Dataset Information

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

ABSTRACT: 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, kb , but to estimate kb in practice it is necessary to separate the intra- and extravascular signals. This is challenging in standard ASL data owing to the small difference in T1 values. Here, a gadolinium-based contrast agent is used to increase this T1 difference and enable the signal components to be disentangled. The optimal post-contrast blood T1 ( T1,bpost ) 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 optimal T1,bpost at 3 T as 0.8 s. Simulations showed that kb could be estimated in individual cortical regions with a relative error ϵ<1 % and coefficient of variation CoV=30 %; however, a high dependence on blood T1 was also observed. In volunteer data, mean parameter values in grey matter were: arterial transit time tA=1.15±0.49 s, cerebral blood flow f=58.0±14.3 mL blood/min/100 mL tissue and water exchange rate kb=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 measured T1 values.

SUBMITTER: Powell E

PROVIDER: S-EPMC10909569 | biostudies-literature | 2023 Nov

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

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

Powell Elizabeth E Dickie Ben R BR Ohene Yolanda Y Maskery Mark M Parker Geoff J M GJM Parkes Laura M LM

NMR in biomedicine 20230904 11

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 estimate k 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 in T 1 values. Here, a gadol ...[more]

PMID: 37666494

Similar Datasets

Project description:Multiple echo-time arterial spin labelling (multi-TE ASL) offers estimation of blood-tissue exchange dynamics by probing the T2 relaxation of the labelled spins. In this study, we provide a recipe for robust assessment of exchange time (Texch) as a proxy measure of blood-brain barrier (BBB) integrity based on a test-retest analysis. This includes a novel scan protocol and an extension of the two-compartment model with an "intra-voxel transit time" (ITT) to address tissue transit effects. With the extended model, we intend to separate the underlying two distinct mechanisms of tissue transit and exchange. The performance of the extended model in comparison with the two-compartment model was evaluated in simulations. Multi-TE ASL sequence with two different bolus durations was used to acquire in vivo data (n = 10). Cerebral blood flow (CBF), arterial transit time (ATT) and Texch were fitted with the two models, and mean grey matter values were compared. Additionally, the extended model also extracted ITT parameter. The test-retest reliability of Texch was assessed for intra-session, inter-session and inter-visit pairs of measurements. Intra-class correlation coefficient (ICC) and within-subject coefficient of variance (CoV) for grey matter were computed to assess the precision of the method. Mean grey matter Texch and ITT values were found to be 227.9 ± 37.9 ms and 310.3 ± 52.9 ms, respectively. Texch estimated by the extended model was 32.6 ± 5.9% lower than the two-compartment model. A significant ICC was observed for all three measures of Texch reliability (P < 0.05). Texch intra-session CoV, inter-session CoV and inter-visit CoV were found to be 6.6%, 7.9%, and 8.4%, respectively. With the described improvements addressing intra-voxel transit effects, multi-TE ASL shows good reproducibility as a non-invasive measure of BBB permeability. These findings offer an encouraging step forward to apply this potential BBB permeability biomarker in clinical research.

Project description:Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is used to quantify the blood-brain barrier (BBB) permeability-surface area product. Serial measurements can indicate changes in BBB health, of interest to the study of normal physiology, neurological disease, and the effect of therapeutics. We performed a scan-rescan study to inform both sample size calculation for future studies and an appropriate reference change value for patient care. The final dataset included 28 healthy individuals (mean age 53.0 years, 82% female) scanned twice with mean interval 9.9 weeks. DCE-MRI was performed at 3T using a 3D gradient echo sequence with whole brain coverage, T1 mapping using variable flip angles, and a 16-min dynamic sequence with a 3.2-s time resolution. Segmentation of white and grey matter (WM/GM) was performed using a 3D magnetization-prepared gradient echo image. The influx constant Ki was calculated using the Patlak method. The primary outcome was the within-subject coefficient of variation (CV) of Ki in both WM and GM. Ki values followed biological expectations in relation to known GM/WM differences in cerebral blood volume (CBV) and consequently vascular surface area. Subject-derived arterial input functions showed marked within-subject variability which were significantly reduced by using a venous input function (CV of area under the curve 46 vs. 12%, p < 0.001). Use of the venous input function significantly improved the CV of Ki in both WM (30 vs. 59%, p < 0.001) and GM (21 vs. 53%, p < 0.001). Further improvement was obtained using motion correction, scaling the venous input function by the artery, and using the median rather than the mean of individual voxel data. The final method gave CV of 27% and 17% in WM and GM, respectively. No further improvement was obtained by replacing the subject-derived input function by one standard population input function. CV of Ki was shown to be highly sensitive to dynamic sequence duration, with shorter measurement periods giving marked deterioration especially in WM. In conclusion, measurement variability of 3D brain DCE-MRI is sensitive to analysis method and a large precision improvement is obtained using a venous input function.

Project description:Key pointsThe blood-brain barrier (BBB) is an important and dynamic structure which contributes to homeostasis in the central nervous system. BBB permeability changes occur in health and disease but measurement of BBB permeability in humans is not straightforward. Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) can be used to model the movement of gadolinium contrast into the brain, expressed as the influx constant Ki . Here evidence is provided that Ki as measured by DCE-MRI behaves as expected for a marker of overall BBB leakage. These results support the use of DCE-MRI for in vivo studies of human BBB permeability in health and disease.AbstractBlood-brain barrier (BBB) leakage can be measured using dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) as the influx constant Ki . To validate this method we compared measured Ki with biological expectations, namely (1) higher Ki in healthy individual grey matter (GM) versus white matter (WM), (2) GM/WM cerebral blood volume (CBV) ratio close to the histologically established GM/WM vascular density ratio, (3) higher Ki in visibly enhancing multiple sclerosis (MS) lesions versus MS normal appearing white matter (NAWM), and (4) higher Ki in MS NAWM versus healthy individual NAWM. We recruited 13 healthy individuals and 12 patients with MS and performed whole-brain 3D DCE-MRI at 3 T. Ki and CBV were calculated using Patlak modelling for manual regions of interest (ROI) and segmented tissue masks. Ki was higher in control GM versus WM (P = 0.001). CBV was higher in GM versus WM (P = 0.005, mean ratio 1.9). Ki was higher in visibly enhancing MS lesions versus MS NAWM (P = 0.002), and in MS NAWM versus controls (P = 0.014). Bland-Altman analysis showed no significant difference between ROI and segmentation methods (P = 0.638) and an intra-class correlation coefficient showed moderate single measure consistency (0.610). Ki behaves as expected for a compound marker of permeability and surface area. The GM/WM CBV ratio measured by this technique is in agreement with the literature. This adds evidence to the validity of Ki measured by DCE-MRI as a marker of overall BBB leakage.

Dataset Information

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

Publications

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

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets