Test-retest reliability and reproducibility of long-label pseudo-continuous arterial spin labeling

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.

Transformer-based deep learning denoising of single and multi-delay 3D arterial spin labeling

PURPOSE

To present a Swin Transformer-based deep learning (DL) model (SwinIR) for denoising single-delay and multi-delay 3D arterial spin labeling (ASL) and compare its performance with convolutional neural network (CNN) and other Transformer-based methods.

METHODS

SwinIR and CNN-based spatial denoising models were developed for single-delay ASL. The models were trained on 66 subjects (119 scans) and tested on 39 subjects (44 scans) from three different vendors. Spatiotemporal denoising models were developed using another dataset (6 subjects, 10 scans) of multi-delay ASL. A range of input conditions was tested for denoising single and multi-delay ASL, respectively. The performance was evaluated using similarity metrics, spatial SNR and quantification accuracy of cerebral blood flow (CBF), and arterial transit time (ATT).

RESULTS

SwinIR outperformed CNN and other Transformer-based networks, whereas pseudo-3D models performed better than 2D models for denoising single-delay ASL. The similarity metrics and image quality (SNR) improved with more slices in pseudo-3D models and further improved when using M0 as input, but introduced greater biases for CBF quantification. Pseudo-3D models with three slices achieved optimal balance between SNR and accuracy, which can be generalized to different vendors. For multi-delay ASL, spatiotemporal denoising models had better performance than spatial-only models with reduced biases in fitted CBF and ATT maps.

CONCLUSIONS

SwinIR provided better performance than CNN and other Transformer-based methods for denoising both single and multi-delay 3D ASL data. The proposed model offers flexibility to improve image quality and/or reduce scan time for 3D ASL to facilitate its clinical use.

Imaging of Angiogenesis in White Matter Hyperintensities

Background White matter hyperintensities (WMHs) are areas of increased signal intensity on T2-weighted magnetic resonance imaging (MRI). WMH penumbra may be a potential target for early intervention in WMHs. We explored the relationship between angiogenesis and WMH penumbra in patients with WMHs. Methods and Results Twenty-one patients with confluent WMHs of Fazekas grade ≥2 were included. All the participants underwent 68Ga-NOTA-PRGD2 positron emission tomography/magnetic resonance imaging. WMH penumbra was analyzed with masks created for the WMH and 7 normal-appearing white matter layers; each layer was dilated away from the WMH by 2 mm. Angiogenesis array and ELISA were used to detect the serum levels of angiogenic factors, inflammatory factors, HIF-1 alpha, and S100B. Fourteen patients with increased 68Ga-NOTA-PRGD2 maximum standardized uptake (>0.17) were classified into group 2. Seven patients with maximum standardized uptake ≤0.17 were classified as group 1. WMH volume and serum levels of integrin αvβ3, vascular endothelial growth factor receptor 22, and interleukin-1β tended to be higher in group 2 than in group 1. In group 2, 68Ga-NOTA-PRGD2 uptake was significantly increased at the border between the WMH and normal-appearing white matter than in WMHs (P=0.004). The structure penumbra, defined by fractional anisotropy, was wider in group 2 (8 mm) than in group 1 (2 mm). The cerebral blood flow penumbra was 12 mm in both groups. Angiogenesis showed a correlation with reduced cerebral blood flow and microstructure integrity. Conclusions Our study provides evidence that angiogenesis occurs in the WMH penumbra. Further studies are warranted to verify the effect of angiogenesis on WMH growth.

Multidelay MR Arterial Spin Labeling Perfusion Map for the Prediction of Cerebral Hyperperfusion After Carotid Endarterectomy

BACKGROUND

Multidelay arterial spin labeling (ASL) generates time-resolved perfusion maps, which may provide sufficient and accurate hemodynamic information in carotid stenosis.

PURPOSE

To use imaging markers derived from multidelay ASL magnetic resonance imaging (MRI) and to determine the optimal strategy for predicting cerebral hyperperfusion after carotid endarterectomy (CEA).

STUDY TYPE

Prospective observational cohort.

SUBJECTS

A total of 79 patients who underwent CEA for carotid stenosis.

FIELD STRENGTH/SEQUENCE

A 3.0 T/pseudo-continuous ASL with three postlabeling delays of 1.0, 1.57, and 2.46 seconds using fast-spin echo readout.

