Clinical evaluation of an arterial-spin-labeling product sequence in steno-occlusive disease of the brain

Subject-specific timing adaption in time-encoded arterial spin labeling imaging

OBJECTIVES

One challenge in arterial spin labeling (ASL) is the high variability of arterial transit times (ATT), which causes associated arterial transit delay (ATD) artifacts. In patients with pathological changes, these artifacts occur when post-labeling delay (PLD) and bolus durations are not optimally matched to the subject, resulting in difficult quantification of cerebral blood flow (CBF) and ATT. This is also true for the free lunch approach in Hadamard-encoded pseudocontinuous ASL (H-pCASL).

MATERIAL AND METHODS

Five healthy volunteers were scanned with a 3 T MR-system. pCASL-subbolus timing was adjusted individually by the developed adaptive Walsh-ordered pCASL sequence and an automatic feedback algorithm. The quantification results for CBF and ATT and the respective standard deviations were compared with results obtained using recommended timings and intentionally suboptimal timings.

RESULTS

The algorithm individually adjusted the pCASL-subbolus PLD for each subject within the range of recommended timing for healthy subjects, with a mean intra-subject adjustment deviation of 47.15 ms for single-shot and 44.5 ms for segmented acquisition in three repetitions.

DISCUSSION

A first positive assessment of the results was performed on healthy volunteers. The extent to which the results can be transferred to patients and are of benefit must be investigated in follow-up studies.

Personalised simulation of hemodynamics in cerebrovascular disease: lessons learned from a study of diagnostic accuracy

Intracranial atherosclerotic disease (ICAD) poses a significant risk of subsequent stroke but current prevention strategies are limited. Mechanistic simulations of brain hemodynamics offer an alternative precision medicine approach by utilising individual patient characteristics. For clinical use, however, current simulation frameworks have insufficient validation. In this study, we performed the first quantitative validation of a simulation-based precision medicine framework to assess cerebral hemodynamics in patients with ICAD against clinical standard perfusion imaging. In a retrospective analysis, we used a 0-dimensional simulation model to detect brain areas that are hemodynamically vulnerable to subsequent stroke. The main outcome measures were sensitivity, specificity, and area under the receiver operating characteristics curve (ROC AUC) of the simulation to identify brain areas vulnerable to subsequent stroke as defined by quantitative measurements of relative mean transit time (relMTT) from dynamic susceptibility contrast MRI (DSC-MRI). In 68 subjects with unilateral stenosis >70% of the internal carotid artery (ICA) or middle cerebral artery (MCA), the sensitivity and specificity of the simulation were 0.65 and 0.67, respectively. The ROC AUC was 0.68. The low-to-moderate accuracy of the simulation may be attributed to assumptions of Newtonian blood flow, rigid vessel walls, and the use of time-of-flight MRI for geometric representation of subject vasculature. Future simulation approaches should focus on integrating additional patient data, increasing accessibility of precision medicine tools to clinicians, addressing disease burden disparities amongst different populations, and quantifying patient benefit. Our results underscore the need for further improvement of mechanistic simulations of brain hemodynamics to foster the translation of the technology to clinical practice.

Comparison of arterial spin labeling perfusion with dynamic susceptibility contrast perfusion in Moyamoya disease

Objectives

Moyamoya disease (MMD) leads to frequent ischemic/hemorrhagic manifestations. Our aim was to compare findings of arterial spin labeling (ASL) with dynamic susceptibility contrast (DSC) perfusion in patients of MMD.

Materials and Methods

Patients diagnosed as MMD underwent magnetic resonance imaging with ASL and DSC perfusion sequences. Perfusion in bilateral anterior cerebral artery and middle cerebral artery territories at two levels (level of thalami and centrum semiovale) was graded as normal (score 1), or reduced (score 2) on DSC and ASL cerebral blood flow (CBF) maps by comparison with normal cerebellar perfusion. Time to peak (TTP) maps of DSC perfusion were also qualitatively scored as normal (score 1), or increased (score 2) similarly. Correlation between scores of ASL, CBF, DSC, CBF, and DSC, TTP maps was assessed by using Spearman's rank correlation.

Results

Among the 34 patients, we did not find any significant correlation between the ASL CBF maps and DSC CBF maps (r = -0.028, P = 0.878), mean matching index 0.39 ± 0.31, whereas significant correlation was noted between the ASL CBF maps and DSC TTP maps (r = 0.58, P = 0.0003), mean matching index 0.79 ± 0.26. ASL CBF underestimated the perfusion compared to DSC perfusion.

Conclusion

ASL perfusion CBF maps do not match the DSC perfusion CBF maps and rather match the TTP maps of DSC perfusion. This is explained by inherent problems in estimation of CBF in these techniques because of delay in arrival of label (in ASL perfusion) or contrast bolus (in DSC perfusion) due to the presence of stenotic lesions.

