T 2 mapping of cerebrospinal fluid: 3 T versus 7 T

Association of Cortical Lesions With Regional Glutamate, GABA, N-Acetylaspartate, and Myoinositol Levels in Patients With Multiple Sclerosis

BACKGROUND AND OBJECTIVES

Cortical lesions contribute to disability in multiple sclerosis (MS), but their impact on regional neurotransmitter levels remains to be clarified. We tested the hypothesis that cortical lesions are associated with regional glutamate and gamma-aminobutyric acid (GABA) concentrations within the affected cortical region.

METHODS

In this cross-sectional study, we used structural 7T MRI to segment cortical lesions and 7T proton MR-spectroscopy of the bilateral sensorimotor hand areas to quantify regional GABA, glutamate, N-acetylaspartate, and myoinositol concentrations in patients with MS (inclusion criteria: diagnosis of relapsing-remitting [RR] or secondary progressive MS [SPMS]; age 18-80 years) and age and sex-matched healthy controls. Data were collected at a single center between August 2018 and September 2020. Linear mixed-effects models were used to test for associations between metabolite concentrations and cortical lesion volumes within the same MR-spectroscopy voxel.

RESULTS

Forty-seven patients with MS (34 RRMS, 13 SPMS; 45.1 ± 12.5 years; 31 women) and 23 healthy controls (44.4 ± 13 years, 15 women) were studied. In patients, higher regional glutamate and lower regional GABA concentrations were associated with larger cortical lesion volume within the MR-spectroscopy voxel [glutamate: 0.61 (95% CI 0.19-1.03) log(mm3), p = 0.005, GABA: -0.71 (-1.24 to -0.18) log(mm3), p = 0.01]. In addition, lower N-acetylaspartate levels [-0.37 (-0.67 to -0.07) log(mm3), p = 0.016] and higher myoinositol levels [0.48 (0.03-0.93) log(mm3), p = 0.037] were associated with a larger regional cortical lesion volume. Furthermore, glutamate concentrations were reduced in patients with SPMS compared with healthy participants [-0.75 (-1.3 to -0.19) mM, p = 0.005] and patients with RRMS [-0.55 (-1.07 to -0.02) mM, p = 0.04]. N-acetylaspartate levels were lower in both patients with RRMS [-0.81 (-1.39 to -0.24) mM, p = 0.003] and SPMS [-1.31 (-2.07 to -0.54) mM, p < 0.001] when compared with healthy controls. Creatine-normalized N-acetylaspartate levels were associated with performance in the 9-hole peg test of the contralateral hand [-0.004 (-0.007 to -0.002) log(s), p = 0.002], and reduced mean creatine-normalized glutamate was associated with increased Expanded Disability Status Scale (R = -0.39, p = 0.02).

DISCUSSION

Cortical lesions are associated with local increases in glutamate and a reduction in GABA concentration within the lesional or perilesional tissue. Further studies are needed to investigate the causal relationship between cortical lesions and changes in neurotransmitter concentrations.

Metabolite T2 relaxation times decrease across the adult lifespan in a large multi-site cohort

Purpose

Relaxation correction is crucial for accurately estimating metabolite concentrations measured using in vivo magnetic resonance spectroscopy (MRS). However, the majority of MRS quantification routines assume that relaxation values remain constant across the lifespan, despite prior evidence of T2 changes with aging for multiple of the major metabolites. Here, we comprehensively investigate correlations between T2 and age in a large, multi-site cohort.

Methods

We recruited approximately 10 male and 10 female participants from each decade of life: 18-29, 30-39, 40-49, 50-59, and 60+ years old (n=101 total). We collected PRESS data at 8 TEs (30, 50, 74, 101, 135, 179, 241, and 350 ms) from voxels placed in white-matter-rich centrum semiovale (CSO) and gray-matter-rich posterior cingulate cortex (PCC). We quantified metabolite amplitudes using Osprey and fit exponential decay curves to estimate T2.

Results

Older age was correlated with shorter T2 for tNAA, tCr3.0, tCr3.9, tCho, Glx, and tissue water in CSO and PCC; rs = -0.21 to -0.65, all p<0.05, FDR-corrected for multiple comparisons. These associations remained statistically significant when controlling for cortical atrophy. T2 values did not differ across the adult lifespan for mI. By region, T2 values were longer in the CSO for tNAA, tCr3.0, tCr3.9, Glx, and tissue water and longer in the PCC for tCho and mI.

Conclusion

These findings underscore the importance of considering metabolite T2 changes with aging in MRS quantification. We suggest that future 3T work utilize the equations presented here to estimate age-specific T2 values instead of relying on uniform default values.

A model-based MR parameter mapping network robust to substantial variations in acquisition settings

Deep learning methods show great potential for the efficient and precise estimation of quantitative parameter maps from multiple magnetic resonance (MR) images. Current deep learning-based MR parameter mapping (MPM) methods are mostly trained and tested using data with specific acquisition settings. However, scan protocols usually vary with centers, scanners, and studies in practice. Thus, deep learning methods applicable to MPM with varying acquisition settings are highly required but still rarely investigated. In this work, we develop a model-based deep network termed MMPM-Net for robust MPM with varying acquisition settings. A deep learning-based denoiser is introduced to construct the regularization term in the nonlinear inversion problem of MPM. The alternating direction method of multipliers is used to solve the optimization problem and then unrolled to construct MMPM-Net. The variation in acquisition parameters can be addressed by the data fidelity component in MMPM-Net. Extensive experiments are performed on R2 mapping and R1 mapping datasets with substantial variations in acquisition settings, and the results demonstrate that the proposed MMPM-Net method outperforms other state-of-the-art MR parameter mapping methods both qualitatively and quantitatively.

Imaging of 17O-labeled Water Using Fast T2 Mapping with T2-preparation: A Phantom Study

17O-labeled water is a T2-shortening contrast agent used in proton MRI and is a promising method for visualizing cerebrospinal fluid (CSF) dynamics because it provides long-term tracking of water molecules. However, various external factors reduce the accuracy of 17O-concentration measurements using conventional signal-intensity-based methods. In addition, T2 mapping, which is expected to provide a stable assessment, is generally limited to temporal-spatial resolution. We developed the T2-prepared based on T2 mapping used in cardiac imaging to adapt to long T2 values and tested whether it could accurately measure 17O-concentration in the CSF using a phantom. The results showed that 17O-concentration in a fluid mimicking CSF could be evaluated with an accuracy comparable to conventional T2-mapping (Carr-Purcell-Meiboom-Gill multi-echo spin-echo method). This method allows 17O-imaging with a high temporal resolution and stability in proton MRI. This imaging technique may be promising for visualizing CSF dynamics using 17O-labeled water.

