Blood-brain barrier permeability measurement by biexponentially modeling whole-brain arterial spin labeling data with multiple T2 -weightings

Water exchange across the blood-brain barrier and epilepsy: Review on pathophysiology and neuroimaging

The blood-brain barrier (BBB) is a barrier protecting the brain and a milieu of continuous exchanges between blood and brain. There is emerging evidence that the BBB plays a major role in epileptogenesis and drug-resistant epilepsy, through several mechanisms, such as water homeostasis dysregulation, overexpression of drug transporters, and inflammation. Studies have shown abnormal water homeostasis in epileptic tissue and altered aquaporin-4 water channel expression in animal epilepsy models. This review focuses on abnormal water exchange in epilepsy and describes recent non-invasive MRI methods of quantifying water exchange. PLAIN LANGUAGE SUMMARY: Abnormal exchange between blood and brain contribute to seizures and epilepsy. The authors describe why correct water balance is necessary for healthy brain functioning and how it is impacted in epilepsy. This review also presents recent MRI methods to measure water exchange in human brain. These measures would improve our understanding of factors leading to seizures.

Enhanced parameter estimation in multiparametric arterial spin labeling using artificial neural networks

PURPOSE

Multiparametric arterial spin labeling (MP-ASL) can quantify cerebral blood flow (CBF) and arterial cerebral blood volume (CBVa). However, its accuracy is compromised owing to its intrinsically low SNR, necessitating complex and time-consuming parameter estimation. Deep neural networks (DNNs) offer a solution to these limitations. Therefore, we aimed to develop simulation-based DNNs for MP-ASL and compared the performance of a supervised DNN (DNNSup), physics-informed unsupervised DNN (DNNUns), and the conventional lookup table method (LUT) using simulation and in vivo data.

METHODS

MP-ASL was performed twice during resting state and once during the breath-holding task. First, the accuracy and noise immunity were evaluated in the first resting state. Second, CBF and CBVa values were statistically compared between the first resting state and the breath-holding task using the Wilcoxon signed-rank test and Cliff's delta. Finally, reproducibility of the two resting states was assessed.

RESULTS

Simulation and first resting-state analyses demonstrated that DNNSup had higher accuracy, noise immunity, and a six-fold faster computation time than LUT. Furthermore, all methods detected task-induced CBF and CBVa elevations, with the effect size being larger with the DNNSup (CBF, p = 0.055, Δ = 0.286; CBVa, p = 0.008, Δ = 0.964) and DNNUns (CBF, p = 0.039, Δ = 0.286; CBVa, p = 0.008, Δ = 1.000) than that with LUT (CBF, p = 0.109, Δ = 0.214; CBVa, p = 0.008, Δ = 0.929). Moreover, all the methods exhibited comparable and satisfactory reproducibility.

CONCLUSION

DNNSup outperforms DNNUns and LUT with respect to estimation performance and computation time.

Blood-Brain Barrier Permeability to Water Measured Using Multiple Echo Time Arterial Spin Labeling MRI in the Aging Human Brain

BACKGROUND

The blood-brain barrier (BBB) plays a vital role in maintaining brain homeostasis, but the integrity of this barrier deteriorates slowly with aging. Noninvasive water exchange magnetic resonance imaging (MRI) methods may identify changes in the BBB occurring with healthy aging.

PURPOSE

To investigate age-related changes in the BBB permeability to water using multiple-echo-time (multi-TE) arterial spin labeling (ASL) MRI.

STUDY TYPE

Prospective, cohort.

POPULATION

Two groups of healthy humans-older group (≥50 years, mean age = 56 ± 4 years, N = 13, females = 5) and younger group (≤20 years, mean age = 18 ± 1, N = 13, females = 7).

FIELD STRENGTH/SEQUENCE

A 3T, multi-TE Hadamard pCASL with 3D Gradient and Spin Echo (GRASE) readout.

ASSESSMENT

Two different approaches of variable complexity were applied. A physiologically informed biophysical model with a higher complexity estimating time ( T ex ) taken by the labeled water to move across the BBB and a simpler model of triexponential decay measuring tissue transition rate ( k lin ) .