Image-to-image generative adversarial networks for synthesizing perfusion parameter maps from DSC-MR images in cerebrovascular disease

Stroke is a major cause of death or disability. As imaging-based patient stratification improves acute stroke therapy, dynamic susceptibility contrast magnetic resonance imaging (DSC-MRI) is of major interest in image brain perfusion. However, expert-level perfusion maps require a manual or semi-manual post-processing by a medical expert making the procedure time-consuming and less-standardized. Modern machine learning methods such as generative adversarial networks (GANs) have the potential to automate the perfusion map generation on an expert level without manual validation. We propose a modified pix2pix GAN with a temporal component (temp-pix2pix-GAN) that generates perfusion maps in an end-to-end fashion. We train our model on perfusion maps infused with expert knowledge to encode it into the GANs. The performance was trained and evaluated using the structural similarity index measure (SSIM) on two datasets including patients with acute stroke and the steno-occlusive disease. Our temp-pix2pix architecture showed high performance on the acute stroke dataset for all perfusion maps (mean SSIM 0.92-0.99) and good performance on data including patients with the steno-occlusive disease (mean SSIM 0.84-0.99). While clinical validation is still necessary for future studies, our results mark an important step toward automated expert-level perfusion maps and thus fast patient stratification.

eICAB: A novel deep learning pipeline for Circle of Willis multiclass segmentation and analysis

BACKGROUND

The accurate segmentation, labeling and quantification of cerebral blood vessels on MR imaging is important for basic and clinical research, yet results are not generalizable, and often require user intervention. New methods are needed to automate this process.

PURPOSE

To automatically segment, label and quantify Circle of Willis (CW) arteries on Magnetic Resonance Angiography images using deep convolutional neural networks.

MATERIALS AND METHODS

MRA images were pooled from three public and private databases. A total of 116 subjects (mean age 56 years ± 21 [standard deviation]; 72 women) were used to make up the training set (N=101) and the testing set (N=15). In each image, fourteen arterial segments making up or surrounding the CW were manually annotated and validated by a clinical expert. Convolutional neural network (CNN) models were trained on a training set to be finally combined in an ensemble to develop eICAB. Model performances were evaluated using (1) quantitative analysis (dice score on test set) and (2) qualitative analysis (external datasets, N=121). The reliability was assessed using multiple MRAs of healthy participants (ICC of vessel diameters and volumes on test-retest).

RESULTS

Qualitative analysis showed that eICAB correctly predicted the large, medium and small arteries in 99±0.4%, 97±1% and 88±7% of all images, respectively. For quantitative assessment, the average dice score coefficients for the large (ICAs, BA), medium (ACAs, MCAs, PCAs-P2), and small (AComm, PComm, PCAs-P1) vessels were 0.76±0.07, 0.76±0.08 and 0.41±0.27, respectively. These results were similar and, in some cases, statistically better (p<0.05) than inter-expert annotation variability and robust to image SNR. Finally, test-retest analysis showed that the model yielded high diameter and volume reliability (ICC=0.99).

CONCLUSION

We have developed a quick and reliable open-source CNN-based method capable of accurately segmenting and labeling the CW in MRA images. This method is largely independent of image quality. In the future, we foresee this approach as a critical step towards fully automated analysis of MRA databases in basic and clinical research.

Baseline Hemodynamic Impairment and Revascularization Outcome in Newly Diagnosed Adult Moyamoya Disease Determined by Pseudocontinuous Arterial Spin Labeling

OBJECTIVE

The study aimed to investigate the hemodynamic features and independent predictors of neoangiogenesis after revascularization in moyamoya disease (MMD) by pseudocontinuous arterial spin labeling magnetic resonance imaging (pCASL MRI).

METHODS

Thirty-nine MMD patients were categorized into infarction group, hemorrhagic group, and atypical group. All patients underwent combined bypass surgery and pCASL MRI with postlabeling delays (PLD) of 1525 ms and 2525 ms. Absolute CBF_MCA (cerebral blood flow in middle cerebral artery territory), relative CBF_MCA (CBF_MCA 2525 ms/CBF_MCA 1525 ms), and spatial coefficient of variation of MCA (CoV_MCA) were analyzed. Relationships between CBF_MCA and the following clinical parameters were assessed: Suzuki stage, modified Rankin scale (mRS), cerebrovascular accident lesion score, and deep medullary veins score. Potential predictors for favorable neoangiogenesis and hemodynamic changes were explored as well.

RESULTS

Preoperative CBF_MCA differed among MMD patients with variable clinical presentations, Matsushima stages, modified Rankin Scale scores, CVA scores, and deep medullary vein scores. After bypass surgery, mean CBF_MCA increased significantly in the infarction group (P = 0.027) and decreased in the hemorrhagic group (P = 0.043), while spatial CoV_MCA was observed to decline in all groups. Higher preoperative relative CBF_MCA and spatial CoV_MCA were independent predictors for robust neoangiogenesis after bypass. The cutoff value of 0.330 of spatial CoV_MCA at long PLD yielded the best sensitivity at 82.1% and specificity at 81.8%. Furthermore, both preoperative relative CBF_MCA and spatial CoV_MCA showed mild positive correlations with ΔmRS in MMD patients.

CONCLUSIONS

pCASL-MRI with multiple PLDs could reflect preoperative hemodynamic impairment and predict the neoangiogenesis after combined bypass surgery in moyamoya patients.

