Relative Cerebral Blood Flow Maps Research Articles

Arterial Spin Labeling Reveals Elevated Cerebral Blood Flow with Distinct Clusters of Hypo- and Hyperperfusion after Traumatic Brain Injury.

Imaging detection of brain perfusion alterations after traumatic brain injury (TBI) may provide prognostic insights. In this study, we used arterial spin labeling (ASL) to quantify cross-sectional and longitudinal changes in cerebral blood flow (CBF) after TBI and correlated changes with clinical outcome. We analyzed magnetic resonance imaging scans from adult participants with TBI requiring hospitalization in the acute (2 weeks post-injury, n = 33) and chronic (6 months post-injury, n = 16) phases, with 13 participants scanned longitudinally at both time points. We also analyzed 18 age- and sex-matched healthy controls. Whole-brain CBF maps were derived using a three-dimensional pseudo-continuous arterial spin label technique. Mean CBF across tissue-based regions (whole brain, gray matter, and white matter) was compared cross-sectionally and longitudinally. In addition, individual-level clusters of abnormal perfusion were identified using voxel-based z-score analysis of relative CBF maps, and number and volume of abnormally hypo- and hyperperfused clusters were assessed cross-sectionally and longitudinally. Finally, all CBF measures were correlated with clinical outcome measures. Mean global and gray matter CBF were significantly elevated in acute and chronic TBI participants compared to controls. Participants with better outcome at 6 months post-injury tended to have higher CBF in the acute phase compared to those with poorer outcome. Acute TBI participants had a significantly greater volume of hypo- and hyperperfused brain tissue compared to controls, with these regions partially normalizing by the chronic phase. Our findings demonstrate global elevation of CBF with focal hypo- and hyperperfusion in the early post-injury period and suggest a reparative role for acute elevation in CBF post-TBI.

Machine learning-based segmentation of ischemic penumbra by using diffusion tensor metrics in a rat model

BackgroundRecent trials have shown promise in intra-arterial thrombectomy after the first 6–24 h of stroke onset. Quick and precise identification of the salvageable tissue is essential for successful stroke management. In this study, we examined the feasibility of machine learning (ML) approaches for differentiating the ischemic penumbra (IP) from the infarct core (IC) by using diffusion tensor imaging (DTI)-derived metrics.MethodsFourteen male rats subjected to permanent middle cerebral artery occlusion (pMCAO) were included in this study. Using a 7 T magnetic resonance imaging, DTI metrics such as fractional anisotropy, pure anisotropy, diffusion magnitude, mean diffusivity (MD), axial diffusivity, and radial diffusivity were derived. The MD and relative cerebral blood flow maps were coregistered to define the IP and IC at 0.5 h after pMCAO. A 2-level classifier was proposed based on DTI-derived metrics to classify stroke hemispheres into the IP, IC, and normal tissue (NT). The classification performance was evaluated using leave-one-out cross validation.ResultsThe IC and non-IC can be accurately segmented by the proposed 2-level classifier with an area under the receiver operating characteristic curve (AUC) between 0.99 and 1.00, and with accuracies between 96.3 and 96.7%. For the training dataset, the non-IC can be further classified into the IP and NT with an AUC between 0.96 and 0.98, and with accuracies between 95.0 and 95.9%. For the testing dataset, the classification accuracy for IC and non-IC was 96.0 ± 2.3% whereas for IP and NT, it was 80.1 ± 8.0%. Overall, we achieved the accuracy of 88.1 ± 6.7% for classifying three tissue subtypes (IP, IC, and NT) in the stroke hemisphere and the estimated lesion volumes were not significantly different from those of the ground truth (p = .56, .94, and .78, respectively).ConclusionsOur method achieved comparable results to the conventional approach using perfusion–diffusion mismatch. We suggest that a single DTI sequence along with ML algorithms is capable of dichotomizing ischemic tissue into the IC and IP.

Predicting MGMT Promoter Methylation of Glioblastoma from Dynamic Susceptibility Contrast Perfusion: A Radiomic Approach.

