedures: 12 female nude mice bearing subcutaneous SKOV3ip1-LC ovarian tumors were administered bevacizumab (6.25ug/g, n=6) or PBS (control, n=6) therapy twice a week for two weeks. T₁ maps of tumors were generated before, two days, and 2 weeks after initiating therapy. Tumor weight was assessed by MR and at necropsy. Histology for microvessel density, proliferation, and apoptosis was performed.

Results

Bevacizumab treatment resulted in tumor growth inhibition (p<0.04, n=6), confirming therapeutic efficacy. Tumor T₁ relaxation times increased in bevacizumab treated mice 2 days and 2 weeks after initiating therapy (p<.05, n=6). Microvessel density decreased 59% and cell proliferation (Ki67+) decreased 50% in the bevacizumab treatment group (p<.001, n=6), but not apoptosis.

Conclusions

Findings suggest that increased tumor T₁ relaxation time is associated with response to bevacizumab therapy in ovarian cancer model and might serve as an early indicator of response.

Increased cerebral water content in hemodialysis patients

Little information is available on the impact of hemodialysis on cerebral water homeostasis and its distribution in chronic kidney disease. We used a neuropsychological test battery, structural magnetic resonance imaging (MRI) and a novel technique for quantitative measurement of localized water content using 3T MRI to investigate ten hemodialysis patients (HD) on a dialysis-free day and after hemodialysis (2.4±2.2 hours), and a matched healthy control group with the same time interval. Neuropsychological testing revealed mainly attentional and executive cognitive dysfunction in HD. Voxel-based-morphometry showed only marginal alterations in the right inferior medial temporal lobe white matter in HD compared to controls. Marked increases in global brain water content were found in the white matter, specifically in parietal areas, in HD patients compared to controls. Although the global water content in the gray matter did not differ between the two groups, regional increases of brain water content in particular in parieto-temporal gray matter areas were observed in HD patients. No relevant brain hydration changes were revealed before and after hemodialysis. Whereas longer duration of dialysis vintage was associated with increased water content in parieto-temporal-occipital regions, lower intradialytic weight changes were negatively correlated with brain water content in these areas in HD patients. Worse cognitive performance on an attention task correlated with increased hydration in frontal white matter. In conclusion, long-term HD is associated with altered brain tissue water homeostasis mainly in parietal white matter regions, whereas the attentional domain in the cognitive dysfunction profile in HD could be linked to increased frontal white matter water content.

Blood flow restricted and traditional resistance training performed to fatigue produce equal muscle hypertrophy

This study investigated the hypertrophic potential of load-matched blood-flow restricted resistance training (BFR) vs free-flow traditional resistance training (low-load TRT) performed to fatigue. Ten healthy young subjects performed unilateral BFR and contralateral low-load TRT elbow flexor dumbbell curl with 40% of one repetition maximum until volitional concentric failure 3 days per week for 6 weeks. Prior to and at 3 (post-3) and 10 (post-10) days post-training, magnetic resonance imaging (MRI) was used to estimate elbow flexor muscle volume and muscle water content accumulation through training. Acute changes in muscle thickness following an early vs a late exercise bout were measured with ultrasound to determine muscle swelling during the immediate 0-48 h post-exercise. Total work was threefold lower for BFR compared with low-load TRT (P < 0.001). Both BRF and low-load TRT increased muscle volume by approximately 12% at post-3 and post-10 (P < 0.01) with no changes in MRI-determined water content. Training increased muscle thickness during the immediate 48 h post-exercise (P < 0.001) and to greater extent with BRF (P < 0.05) in the early training phase. In conclusion, BFR and low-load TRT, when performed to fatigue, produce equal muscle hypertrophy, which may partly rely on transient exercise-induced increases in muscle water content.

Lifespan maturation and degeneration of human brain white matter

Properties of human brain tissue change across the lifespan. Here we model these changes in the living human brain by combining quantitative magnetic resonance imaging (MRI) measurements of R1 (1/T1) with diffusion MRI and tractography (N=102, ages 7-85). The amount of R1 change during development differs between white-matter fascicles, but in each fascicle the rate of development and decline are mirror-symmetric; the rate of R1 development as the brain approaches maturity predicts the rate of R1 degeneration in aging. Quantitative measurements of macromolecule tissue volume (MTV) confirm that R1 is an accurate index of the growth of new brain tissue. In contrast to R1, diffusion development follows an asymmetric time-course with rapid childhood changes but a slow rate of decline in old age. Together, the time-courses of R1 and diffusion changes demonstrate that multiple biological processes drive changes in white-matter tissue properties over the lifespan.

Sensitivity of near-infrared spectroscopy and diffuse correlation spectroscopy to brain hemodynamics: simulations and experimental findings during hypercapnia

Near-infrared spectroscopy (NIRS) and diffuse correlation spectroscopy (DCS) are two diffuse optical technologies for brain imaging that are sensitive to changes in hemoglobin concentrations and blood flow, respectively. Measurements for both modalities are acquired on the scalp, and therefore hemodynamic processes in the extracerebral vasculature confound the interpretation of cortical hemodynamic signals. The sensitivity of NIRS to the brain versus the extracerebral tissue and the contrast-to-noise ratio (CNR) of NIRS to cerebral hemodynamic responses have been well characterized, but the same has not been evaluated for DCS. This is important to assess in order to understand their relative capabilities in measuring cerebral physiological changes. We present Monte Carlo simulations on a head model that demonstrate that the relative brain-to-scalp sensitivity is about three times higher for DCS (0.3 at 3 cm) than for NIRS (0.1 at 3 cm). However, because DCS has higher levels of noise due to photon-counting detection, the CNR is similar for both modalities in response to a physiologically realistic simulation of brain activation. Even so, we also observed higher CNR of the hemodynamic response during graded hypercapnia in adult subjects with DCS than with NIRS.

Review of treatment assessment using DCE-MRI in breast cancer radiation therapy

As a noninvasive functional imaging technique, dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is being used in oncology to measure properties of tumor microvascular structure and permeability. Studies have shown that parameters derived from certain pharmacokinetic models can be used as imaging biomarkers for tumor treatment response. The use of DCE-MRI for quantitative and objective assessment of radiation therapy has been explored in a variety of methods and tumor types. However, due to the complexity in imaging technology and divergent outcomes from different pharmacokinetic approaches, the method of using DCE-MRI in treatment assessment has yet to be standardized, especially for breast cancer. This article reviews the basic principles of breast DCE-MRI and recent studies using DCE-MRI in treatment assessment. Technical and clinical considerations are emphasized with specific attention to assessment of radiation treatment response.

Myelin, myelination, and corresponding magnetic resonance imaging changes

Accurate diagnosis of white matter diseases requires a thorough understanding of white matter maturation. These maturational changes are complex and require knowledge of the histologic background and time course of development. This article reviews the in vivo magnetic resonance (MR) appearance of myelination with emphasis on the appearance of different regions of the brain using various pulse sequences at different developmental time points. The appearance of white matter, using the MR pulse sequences that have been shown to be most useful during the stages of myelination, is also discussed.

A general linear relaxometry model of R1 using imaging data

PURPOSE

The longitudinal relaxation rate (R1 ) measured in vivo depends on the local microstructural properties of the tissue, such as macromolecular, iron, and water content. Here, we use whole brain multiparametric in vivo data and a general linear relaxometry model to describe the dependence of R1 on these components. We explore a) the validity of having a single fixed set of model coefficients for the whole brain and b) the stability of the model coefficients in a large cohort.

METHODS

Maps of magnetization transfer (MT) and effective transverse relaxation rate (R2 *) were used as surrogates for macromolecular and iron content, respectively. Spatial variations in these parameters reflected variations in underlying tissue microstructure. A linear model was applied to the whole brain, including gray/white matter and deep brain structures, to determine the global model coefficients. Synthetic R1 values were then calculated using these coefficients and compared with the measured R1 maps.

RESULTS

The model's validity was demonstrated by correspondence between the synthetic and measured R1 values and by high stability of the model coefficients across a large cohort.

CONCLUSION

A single set of global coefficients can be used to relate R1 , MT, and R2 * across the whole brain. Our population study demonstrates the robustness and stability of the model.

High resolution MRI anatomy of the cat brain at 3 Tesla

BACKGROUND

Feline models of neurologic diseases, such as lysosomal storage diseases, leukodystrophies, Parkinson's disease, stroke and NeuroAIDS, accurately recreate many aspects of human disease allowing for comparative study of neuropathology and the testing of novel therapeutics. Here we describe in vivo visualization of fine structures within the feline brain that were previously only visible post mortem.

NEW METHOD

3Tesla MR images were acquired using T1-weighted (T1w) 3D magnetization-prepared rapid gradient echo (MPRAGE) sequence (0.4mm isotropic resolution) and T2-weighted (T2w) turbo spin echo (TSE) images (0.3mm×0.3mm×1mm resolution). Anatomic structures were identified based on feline and canine histology.

RESULTS

T2w high resolution MR images with detailed structural identification are provided in transverse, sagittal and dorsal planes. T1w MR images are provided electronically in three dimensions for unrestricted spatial evaluation.

COMPARISON WITH EXISTING METHODS

Many areas of the feline brain previously unresolvable on MRI are clearly visible in three orientations, including the dentate, interpositus and fastigial cerebellar nuclei, cranial nerves, lateral geniculate nucleus, optic radiation, cochlea, caudal colliculus, temporal lobe, precuneus, spinocerebellar tract, vestibular nuclei, reticular formation, pyramids and rostral and middle cerebral arteries. Additionally, the feline brain is represented in three dimensions for the first time.

CONCLUSIONS

These data establish normal appearance of detailed anatomical structures of the feline brain, which provide reference when evaluating neurologic disease or testing efficacy of novel therapeutics in animal models.