Toward Sharing Brain Images: Differentially Private TOF-MRA Images With Segmentation Labels Using Generative Adversarial Networks

Sharing labeled data is crucial to acquire large datasets for various Deep Learning applications. In medical imaging, this is often not feasible due to privacy regulations. Whereas anonymization would be a solution, standard techniques have been shown to be partially reversible. Here, synthetic data using a Generative Adversarial Network (GAN) with differential privacy guarantees could be a solution to ensure the patient's privacy while maintaining the predictive properties of the data. In this study, we implemented a Wasserstein GAN (WGAN) with and without differential privacy guarantees to generate privacy-preserving labeled Time-of-Flight Magnetic Resonance Angiography (TOF-MRA) image patches for brain vessel segmentation. The synthesized image-label pairs were used to train a U-net which was evaluated in terms of the segmentation performance on real patient images from two different datasets. Additionally, the Fréchet Inception Distance (FID) was calculated between the generated images and the real images to assess their similarity. During the evaluation using the U-Net and the FID, we explored the effect of different levels of privacy which was represented by the parameter ϵ. With stricter privacy guarantees, the segmentation performance and the similarity to the real patient images in terms of FID decreased. Our best segmentation model, trained on synthetic and private data, achieved a Dice Similarity Coefficient (DSC) of 0.75 for ϵ = 7.4 compared to 0.84 for ϵ = ∞ in a brain vessel segmentation paradigm (DSC of 0.69 and 0.88 on the second test set, respectively). We identified a threshold of ϵ <5 for which the performance (DSC <0.61) became unstable and not usable. Our synthesized labeled TOF-MRA images with strict privacy guarantees retained predictive properties necessary for segmenting the brain vessels. Although further research is warranted regarding generalizability to other imaging modalities and performance improvement, our results mark an encouraging first step for privacy-preserving data sharing in medical imaging.

Arterial spin labeling signal ratio between the lesion and contralateral sides for evaluation of acute middle cerebral artery infarct

The purpose of our study was to differentiate arterial transit artifact from post-recanalization luxury perfusion on arterial spin labeling (ASL) image, and obtain the relationship between ASL signal intensity and clinical outcomes in patients with acute ischemic stroke.Thirty-five subjects with an acute middle cerebral artery (MCA) infarct were enrolled (18 with recanalized and 17 with non-recanalized MCAs). ASL images were obtained using pseudo-continuous ASL technique with 1600 ms (millisecond) of post-label delay within 3 days from symptom onset. Signal intensities on color ASL images were classified as high, intermediate, and poor grade visually. The ratio of maximum ASL signal between the ischemic area and contralateral side was calculated and compared between patients with and without MCA recanalization. Among patients with non-recanalized MCA, ASL signal ratios were compared between patients with and without hyperintense vessel sign on fluid attenuated inversion recovery (FLAIR). Also, correlation between the ASL signal ratio and National Institutes of Health Stroke Scale (NIHSS) score was evaluated.High or intermediate grade on color ASL images were more frequently found in patients with recanalized MCA (P < .01). Patients with non-recanalized MCA had higher ASL signal ratio in overall ASL signal grade (P = .010) and intermediate grade (P = .011). Among patients with non-recanalized MCA, those with hyperintense vessel sign on FLAIR had higher ASL signal ratios (P = .049). ASL signal ratio was negatively correlated with both initial (P = .023) and final (P = .003) NIHSS scores.The ASL signal ratio could help to differentiate between the pial collaterals and post-recanalization luxury perfusion. A higher ASL ratio was related with the hyperintense vessel sign on FLAIR and lower NIHSS score.

Quantification of Regional Cerebral Blood Flow Using Diffusion Imaging With Phase Contrast

BACKGROUND

The perfusion-related diffusion coefficient obtained from triexponential diffusion analysis is closely correlated with regional cerebral blood flow (rCBF), as assessed by arterial spin labeling (ASL) methods. However, this provides only a semiquantitative measure of rCBF, thereby making absolute rCBF quantification challenging.

PURPOSE

To obtain rCBF in a noninvasive manner using a novel diffusion imaging method with phase contrast (DPC), in which the total CBF from phase-contrast (PC) MRI was utilized to convert perfusion-related diffusion coefficients to rCBF values.

STUDY TYPE

Prospective.

SUBJECTS

Eleven healthy volunteers (nine men and two women; mean age, 23.9 years) participated in this study.

FIELD STRENGTH/SEQUENCE

A 3.0 T, single-shot diffusion echo-planar imaging with multiple b-values (0-3000 s/mm² ), PC-MRI, pulsed continuous ASL, and 3D T₁ -weighted fast field echo.

ASSESSMENT

rCBF and its correlations in the gray matter (GM) and white matter (WM) were compared between DPC and ASL methods. rCBF in the GM and WM and the GM/WM ratio were compared with the literature values obtained using [¹⁵ O]-water positron emission tomography (¹⁵ O-H₂ O PET).

STATISTICAL TESTS

Spearman's correlation coefficient and Wilcoxon signed-rank test were used. Significance was set at P < 0.05.

RESULTS

A significant positive correlation between DPC and ASL in terms of rCBF was observed in GM (R = 0.9), whereas the correlation between the two methods was poor in WM (R = 0.09). The rCBF in GM and WM and the GM/WM ratio obtained using DPC were consistent with the literature values assessed using ¹⁵ O-H₂ O PET. The rCBF value obtained using DPC was significantly higher in the GM and WM than that using ASL.

DATA CONCLUSION

DPC enabled noninvasive quantification of rCBF.