This study aims to investigate whether radiomic quantitative image features (IFs) from perfusion dynamic susceptibility contrast magnetic resonance imaging (DSC-MRI) retain sufficient strength to predict O6-methylguanine-DNA methyltransferase promoter methylation (MGMT_pm) in newly diagnosed glioblastoma (GB) patients. We retrospectively reviewed the perfusion DSC-MRI of 59 patients with GB. Patients were classified into three groups: (1) unmethylated if MGMT_pm ≤ 9% (UM); (2) intermediate-methylated if MGMT_pm ranged between 10% and 29% (IM); (3) methylated if MGMT_pm ≥ 30% (M). A total of 92 quantitative IFs were obtained from relative cerebral blood volume and relative cerebral blood flow maps. The Mann-Whitney U-test was applied to assess whether there were statistical differences in IFs between patient groups. Those IFs showing significant difference between two patient groups were termed relevant IFs (rIFs). rIFs were uploaded to a machine learning model to predict the MGMT_pm. No rIFs were found between UM and IM groups. Fourteen rIFs were found among UM-M, IM-M, and (UM + IM)-M groups. We built a multilayer perceptron deep learning model that classified patients as belonging to UM + IM and M group. The model performed well with 75% sensitivity, 85% specificity, and an area under the receiver-operating curve of .84. rIFs from perfusion DSC-MRI are potential biomarkers in GBs with a ≥30% MGMT_pm. Otherwise, unmethylated and intermediate-methylated GBs lack of rIFs. Five of 14 rIFs show sufficient strength to build an accurate prediction model of MGMT_pm.

Evaluation of B0-correction of relative CBF maps using tagging distance dependent Z-spectrum (TADDZ)

Arterial spin labeling (ASL) MRI, based on endogenous contrast from blood water, is used in research and diagnosis of cerebral vascular conditions. However, artifacts due to imperfect imaging conditions such as B0-inhomogeneity (ΔB0) could lead to variations in the quantification of relative cerebral blood flow (CBF). In this study, we evaluate a new approach using tagging distance dependent Z-spectrum (TADDZ) data, similar to the ΔB0 corrections in the chemical exchange saturation transfer (CEST) experiments, to remove the imaging plane B0 inhomogeneity induced CBF artifacts in ASL MRI. Our results indicate that imaging-plane B0-inhomogeneity can lead to variations and errors in the relative CBF maps especially under small tagging distances. Along with an acquired B0 map, TADDZ data helps to eliminate B0-inhomogeneity induced artifacts in the resulting relative CBF maps. We demonstrated the effective use of TADDZ data to reduce variation while subjected to systematic changes in ΔB0. In addition, TADDZ corrected ASL MRI, with improved consistency, was shown to outperform conventional ASL MRI by differentiating the subtle CBF difference in Alzheimer's disease (AD) mice brains with different APOE genotypes.

Arterial Spin-Labeling Parameters Influence Signal Variability and Estimated Regional Relative Cerebral Blood Flow in Normal Aging and Mild Cognitive Impairment: FAIR versus PICORE Techniques.

Arterial spin-labeling is a noninvasive method to map cerebral blood flow, which might be useful for early diagnosis of neurodegenerative diseases. We directly compared 2 arterial spin-labeling techniques in healthy elderly controls and individuals with mild cognitive impairment. This prospective study was approved by the local ethics committee and included 198 consecutive healthy controls (mean age, 73.65 ± 4.02 years) and 43 subjects with mild cognitive impairment (mean age, 73.38 ± 5.85 years). Two pulsed arterial spin-labeling sequences were performed at 3T: proximal inversion with a control for off-resonance effects (PICORE) and flow-sensitive alternating inversion recovery technique (FAIR). Relative cerebral blood flow maps were calculated by using commercial software and standard parameters. Data analysis included spatial normalization of gray matter-corrected relative CBF maps, whole-brain average, and voxelwise comparison of both arterial spin-labeling sequences. Overall, FAIR yielded higher relative CBF values compared with PICORE (controls, 32.7 ± 7.1 versus 30.0 ± 13.1 mL/min/100 g, P = .05; mild cognitive impairment, 29.8 ± 5.4 versus 26.2 ± 8.6 mL/min/100 g, P < .05; all, 32.2 ± 6.8 versus 29.3 ± 12.3 mL/min/100 g, P < .05). FAIR had lower variability (controls, 36.2% versus 68.8%, P < .00001; mild cognitive impairment, 18.9% versus 22.9%, P < .0001; all, 34.4% versus 64.9% P < .00001). The detailed voxelwise analysis revealed a higher signal for FAIR, notably in both convexities, while PICORE had higher signal predominantly in deep cerebral regions. Overall, FAIR had higher estimated relative CBF and lower interindividual variability than PICORE. In more detail, there were regional differences between both arterial spin-labeling sequences. In summary, these results highlight the need to calibrate arterial spin-labeling sequences.

Comparison of three‐dimensional pseudo‐continuous arterial spin labeling perfusion imaging with gradient‐echo and spin‐echo dynamic susceptibility contrast MRI

To compare the relative cerebral blood flow (CBF) obtained by pseudo-continuous arterial spin labeling sequence incorporated with volumetric fast spin-echo readout (3D-PCASL) with those by gradient-echo (GE) and spin-echo (SE) dynamic susceptibility contrast (DSC) MRI. Thirty patients with various neurological diseases participated in this study. In addition to 3D-PCASL, 15 patients received GE-DSC and the others received SE-DSC imaging on a 3 Tesla scanner. A cortical gray matter (GM) to white matter (WM) and a thalamus (TM) to WM CBF ratio were determined from each perfusion scan. In addition, histograms of relative CBF distributions were obtained from each method for comparison. Significant correlations of CBF ratios were found between 3D-PCASL and the two DSC methods (P < 0.05). The 3D-PCASL resulted in GM/WM CBF ratios similar to SE-DSC but significantly smaller than GE-DSC (P = 2.3 × 10(-7) ). TM/WM CBF ratio obtained by 3D-PCASL was significantly smaller than those by GE- and SE-DSC (P = 4.1 × 10(-7) and 1.2 × 10(-6) , respectively). The histogram of relative CBF maps obtained from SE-DSC, after applied spatial smoothing, agreed well with that from 3D-PCASL. This study suggested that perfusion images obtained from 3D-PCASL exhibited significant correlations with DSC-MRI, with greater microvascular weighting like SE-DSC.

MR Relative Cerebral Blood Flow Mapping of Alzheimer Disease: Correlation with Tc-99m HMPAO SPECT

Rationale and Objectives To evaluate the value of magnetic resonance (MR) perfusion imaging for diagnosis of Alzheimer disease (AD), the authors compared relative cerebral blood flow (CBF) maps obtained with MR perfusion imaging and technetium-99m hexamethyl-propyleneamine oxime (HMPAO) single photon emission computed tomography (SPECT) in patients with AD. Materials and Methods Eight patients with AD were studied with MR perfusion imaging and HMPAO SPECT. The relative CBF maps from the two techniques were spatially coregistered, and relative CBF values in 13 cerebral gray matter regions (total, 26 regions of interest) were compared with regression analysis. To evaluate the degree of deviation of each brain region from the regression line, a P value for the residual was calculated for each region. Results A significant overall correlation was seen between the relative CBF values produced by the two techniques ( r = 68, P < .0001). Smaller P values for the residuals were obtained in the anterior cingulate cortex ( P = 05) and posterior cingulate cortex ( P < .001), indicating larger deviations in these regions. When data from these two regions were eliminated, the correlation coefficient rose to 0.80 ( P < .0001). Conclusion Despite fairly large discrepancies in the anterior and posterior cingulate cortices, the relative CBF map obtained with MR imaging is generally in close agreement with the HMPAO SPECT map, suggesting that MR perfusion imaging can provide clinically useful information regarding CBF abnormalities in patients with AD.