SIMPLEX: Multiple phase-cycled bSSFP quantitative magnetization transfer imaging with physic-guided simulation learning of neural network

Most quantitative magnetization transfer (qMT) imaging methods require acquiring additional quantitative maps (such as T1) for data fitting. A method based on multiple phase-cycled bSSFP was recently proposed to enable high-resolution 3D qMT imaging based on least square fitting without any extra acquisition, and thus has high potential for simplifying the qMT procedure. However, the quantification of qMT parameters with this method was suboptimal, limiting its potential for clinical application despite its simpler protocol and higher spatial resolution. To improve the fitting of qMT data obtained with multiple phase-cycled bSSFP, we propose SIMulation-based Physics-guided Learning of neural network for qMT parameters EXtraction, or SIMPLEX. In contrast to previous deep learning supervised approaches for quantitative MR that require the acquisition of input data and corresponding ground truth for training, we leveraged the MR signal model to generate training samples without expensive data curation. The network was trained exclusively with simulation data by predicting the simulation parameters. The same network was applied directly to in-vivo data without additional training. The approach was verified with both simulation and in-vivo data. SIMPLEX showed a decrease in fitting mean squared error for all simulation data compared to the existing least-square fitting method. The in-vivo experiment revealed that the network performed well with the real in vivo data unseen during training. For all experiments, we observed that SIMPLEX consistently improved the quantification quality of the qMT parameters whilst being more robust to noise compared to the prior technique. The proposed SIMPLEX will expedite the routine clinical application of qMT by providing qMT parameters (exchange rate, pool fraction) as well as T1, T2, and ΔB0 maps simultaneously with high spatial resolution, better reliability, and reduced processing time.

Quantification of T1 and T2 of subarachnoid CSF: Implications for water exchange between CSF and brain tissues

PURPOSE

To quantify the T1 and T2 values of CSF in the subarachnoid space (SAS) at 3 T and interpret them in the context of water exchange between CSF and brain tissues.

METHODS

CSF T1 was measured using inversion recovery, and CSF T2 was assessed using T2 -preparation. T1 and T2 values in the SAS were compared with those in the frontal horns of lateral ventricles, which have less brain-CSF exchange. Phantom experiments were performed to examine whether there were spatial variations in T1 and T2 that were unrelated to brain-CSF exchange. Simulations were conducted to investigate the relationship between the brain-CSF exchange rate and the apparent T1 and T2 values of SAS CSF.

RESULTS

The CSF T1 and T2 values were 4308.7 ± 146.9 ms and 1885.5 ± 67.9 ms, respectively, in the SAS and were 4454.0 ± 187.9 ms and 2372.9 ± 72.0 ms in the frontal horns. The SAS CSF had shorter T1 (p = 0.006) and T2 (p < 0.0001) than CSF in the frontal horns. Phantom experiments showed negligible (< 6 ms for T1 ; < 1 ms for T2 ) spatial variations in T1 and T2 , suggesting that the T1 and T2 differences between SAS and frontal horns were largely attributed to physiological reasons. Simulations revealed that faster brain-CSF exchange rates lead to shorter apparent T1 and T2 of SAS CSF. However, the experimentally observed T2 difference between SAS and frontal horns was greater than that attributable to typical exchange effect, suggesting that the T2 shortening in SAS may reflect a combined effect of exchange and deoxyhemoglobin susceptibility.

CONCLUSION

Quantification of SAS CSF relaxation times may be useful to assess the brain-CSF exchange.

Data-driven electrical conductivity brain imaging using 3 T MRI

Magnetic resonance electrical properties tomography (MR-EPT) is a non-invasive measurement technique that derives the electrical properties (EPs, e.g., conductivity or permittivity) of tissues in the radiofrequency range (64 MHz for 1.5 T and 128 MHz for 3 T MR systems). Clinical studies have shown the potential of tissue conductivity as a biomarker. To date, model-based conductivity reconstructions rely on numerical assumptions and approximations, leading to inaccuracies in the reconstructed maps. To address such limitations, we propose an artificial neural network (ANN)-based non-linear conductivity estimator trained on simulated data for conductivity brain imaging. Network training was performed on 201 synthesized T2-weighted spin-echo (SE) data obtained from the finite-difference time-domain (FDTD) electromagnetic (EM) simulation. The dataset was composed of an approximated T2-w SE magnitude and transceive phase information. The proposed method was tested three in-silico and in-vivo on two volunteers and three patients' data. For comparison purposes, various conventional phase-based EPT reconstruction methods were used that ignoreB 1 + magnitude information, such as Savitzky-Golay kernel combined with Gaussian filter (S-G Kernel), phase-based convection-reaction EPT (cr-EPT), magnitude-weighted polynomial-fitting phase-based EPT (Poly-Fit), and integral-based phase-based EPT (Integral-based). From the in-silico experiments, quantitative analysis showed that the proposed method provides more accurate and improved quality (e.g., high structural preservation) conductivity maps compared to conventional reconstruction methods. Representatively, in the healthy brain in-silico phantom experiment, the proposed method yielded mean conductivity values of 1.97 ± 0.20 S/m for CSF, 0.33 ± 0.04 S/m for WM, and 0.52 ± 0.08 S/m for GM, which were closer to the ground-truth conductivity (2.00, 0.30, 0.50 S/m) than the integral-based method (2.56 ± 2.31, 0.39 ± 0.12, 0.68 ± 0.33 S/m). In-vivo ANN-based conductivity reconstructions were also of improved quality compared to conventional reconstructions and demonstrated network generalizability and robustness to in-vivo data and pathologies. The reported in-vivo brain conductivity values were in agreement with literatures. In addition, the proposed method was observed for various SNR levels (SNR levels = 10, 20, 40, and 58) and repeatability conditions (the eight acquisitions with the number of signal averages = 1). The preliminary investigations on brain tumor patient datasets suggest that the network trained on simulated dataset can generalize to unforeseen in-vivo pathologies, thus demonstrating its potential for clinical applications.

