Arterial spin labeled MRI in prodromal Alzheimer's disease: A multi-site study.
ABSTRACT: We examined differences in cerebral blood flow (CBF) measured by Arterial Spin Labeled perfusion MRI (ASL MRI) across the continuum from cognitively normal (CN) older adults to mild Alzheimer's Disease (AD) using data from the multi-site Alzheimer's Disease Neuroimaging Initiative (ADNI). Measures of CBF, in a predetermined set of regions (meta-ROI), and hippocampal volume were compared between CN (n = 47), patients with early and late Mild Cognitive Impairment [EMCI (n = 32), LMCI (n = 35)], and AD (n = 15). Associations between these measures and disease severity, assessed by Clinical Dementia Rating scale sum of boxes (CDR SB), were also assessed. Mean meta-ROI CBF was associated with group status and significant hypoperfusion was observed in LMCI and AD relative to CN. Hippocampal volume was associated with group status, but only AD patients had significantly smaller volumes than the CN. When examining the relationship between these measures and disease severity, both were significantly associated with CDR SB and appeared to provide independent prediction of status. In light of the tight link between CBF and metabolism, ASL MRI represents a promising functional biomarker for early diagnosis and disease tracking in AD and this study is the first to demonstrate the feasibility in a multi-site context in this population. Combining functional and structural measures, which can be acquired in the same scanning session, appears to provide additional information about disease severity relative to either measure alone.
Project description:<h4>Objective</h4>We compared the ability of arterial spin labeling (ASL), an MRI method that measures cerebral blood flow (CBF), to that of FDG-PET in distinguishing patients with Alzheimer disease (AD) from healthy, age-matched controls.<h4>Methods</h4>Fifteen patients with AD (mean age 72 ± 6 years, Mini-Mental State Examination score [MMSE] 20 ± 6) and 19 age-matched controls (mean age 68 ± 6 years, MMSE 29 ± 1) underwent structural MRI. Participants were injected with 5 mCi of FDG during pseudocontinuous ASL scan, which was followed by PET scanning. Statistical parametric mapping and regions of interest (ROI) analysis were used to compare the ability of the 2 modalities in distinguishing patients from controls. Similarity between the 2 modalities was further assessed with linear correlation maps of CBF and metabolism to neuropsychological test scores.<h4>Results</h4>Good agreement between hypoperfusion and hypometabolism patterns was observed, with overlap primarily in bilateral angular gyri and posterior cingulate. ROI results showed similar scales of functional deficit between patients and controls in both modalities. Both ASL and FDG-PET were able to distinguish neural networks associated with different neuropsychological tests with good overlap between modalities.<h4>Conclusions</h4>Our voxel-wise results indicated that ASL-MRI provides largely overlapping information with FDG-PET. ROI analysis demonstrated that both modalities detected similar degrees of functional deficits in affected areas. Given its ease of acquisition and noninvasiveness, ASL-MRI may be an appealing alternative for AD studies.
Project description:Because hypoperfusion of brain tissue precedes atrophy in dementia, the detection of dementia may be advanced by the use of perfusion information. Such information can be obtained noninvasively with arterial spin labeling (ASL), a relatively new MR technique quantifying cerebral blood flow (CBF). Using ASL and structural MRI, we evaluated diagnostic classification in 32 prospectively included presenile early stage dementia patients and 32 healthy controls. Patients were suspected of Alzheimer's disease (AD) or frontotemporal dementia. Classification was based on CBF as perfusion marker, gray matter (GM) volume as atrophy marker, and their combination. These markers were each examined using six feature extraction methods: a voxel-wise method and a region of interest (ROI)-wise approach using five ROI-sets in the GM. These ROI-sets ranged in number from 72 brain regions to a single ROI for the entire supratentorial brain. Classification was performed with a linear support vector machine classifier. For validation of the classification method on the basis of GM features, a reference dataset from the AD Neuroimaging Initiative database was used consisting of AD patients and healthy controls. In our early stage dementia population, the voxelwise feature-extraction approach achieved more accurate results (area under the curve (AUC) range?=?86?-?91%) than all other approaches (AUC?=?57?-?84%). Used in isolation, CBF quantified with ASL was a good diagnostic marker for dementia. However, our findings indicated only little added diagnostic value when combining ASL with the structural MRI data (AUC?=?91%), which did not significantly improve over accuracy of structural MRI atrophy marker by itself.