STATISTICS

Two-tailed unpaired Student t-test, Pearson's correlation coefficient and effect size. P < 0.05 was considered significant.

RESULTS

Older volunteers showed significant differences of 36% lower T ex , 29% lower cerebral perfusion, 17% pronged arterial transit time and 22% shorter intra-voxel transit time compared to the younger volunteers. Tissue fraction ( f EV ) at the earliest TI = 1600 msec was significantly higher in the older group, which contributed to a significantly lower k lin compared to the younger group. f EV at TI = 1600 msec showed significant negative correlation with T ex (r = -0.80), and k lin and T ex showed significant positive correlation (r = 0.73).

DATA CONCLUSIONS

Both approaches of Multi-TE ASL imaging showed sensitivity to detect age-related changes in the BBB permeability. High tissue fractions at the earliest TI and short T ex in the older volunteers indicate that the BBB permeability increased with age.

EVIDENCE LEVEL

2 TECHNICAL EFFICACY: Stage 1.

Blood-brain barrier water exchange measurements using contrast-enhanced ASL

A technique for quantifying regional blood-brain barrier (BBB) water exchange rates using contrast-enhanced arterial spin labelling (CE-ASL) is presented and evaluated in simulations and in vivo. The two-compartment ASL model describes the water exchange rate from blood to tissue,k b , but to estimatek b in practice it is necessary to separate the intra- and extravascular signals. This is challenging in standard ASL data owing to the small difference inT 1 values. Here, a gadolinium-based contrast agent is used to increase thisT 1 difference and enable the signal components to be disentangled. The optimal post-contrast bloodT 1 (T 1 , b post ) at 3 T was determined in a sensitivity analysis, and the accuracy and precision of the method quantified using Monte Carlo simulations. Proof-of-concept data were acquired in six healthy volunteers (five female, age range 24-46 years). The sensitivity analysis identified the optimalT 1 , b post at 3 T as 0.8 s. Simulations showed thatk b could be estimated in individual cortical regions with a relative error ϵ < 1 % and coefficient of variation CoV = 30 %; however, a high dependence on bloodT 1 was also observed. In volunteer data, mean parameter values in grey matter were: arterial transit timet A = 1 . 15 ± 0 . 49  s, cerebral blood flow f = 58 . 0 ± 14 . 3  mL blood/min/100 mL tissue and water exchange ratek b = 2 . 32 ± 2 . 49 s-1 . CE-ASL can provide regional BBB water exchange rate estimates; however, the clinical utility of the technique is dependent on the achievable accuracy of measuredT 1 values.

Blood-brain barrier water exchange measurements using FEXI: Impact of modeling paradigm and relaxation time effects

PURPOSE

To evaluate potential modeling paradigms and the impact of relaxation time effects on human blood-brain barrier (BBB) water exchange measurements using FEXI (BBB-FEXI), and to quantify the accuracy, precision, and repeatability of BBB-FEXI exchange rate estimates at 3 T $$ \mathrm{T} $$ .

METHODS

Three modeling paradigms were evaluated: (i) the apparent exchange rate (AXR) model; (ii) a two-compartment model (2 CM $$ 2\mathrm{CM} $$ ) explicitly representing intra- and extravascular signal components, and (iii) a two-compartment model additionally accounting for finite compartmentalT 1 $$ {\mathrm{T}}_1 $$ andT 2 $$ {\mathrm{T}}_2 $$ relaxation times (2 CM r $$ 2{\mathrm{CM}}_r $$ ). Each model had three free parameters. Simulations quantified biases introduced by the assumption of infinite relaxation times in the AXR and2 CM $$ 2\mathrm{CM} $$ models, as well as the accuracy and precision of all three models. The scan-rescan repeatability of all paradigms was quantified for the first time in vivo in 10 healthy volunteers (age range 23-52 years; five female).

