Accuracy Of Arterial Spin Labeling Research Articles

Diagnostic Accuracy of Arterial Spin Labeling in Comparison With Dynamic Susceptibility Contrast-Enhanced Perfusion for Brain Tumor Surveillance at 3T MRI.

PurposeWe aimed to compare arterial spin labeling (ASL) with dynamic susceptibility contrast (DSC) enhanced perfusion MRI for the surveillance of primary and metastatic brain tumors at 3T, both in terms of lesion perfusion metrics and diagnostic accuracy.MethodsIn this retrospective study, we included 115 patients, who underwent both ASL and DSC perfusion in the same 3T MRI scanning session between 1 January and 31 December 2019. ASL-derived cerebral blood flow (CBF) maps and DSC-derived relative cerebral blood volume (rCBV) maps, both uncorrected and corrected for leakage, were created with commercially available software. Lesions were identified as T2-/T2-FLAIR hyperintensity with or without contrast enhancement. Measurements were done by placing a region of interest in the visually determined area of highest perfusion, copying to the contralateral normal appearing white matter (NAWM), and then propagating to the other perfusion maps. Pearson’s correlation coefficients were calculated between the CBF and rCBV ratios of tumor versus NAWM. Accuracy for diagnosing tumor progression was calculated as the area under the receiver operating characteristics (ROC) curve (AUC) for the ASL-CBF and leakage corrected DSC-rCBV ratios.ResultsWe identified 178 lesions, 119 with and 59 without contrast enhancement. Correlation coefficients between ASL-derived CBF versus DSC-derived rCBV ratios were 0.60–0.67 without and 0.72–0.78 with leakage correction in all lesions (n = 178); these were 0.65–0.80 in enhancing glioma (n = 80), 0.58–0.73 in non-enhancing glioma, and 0.14–0.40 in enhancing metastasis (n = 31). No significant correlation was found in enhancing (n = 8) or non-enhancing (n = 7) lymphomas. The areas under the ROC curves (AUCs) for all patients were similar for ASL and DSC (0.73–0.78), and were higher for enhancing glioma (AUC = 0.78–0.80) than for non-enhancing glioma (AUC = 0.56–0.62). In brain metastasis, the AUC was lower for ASL-derived CBF (AUC = 0.72) than for DSC-derived rCBV ratios (AUC = 0.87–0.93).ConclusionWe found that ASL and DSC have more or less the same diagnostic accuracy. Our findings suggest that ASL can be used as an alternative to DSC to measure perfusion in enhancing and non-enhancing gliomas and brain metastasis at 3T. For lymphoma, this should be further investigated in a larger population.

Improvement of Shunt Detection with Arterial Spin-Labeling MR Imaging in Follow-Up of a Treated Cerebral Arteriovenous Malformation

Objective: To identify and evaluate the pitfalls of using arterial spin labeling (ASL) to diagnose cerebral arteriovenous malformation (AVM) and improve its accuracy in clinical practice. Materials and Methods: A retrospective study of 54 patients with cerebral AVM was performed. Each patient underwent magnetic resonance imaging (MRI) studies, including pseudo-continuous ASL (pCASL) and conventional cerebral angiography with a digital subtraction angiography (DSA) during a 3-year period. The consensus of the results of the imaging studies was used to evaluate the diagnostic performance of the MRI technique, with DSA used as the gold standard. Results: Diagnostic accuracy was 94.4% when a positive arteriovenous shunt (AVS) was defined as a high ASL signal in the venous structure or nidus, compared to magnetic resonance angiography (MRA). The misinterpretations of the ASL images of cerebral AVM were due to an arterial transit artifact (ATA) associated with a residual AVS. The other pitfalls were micro-AVMs and very slow-flow AVSs. Conclusion: To improve the accuracy of ASL in evaluating an AVS in cerebral AVM, it is mandatory to detect high ASL signals in venous structures by comparing with MRA. Keywords: Arterial spin labeling; Arteriovenous malformation; Arteriovenous shunt; Magnetic resonance angiography

Differences in cerebral blood flow measurement using arterial spin labeling MRI between patients with moyamoya disease and patients with arteriosclerotic cerebrovascular disease.