Towards a barrier-free anthropomorphic brain phantom for quantitative magnetic resonance imaging: Design, first construction attempt, and challenges

Existing magnetic resonance imaging (MRI) reference objects, or phantoms, are typically constructed from simple liquid or gel solutions in containers with specific geometric configurations to enable multi-year stability. However, there is a need for phantoms that better mimic the human anatomy without barriers between the tissues. Barriers result in regions without MRI signal between the different tissue mimics, which is an artificial image artifact. We created an anatomically representative 3D structure of the brain that mimicked the T1 and T2 relaxation properties of white and gray matter at 3 T. While the goal was to avoid barriers between tissues, the 3D printed barrier between white and gray matter and other flaws in the construction were visible at 3 T. Stability measurements were made using a portable MRI system operating at 64 mT, and T2 relaxation time was stable from 0 to 22 weeks. The phantom T1 relaxation properties did change from 0 to 10 weeks; however, they did not substantially change between 10 weeks and 22 weeks. The anthropomorphic phantom used a dissolvable mold construction method to better mimic anatomy, which worked in small test objects. The construction process, though, had many challenges. We share this work with the hope that the community can build on our experience.

Association of brain tissue cerebrospinal fluid fraction with age in healthy cognitively normal adults

Background and purpose

Our objective was to apply multi-compartment T2 relaxometry in cognitively normal individuals aged 20-80 years to study the effect of aging on the parenchymal CSF fraction (CSFF), a potential measure of the subvoxel CSF space.

Materials and methods

A total of 60 volunteers (age range, 22-80 years) were enrolled. Voxel-wise maps of short-T2 myelin water fraction (MWF), intermediate-T2 intra/extra-cellular water fraction (IEWF), and long-T2 CSFF were obtained using fast acquisition with spiral trajectory and adiabatic T2prep (FAST-T2) sequence and three-pool non-linear least squares fitting. Multiple linear regression analyses were performed to study the association between age and regional MWF, IEWF, and CSFF measurements, adjusting for sex and region of interest (ROI) volume. ROIs include the cerebral white matter (WM), cerebral cortex, and subcortical deep gray matter (GM). In each model, a quadratic term for age was tested using an ANOVA test. A Spearman's correlation between the normalized lateral ventricle volume, a measure of organ-level CSF space, and the regional CSFF, a measure of tissue-level CSF space, was computed.

Results

Regression analyses showed that there was a statistically significant quadratic relationship with age for CSFF in the cortex (p = 0.018), MWF in the cerebral WM (p = 0.033), deep GM (p = 0.017) and cortex (p = 0.029); and IEWF in the deep GM (p = 0.033). There was a statistically highly significant positive linear relationship between age and regional CSFF in the cerebral WM (p < 0.001) and deep GM (p < 0.001). In addition, there was a statistically significant negative linear association between IEWF and age in the cerebral WM (p = 0.017) and cortex (p < 0.001). In the univariate correlation analysis, the normalized lateral ventricle volume correlated with the regional CSFF measurement in the cerebral WM (ρ = 0.64, p < 0.001), cortex (ρ = 0.62, p < 0.001), and deep GM (ρ = 0.66, p < 0.001).

Conclusion

Our cross-sectional data demonstrate that brain tissue water in different compartments shows complex age-dependent patterns. Parenchymal CSFF, a measure of subvoxel CSF-like water in the brain tissue, is quadratically associated with age in the cerebral cortex and linearly associated with age in the cerebral deep GM and WM.

Non-invasive flow mapping of parasagittal meningeal lymphatics using 2D interslice flow saturation MRI

The clearance pathways of brain waste products in humans are still under debate in part due to the lack of noninvasive imaging techniques for meningeal lymphatic vessels (mLVs). In this study, we propose a new noninvasive mLVs imaging technique based on an inter-slice blood perfusion MRI called alternate ascending/descending directional navigation (ALADDIN). ALADDIN with inversion recovery (IR) at single inversion time of 2300 ms (single-TI IR-ALADDIN) clearly demonstrated parasagittal mLVs around the human superior sagittal sinus (SSS) with better detectability and specificity than the previously suggested noninvasive imaging techniques. While in many studies it has been difficult to detect mLVs and confirm their signal source noninvasively, the detection of mLVs in this study was confirmed by their posterior to anterior flow direction and their velocities and morphological features, which were consistent with those from the literature. In addition, IR-ALADDIN was compared with contrast-enhanced black blood imaging to confirm the detection of mLVs and its similarity. For the quantification of flow velocity of mLVs, IR-ALADDIN was performed at three inversion times of 2000, 2300, and 2600 ms (three-TI IR-ALADDIN) for both a flow phantom and humans. For this preliminary result, the flow velocity of the dorsal mLVs in humans ranged between 2.2 and 2.7 mm/s. Overall, (i) the single-TI IR-ALADDIN can be used as a novel non-invasive method to visualize mLVs in the whole brain with scan time of ~ 17 min and (ii) the multi-TI IR-ALADDIN can be used as a way to quantify the flow velocity of mLVs with a scan time of ~ 10 min (or shorter) in a limited coverage. Accordingly, the suggested approach can be applied to noninvasively studying meningeal lymphatic flows in general and also understanding the clearance pathways of waste production through mLVs in humans, which warrants further investigation.

Combining arterial blood contrast with BOLD increases fMRI intracortical contrast

BOLD fMRI is widely applied in human neuroscience but is limited in its spatial specificity due to a cortical-depth-dependent venous bias. This reduces its localization specificity with respect to neuronal responses, a disadvantage for neuroscientific research. Here, we modified a submillimeter BOLD protocol to selectively reduce venous and tissue signal and increase cerebral blood volume weighting through a pulsed saturation scheme (dubbed Arterial Blood Contrast) at 7 T. Adding Arterial Blood Contrast on top of the existing BOLD contrast modulated the intracortical contrast. Isolating the Arterial Blood Contrast showed a response free of pial-surface bias. The results suggest that Arterial Blood Contrast can modulate the typical fMRI spatial specificity, with important applications in in-vivo neuroscience.

Accuracy, repeatability, and reproducibility of T1 and T2 relaxation times measurement by 3D magnetic resonance fingerprinting with different dictionary resolutions

OBJECTIVES

To assess the accuracy, repeatability, and reproducibility of T₁ and T₂ relaxation time measurements by three-dimensional magnetic resonance fingerprinting (3D MRF) using various dictionary resolutions.