Project description:Neurodegenerative biomarkers support diagnosis and measurement of disease progression in the Alzheimer's disease (AD) continuum. <sup>18</sup>F-Fluorodeoxyglucose Positron Emission Tomography (<sup>18</sup>F-FDG-PET), which measures glucose metabolism, is one of the most commonly used biomarkers of neurodegeneration, but is expensive and requires exposure to ionizing radiation. Arterial Spin Labeled (ASL) perfusion Magnetic Resonance Imaging (MRI) provides non invasive quantification of cerebral blood flow (CBF), which is believed to be tightly coupled to glucose metabolism. Here we aimed to compare the performances of ASL derived CBF and <sup>18</sup>F-FDG-PET derived standardized uptake value ratio (SUVR) in discriminating patients with mild cognitive impairment (MCI) from older Controls. 2D pseudo continuous ASL and <sup>18</sup>F-FDG-PET data with adequate scan quality from 50 MCI study participants (age=73.0 ± 7.0 years, 16 female) and 35 older controls (age=70.2 ± 6.9 years, 20 female), acquired in close temporal proximity, usually on the same day, were considered for this study. We assessed Control-patient group differences both at voxel level and within a priori regions of interest (ROIs). We also compared their area under receiver operating characteristic curves (AUC) with mean CBF or SUVR in a priori selected posterior cingulate cortex (PCC). CBF and <sup>18</sup>F-FDG-PET showed abnormalities in similar areas, particularly in medial temporoparietal regions, consistent with the typically observed pattern of prodromal AD. The hypoperfusion pattern with relative CBF (obtained by normalizing voxel CBF values with mean CBF in putamen) was more localized than with absolute CBF. Pearson's correlation coefficients between the T-scores corresponding to the group-differences obtained with <sup>18</sup>F-FDG-PET SUVR and absolute and relative ASL CBF were 0.46 and 0.43 (p<0.001), respectively. ROI analyses were also consistent, with the strongest differences observed in PCC (p<0.01). <sup>18</sup>F-FDG-PET SUVR, absolute and relative CBF in the PCC ROI demonstrated moderate and similar discriminatory power in predicting MCI status with AUC of 0.71 ± 0.12, 0.77 ± 0.12 and 0.74 ± 0.13, respectively. In conclusion, ASL CBF may be a reasonable, less expensive and safer substitute for <sup>18</sup>F-FDG-PET in clinical research.
Project description:<h4>Objectives</h4>Alzheimer's disease (AD) and frontotemporal (FTD) dementia can be differentiated using [(18)F]-2-deoxy-2-fluoro-D-glucose (FDG)-PET. Since cerebral blood flow (CBF) is related to glucose metabolism, our aim was to investigate the extent of overlap of abnormalities between AD and FTD.<h4>Methods</h4>Normalized FDG-PET and arterial spin labelling (ASL-MRI)-derived CBF was measured in 18 AD patients (age, 64 ± 8), 12 FTD patients (age, 61 ± 8), and 10 controls (age, 56 ± 10). Voxel-wise comparisons, region-of-interest (ROI), correlation, and ROC curve analyses were performed.<h4>Results</h4>Voxel-wise comparisons showed decreased CBF and FDG uptake in AD compared with controls and FTD in both precuneus and inferior parietal lobule (IPL). Compared with controls and AD, FTD patients showed both hypometabolism and hypoperfusion in medial prefrontal cortex (mPFC). ASL and FDG were related in precuneus (r = 0.62, p < 0.001), IPL (r = 0.61, p < 0.001), and mPFC across groups (r = 0.74, p < 001). ROC analyses indicated comparable performance of perfusion and metabolism in the precuneus (AUC, 0.72 and 0.74), IPL (0.85 and 0.94) for AD relative to FTD, and in the mPFC in FTD relative to AD (both 0.68).<h4>Conclusions</h4>Similar patterns of hypoperfusion and hypometabolism were observed in regions typically associated with AD and FTD, suggesting that ASL-MRI provides information comparable to FDG-PET.<h4>Key points</h4>• Similar patterns of hypoperfusion and hypometabolism were observed in patients with dementia. • For both imaging modalities, parietal abnormalities were found in Alzheimer's disease. • For both imaging modalities, prefrontal abnormalities were found in frontotemporal dementia.