EVIDENCE LEVEL

2 TECHNICAL EFFICACY: Stage 1.

A precision medicine framework for personalized simulation of hemodynamics in cerebrovascular disease

BACKGROUND

Cerebrovascular disease, in particular stroke, is a major public health challenge. An important biomarker is cerebral hemodynamics. To measure and quantify cerebral hemodynamics, however, only invasive, potentially harmful or time-to-treatment prolonging methods are available.

RESULTS

We present a simulation-based approach which allows calculation of cerebral hemodynamics based on the patient-individual vessel configuration derived from structural vessel imaging. For this, we implemented a framework allowing segmentation and annotation of brain vessels from structural imaging followed by 0-dimensional lumped simulation modeling of cerebral hemodynamics. For annotation, a 3D-graphical user interface was implemented. For 0D-simulation, we used a modified nodal analysis, which was adapted for easy implementation by code. The simulation enables identification of areas vulnerable to stroke and simulation of changes due to different systemic blood pressures. Moreover, sensitivity analysis was implemented allowing the live simulation of changes to simulate procedures and disease progression. Beyond presentation of the framework, we demonstrated in an exploratory analysis in 67 patients that the simulation has a high specificity and low-to-moderate sensitivity to detect perfusion changes in classic perfusion imaging.

CONCLUSIONS

The presented precision medicine approach using novel biomarkers has the potential to make the application of harmful and complex perfusion methods obsolete.

Synthesizing anonymized and labeled TOF-MRA patches for brain vessel segmentation using generative adversarial networks

Anonymization and data sharing are crucial for privacy protection and acquisition of large datasets for medical image analysis. This is a big challenge, especially for neuroimaging. Here, the brain's unique structure allows for re-identification and thus requires non-conventional anonymization. Generative adversarial networks (GANs) have the potential to provide anonymous images while preserving predictive properties. Analyzing brain vessel segmentation, we trained 3 GANs on time-of-flight (TOF) magnetic resonance angiography (MRA) patches for image-label generation: 1) Deep convolutional GAN, 2) Wasserstein-GAN with gradient penalty (WGAN-GP) and 3) WGAN-GP with spectral normalization (WGAN-GP-SN). The generated image-labels from each GAN were used to train a U-net for segmentation and tested on real data. Moreover, we applied our synthetic patches using transfer learning on a second dataset. For an increasing number of up to 15 patients we evaluated the model performance on real data with and without pre-training. The performance for all models was assessed by the Dice Similarity Coefficient (DSC) and the 95th percentile of the Hausdorff Distance (95HD). Comparing the 3 GANs, the U-net trained on synthetic data generated by the WGAN-GP-SN showed the highest performance to predict vessels (DSC/95HD 0.85/30.00) benchmarked by the U-net trained on real data (0.89/26.57). The transfer learning approach showed superior performance for the same GAN compared to no pre-training, especially for one patient only (0.91/24.66 vs. 0.84/27.36). In this work, synthetic image-label pairs retained generalizable information and showed good performance for vessel segmentation. Besides, we showed that synthetic patches can be used in a transfer learning approach with independent data. This paves the way to overcome the challenges of scarce data and anonymization in medical imaging.

Quantitative perfusion mapping with induced transient hypoxia using BOLD MRI

PURPOSE

Gadolinium-based dynamic susceptibility contrast (DSC) is commonly used to characterize blood flow in patients with stroke and brain tumors. Unfortunately, gadolinium contrast administration has been associated with adverse reactions and long-term accumulation in tissues. In this work, we propose an alternative deoxygenation-based DSC (dDSC) method that uses a transient hypoxia gas paradigm to deliver a bolus of paramagnetic deoxygenated hemoglobin to the cerebral vasculature for perfusion imaging.

METHODS

Through traditional DSC tracer kinetic modeling, the MR signal change induced by this hypoxic bolus can be used to generate regional perfusion maps of cerebral blood flow, cerebral blood volume, and mean transit time. This gas paradigm and blood-oxygen-level-dependent (BOLD)-MRI were performed concurrently on a cohort of 66 healthy and chronically anemic subjects (age 23.5 ± 9.7, female 64%).

RESULTS

Our results showed reasonable global and regional agreement between dDSC and other flow techniques, such as phase contrast and arterial spin labeling.

CONCLUSION

In this proof-of-concept study, we demonstrated the feasibility of using transient hypoxia to generate a contrast bolus that mimics the effect of gadolinium and yields reasonable perfusion estimates. Looking forward, optimization of the hypoxia boluses and measurement of the arterial-input function is necessary to improve the accuracy of dDSC. Additionally, a cross-validation study of dDSC and DSC in brain tumor and ischemic stroke subjects is warranted to evaluate the clinical diagnostic utility of this approach.

Arterial transit artifacts observed by arterial spin labeling in Moyamoya disease

OBJECTIVES

Arterial spin labeling (ASL) is a magnetic resonance imaging (MRI) technique used to assess cerebral perfusion. When tissue perfusion is impaired, such as in Moyamoya disease, a hyperintense band called the arterial transit artifact (ATA) may occur, which interferes with accurate measurements on ASL-MRI. In this study, we evaluated the correlation of ATAs with magnetic resonance angiography (MRA) and single-photon emission computed tomography (SPECT) imaging results in Moyamoya disease. The aim of our study was to elucidate the pathophysiology of ATAs and risk factors for high ATA scores.

MATERIALS AND METHODS

This retrospective study included 28 patients (56 hemispheres) with Moyamoya disease treated at our institution. MRI, MRA, ASL perfusion, and N-isopropyl-[¹²³I] b-iodoamphetamine (¹²³I-IMP) SPECT were performed. In order to semi-quantitatively evaluate the degree of ATA, the ATA scores were measured according to the number of hyperintense signal bands in the cerebral cortex. The relationship between the ATA scores and clinical and radiological factors were analyzed.

RESULTS

Regional cerebral blood flow (rCBF) determined with ASL weakly correlated with that determined by ¹²³I-IMP SPECT (ρ=0.31, p=0.027). There was no significant association between the ATA scores and rCBF values determined with ¹²³I-IMP SPECT (p=0.872, 0.745, 0.743 at PLD1000 (post-labeling delay), 1500, and 2000, respectively). However, there was a significant correlation between ATA scores and MRA scores (ρ=0.427 p=0.001; ρ=0.612 p=0.001; ρ=0.563 p=0.001 at PLD1000, 1500, and 2000, respectively). An analysis of patient background characteristics revealed a significantly higher incidence of high ATA scores in female patients, patients with high MRA scores, and patients with a distinguishable ivy sign. A multivariate analysis confirmed that female sex, high MRA score, and presence of an ivy sign were risk factors for high ATA scores.

CONCLUSION

ATA scores were moderately correlated with MRA scores, and presence of an ivy sign was the most predictive factor for high ATA scores. A high ATA score determined using ASL in a patient with Moyamoya disease might suggest an advanced disease stage and a reduction in cerebrovascular reserve capacity.

High Intravascular Signal Arterial Transit Time Artifacts Have Negligible Effects on Cerebral Blood Flow and Cerebrovascular Reserve Capacity Measurement Using Single Postlabel Delay Arterial Spin-Labeling in Patients with Moyamoya Disease

BACKGROUND AND PURPOSE

Arterial spin-labeling-derived CBF values may be affected by arterial transit time artefacts. Thus, our aim was to assess to what extent arterial spin-labeling-derived CBF and cerebrovascular reserve capacity values in major vascular regions are overestimated due to the arterial transit time artifacts in patients with Moyamoya disease.

MATERIALS AND METHODS

Eight patients with Moyamoya disease were included before or after revascularization surgery. CBF maps were acquired using a 3D pseudocontinuous arterial spin-labeling sequence, before and 5, 15, and 25 minutes after an IV acetazolamide injection and were registered to each patient's 3D-T1-weighted images. Vascular regions were defined by spatial normalization to a Montreal Neurological Institute-based vascular regional template. The arterial transit time artifacts were defined as voxels with high signal intensity corresponding to the right tail of the histogram for a given vascular region, with the cutoff selected by visual inspection. Arterial transit time artifact maps were created and applied as masks to exclude arterial transit time artifacts on CBF maps, to create corrected CBF maps. The cerebrovascular reserve capacity was calculated as CBF after acetazolamide injection relative to CBF at baseline for corrected and uncorrected CBF values, respectively.

RESULTS

A total of 16 examinations were analyzed. Arterial transit time artifacts were present mostly in the MCA, whereas the posterior cerebral artery was generally unaffected. The largest differences between corrected and uncorrected CBF and cerebrovascular reserve capacity values, reported as patient group average ratio and percentage point difference, respectively, were 0.978 (95% CI, 0.968-0.988) and 1.8 percentage points (95% CI, 0.3-3.2 percentage points). Both were found in the left MCA, 15 and 5 minutes post-acetazolamide injection, respectively.

CONCLUSIONS

Arterial transit time artifacts have negligible overestimation effects on calculated vascular region-based CBF and cerebrovascular reserve capacity values derived from single-delay 3D pseudocontinuous arterial spin-labeling.

Comparison of CBF Measured with Combined Velocity-Selective Arterial Spin-Labeling and Pulsed Arterial Spin-Labeling to Blood Flow Patterns Assessed by Conventional Angiography in Pediatric Moyamoya

BACKGROUND AND PURPOSE

Imaging CBF is important for managing pediatric moyamoya. Traditional arterial spin-labeling MR imaging detects delayed transit thorough diseased arteries but is inaccurate for measuring perfusion because of these delays. Velocity-selective arterial spin-labeling is insensitive to transit delay and well-suited for imaging Moyamoya perfusion. This study assesses the accuracy of a combined velocity-selective arterial spin-labeling and traditional pulsed arterial spin-labeling CBF approach in pediatric moyamoya, with comparison to blood flow patterns on conventional angiography.

MATERIALS AND METHODS

Twenty-two neurologically stable pediatric patients with moyamoya and 5 asymptomatic siblings without frank moyamoya were imaged with velocity-selective arterial spin-labeling, pulsed arterial spin-labeling, and DSA (patients). Qualitative comparison was performed, followed by a systematic comparison using ASPECTS-based scoring. Quantitative pulsed arterial spin-labeling CBF and velocity-selective arterial spin-labeling CBF for the middle cerebral artery, anterior cerebral artery, and posterior cerebral artery territories were also compared.