METHODS

The ISMRM/NIST phantom was scanned daily for 10 days in two 3 T MR scanners using a 3D MRF sequence reconstructed using four dictionaries with varying step sizes and one dictionary with wider ranges. Thirty-nine healthy volunteers were enrolled: 20 subjects underwent whole-brain MRF scans in both scanners and the rest in one scanner. ROI/VOI analyses were performed on phantom and brain MRF maps. Accuracy, repeatability, and reproducibility metrics were calculated.

RESULTS

In the phantom study, all dictionaries showed high T₁ linearity to the reference values (R² > 0.99), repeatability (CV < 3%), and reproducibility (CV < 3%) with lower linearity (R² > 0.98), repeatability (CV < 6%), and reproducibility (CV ≤ 4%) for T₂ measurement. The volunteer study demonstrated high T₁ reproducibility of within-subject CV (wCV) < 4% by all dictionaries with the same ranges, both in the brain parenchyma and CSF. Yet, reproducibility was moderate for T₂ measurement (wCV < 8%). In CSF measurement, dictionaries with a smaller range showed a seemingly better reproducibility (T₁, wCV 3%; T₂, wCV 8%) than the much wider range dictionary (T₁, wCV 5%; T₂, wCV 13%). Truncated CSF relaxometry values were evident in smaller range dictionaries.

CONCLUSIONS

The accuracy, repeatability, and reproducibility of 3D MRF across various dictionary resolutions were high for T₁ and moderate for T₂ measurements. A lower-resolution dictionary with a well-defined range may be adequate, thus significantly reducing the computational load.

KEY POINTS

• A lower-resolution dictionary with a well-defined range may be sufficient for 3D MRF reconstruction. • CSF relaxation times might be underestimated due to truncation by the upper dictionary range. • Dictionary with a higher upper range might be advisable, especially for CSF evaluation and elderly subjects whose perivascular spaces are more prominent.

Arterial spin labeling signal in the CSF: Implications for partial volume correction and blood-CSF barrier characterization

For better quantification of perfusion with arterial spin labeling (ASL), partial volume correction (PVC) is used to disentangle the signals from gray matter (GM) and white matter within any voxel. Based on physiological considerations, PVC algorithms typically assume zero signal in the cerebrospinal fluid (CSF). Recent measurements, however, have shown that CSF-ASL signal can exceed 10% of GM signal, even when using recommended ASL labeling parameters. CSF signal is expected to particularly affect PVC results in the choroid plexus. This study aims to measure the impact of CSF signal on PVC perfusion measurements, and to investigate the potential use of PVC to retrieve pure CSF-ASL signal for blood-CSF barrier characterization. In vivo imaging included six pCASL sequences with variable label duration and post-labeling delay (PLD), and an eight-echo 3D-GRASE readout. A dataset was simulated to estimate the effect of CSF-PVC with known ground-truth parameters. Differences between the results of CSF-PVC and non-CSF-PVC were estimated for regions of interest (ROIs) based on GM probability, and a separate ROI isolating the choroid plexus. In vivo, the suitability of PVC-CSF signal as an estimate of pure CSF was investigated by comparing its time course with the long-TE CSF signal. Results from both simulation and in vivo data indicated that including the CSF signal in PVC improves quantification of GM CBF by approximately 10%. In simulated data, this improvement was greater for multi-PLD (model fitting) quantification than for single PLD (~1-5% difference). In the choroid plexus, the difference between CSF-PVC and non-CSF-PVC was much larger, averaging around 30%. Long-TE (pure) CSF signal could not be estimated from PVC CSF signal as it followed a different time course, indicating the presence of residual macrovascular signal in the PVC. The inclusion of CSF adds value to PVC for more accurate measurements of GM perfusion, and especially for quantification of perfusion in the choroid plexus and study of the glymphatic system.

Measurements of cerebrospinal fluid production: a review of the limitations and advantages of current methodologies

Cerebrospinal fluid (CSF) is an essential and critical component of the central nervous system (CNS). According to the concept of the "third circulation" originally proposed by Cushing, CSF is mainly produced by the choroid plexus and subsequently leaves the cerebral ventricles via the foramen of Magendie and Luschka. CSF then fills the subarachnoid space from whence it disperses to all parts of the CNS, including the forebrain and spinal cord. CSF provides buoyancy to the submerged brain, thus protecting it against mechanical injury. CSF is also transported via the glymphatic pathway to reach deep interstitial brain regions along perivascular channels; this CSF clearance pathway promotes transport of energy metabolites and signaling molecules, and the clearance of metabolic waste. In particular, CSF is now intensively studied as a carrier for the removal of proteins implicated in neurodegeneration, such as amyloid-β and tau. Despite this key function of CSF, there is little information about its production rate, the factors controlling CSF production, and the impact of diseases on CSF flux. Therefore, we consider it to be a matter of paramount importance to quantify better the rate of CSF production, thereby obtaining a better understanding of CSF dynamics. To this end, we now review the existing methods developed to measure CSF production, including invasive, noninvasive, direct, and indirect methods, and MRI-based techniques. Depending on the methodology, estimates of CSF production rates in a given species can extend over a ten-fold range. Throughout this review, we interrogate the technical details of CSF measurement methods and discuss the consequences of minor experimental modifications on estimates of production rate. Our aim is to highlight the gaps in our knowledge and inspire the development of more accurate, reproducible, and less invasive techniques for quantitation of CSF production.