RESULTS

The assumption of infinite relaxation times yielded exchange rate errors in simulations up to 42%/14% in the AXR/2 CM $$ 2\mathrm{CM} $$ models, respectively. Accuracy was highest in the compartmental models; precision was best in the AXR model. Scan-rescan repeatability in vivo was good for all models, with negligible bias and repeatability coefficients in grey matter ofRC AXR = 0 . 43 $$ {\mathrm{RC}}_{\mathrm{AXR}}=0.43 $$  s - 1 $$ {\mathrm{s}}^{-1} $$ ,RC 2 CM = 0 . 51 $$ {\mathrm{RC}}_{2\mathrm{CM}}=0.51 $$  s - 1 $$ {\mathrm{s}}^{-1} $$ , andRC 2 CM r = 0 . 61 $$ {\mathrm{RC}}_{2{\mathrm{CM}}_r}=0.61 $$  s - 1 $$ {\mathrm{s}}^{-1} $$ .

CONCLUSION

Compartmental modelling of BBB-FEXI signals can provide accurate and repeatable measurements of BBB water exchange; however, relaxation time and partial volume effects may cause model-dependent biases.

The neurovasculature as a target in temporal lobe epilepsy

The blood-brain barrier (BBB) is a physiological barrier maintaining a specialized brain micromilieu that is necessary for proper neuronal function. Endothelial tight junctions and specific transcellular/efflux transport systems provide a protective barrier against toxins, pathogens, and immune cells. The barrier function is critically supported by other cell types of the neurovascular unit, including pericytes, astrocytes, microglia, and interneurons. The dysfunctionality of the BBB is a hallmark of neurological diseases, such as ischemia, brain tumors, neurodegenerative diseases, infections, and autoimmune neuroinflammatory disorders. Moreover, BBB dysfunction is critically involved in epilepsy, a brain disorder characterized by spontaneously occurring seizures because of abnormally synchronized neuronal activity. While resistance to antiseizure drugs that aim to reduce neuronal hyperexcitability remains a clinical challenge, drugs targeting the neurovasculature in epilepsy patients have not been explored. The use of novel imaging techniques permits early detection of BBB leakage in epilepsy; however, the detailed mechanistic understanding of causes and consequences of BBB compromise remains unknown. Here, we discuss the current knowledge of BBB involvement in temporal lobe epilepsy with the emphasis on the neurovasculature as a therapeutic target.

DeePred-BBB: A Blood Brain Barrier Permeability Prediction Model With Improved Accuracy

The blood-brain barrier (BBB) is a selective and semipermeable boundary that maintains homeostasis inside the central nervous system (CNS). The BBB permeability of compounds is an important consideration during CNS-acting drug development and is difficult to formulate in a succinct manner. Clinical experiments are the most accurate method of measuring BBB permeability. However, they are time taking and labor-intensive. Therefore, numerous efforts have been made to predict the BBB permeability of compounds using computational methods. However, the accuracy of BBB permeability prediction models has always been an issue. To improve the accuracy of the BBB permeability prediction, we applied deep learning and machine learning algorithms to a dataset of 3,605 diverse compounds. Each compound was encoded with 1,917 features containing 1,444 physicochemical (1D and 2D) properties, 166 molecular access system fingerprints (MACCS), and 307 substructure fingerprints. The prediction performance metrics of the developed models were compared and analyzed. The prediction accuracy of the deep neural network (DNN), one-dimensional convolutional neural network, and convolutional neural network by transfer learning was found to be 98.07, 97.44, and 97.61%, respectively. The best performing DNN-based model was selected for the development of the “DeePred-BBB” model, which can predict the BBB permeability of compounds using their simplified molecular input line entry system (SMILES) notations. It could be useful in the screening of compounds based on their BBB permeability at the preliminary stages of drug development. The DeePred-BBB is made available at https://github.com/12rajnish/DeePred-BBB.

Current Concepts in Intracranial Interstitial Fluid Transport and the Glymphatic System: Part II-Imaging Techniques and Clinical Applications