RESULTS

Qualitatively, velocity-selective arterial spin-labeling perfusion maps reflect the DSA parenchymal phase, regardless of postinjection timing. Conversely, pulsed arterial spin-labeling maps reflect the DSA appearance at postinjection times closer to the arterial spin-labeling postlabeling delay, regardless of vascular phase. ASPECTS comparison showed excellent agreement (88%, κ = 0.77, P < .001) between arterial spin-labeling and DSA, suggesting velocity-selective arterial spin-labeling and pulsed arterial spin-labeling capture key perfusion and transit delay information, respectively. CBF coefficient of variation, a marker of perfusion variability, was similar for velocity-selective arterial spin-labeling in patient regions of delayed-but-preserved perfusion compared to healthy asymptomatic sibling regions (coefficient of variation = 0.30 versus 0.26, respectively, Δcoefficient of variation = 0.04), but it was significantly different for pulsed arterial spin-labeling (coefficient of variation = 0.64 versus 0.34, Δcoefficient of variation = 0.30, P < .001).

CONCLUSIONS

Velocity-selective arterial spin-labeling offers a powerful approach to image perfusion in pediatric moyamoya due to transit delay insensitivity. Coupled with pulsed arterial spin-labeling for transit delay information, a volumetric MR imaging approach capturing key DSA information is introduced.

Diagnostic and prognostic benefit of arterial spin labeling in subacute stroke

BACKGROUND AND PURPOSE

Brain perfusion measurement in the subacute phase of stroke may support therapeutic decisions. We evaluated whether arterial spin labeling (ASL), a noninvasive perfusion imaging technique based on magnetic resonance imaging (MRI), adds diagnostic and prognostic benefit to diffusion-weighted imaging (DWI) in subacute stroke.

METHODS

In a single-center imaging study, patients with DWI lesion(s) in the middle cerebral artery (MCA) territory were included. Onset to imaging time was ≤7 days and imaging included ASL and DWI sequences. Qualitative (standardized visual analysis) and quantitative perfusion analyses (region of interest analysis) were performed. Dichotomized early outcome (modified Rankin Scale [mRS] 0-2 vs. 3-6) was analyzed in two logistic regression models. Model 1 included DWI lesion volume, age, vascular pathology, admission NIHSS, and acute stroke treatment as covariates. Model 2 added the ASL-based perfusion pattern to Model 1. Receiver-operating-characteristic (ROC) and area-under-the-curve (AUC) were calculated for both models to assess their predictive power. The likelihood-ratio-test compared both models.

RESULTS

Thirty-eight patients were included (median age 70 years, admission NIHSS 4, onset to imaging time 67 hr, discharge mRS 2). Qualitative perfusion analysis yielded additional diagnostic information in 84% of the patients. In the quantitative analysis, AUC for outcome prediction was 0.88 (95% CI 0.77-0.99) for Model 1 and 0.97 (95% CI 0.91-1.00) for Model 2. Inclusion of perfusion data significantly improved performance and outcome prediction (p = 0.002) of stroke imaging.

CONCLUSIONS

In patients with subacute stroke, our study showed that adding perfusion imaging to structural imaging and clinical data significantly improved outcome prediction. This highlights the usefulness of ASL and noninvasive perfusion biomarkers in stroke diagnosis and management.

A U-Net Deep Learning Framework for High Performance Vessel Segmentation in Patients With Cerebrovascular Disease

Brain vessel status is a promising biomarker for better prevention and treatment in cerebrovascular disease. However, classic rule-based vessel segmentation algorithms need to be hand-crafted and are insufficiently validated. A specialized deep learning method-the U-net-is a promising alternative. Using labeled data from 66 patients with cerebrovascular disease, the U-net framework was optimized and evaluated with three metrics: Dice coefficient, 95% Hausdorff distance (95HD) and average Hausdorff distance (AVD). The model performance was compared with the traditional segmentation method of graph-cuts. Training and reconstruction was performed using 2D patches. A full and a reduced architecture with less parameters were trained. We performed both quantitative and qualitative analyses. The U-net models yielded high performance for both the full and the reduced architecture: A Dice value of ~0.88, a 95HD of ~47 voxels and an AVD of ~0.4 voxels. The visual analysis revealed excellent performance in large vessels and sufficient performance in small vessels. Pathologies like cortical laminar necrosis and a rete mirabile led to limited segmentation performance in few patients. The U-net outperfomed the traditional graph-cuts method (Dice ~0.76, 95HD ~59, AVD ~1.97). Our work highly encourages the development of clinically applicable segmentation tools based on deep learning. Future works should focus on improved segmentation of small vessels and methodologies to deal with specific pathologies.

Arterial spin labeling: a technical overview

Arterial spin labeling (ASL) is a non-invasive magnetic resonance imaging perfusion method based on changes in net-magnetization of blood water. The absence of contrast use and ionizing radiation, renders ASL valuable in hyper-acute settings as a monitoring tool for repeated dynamical measurements during and after intervention, and for patients with known co-morbidities. This text provides a short methodological introduction to ASL and contrasts it with traditional contrast-enhanced perfusion imaging. The review focused on sequence usefulness in the clinical setting of acute cerebral ischemia investigation.

An Arterial Spin Labeling MRI Perfusion Study of Migraine without Aura Attacks

Background

Studies of brain perfusion during migraine without aura attacks have inconsistent results.

Methods

Arterial spin labeling MRI, a non-invasive quantitative perfusion technique, was used to prospectively study a spontaneous untreated migraine without aura attack and a headache-free period. Image analysis used FSL and MATLAB software; Group analysis used permutation methods for perfusion differences between sessions.