It is unclear whether the accuracy of arterial spin labeling (ASL) magnetic resonance imaging (MRI) is the same between moyamoya disease (MMD), which is known to have markedly elevated cerebral blood volume (CBV), and atherosclerotic intracranial arterial stenosis (AS), which has relatively less elevated CBV. To investigate how the differences in hemodynamics affect measurement of ASL-cerebral blood flow (CBF) using ASL for patients with MMD and AS. Fourteen MMD and ten AS patients were evaluated with ASL-MRI, magnetic resonance angiography (MRA), and 15O-gas positron emission computed tomography (PET). The regional CBF values of ASL using two post-labeling delays (PLDs; 1525 ms and 2525 ms) were compared with the PET-derived CBF, CBV, and mean transit time (MTT). Corresponding anterior circulation results were evaluated by flow territory map-based analysis. The correlation between the ASL-CBF values (2525 ms) and PET-CBF declined in the MMD group (r = 0.28; P < 0.01), while the AS group showed good correlation (r = 0.77; P < 0.01). In the MMD group, the ASL-CBF values (2525 ms) overestimated the PET-CBF values as the regional CBV values increased (r = 0.35; P < 0.01). When the regions of interest were divided into two subgroups according to the degree of arterial stenosis by MRA, the correlation coefficient between the ASL-CBF (2525 ms) and PET-CBF values improved (mild stenosis: r = 0.36; P = 0.06; severe stenosis: r = 0.51; P < 0.01). The accuracy of CBF measurements using ASL-MRI differed between patients with MMD and AS. The prominent increase of CBV and the degree of arterial stenosis may have affected the accuracy of ASL-CBF in patients with MMD.

Bias and Precision in Magnetic Resonance Imaging-Based Estimates of Renal Blood Flow: Assessment by Triangulation.

Renal blood flow (RBF) can be measured with dynamic contrast enhanced-MRI (DCE-MRI) and arterial spin labeling (ASL). Unfortunately, individual estimates from both methods vary and reference-standard methods are not available. A potential solution is to include a third, arbitrating MRI method in the comparison. To compare RBF estimates between ASL, DCE, and phase contrast (PC)-MRI. Prospective. Twenty-five patients with type-2 diabetes (36% female) and five healthy volunteers (HV, 80% female). A 3 T; gradient-echo 2D-DCE, pseudo-continuous ASL (pCASL) and cine 2D-PC. ASL, DCE, and PC were acquired once in all patients. ASL and PC were acquired four times in each HV. RBF was estimated and split-RBF was derived as (right kidney RBF)/total RBF. Repeatability error (RE) was calculated for each HV, RE=1.96×SD, where SD is the standard deviation of repeat scans. Paired t-tests and one-way analysis of variance (ANOVA) were used for statistical analysis. The 95% confidence interval (CI) for difference between ASL/PC and DCE/PC was assessed using two-sample F-test for variances. Statistical significance level was P < 0.05. Influential outliers were assessed with Cook's distance (Di > 1) and results with outliers removed were presented. In patients, the mean RBF (mL/min/1.73m2 ) was 618 ± 62 (PC), 526 ± 91 (ASL), and 569 ± 110 (DCE). Differences between measurements were not significant (P=0.28). Intrasubject agreement was poor for RBF with limits-of-agreement (mL/min/1.73m2 ) [-687, 772] DCE-ASL, [-482, 580] PC-DCE, and [-277, 460] PC-ASL. The difference PC-ASL was significantly smaller than PC-DCE, but this was driven by a single-DCE outlier (P=0.31, after removing outlier). The difference in split-RBF was comparatively small. In HVs, mean RE (±95% CI; mL/min/1.73 m2 ) was significantly smaller for PC (79 ± 41) than for ASL (241 ± 85). ASL, DCE, and PC RBF show poor agreement in individual subjects but agree well on average. Triangulation with PC suggests that the accuracy of ASL and DCE is comparable. 2 TECHNICAL EFFICACY: Stage 2.