ASSESSMENT

Cerebral perfusion pressure, antegrade, and collateral flow were scored on a four-grade ordinal scale based on preoperative multidelay ASL perfusion maps. Simultaneously, quantitative hemodynamic parameters including cerebral blood flow (CBF), arterial transit time (ATT), relative CBF (rCBF) and relative ATT (rATT; ipsilateral/contralateral values) were calculated. On the CBF ratio map obtained through dividing postoperative by preoperative CBF map, regions of interest were placed covering ipsilateral middle cerebral artery territory. Three neuroradiologists conducted this procedure. Cerebral hyperperfusion was defined as a CBF ratio >2.

STATISTICAL TESTS

Weighted κ values, independent sample t test, chi-square test, Mann-Whitney U-test, multivariable logistic regression analysis, receiver-operating characteristic curve analysis, and Delong test. Significance level was P < 0.05.

RESULTS

Cerebral hyperperfusion was observed in 15 (19%) patients. Higher blood pressure (odd ratio [OR] = 1.08) and carotid near-occlusion (NO; OR = 7.31) were clinical risk factors for postoperative hyperperfusion. Poor ASL perfusion score (OR = 37.33), decreased CBF (OR = 0.74), prolonged ATT (OR = 1.02), lower rCBF (OR = 0.91), and higher rATT (OR = 1.12) were independent imaging predictors of hyperperfusion. ASL perfusion score exhibited the highest specificity (95.3%), while CBF exhibited the highest sensitivity (93.3%) for the prediction of hyperperfusion. When combined with ASL perfusion score, CBF and ATT, the predictive ability was significantly higher than using blood pressure and NO alone (AUC: 0.98 vs. 0.78).

DATA CONCLUSIONS

Multidelay ASL can accurately predict cerebral hyperperfusion after CEA with high sensitivity and specificity.

EVIDENCE LEVEL

2 TECHNICAL EFFICACY: Stage 5.

Test-retest reliability of 3D velocity-selective arterial spin labeling for detecting normal variations of cerebral blood flow

Velocity-selective inversion (VSI) based velocity-selective arterial spin labeling (VSASL) has been developed to measure cerebral blood flow (CBF) with low susceptibility to the prolonged arterial transit time and high sensitivity to brain perfusion signal. The purpose of this magnetic resonance imaging study is to evaluate the test-retest reliability of a VSI-prepared 3D VSASL protocol with whole-brain coverage to detect baseline CBF variations among cognitively normal participants in different brain regions. Coefficients of variation (CoV) of both absolute and relative CBF across scans or sessions, subjects, and gray matter regions were calculated, and corresponding intraclass correlation coefficients (ICC) were computed. The higher between-subject CoV of absolute CBF (13.4 ± 2.0%) over within-subject CoV (within-session: 3.8 ± 1.1%; between-session: 4.9 ± 0.9%) yielded moderate to excellent ICC (within-session: 0.88±0.08; between-session: 0.77±0.14) to detect normal variations of individual CBF. The higher between-region CoV of relative CBF (11.4 ± 3.0%) over within-region CoV (within-session: 2.3 ± 0.9%; between-session: 3.3 ± 1.0%) yielded excellent ICC (within-session: 0.92±0.06; between-session: 0.85±0.12) to detect normal variations of regional CBF. Age, blood pressure, end-tidal CO2, and hematocrit partially explained the variability of CBF across subjects. Together these results show excellent test-retest reliability of VSASL to detect both between-subject and between-region variations supporting its clinical utility.

Transformer based deep learning denoising of single and multi-delay 3D Arterial Spin Labeling

Purpose

To present a Swin Transformer-based deep learning (DL) model for denoising of single-delay and multi-delay 3D arterial spin labeling (ASL) and compare its performance with convolutional neural network (CNN) methods.

Methods

Swin Transformer and CNN-based spatial denoising models were developed for single-delay ASL. The models were trained on 59 subjects (104 scans) and tested on 44 subjects (57 scans) from 3 different vendors. Spatiotemporal denoising models were developed using another dataset (6 subjects, 10 scans) of multi-delay ASL. A range of input conditions was tested for denoising single and multi-delay ASL respectively. The performance was evaluated using similarity metrics, spatial signal-to-noise ratio (SNR) and quantification accuracy of cerebral blood flow (CBF) and arterial transit time (ATT).