Results

Thirteen women (age 35.7) were scanned during an attack of an average intensity of 6.8 (on 0–10 Visual Analog Scale) and 16 h duration. No global or regional perfusion differences were identified when comparing migraine and migraine-free sessions.

Discussion

Our findings suggest that the painful phase of migraine without aura attacks is not associated with brain perfusion abnormalities.

Association of Collateral Blood Vessels Detected by Arterial Spin Labeling Magnetic Resonance Imaging With Neurological Outcome After Ischemic Stroke

Importance

Robust collateral blood vessels have been associated with better neurologic outcome following acute ischemic stroke (AIS). The most commonly used methods for identifying collaterals are contrast-based angiographic imaging techniques, which are not possible in all patients after AIS.

Objective

To assess the association between the presence of collateral vessels identified using arterial spin labeling (ASL) magnetic resonance imaging, a technique that does not require exogenous administration of contrast, and neurologic outcome in patients after AIS.

Design, Setting, and Participants

This retrospective cohort study examined 38 patients after AIS admitted to a tertiary academic medical center between 2012 and 2014 who underwent MRI with ASL.

Main Outcomes and Measures

According to a prespecified hypothesis, ASL images were graded for the presence of collaterals by 2 neuroradiologists. Modified Rankin Scale (mRS) scores at discharge and other composite data were abstracted from the medical record by a neurologist blinded to radiologic data.

Results

Of the 38 patients, 19 (50.0%) were male, and the mean (SD) age was 61 (20) years. In 25 of 38 patients (65.8%), collaterals were detected using ASL, which were significantly associated with both a good outcome (mRS score of 0-2 at discharge; P = .02) and a 1-point decrease in mRS score at discharge (odds ratio, 6.4; 95% CI, 1.7-23.4; P = .005). In a multivariable ordinal logistic regression model, controlling for admission National Institutes of Health Stroke Scale score, history of atrial fibrillation, premorbid mRS score, and stroke parent artery status, there was a strong association between the presence of ASL collaterals and a 1-point decrease in the mRS score at discharge (odds ratio, 5.1; 95% CI, 1.2-22.1; P = .03).

Conclusions and Relevance

Following AIS, the presence of ASL collaterals is strongly associated with better neurological outcome at hospital discharge. This novel association between ASL collaterals and improved neurologic outcome may help guide prognosis and management, particularly in patients who are unable to undergo contrast-based radiological studies.

Implication of cerebral circulation time in intracranial stenosis measured by digital subtraction angiography on cerebral blood flow estimation measured by arterial spin labeling

PURPOSE

Arterial spin labeling (ASL) magnetic resonance imaging to assess cerebral blood flow (CBF) is of increasing interest in basic research and in diagnostic applications, since ASL provides similar information to positron emission tomography about perfusion in vascular territories. However, in patients with steno-occlusive arterial disease (SOAD), CBF as measured by ASL might be underestimated due to delayed bolus arrival, and thus increased spin relaxation. We aimed to estimate the extent to which bolus arrival time (BAT) was delayed in patients with SOAD and whether this resulted in underestimation of CBF.

METHODS

BAT was measured using digital subtraction angiography (DSA) in ten patients with high-grade stenosis of the middle carotid artery (MCA). Regional CBF was assessed with pseudocontinuous ASL.

RESULTS

BATs were nonsignificantly prolonged in the stenotic hemisphere 4.1±2.0 s compared with the healthy hemisphere 3.3±0.9 s; however, there were substantial individual differences on the stenotic side. CBF in the anterior and posterior MCA territories were significantly reduced on the stenotic hemisphere. Severe stenosis was correlated with longer BAT and lower quantified CBF.

CONCLUSION

ASL-based perfusion measurement involves a race between the decay of the spins and the delivery of labeled blood to the region of interest. Special caution is needed when interpreting CBF values quantified in individuals with altered blood flow and delayed circulation times. However, from a clinician's point of view, an accentuation of hypoperfusion (even if caused by underestimation of CBF due to prolonged BATs) might be desirable since it indexes potentially harmful physiologic deficits.

Walsh-ordered hadamard time-encoded pseudocontinuous ASL (WH pCASL)

PURPOSE

Walsh ordering of Hadamard encoding-matrices and an additional averaging strategy are proposed for Hadamard-encoded pseudocontinuous arterial spin labeling (H-pCASL). In contrast to conventional H-pCASL the proposed method generates more perfusion-weighted images which are accessible already during a running experiment and even from incomplete sets of encoded images.

THEORY

Walsh-ordered Hadamard matrices consist of fully decodable Hadamard submatrices. At any time during a measurement these submatrices may yield perfusion-weighted images, even at runtime and with incomplete datasets. The usage of an additional so-called mirrored matrix for averaging leads to more decodable subboli.

METHODS

Perfusion-weighted images (five healthy volunteers) are generated using both a Walsh-ordered and a corresponding mirrored Hadamard matrix. To test their correctness they are compared with equivalent images from conventional multi postlabeling-delay (PLD) pCASL-measurements.

RESULTS

All predicted perfusion-weighted images could be generated and correlated very well with multi-PLD images. Already small subsets of encoded images, acquired early during the measurement, yielded perfusion-weighted images. The mirrored matrix generates more perfusion-weighted images without time penalty.