Improving the image quality and quantitative accuracy of arterial spin labeling based on generative adversarial network

Objective: To investigate the use of deep learning approaches to improve the image quality of arterial spin labeling (ASL) and optimize its quantitative accuracy for cerebral blood flow (CBF). Methods: The clinical and imaging data of 101 patients with cerebrovascular disease in Tianjin Huanhu Hospital from May 2018 to August 2019 were retrospectively collected. Patients were divided into a training set (71 cases) and a validation set (30 cases). In training set, there were 53 cases of male,18 cases of female,with age of 55.0 (41.3, 64.5), and in validation set, there were 23 cases of male,7 cases of female,with age of57.5 (49.0, 65.0). Quantitative perfusion weighted imaging was used as the reference standard, and the original ASL-CBF images were reconstructed by training a deep learning generative adversarial network (GAN). The image quality of original ASL-CBF and GAN-CBF was compared by the structural similarity index and the normalized root mean square error. Pearson correlation coefficient was used to analyze the correlation between ASL-CBF, GAN-CBF and quantitative perfusion in different cerebral vascular blood supply areas and stroke areas, and to verify the improvement effect of GAN on the image quality and quantitative accuracy of ASL. Results: There were significant differences in gender, age, disease type, site and size between training set and validation set (all P>0.05). Compared with ASL-CBF, GAN-CBF had a higher structural similarity index (0.888 vs 0.801, P<0.001), and a lower normalized root mean square error (0.628 vs 0.775, P<0.001). The correlation between GAN-CBF and quantitative perfusion in different blood vessel supply areas and stroke lesion areas was improved compared with the original ASL-CBF, in which the perforating branch of the middle artery (r=0.853) and stroke lesion areas (r=0.765) were the most obvious (all P<0.001). Conclusion: The generative adversarial network could improve the image quality and quantization accuracy of ASL without increasing the scanning time, and expand the clinical application value of ASL.

Based on arterial spin labeling helps to differentiate high-grade gliomas from brain solitary metastasis: A systematic review and meta-analysis.

Background:We first introduced this meta-analysis was to assess the accuracy of arterial spin labeling (ASL) in the differentiating high-grade gliomas (HGG) from brain solitary metastases (BSM).Methods:The PubMed, Web of Knowledge, and Cochrane Libraries and China National Knowledge Infrastructure databases were searched up to August 31, 2018. The pooled weighted sensitivity and specificity, summary receiver operating characteristic curve (SROC), sensitivity analysis, and threshold effect analysis were performed on Stata version 12.0 and Meta-Disc version 1.4. Deeks’ funnel plot asymmetry test was performed to assess publication bias.Results:Of 5 eligible articles, of the 346 lesions from 346 patients, 274 were HGG, and 72 were BSM. The forest pooled sensitivity of 0.88 (95% confidence interval [CI]: 0.65, 0.96) and specificity of 0.85 (95% CI: 0.74, 0.92) of ASL were reported in this meta-analysis. The pooled area under the curve of SROC was 0.92 (95% CI: 0.89, 0.94). Sensitivity analysis demonstrated that the pooled estimates were reliable. No evident publication bias was obtained (P = .38).Conclusion:The parameters derived from ASL with high accuracy in differentiating HGG from BSM. However, results must be interpreted with caution due to the small sample size considered. Large sample prospective studies were necessary to assess and confirm its clinical value.

Effects of arterial transit delay on cerebral blood flow quantification using arterial spin labeling in an elderly cohort.