Results

Swin Transformer outperformed CNN-based networks, whereas pseudo-3D models showed better performance than 2D models for denoising single-delay ASL. The similarity metrics and image quality (SNR) improved with more slices in pseudo-3D models, and further improved when using M0 as input but introduced greater biases for CBF quantification. Pseudo-3D models with 3 slices as input achieved optimal balance between SNR and accuracy, which can be generalized to different vendors. For multi-delay, spatiotemporal denoising models had better performance than spatial-only models with reduced biases in fitted CBF and ATT maps.

Conclusions

Swin Transformer DL models provided better performance than CNN methods for denoising both single and multi-delay 3D ASL data. The proposed model offers flexibility to improve image quality and/or reduce scan time for 3D ASL to facilitate its clinical use.

Reproducibility of cerebral perfusion measurements using BOLD delay

BOLD delay is an emerging, noninvasive method for assessing cerebral perfusion that does not require the use of intravenous contrast agents and is thus particularly suited for longitudinal monitoring. In this study, we assess the reproducibility of BOLD delay using data from 136 subjects with normal cerebral perfusion scanned on two separate occasions with scanners, sequence parameters, and intervals between scans varying between subjects. The effects of various factors on the reproducibility of BOLD delay, defined here as the differences in BOLD delay values between the scanning sessions, were investigated using a linear mixed model. Reproducibility was additionally assessed using the intraclass correlation coefficient of BOLD delay between sessions. Reproducibility was highest in the posterior cerebral artery territory. The mean BOLD delay test-retest difference after accounting for the aforementioned factors was 1.2 s (95% CI = 1.0 to 1.4 s). Overall, BOLD delay shows good reproducibility, but care should be taken when interpreting longitudinal BOLD delay changes that are either very small or are located in certain brain regions.

Recent advances in arterial spin labeling perfusion MRI in patients with vascular cognitive impairment

Cognitive impairment (CI) is a major health concern in aging populations. It impairs patients' independent life and may progress to dementia. Vascular cognitive impairment (VCI) encompasses all cerebrovascular pathologies that contribute to cognitive impairment (CI). Moreover, the majority of CI subtypes involve various aspects of vascular dysfunction. Recent research highlights the critical role of reduced cerebral blood flow (CBF) in the progress of VCI, and the detection of altered CBF may help to detect or even predict the onset of VCI. Arterial spin labeling (ASL) is a non-invasive, non-ionizing perfusion MRI technique for assessing CBF qualitatively and quantitatively. Recent methodological advances enabling improved signal-to-noise ratio (SNR) and data acquisition have led to an increase in the use of ASL to assess CBF in VCI patients. Combined with other imaging modalities and biomarkers, ASL has great potential for identifying early VCI and guiding prediction and prevention strategies. This review focuses on recent advances in ASL-based perfusion MRI for identifying patients at high risk of VCI.

Multidelay ASL of the pediatric brain

Arterial spin labeling (ASL) is a powerful noncontrast MRI technique for evaluation of cerebral blood flow (CBF). A key parameter in single-delay ASL is the choice of postlabel delay (PLD), which refers to the timing between the labeling of arterial free water and measurement of flow into the brain. Multidelay ASL (MDASL) utilizes several PLDs to improve the accuracy of CBF calculations using arterial transit time (ATT) correction. This approach is particularly helpful in situations where ATT is unknown, including young subjects and slow-flow conditions. In this article, we discuss the technical considerations for MDASL, including labeling techniques, quantitative metrics, and technical artefacts. We then provide a practical summary of key clinical applications with real-life imaging examples in the pediatric brain, including stroke, vasculopathy, hypoxic-ischemic injury, epilepsy, migraine, tumor, infection, and metabolic disease.

Arterial transit artifacts on arterial spin labeling MRI can predict cerebral hyperperfusion after carotid endarterectomy: an initial study

OBJECTIVES

To investigate whether preoperative arterial spin labeling (ASL) MRI can predict cerebral hyperperfusion after carotid endarterectomy (CEA) in patients with carotid stenosis.