Project description:Autosomal dominant Alzheimer's disease (ADAD) is a small subset of Alzheimer's disease that is genetically determined with 100% penetrance. It provides a valuable window into studying the course of pathologic processes that leads to dementia. Arterial spin labeling (ASL) MRI is a potential AD imaging marker that non-invasively measures cerebral perfusion. In this study, we investigated the relationship of cerebral blood flow measured by pseudo-continuous ASL (pCASL) MRI with measures of cerebral metabolism (FDG PET) and amyloid deposition (Pittsburgh Compound B (PiB) PET). Thirty-one participants at risk for ADAD (age 39 ± 13 years, 19 females) were recruited into this study, and 21 of them received both MRI and FDG and PiB PET scans. Considerable variability was observed in regional correlations between ASL-CBF and FDG across subjects. Both regional hypo-perfusion and hypo-metabolism were associated with amyloid deposition. Cross-sectional analyses of each biomarker as a function of the estimated years to expected dementia diagnosis indicated an inverse relationship of both perfusion and glucose metabolism with amyloid deposition during AD development. These findings indicate that neurovascular dysfunction is associated with amyloid pathology, and also indicate that ASL CBF may serve as a sensitive early biomarker for AD. The direct comparison among the three biomarkers provides complementary information for understanding the pathophysiological process of AD.
Project description:<h4>Objectives</h4>To investigate the added diagnostic value of arterial spin labelling (ASL) and diffusion tensor imaging (DTI) to structural MRI for computer-aided classification of Alzheimer's disease (AD), frontotemporal dementia (FTD), and controls.<h4>Methods</h4>This retrospective study used MRI data from 24 early-onset AD and 33 early-onset FTD patients and 34 controls (CN). Classification was based on voxel-wise feature maps derived from structural MRI, ASL, and DTI. Support vector machines (SVMs) were trained to classify AD versus CN (AD-CN), FTD-CN, AD-FTD, and AD-FTD-CN (multi-class). Classification performance was assessed by the area under the receiver-operating-characteristic curve (AUC) and accuracy. Using SVM significance maps, we analysed contributions of brain regions.<h4>Results</h4>Combining ASL and DTI with structural MRI resulted in higher classification performance for differential diagnosis of AD and FTD (AUC?=?84%; p?=?0.05) than using structural MRI by itself (AUC?=?72%). The performance of ASL and DTI themselves did not improve over structural MRI. The classifications were driven by different brain regions for ASL and DTI than for structural MRI, suggesting complementary information.<h4>Conclusions</h4>ASL and DTI are promising additions to structural MRI for classification of early-onset AD, early-onset FTD, and controls, and may improve the computer-aided differential diagnosis on a single-subject level.<h4>Key points</h4>• Multiparametric MRI is promising for computer-aided diagnosis of early-onset AD and FTD. • Diagnosis is driven by different brain regions when using different MRI methods. • Combining structural MRI, ASL, and DTI may improve differential diagnosis of dementia.
Project description:Mild cognitive impairment (MCI) is considered a prodromal stage of Alzheimer's disease (AD), but is also recognized to be a heterogeneous condition. Biomarkers that predict AD progression in MCI are of clinical significance because they can be used to better identify appropriate candidates for therapeutic intervention studies. It has been hypothesized that comparing to structural measurements, functional ones may be more sensitive to early disease abnormalities and the sensitivity could be further enhanced when combined with cognitive task, a "brain stress test." In this study, we investigated the value of regional cerebral blood flow (CBF), measured by arterial spin labeled perfusion MRI (ASL MRI) during a memory-encoding task, in predicting the estimated rate of hippocampal atrophy, an established marker of AD progression. Thirty-one amnestic MCI patients (20 male and 11 female; age: 70.9?±?6.5 years, range from 56 to 83?years; mini mental status examination: 27.8?±?1.8) and 42 normal control subjects (13 male and 29 female; age: 70.6?±?8.8 years, range from 55 to 88?years; mini mental status examination: 29.1?±?1.2) were included in this study. We compared the predictive value of CBF during task to CBF during rest and structural volumetry. Both region-of-interest and voxelwise analyses showed that baseline CBF measurements during task (strongest effect in fusiform gyrus, region-of-interest analysis statistics: r?=?0.56, p?=?.003), but not resting ASL MRI or structural volumetry, were correlated with the estimated rate of hippocampal atrophy in amnestic MCI patients. Further, stepwise linear regression demonstrated that resting ASL MRI and volumetry did not provide complementary information in prediction. These results support the notion that physiologic measures during a cognitive challenge may increase the ability to detect subtle functional changes that predict progression. As such, ASL MRI could have important utility in stratifying candidates for AD treatment trials.