To investigate whether measurement of arterial transit time (ATT) can improve the accuracy of arterial spin labeling (ASL) cerebral blood flow (CBF) quantification in an elderly cohort due to the potentially prolonged ATT in the cohort. We employed a 1-minute, low-resolution (12 mm in-plane), sequential multidelay ATT measurement (both with and without vessel suppression) approach to characterize and correct ATT errors in CBF imaging of an elderly, clinical cohort. In all, 140 nondemented subjects greater than 70 years old were imaged at 3T with a single delay, volumetric continuous ASL sequence and also with the fast ATT measurement method. Nine healthy young subjects (28 ± 6 years old) were also imaged. ATTs measured without vessel suppression (superior frontal: 1.51 ± 0.27 sec) in the elderly were significantly shorter than those with suppression (P < 0.0001). Correction of CBF for ATT significantly increased average CBF in multiple brain regions where ATT was longer than the postlabeling delay (P < 0.01) and decreased intersubject variability of CBF in frontal, parietal, and occipital regions (P < 10-8 ). Measured ATT with vessel suppression was significantly longer in the elderly subjects (eg, superior frontal: 1.76 ± 0.25 sec) compared to the younger adults (superior frontal: 1.59 ± 0.19 sec) in basal ganglia and frontal cortical regions (P < 0.05). The ATT measurement is beneficial for imaging of elderly clinical populations. If ATT mapping is not feasible or available, postlabeling delays of 2-2.3 seconds should be used for elderly populations based on longest measured regional ATTs. 1 J. Magn. Reson. Imaging 2017;45:472-481.

Accuracy of arterial spin labeling magnetic resonance imaging (MRI) perfusion in detecting the epileptogenic zone in patients with drug‐resistant neocortical epilepsy: comparison with electrophysiological data, structural MRI, SISCOM and FDG‐PET

Locating the epileptogenic zone (EZ) in patients with neocortical epilepsy presents major challenges. Our aim was to assess the accuracy of arterial spin labeling (ASL), an emerging non-invasive magnetic resonance imaging (MRI) perfusion technique, to locate the EZ in patients with drug-resistant neocortical epilepsy. Twenty-five consecutive patients with neocortical epilepsy referred to our epilepsy unit for pre-surgical evaluation underwent a standardized assessment including video-electroencephalography (EEG) monitoring, structural MRI, subtraction ictal single-photon emission computed tomography co-registered to MRI (SISCOM) and fluorodeoxyglucose positron emission tomography (FDG-PET) studies. An ASL sequence was included in the MRI studies. Areas of hypoperfusion or hyperperfusion on ASL were classified into 15 anatomic-functional cortical regions; these regional cerebral blood flow maps were compared with the EZ determined by the other tests and the strength of concordance was assessed with the kappa coefficient. Of the 25 patients [16 (64%) women; mean age 32.4 (±13.8) years], 18 (72%) had lesions on structural MRI. ASL abnormalities were seen in 15 (60%) patients (nine hypoperfusion, six hyperperfusion). ASL had a very good concordance with FDG-PET (k = 0.84), a good concordance with structural MRI (k = 0.76), a moderate concordance with video-EEG monitoring (k = 0.53) and a fair concordance with SISCOM (k = 0.28). Arterial spin labeling might help to confirm the location and extent of the EZ in the pre-surgical workup of patients with drug-resistant neocortical epilepsy.

Monitoring Cerebrovascular Reactivity through the Use of Arterial Spin Labeling in Patients with Moyamoya Disease.

To assess arterial spin labeling in the identification of impaired cerebrovascular reactivity in patients with moyamoya disease. The institutional review board approved this prospective study, and written informed consent was obtained from all patients. A prospective study was conducted in 78 subjects with moyamoya disease (of whom 31 underwent unilateral direct arterial anastomosis). The concordance between the cerebrovascular reactivity index values from arterial spin labeling and single photon emission computed tomography (SPECT) was assessed by using Bland-Altman analysis, and the area under the receiver operating characteristic curve was used to evaluate the diagnostic accuracy of arterial spin labeling to depict impaired cerebrovascular reactivity (in which the cerebrovascular reactivity index value is less than 0% on SPECT images). The cerebrovascular reactivity index from arterial spin labeling had a lower value than that from SPECT (mean difference, -4.2%). The area under the receiver operating characteristic curve for arterial spin labeling in the detection of impaired cerebrovascular reactivity was at least 0.85. On the anastomotic side, a significant increase was found between the cerebrovascular reactivity index values on arterial spin labeling images obtained preoperatively and those obtained 6 months after surgery, as well as on SPECT images (mean ± standard deviation values of cerebrovascular reactivity index increased by 5.9% ± 10.9 and 3.0% ± 6.3 for arterial spin labeling and SPECT, respectively). Arterial spin labeling has excellent performance in the identification of impaired cerebrovascular reactivity in patients with moyamoya disease, and it has the potential to serve as a noninvasive imaging tool to monitor cerebrovascular reactivity in patients with moyamoya disease.