Structural and functional imaging of brains

Analyzing the complex structures and functions of brain is the key issue to understanding the physiological and pathological processes. Although neuronal morphology and local distribution of neurons/blood vessels in the brain have been known, the subcellular structures of cells remain challenging, especially in the live brain. In addition, the complicated brain functions involve numerous functional molecules, but the concentrations, distributions and interactions of these molecules in the brain are still poorly understood. In this review, frontier techniques available for multiscale structure imaging from organelles to the whole brain are first overviewed, including magnetic resonance imaging (MRI), computed tomography (CT), positron emission tomography (PET), serial-section electron microscopy (ssEM), light microscopy (LM) and synchrotron-based X-ray microscopy (XRM). Specially, XRM for three-dimensional (3D) imaging of large-scale brain tissue with high resolution and fast imaging speed is highlighted. Additionally, the development of elegant methods for acquisition of brain functions from electrical/chemical signals in the brain is outlined. In particular, the new electrophysiology technologies for neural recordings at the single-neuron level and in the brain are also summarized. We also focus on the construction of electrochemical probes based on dual-recognition strategy and surface/interface chemistry for determination of chemical species in the brain with high selectivity and long-term stability, as well as electrochemophysiological microarray for simultaneously recording of electrochemical and electrophysiological signals in the brain. Moreover, the recent development of brain MRI probes with high contrast-to-noise ratio (CNR) and sensitivity based on hyperpolarized techniques and multi-nuclear chemistry is introduced. Furthermore, multiple optical probes and instruments, especially the optophysiological Raman probes and fiber Raman photometry, for imaging and biosensing in live brain are emphasized. Finally, a brief perspective on existing challenges and further research development is provided.

Magnetization transfer weighted laminar fMRI with multi-echo FLASH

Laminar functional magnetic resonance imaging (fMRI) using the gradient echo (GRE) blood oxygenation level dependent (BOLD) contrast is prone to signal changes arising from large unspecific venous vessels. Alternatives based on changes of cerebral blood volume (CBV) become more popular since it is expected that this hemodynamic response is dominant in microvasculature. One approach to sensitize the signal toward changes in CBV, and to simultaneously reduce unwanted extravascular (EV) BOLD blurring, is to selectively reduce gray matter (GM) signal via magnetization transfer (MT). In this work, we use off-resonant MT-pulses with a 3D FLASH readout to perform MT-prepared (MT-prep) laminar fMRI of the primary visual cortex (V1) at multiple echo times at 7 T. With a GRE-BOLD contrast without additional MT-weighting as reference, we investigated the influence of the MT-preparation on the shape and the echo time dependency of laminar profiles. Through numerical simulations, we optimized the sequence parameters to increase the sensitivity toward signal changes induced by changes in arterial CBV and to delineate the contributions of different compartments to the signal. We show that at 7 T, GM signals can be reduced by 30 %. Our laminar fMRI responses exhibit an increased signal change in the parenchyma at very short TE compared to a BOLD-only reference as a result of reduced EV signal intensity. By varying echo times, we could show that MT-prep results in less sensitivity toward unwanted signal changes based on changes in T₂*. We conclude that when accounting for nuclear overhauser enhancement effects in blood, off-resonant MT-prep combined with efficient short TE readouts can become a promising method to reduce unwanted EV venous contributions in GRE-BOLD and/or to allow scanning at much shorter echo times without incurring a sensitivity penalty in laminar fMRI.

The “Coherent Data Set”: Combining Patient Data and Imaging in a Comprehensive, Synthetic Health Record

The “Coherent Data Set” is a novel synthetic data set that leverages structured data from Synthea™ to create a longitudinal, “coherent” patient-level electronic health record (EHR). Comprised of synthetic patients, the Coherent Data Set is publicly available, reproducible using Synthea™, and free of the privacy risks that arise from using real patient data. The Coherent Data Set provides complex and representative health records that can be leveraged by health IT professionals without the risks associated with de-identified patient data. It includes familial genomes that were created through a simulation of the genetic reproduction process; magnetic resonance imaging (MRI) DICOM files created with a voxel-based computational model; clinical notes in the style of traditional subjective, objective, assessment, and plan notes; and physiological data that leverage existing System Biology Markup Language (SBML) models to capture non-linear changes in patient health metrics. HL7 Fast Healthcare Interoperability Resources (FHIR®) links the data together. The models can generate clinically logical health data, but ensuring clinical validity remains a challenge without comparable data to substantiate results. We believe this data set is the first of its kind and a novel contribution to practical health interoperability efforts.

Avoiding data loss: Synthetic MRIs generated from diffusion imaging can replace corrupted structural acquisitions for freesurfer-seeded tractography

Magnetic Resonance Imaging (MRI) motion artefacts frequently complicate structural and diffusion MRI analyses. While diffusion imaging is easily ‘scrubbed’ of motion affected volumes, the same is not true for T1w or T2w ‘structural’ images. Structural images are critical to most diffusion-imaging pipelines thus their corruption can lead to disproportionate data loss. To enable diffusion-image processing when structural images are missing or have been corrupted, we propose a means by which synthetic structural images can be generated from diffusion MRI. This technique combines multi-tissue constrained spherical deconvolution, which is central to many existing diffusion analyses, with the Bloch equations that allow simulation of MRI intensities for given scanner parameters and magnetic resonance (MR) tissue properties. We applied this technique to 32 scans, including those acquired on different scanners, with different protocols and with pathology present. The resulting synthetic T1w and T2w images were visually convincing and exhibited similar tissue contrast to acquired structural images. These were also of sufficient quality to drive a Freesurfer-based tractographic analysis. In this analysis, probabilistic tractography connecting the thalamus to the primary sensorimotor cortex was delineated with Freesurfer, using either real or synthetic structural images. Tractography for real and synthetic conditions was largely identical in terms of both voxels encountered (Dice 0.88–0.95) and mean fractional anisotropy (intrasubject absolute difference 0.00–0.02). We provide executables for the proposed technique in the hope that these may aid the community in analysing datasets where structural image corruption is common, such as studies of children or cognitively impaired persons.

Constrained Ellipse Fitting for Efficient Parameter Mapping With Phase-Cycled bSSFP MRI

Balanced steady-state free precession (bSSFP) imaging enables high scan efficiency in MRI, but differs from conventional sequences in terms of elevated sensitivity to main field inhomogeneity and nonstandard [Formula: see text]-weighted tissue contrast. To address these limitations, multiple bSSFP images of the same anatomy are commonly acquired with a set of different RF phase-cycling increments. Joint processing of phase-cycled acquisitions serves to mitigate sensitivity to field inhomogeneity. Recently phase-cycled bSSFP acquisitions were also leveraged to estimate relaxation parameters based on explicit signal models. While effective, these model-based methods often involve a large number of acquisitions (N ≈ 10-16), degrading scan efficiency. Here, we propose a new constrained ellipse fitting method (CELF) for parameter estimation with improved efficiency and accuracy in phase-cycled bSSFP MRI. CELF is based on the elliptical signal model framework for complex bSSFP signals; and it introduces geometrical constraints on ellipse properties to improve estimation efficiency, and dictionary-based identification to improve estimation accuracy. CELF generates maps of [Formula: see text], [Formula: see text], off-resonance and on-resonant bSSFP signal by employing a separate [Formula: see text] map to mitigate sensitivity to flip angle variations. Our results indicate that CELF can produce accurate off-resonance and banding-free bSSFP maps with as few as N = 4 acquisitions, while estimation accuracy for relaxation parameters is notably limited by biases from microstructural sensitivity of bSSFP imaging.

Ultra-long-TE arterial spin labeling reveals rapid and brain-wide blood-to-CSF water transport in humans

The study of brain clearance mechanisms is an active area of research. While we know that the cerebrospinal fluid (CSF) plays a central role in one of the main existing clearance pathways, the exact processes for the secretion of CSF and the removal of waste products from tissue are under debate. CSF is thought to be created by the exchange of water and ions from the blood, which is believed to mainly occur in the choroid plexus. This exchange has not been thoroughly studied in vivo.

We propose a modified arterial spin labeling (ASL) MRI sequence and image analysis to track blood water as it is transported to the CSF, and to characterize its exchange from blood to CSF. We acquired six pseudo-continuous ASL sequences with varying labeling duration (LD) and post-labeling delay (PLD) and a segmented 3D-GRASE readout with a long echo train (8 echo times (TE)) which allowed separation of the very long-T₂ CSF signal. ASL signal was observed at long TEs (793 ms and higher), indicating presence of labeled water transported from blood to CSF. This signal appeared both in the CSF proximal to the choroid plexus and in the subarachnoid space surrounding the cortex. ASL signal was separated into its blood, gray matter and CSF components by fitting a triexponential function with T₂s taken from literature. A two-compartment dynamic model was introduced to describe the exchange of water through time and TE. From this, a water exchange time from the blood to the CSF (T_bl->CSF) was mapped, with an order of magnitude of approximately 60 s.

Simultaneous T1 -weighted and T2 -weighted 3D MRI using RF phase-modulated gradient echo imaging

PURPOSE

T₁ -weighted and T₂ -weighted (T1w and T2w) imaging are essential sequences in routine clinical practice to detect and characterize a wide variety of pathologies. Many approaches have been proposed to obtain T1w and T2w contrast, although many challenges still remain, including long acquisition time and limitations that favor 2D imaging. In this study, we propose a novel method for simultaneous T1w and T2w imaging using RF phase-modulated 3D gradient-echo imaging.

THEORY

Configuration theory is used to derive closed-form equations for the steady state of RF phase-modulated gradient-echo signal. These equations suggest the use of small RF phase increments to provide orthogonal signal contrast with T2w and T1w in the real and imaginary components, respectively. Background phase can be removed using a two-pass acquisition with opposite RF phase increments.

METHODS

Simulation and phantom experiments were performed to validate our proposed method. Volunteer images of the brain and knee were acquired to demonstrate the clinical feasibility. The proposed method was compared with T1w and T2w fast spin-echo imaging.

RESULTS

The relative signal intensity of images acquired using the proposed method agreed closely with simulations and fast spin-echo imaging in phantoms. Images from volunteer imaging showed very similar contrast compared to conventional fast spin-echo imaging.

CONCLUSION

Radiofrequency phase-modulated gradient-echo with small RF phase increments is an alternative method that provides simultaneous T1w and T2w contrast in short scan times with 3D volumetric coverage.

Simultaneous pure T2 and varying T2'-weighted BOLD fMRI using Echo Planar Time-resolved Imaging for mapping cortical-depth dependent responses

Spin-echo (SE) BOLD fMRI has high microvascular specificity, and thus provides a more reliable means to localize neural activity compared to conventional gradient-echo BOLD fMRI. However, the most common SE BOLD acquisition method, SE-EPI, is known to suffer from T₂′ contrast contamination with undesirable draining vein bias. To address this, in this study, we extended a recently developed distortion/blurring-free multi-shot EPI technique, Echo-Planar Time-resolved Imaging (EPTI), to cortical-depth dependent SE-fMRI at 7T to test whether it could provide purer SE BOLD contrast with minimal T₂′ contamination for improved neuronal specificity. From the same acquisition, the time-resolved feature of EPTI also provides a series of asymmetric SE (ASE) images with varying T₂′ weightings, and enables extraction of data equivalent to conventional SE EPI with different echo train lengths (ETLs). This allows us to systematically examine how T₂′-contribution affects different SE acquisition strategies using a single dataset. A low-rank spatiotemporal subspace reconstruction was implemented for the SE-EPTI acquisition, which incorporates corrections for both shot-to-shot phase variations and dynamic B₀ drifts. SE-EPTI was used in a visual task fMRI experiment to demonstrate that i) the pure SE image provided by EPTI results in the highest microvascular specificity; ii) the ASE EPTI series, with a graded introduction of T₂′ weightings at time points farther away from the pure SE, show a gradual sensitivity increase along with increasing draining vein bias; iii) the longer ETL seen in conventional SE EPI acquisitions will induce more draining vein bias. Consistent results were observed across multiple subjects, demonstrating the robustness of the proposed technique for SE-BOLD fMRI with high specificity.

In vivo T1 and T2 relaxation time maps of brain tissue, skeletal muscle, and lipid measured in healthy volunteers at 50 mT

PURPOSE

Low-field (B₀ < 0.1 T) MRI has generated much interest as a means of increased accessibility via reduced cost and improved portability compared to conventional clinical systems (B₀ ≥ 1.5 Tesla). Here we measure MR relaxation times at 50 mT and compare results with commonly used models based on both in vivo and ex vivo measurements.

METHODS

Using 3D turbo spin echo readouts, T₁ and T₂ maps of the human brain and lower leg were acquired on a custom-built 50 mT MRI scanner using inversion-recovery and multi-echo-based sequences, respectively. Image segmentation was performed based on a histogram analysis of the relaxation times.

RESULTS

The average T₁ times of gray matter, white matter, and cerebrospinal fluid (CSF) were 327 ± 10 ms, 275 ± 5 ms, and 3695 ± 287 ms, respectively. Corresponding values of T₂ were 102 ± 6 ms, 102 ± 6 ms, and 1584 ± 124 ms. T₁ times in the calf muscle were measured to be 171 ± 11 ms and were 130 ± 5 ms in subcutaneous and bone marrow lipid. Corresponding T₂ times were 39 ± 2 ms in muscle and 90 ± 13 ms in lipid.