METHODS

Consecutive patients with carotid stenosis who underwent CEA between May 2015 and July 2021 were included. For each patient, a cerebral blood flow ratio (rCBF) map was obtained by dividing postoperative CBF with preoperative CBF images from two pseudo-continuous ASL scans. Hyperperfusion regions with rCBF > 2 were extracted and weighted with rCBF to calculate the hyperperfusion index. According to the distribution of the hyperperfusion index, patients were divided into hyperperfusion and non-hyperperfusion groups. Preoperative ASL images were scored based on the presence of arterial transit artifacts (ATAs) in 10 regions of interest corresponding to the Alberta Stroke Programme Early Computed Tomography Score methodology. The degree of stenosis and primary and secondary collaterals were evaluated to correlate with the ASL score. Logistic regression and receiver operating characteristic curve analyses were performed to assess the predictive ability of the ASL score for cerebral hyperperfusion.

RESULTS

Of 86 patients included, cerebral hyperperfusion was present in 17 (19.8%) patients. Carotid near occlusion, opening of posterior communicating arteries with incomplete anterior semicircle, and leptomeningeal collaterals were associated with lower ASL scores (p < 0.05). The preoperative ASL score was an independent predictor of cerebral hyperperfusion (OR = 0.48 [95% CI [0.33-0.71]], p < 0.001) with the optimal cutoff value of 25 points (AUC = 0.98, 94.1% sensitivity, 88.4% specificity).

CONCLUSIONS

Based on the presence of ATAs, ASL can non-invasively predict cerebral hyperperfusion after CEA in patients with carotid stenosis.

KEY POINTS

• Carotid near occlusion, opening of posterior communicating arteries with incomplete anterior semicircle, and leptomeningeal collaterals were associated with lower ASL scores. • The ASL score performed better than the degree of stenosis, type of CoW, and leptomeningeal collaterals, as well as the combination of the three factors for the prediction of cerebral hyperperfusion. • For patients with carotid stenosis, preoperative ASL can non-invasively identify patients at high risk of cerebral hyperperfusion after carotid endarterectomy without complex post-processing steps.

Noncontrast Pediatric Brain Perfusion: Arterial Spin Labeling and Intravoxel Incoherent Motion

Noncontrast magnetic resonance imaging techniques for measuring brain perfusion include arterial spin labeling (ASL) and intravoxel incoherent motion (IVIM). These techniques provide noninvasive and repeatable assessment of cerebral blood flow or cerebral blood volume without the need for intravenous contrast. This article discusses the technical aspects of ASL and IVIM with a focus on normal physiologic variations, technical parameters, and artifacts. Multiple pediatric clinical applications are presented, including tumors, stroke, vasculopathy, vascular malformations, epilepsy, migraine, trauma, and inflammation.

Choroid plexus perfusion in sickle cell disease and moyamoya vasculopathy: Implications for glymphatic flow

Cerebrospinal fluid (CSF) and interstitial fluid exchange have been shown to increase following pharmacologically-manipulated increases in cerebral arterial pulsatility, consistent with arterial pulsatility improving CSF circulation along perivascular glymphatic pathways. The choroid plexus (CP) complexes produce CSF, and CP activity may provide a centralized indicator of perivascular flow. We tested the primary hypothesis that elevated cortical cerebral blood volume and flow, present in sickle cell disease (SCD), is associated with fractionally-reduced CP perfusion relative to healthy adults, and the supplementary hypothesis that reduced arterial patency, present in moyamoya vasculopathy, is associated with elevated fractional CP perfusion relative to healthy adults. Participants (n = 75) provided informed consent and were scanned using a 3-Tesla arterial-spin-labeling MRI sequence for CP and cerebral gray matter (GM) perfusion quantification. ANOVA was used to calculate differences in CP-to-GM perfusion ratios between groups, and regression analyses applied to evaluate the dependence of the CP-to-GM perfusion ratio on group after co-varying for age and sex. ANOVA yielded significant (p < 0.001) group differences, with CP-to-GM perfusion ratios increasing between SCD (ratio = 0.93 ± 0.28), healthy (ratio = 1.04 ± 0.32), and moyamoya (ratio = 1.29 ± 0.32) participants, which was also consistent with regression analyses. Findings are consistent with CP perfusion being inversely associated with cortical perfusion.