Effects of Subanesthetic Dose of Nitrous Oxide on Cerebral Blood Flow and Metabolism

Nitrous oxide, in a concentration of 50% or more, is a known cerebral vasodilator. This study investigated whether a lower dose (30%) of nitrous oxide would also increase cerebral blood flow. In addition, the authors wished to study whether the increase in cerebral blood flow was accompanied by an increase in cerebral metabolism. Multimodal Magnetic Resonance Imaging at 3T was performed, and data were obtained in 17 healthy volunteers during three inhalation conditions: medical air, oxygen-enriched medical air (40% oxygen), and 30% nitrous oxide with oxygen-enriched medical air (40% oxygen). Arterial spin labeling was used to derive the primary tissue specific hemodynamic outcomes: cerebral blood flow, arterial blood volume and arterial transit times. Magnetic Resonance Susceptometry and proton Magnetic Resonance Spectroscopy were used for secondary metabolic outcomes: venous oxygenation, oxygen extraction fraction, cerebral metabolic oxygen rate and prefrontal metabolites. Nitrous oxide in 40% oxygen, but not 40% oxygen alone, significantly increased gray matter cerebral blood flow (22%; P < 0.05) and arterial blood volume (41%; P < 0.05). Venous oxygenation increased in both oxygen and nitrous oxide conditions. Compared with medical air inhalation, nitrous oxide condition caused a significantly larger decrease in oxygen extraction fraction than 40% oxygen alone (mean [SD] 11.3 [5.6]% vs. 8.3 [5.9]% P < 0.05), while global cerebral metabolic rate and prefrontal metabolites remained unchanged. This study demonstrates that 30% nitrous oxide in oxygen-enriched air (40% oxygen) significantly increases cerebral perfusion, and reduces oxygen extraction fraction, reflecting a strong arterial vasodilatory effect without associated increases in metabolism.

Abstract TMP39: Identifying Cerebrovascular Reserve Capacity by Arterial Spin Labeling MR in Patients with Moyamoya Disease

Background— The diagnostic accuracy to identify the cerebrocascular reserve capacity (CVRC) by arterial spin labeling (ASL) MR in patients with moyamoya disease is unclear. Methods— We conducted a prospective study to examine the accuracy of ASL as compared with single-photon emission CT (SPECT) in patients with moyamoya disease. Preoperative ASL and SPECT images from 61 adult patients with moyamoya disease were analyzed. For 122 hemispheres from the patients, voxels of interest consisting of bilateral ICA and MCA territories were applied to the spatially normalized cerebral blood flow maps from basal and acetazolamide challenge ASL and SPECT. The correlation between cerebrovascular reserve capacity (CVRC) from ASL and SPECT was analyzed by a using Pearson correlation analysis and the area under the receiver-operating-characteristic curve (AUC) was used to evaluate diagnostic accuracy relative to that of SPECT for various cutoff points by CVRC. Results— Significant relationships were observed between CVRC from ASL and SPECT for the internal carotid artery (ICA) and middle cerebral artery (MCA) (correlation coefficient r = .7093, P &lt; .0001 and r = .7319, P &lt; .0001, respectively) (Table). The diagnostic accuracies of ASL for detecting ICA and MCA areas, in which CVRC are &lt; -5.0%, revealed an AUC of 0.96 (95% confidence interval [CI], 0.91 to 0.99) and 0.96 (95% CI, 0.91 to 0.99, respectively). Conclusions— ASL can identify the reduced CVRC with good performance and has the potential as a noninvasive imaging tool for determining CVRC in patients with moyamoya disease. Table. Correlations between CBF and CVRI values from ASL and SPECT