CONCLUSION

Early access to perfusion-weighted images despite incomplete datasets allows dynamic adaptation of parameters and increases robustness against artifacts. Thus, the approach may be well suited for clinical applications, where pathologies demand rapid parameter adaptation and increase the chance of artifacts. Magn Reson Med 76:1814-1824, 2016. © 2015 International Society for Magnetic Resonance in Medicine.

Feasibility of Using Pseudo-Continuous Arterial Spin Labeling Perfusion in a Geriatric Population at 1.5 Tesla

Objectives

To evaluate the feasibility of using pseudo-continuous arterial spin labeling (pCASL) perfusion in a geriatric population at 1.5-Tesla.

Materials and Methods

In 17 participants (mean age 78.8±1.63 years) we assessed; 1) inter-session repeatability and reliability of resting state perfusion in 27 brain regions; 2) brain activation using finger-tapping as a means to evaluate the ability to detect flow differences; 3) reliability by comparing cerebral blood flow (CBF) with pCASL to CBF with phase contrast (PC-MR).

Results

The CBF (mean±standard deviation (SD)) for the whole brain grey matter (GM) was 40.6±8.4 and 41.4±8.7 ml/100g/min for the first and second scan respectively. The within-subject standard deviation (SDw), the repeatability index (RI) and intra-class correlation coefficient (ICC) across the 27 regions ranged from 1.1 to 7.9, 2.2 to 15.5 and 0.35 to 0.98 respectively. For whole brain GM the SDw, RI and ICC were 1.6, 3.2 and 0.96 respectively. The between-subject standard deviation (SD_B) was larger than the SDw for all regions. Comparison of CBF at rest and activation on a voxel level showed significantly higher perfusion during finger tapping in the motor- and somatosensory regions. The mean CBF for whole brain GM was 40.6±8.4 ml/100g/min at rest and 42.6±8.6 ml/100g/min during activation. Finally the reliability of pCASL against the reference standard of PC-MR was high (ICC = 0.80). The mean CBF for whole brain measured with PC-MRI was 54.3±10.1 ml/100g/min and 38.3±7.8 ml/100g/min with pCASL.

Conclusions

The results demonstrate moderate to high levels of repeatability and reliability for most brain regions, comparable to what has been reported for younger populations. The performance of pCASL at 1.5-Tesla shows that region-specific perfusion measurements with this technique are feasible in studies of a geriatric population.

3D GRASE pulsed arterial spin labeling at multiple inflow times in patients with long arterial transit times: comparison with dynamic susceptibility-weighted contrast-enhanced MRI at 3 Tesla

Pulsed arterial spin labeling (PASL) at multiple inflow times (multi-TIs) is advantageous for the measurement of brain perfusion in patients with long arterial transit times (ATTs) as in steno-occlusive disease, because bolus-arrival-time can be measured and blood flow measurements can be corrected accordingly. Owing to its increased signal-to-noise ratio, a combination with a three-dimensional gradient and spin echo (GRASE) readout allows acquiring a sufficient number of multi-TIs within a clinically feasible acquisition time of 5 minutes. We compared this technique with the clinical standard dynamic susceptibility-weighted contrast-enhanced imaging-magnetic resonance imaging in patients with unilateral stenosis >70% of the internal carotid or middle cerebral artery (MCA) at 3 Tesla. We performed qualitative (assessment by three expert raters) and quantitative (region of interest (ROI)/volume of interest (VOI) based) comparisons. In 43 patients, multi-TI PASL-GRASE showed perfusion alterations with moderate accuracy in the qualitative analysis. Quantitatively, moderate correlation coefficients were found for the MCA territory (ROI based: r=0.52, VOI based: r=0.48). In the anterior cerebral artery (ACA) territory, a readout related right-sided susceptibility artifact impaired correlation (ROI based: r=0.29, VOI based: r=0.34). Arterial transit delay artifacts were found only in 12% of patients. In conclusion, multi-TI PASL-GRASE can correct for arterial transit delay in patients with long ATTs. These results are promising for the transfer of ASL to the clinical practice.

Improving perfusion quantification in arterial spin labeling for delayed arrival times by using optimized acquisition schemes

OBJECTIVE

The improvement in Arterial Spin Labeling (ASL) perfusion quantification, especially for delayed bolus arrival times (BAT), with an acquisition redistribution scheme mitigating the T1 decay of the label in multi-TI ASL measurements is investigated. A multi inflow time (TI) 3D-GRASE sequence is presented which adapts the distribution of acquisitions accordingly, by keeping the scan time constant.

MATERIAL AND METHODS

The MR sequence increases the number of averages at long TIs and decreases their number at short TIs and thus compensating the T1 decay of the label. The improvement of perfusion quantification is evaluated in simulations as well as in-vivo in healthy volunteers and patients with prolonged BATs due to age or steno-occlusive disease.

RESULTS

The improvement in perfusion quantification depends on BAT. At healthy BATs the differences are small, but become larger for longer BATs typically found in certain diseases. The relative error of perfusion is improved up to 30% at BATs>1500ms in comparison to the standard acquisition scheme.

CONCLUSION

This adapted acquisition scheme improves the perfusion measurement in comparison to standard multi-TI ASL implementations. It provides relevant benefit in clinical conditions that cause prolonged BATs and is therefore of high clinical relevance for neuroimaging of steno-occlusive diseases.