The glymphatic system is a recently discovered network unique to the central nervous system that allows for dynamic exchange of interstitial fluid (ISF) and cerebrospinal fluid (CSF). As detailed in part I, ISF and CSF transport along paravascular channels of the penetrating arteries and possibly veins allow essential clearance of neurotoxic solutes from the interstitium to the CSF efflux pathways. Imaging tests to investigate this neurophysiologic function, although challenging, are being developed and are reviewed herein. These include direct visualization of CSF transport using postcontrast imaging techniques following intravenous or intrathecal administration of contrast material and indirect glymphatic assessment with detection of enlarged perivascular spaces. Application of MRI techniques, including intravoxel incoherent motion, diffusion tensor imaging, and chemical exchange saturation transfer, is also discussed, as are methods for imaging dural lymphatic channels involved with CSF efflux. Subsequently, glymphatic function is considered in the context of proteinopathies associated with neurodegenerative diseases and traumatic brain injury, cytotoxic edema following acute ischemic stroke, and chronic hydrocephalus after subarachnoid hemorrhage. These examples highlight the substantial role of the glymphatic system in neurophysiology and the development of certain neuropathologic abnormalities, stressing the importance of its consideration when interpreting neuroimaging investigations. © RSNA, 2021.

Separating spin compartments in arterial spin labeling using delays alternating with nutation for tailored excitation (DANTE) pulse: A validation study using T2 -relaxometry and application to arterial cerebral blood volume imaging

PURPOSE

To clarify the type of spin compartment in arterial spin labeling (ASL) that is eliminated by delays alternating with nutation for tailored excitation (DANTE) pulse using T₂ -relaxometry, and to demonstrate the feasibility of arterial cerebral blood volume (CBV_a ) imaging using DANTE-ASL in combination with a simplified two-compartment model.

METHOD

The DANTE and T₂ -preparation modules were combined into a single ASL sequence. T₂ values under the application of DANTE were determined to evaluate changes in T₂ , along with the post-labeling delay (PLD) and the relationship between transit time without DANTE (TT_noVS ) and T₂ . The reference tissue T₂ (T_{2_ref} ) was also obtained. Subsequently, the DANTE module was embedded into the Hadamard-encoded ASL. Cerebral blood flow (CBF) and CBV_a were computed using two Hadamard-encoding datasets (with and without DANTE) in a rest and breath-holding (BH) task.

RESULTS

While T₂ without DANTE (T_{2_noVS} ) decreased as the PLD increased, T₂ with DANTE (T_{2_DANTE} ) was equivalent to T_{2_ref} and did not change with the PLD. Although there was a significant positive correlation between TT_noVS and T_{2_noVS} with short PLD, T_{2_DANTE} was not correlated with TT_noVS nor PLD. Baseline CBV_a values obtained at rest were 0.64 ± 0.12, 0.64 ± 0.11, and 0.58 ± 0.15 mL/100 g for anterior, middle, and posterior cerebral arteries, respectively. Significant CBF and CBV_a elevations were observed in the BH task.

CONCLUSION

Microvascular compartment signals were eliminated from the total ASL signals by DANTE. CBV_a can be measured using Hadamard-encoded DANTE-ASL in combination with a simplified two-compartment model.

Measuring 129 Xe transfer across the blood-brain barrier using MR spectroscopy

PURPOSE

This study develops a tracer kinetic model of xenon uptake in the human brain to determine the transfer rate of inhaled hyperpolarized ¹²⁹ Xe from cerebral blood to gray matter that accounts for the effects of cerebral physiology, perfusion and magnetization dynamics. The ¹²⁹ Xe transfer rate is expressed using a tracer transfer coefficient, which estimates the quantity of hyperpolarized ¹²⁹ Xe dissolved in cerebral blood under exchange with depolarized ¹²⁹ Xe dissolved in gray matter under equilibrium of concentration.

THEORY AND METHODS

Time-resolved MR spectra of hyperpolarized ¹²⁹ Xe dissolved in the human brain were acquired from three healthy volunteers. Acquired spectra were numerically fitted with five Lorentzian peaks in accordance with known ¹²⁹ Xe brain spectral peaks. The signal dynamics of spectral peaks for gray matter and red blood cells were quantified, and correction for the ¹²⁹ Xe T₁ dependence upon blood oxygenation was applied. ¹²⁹ Xe transfer dynamics determined from the ratio of the peaks for gray matter and red blood cells was numerically fitted with the developed tracer kinetic model.

RESULTS

For all the acquired NMR spectra, the developed tracer kinetic model fitted the data with tracer transfer coefficients between 0.1 and 0.14.

CONCLUSION

In this study, a tracer kinetic model was developed and validated that estimates the transfer rate of HP ¹²⁹ Xe from cerebral blood to gray matter in the human brain.