The Association Between Perivascular Spaces and Cerebral Blood Flow, Brain Volume, and Cardiovascular Risk

Background: Basal ganglia perivascular spaces are associated with cognitive decline and cardiovascular risk factors. There is a lack of studies on the cardiovascular risk burden of basal ganglia perivascular spaces (BG-PVS) and their relationship with gray matter volume (GMV) and GM cerebral blood flow (CBF) in the aging brain. Here, we investigated these two issues in a large sample of cognitively intact older adults.

Methods: A total of 734 volunteers were recruited. MRI was performed with 3.0 T using a pseudo-continuous arterial spin labeling (pCASL) sequence and a sagittal isotropic T1-weighted sequence for CBF and GMV analysis. The images obtained from 406 participants were analyzed to investigate the relationship between the severity of BG-PVS and GMV/CBF. False discovery rate-corrected P-values (P_FDR) of <0.05 were considered significant. The images obtained from 254 participants were used to study the relationship between the severity of BG-PVS and cardiovascular risk burden. BG-PVS were rated using a 5-grade score. The severity of BG-PVS was classified as mild (grade <3) and severe (grade ≥3). Cardiovascular risk burden was assessed with the Framingham General Cardiovascular Risk Score (FGCRS).

Results: Severe basal ganglia perivascular spaces were associated with significantly smaller GMV and CBF in multiple cortical regions (P_FDR <0.05), and were associated with significantly larger volume in the bilateral caudate nucleus, pallidum, and putamen (P_FDR <0.05). The participants with severe BG-PVS were more likely to have a higher cardiovascular risk burden than the participants with mild BG-PVS (60.71% vs. 42.93%; P =0.02).

Conclusion: In cognitively intact older adults, severe BG-PVS are associated with smaller cortical GMV and CBF, larger subcortical GMV, and higher cardiovascular risk burden.

Evaluation of Cerebral Blood Flow Measured by 3D PCASL as Biomarker of Vascular Cognitive Impairment and Dementia (VCID) in a Cohort of Elderly Latinx Subjects at Risk of Small Vessel Disease

Cerebral small vessel disease (cSVD) affects arterioles, capillaries, and venules and can lead to cognitive impairments and clinical symptomatology of vascular cognitive impairment and dementia (VCID). VCID symptoms are similar to Alzheimer’s disease (AD) but the neurophysiologic alterations are less well studied, resulting in no established biomarkers. The purpose of this study was to evaluate cerebral blood flow (CBF) measured by 3D pseudo-continuous arterial spin labeling (pCASL) as a potential biomarker of VCID in a cohort of elderly Latinx subjects at risk of cSVD. Forty-five elderly Latinx subjects (12 males, 69 ± 7 years) underwent repeated MRI scans ∼6 weeks apart. CBF was measured using 3D pCASL in the whole brain, white matter and 4 main vascular territories (leptomeningeal anterior, middle, and posterior cerebral artery (leptoACA, leptoMCA, leptoPCA), as well as MCA perforator). The test-retest repeatability of CBF was assessed by intra-class correlation coefficient (ICC) and within-subject coefficient of variation (wsCV). Absolute and relative CBF was correlated with gross cognitive measures and domain specific assessment of executive and memory function, vascular risks, and Fazekas scores and volumes of white matter hyperintensity (WMH). Neurocognitive evaluations were performed using Montreal Cognitive Assessment (MoCA) and neuropsychological test battery in the Uniform Data Set v3 (UDS3). Good to excellent test-retest repeatability was achieved (ICC = 0.77–0.85, wsCV 3–9%) for CBF measurements in the whole brain, white matter, and 4 vascular territories. Relative CBF normalized by global mean CBF in the leptoMCA territory was positively correlated with the executive function composite score, while relative CBF in the leptoMCA and MCA perforator territory was positively correlated with MoCA scores, controlling for age, gender, years of education, and testing language. Relative CBF in WM was negatively correlated with WMH volume and MoCA scores, while relative leptoMCA CBF was positively correlated with WMH volume. Reliable 3D pCASL CBF measurements were achieved in the cohort of elderly Latinx subjects. Relative CBF in the leptomeningeal and perforator MCA territories were the most likely candidate biomarker of VCID. These findings need to be replicated in larger cohorts with greater variability of stages of cSVD.