CONCLUSIONS

For tissues except for CSF, the measured T₁ times are much shorter than reported at higher fields and generally lie within the range of different models in the literature. As expected, T₂ times are similar to those seen at typical clinical field strengths. Analysis of the relaxation maps indicates that segmentation of white and gray matter based purely on T₁ or T₂ will be quite challenging at low field given the relatively small difference in relaxation times.

Double delay alternating with nutation for tailored excitation facilitates banding-free isotropic high-resolution intracranial vessel wall imaging

The purpose of this study was to evaluate the use of a double delay alternating with nutation for tailored excitation (D-DANTE)-prepared sequence for banding-free isotropic high-resolution intracranial vessel wall imaging (IC-VWI) and to compare its performance with regular DANTE in terms of signal-to-noise ratio (SNR) as well as cerebrospinal fluid (CSF) and blood suppression efficiency. To this end, a D-DANTE-prepared 3D turbo spin echo sequence was implemented by interleaving two separate DANTE pulse trains with different RF phase-cycling schemes, but keeping all other DANTE parameters unchanged, including the total number of pulses and total preparation time. This achieved a reduction of the banding distance compared with regular DANTE enabling banding-free imaging up to higher resolutions. Bloch simulations assuming static vessel wall and flowing CSF spins were performed to compare DANTE and D-DANTE in terms of SNR and vessel wall/CSF contrast. Similar image quality measures were assessed from measurements on 13 healthy middle-aged volunteers. Both simulation and in vivo results showed that D-DANTE had only slightly lower vessel wall/CSF and vessel wall/blood contrast-to-noise ratio values compared with regular DANTE, which originated from a 10%-15% reduction in vessel wall SNR but not from reduced CSF or blood suppression efficiency. As anticipated, IC-VWI acquisitions showed that D-DANTE can successfully remove banding artifacts compared with regular DANTE with equal scan time or DANTE preparation length. Moreover, application was demonstrated in a patient with an intracranial aneurysm, indicating improved robustness to slow flow artifacts compared with clinically available 3D turbo spin echo scans. In conclusion, D-DANTE provides banding artifact-free IC-VWI up to higher isotropic resolutions compared with regular DANTE. This allows for a more flexible choice of DANTE preparation parameters in high-resolution IC-VWI protocols.

On the potential for mapping apparent neural soma density via a clinically viable diffusion MRI protocol

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B-tensor encoding enables estimation of spherical cellular structures in the brain.

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Spherical compartments may provide markers for apparent neural soma density.

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Model parameters can be estimated in a fast and robust way using deep learning.

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Practical acquisition times are achievable on widely available clinical scanners.

Diffusion MRI is a valuable tool for probing tissue microstructure in the brain noninvasively. Today, model-based techniques are widely available and used for white matter characterisation where their development is relatively mature. Conversely, tissue modelling in grey matter is more challenging, and no generally accepted models exist. With advances in measurement technology and modelling efforts, a clinically viable technique that reveals salient features of grey matter microstructure, such as the density of quasi-spherical cell bodies and quasi-cylindrical cell projections, is an exciting prospect. As a step towards capturing the microscopic architecture of grey matter in clinically feasible settings, this work uses a biophysical model that is designed to disentangle the diffusion signatures of spherical and cylindrical structures in the presence of orientation heterogeneity, and takes advantage of B-tensor encoding measurements, which provide additional sensitivity compared to standard single diffusion encoding sequences. For the fast and robust estimation of microstructural parameters, we leverage recent advances in machine learning and replace conventional fitting techniques with an artificial neural network that fits complex biophysical models within seconds. Our results demonstrate apparent markers of spherical and cylindrical geometries in healthy human subjects, and in particular an increased volume fraction of spherical compartments in grey matter compared to white matter. We evaluate the extent to which spherical and cylindrical geometries may be interpreted as correlates of neural soma and neural projections, respectively, and quantify parameter estimation errors in the presence of various departures from the modelling assumptions. While further work is necessary to translate the ideas presented in this work to the clinic, we suggest that biomarkers focussing on quasi-spherical cellular geometries may be valuable for the enhanced assessment of neurodevelopmental disorders and neurodegenerative diseases.

Slice encoding for the reduction of outflow signal artifacts in cine balanced SSFP imaging

PURPOSE

Standard balanced SSFP (bSSFP) cine MRI often suffers from blood outflow artifacts. We propose a method that spatially encodes these outflowing spins to reduce their effects in the intended slice.

METHODS

Bloch simulations were performed to characterize through-plane flow and to investigate how the use of phase encoding along the slice select's direction ("slice encoding") could alleviate its issues. Phantom scans and in vivo cines were acquired on a 3T system, comparing the standard 2D acquisition to the proposed slice-encoding method. Nineteen healthy volunteers were recruited for short-axis and horizontal long-axis oriented scans. An expert radiologist evaluated each slice-encoded/standard cine pairs in a rank comparison test and graded their quality on a 1-5 scale. The grades were used for a nonparametric paired evaluation for independent samples with a null hypothesis that there was no statistical difference between the two quality-grade distributions for α = 0.05 significance.

RESULTS

Bloch simulation results demonstrated this technique's feasibility, showing a fully resolved slice profile given a sufficient number of slice encodes. These results were confirmed with the phantom experiments. Each in vivo slice-encoded cine had a higher quality than its corresponding standard acquisition. The nonparametric paired evaluation came to 0.01 significance, encouraging us to reject the null hypothesis and conclude that slice-encoding effectively works in reducing outflow effects.

CONCLUSION

The slice-encoding balanced SSFP technique is helpful in mitigating outflow effects and is achievable within a single breath hold, being a useful alternative for cases in which the flow artifacts are significant.

Laminar fMRI using T2-prepared multi-echo FLASH

Functional magnetic resonance imaging (fMRI) using blood oxygenation level dependent (BOLD) contrast at a sub-millimeter scale is a promising technique to probe neural activity at the level of cortical layers. While gradient echo (GRE) BOLD sequences exhibit the highest sensitivity, their signal is confounded by unspecific extravascular (EV) and intravascular (IV) effects of large intracortical ascending veins and pial veins leading to a downstream blurring effect of local signal changes. In contrast, spin echo (SE) fMRI promises higher specificity towards signal changes near the microvascular compartment. However, the T₂-weighted signal is typically sampled with a gradient echo readout imposing additional T₂'-weighting. In this work, we used a T₂-prepared (T₂-prep) sequence with short GRE readouts to investigate its capability to acquire laminar fMRI data during a visual task in humans at 7 T. By varying the T₂-prep echo time (TE_prep) and acquiring multiple gradient echoes (TE_GRE) per excitation, we studied the specificity of the sequence and the influence of possible confounding contributions to the shape of laminar fMRI profiles. By fitting and extrapolating the multi-echo GRE data to a TE_GRE = 0 ms condition, we show for the first time laminar profiles free of T₂'-pollution, confined to gray matter. This finding is independent of TE_prep, except for the shortest one (31 ms) where hints of a remaining intravascular component can be seen. For TE_GRE > 0 ms a prominent peak at the pial surface is observed that increases with longer TE_GRE and dominates the shape of the profiles independent of the amount of T₂-weighting. Simulations show that the peak at the pial surface is a result of static EV dephasing around pial vessels in CSF visible in GM due to partial voluming. Additionally, another, weaker, static dephasing effect is observed throughout all layers of the cortex, which is particularly obvious in the data with shortest T₂-prep echo time. Our simulations show that this cannot be explained by intravascular dephasing but that it is likely caused by extravascular effects of the intracortical and pial veins. We conclude that even for TE_GRE as short as 2.3 ms, the T₂'-weighting added to the T₂-weighting is enough to dramatically affect the laminar specificity of the BOLD signal change. However, the bulk of this corruption stems from CSF partial volume effects which can in principle be addressed by increasing the spatial resolution of the acquisition.

Whole-brain 3D MR fingerprinting brain imaging: clinical validation and feasibility to patients with meningioma

Purpose

MR fingerprinting (MRF) is a MR technique that allows assessment of tissue relaxation times. The purpose of this study is to evaluate the clinical application of this technique in patients with meningioma.

Materials and methods

A whole-brain 3D isotropic 1mm³ acquisition under a 3.0T field strength was used to obtain MRF T₁ and T₂-based relaxometry values in 4:38 s. The accuracy of values was quantified by scanning a quantitative MR relaxometry phantom. In vivo evaluation was performed by applying the sequence to 20 subjects with 25 meningiomas. Regions of interest included the meningioma, caudate head, centrum semiovale, contralateral white matter and thalamus. For both phantom and subjects, mean values of both T₁ and T₂ estimates were obtained. Statistical significance of differences in mean values between the meningioma and other brain structures was tested using a Friedman’s ANOVA test.

Results

MR fingerprinting phantom data demonstrated a linear relationship between measured and reference relaxometry estimates for both T₁ (r² = 0.99) and T₂ (r² = 0.97). MRF T₁ relaxation times were longer in meningioma (mean ± SD 1429 ± 202 ms) compared to thalamus (mean ± SD 1054 ± 58 ms; p = 0.004), centrum semiovale (mean ± SD 825 ± 42 ms; p < 0.001) and contralateral white matter (mean ± SD 799 ± 40 ms; p < 0.001). MRF T₂ relaxation times were longer for meningioma (mean ± SD 69 ± 27 ms) as compared to thalamus (mean ± SD 27 ± 3 ms; p < 0.001), caudate head (mean ± SD 39 ± 5 ms; p < 0.001) and contralateral white matter (mean ± SD 35 ± 4 ms; p < 0.001)

Conclusions

Phantom measurements indicate that the proposed 3D-MRF sequence relaxometry estimations are valid and reproducible. For in vivo, entire brain coverage was obtained in clinically feasible time and allows quantitative assessment of meningioma in clinical practice.

Bloch modelling enables robust T2 mapping using retrospective proton density and T2-weighted images from different vendors and sites

T2 quantification is commonly attempted by applying an exponential fit to proton density (PD) and transverse relaxation (T2)-weighted fast spin echo (FSE) images. However, inter-site studies have noted systematic differences between vendors in T2 maps computed via standard exponential fitting due to imperfect slice refocusing, different refocusing angles and transmit field (B1⁺) inhomogeneity. We examine T2 mapping at 3T across 13 sites and two vendors in healthy volunteers from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database using both a standard exponential and a Bloch modelling approach. The standard exponential approach resulted in highly variable T2 values across different sites and vendors. The two-echo fitting method based on Bloch equation modelling of the pulse sequence with prior knowledge of the nominal refocusing angles, slice profiles, and estimated B1⁺ maps yielded similar T2 values across sites and vendors by accounting for the effects of indirect and stimulated echoes. By modelling the actual refocusing angles used, T2 quantification from PD and T2-weighted images can be applied in studies across multiple sites and vendors.

Fast whole brain MR imaging of dynamic susceptibility contrast changes in the cerebrospinal fluid (cDSC MRI)

PURPOSE

The circulation of cerebrospinal fluid (CSF) is closely associated with many aspects of brain physiology. When gadolinium(Gd)-based contrast is administered intravenously, pre- and post-contrast MR signal changes can often be observed in the CSF at certain locations within the intra-cranial space, mainly due to the lack of a blood-brain barrier in the dural blood vessels. This study aims to develop and systemically optimize MRI sequences that can detect dynamic signal changes in the CSF after Gd administration with a sub-millimeter spatial resolution, a temporal resolution of <10 s, and whole brain coverage.

METHODS

Bloch simulations were performed to determine optimal imaging parameters for maximum CSF contrast before and after Gd injection. Simulations were validated with phantom scans. An optimized turbo-spin-echo (TSE) sequence was performed on healthy volunteers on 3T and 7T.

RESULTS

Simulation results agreed well with phantom scans. In human scans, dynamic signal changes after Gd injection in the CSF were detected at several locations where cerebral lymphatic vessels were identified in previous studies. The concentration of Gd in CSF in these regions was estimated to be approximately 0.2 mmol/L.

CONCLUSION

Dynamic signal changes induced by the distribution of Gd in the CSF can be detected in healthy human subjects with an optimized TSE sequence. The proposed methodology does not rely on any particular theory on CSF circulation. We expect it to be useful for studies on CSF circulation and cerebral lymphatic vessels in the brain.