Project description:Combining machine learning with neuroimaging data has a great potential for early diagnosis of mild cognitive impairment (MCI) and Alzheimer's disease (AD). However, it remains unclear how well the classifiers built on one population can predict MCI/AD diagnosis of other populations. This study aimed to employ a spectral graph convolutional neural network (graph-CNN), that incorporated cortical thickness and geometry, to identify MCI and AD based on 3089 T1-weighted MRI data of the ADNI-2 cohort, and to evaluate its feasibility to predict AD in the ADNI-1 cohort (n?=?3602) and an Asian cohort (n?=?347). For the ADNI-2 cohort, the graph-CNN showed classification accuracy of controls (CN) vs. AD at 85.8% and early MCI (EMCI) vs. AD at 79.2%, followed by CN vs. late MCI (LMCI) (69.3%), LMCI vs. AD (65.2%), EMCI vs. LMCI (60.9%), and CN vs. EMCI (51.8%). We demonstrated the robustness of the graph-CNN among the existing deep learning approaches, such as Euclidean-domain-based multilayer network and 1D CNN on cortical thickness, and 2D and 3D CNNs on T1-weighted MR images of the ADNI-2 cohort. The graph-CNN also achieved the prediction on the conversion of EMCI to AD at 75% and that of LMCI to AD at 92%. The find-tuned graph-CNN further provided a promising CN vs. AD classification accuracy of 89.4% on the ADNI-1 cohort and >90% on the Asian cohort. Our study demonstrated the feasibility to transfer AD/MCI classifiers learned from one population to the other. Notably, incorporating cortical geometry in CNN has the potential to improve classification performance.
Project description:Diffusion tensor imaging (DTI) is a sensitive tool for detecting brain tissue microstructural alterations in Parkinson's disease (PD). Abnormal cerebral perfusion patterns have also been reported in PD patients using arterial spin labeling (ASL) MRI. In this study we aimed to perform a combined DTI and ASL assessment in PD patients within the basal ganglia, in order to test the relationship between microstructural and perfusion alterations. Fifty-two subjects participated in this study. Specifically, 26 PD patients [mean age (SD) = 66.7 (8.9) years, 21 males, median (IQR) Modified Hoehn and Yahr = 1.5 (1-1.6)] and twenty-six healthy controls [HC, mean age (SD) = 65.2 (7.5), 15 males] were scanned with 1.5T MRI. Fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), radial diffusivity (RD) maps were derived from diffusion-weighted images, while cerebral blood flow (CBF) maps were computed from ASL data. After registration to Montreal Neurological Institute standard space, FA, MD, AD, RD and CBF median values were extracted within specific regions of interest: substantia nigra, caudate, putamen, globus pallidus, thalamus, red nucleus and subthalamic nucleus. DTI measures and CBF were compared between the two groups. The relationship between diffusion parameters and CBF was tested with Spearman's correlations. False discovery rate (FDR)-corrected <i>p</i>-values lower than 0.05 were considered significant, while uncorrected <i>p</i>-values <0.05 were considered a trend. No significant FA, MD and RD differences were observed. AD was significantly increased in PD patients compared with HC in the putamen (<i>p</i> = 0.005, p<sub>FDR</sub> = 0.035). No significant CBF differences were found between PD patients and HC. Diffusion parameters were not significantly correlated with CBF in the HC group, while a significant correlation emerged for PD patients in the caudate nucleus, for all DTI measures (with FA: <i>r</i> = 0.543, p<sub>FDR</sub> = 0.028; with MD: <i>r</i> = -0.661, p<sub>FDR</sub> = 0.002; with AD: <i>r</i> = -0.628, p<sub>FDR</sub> = 0.007; with RD: <i>r</i> = -0.635, p<sub>FDR</sub> = 0.003). This study showed that DTI is a more sensitive technique than ASL to detect alterations in the basal ganglia in the early phase of PD. Our results suggest that, although DTI and ASL convey different information, a relationship between microstructural integrity and perfusion changes in the caudate may be present.
Project description:Cerebral blood flow (CBF) measured with arterial spin labelling (ASL) magnetic resonance imaging (MRI) reflects cerebral perfusion, related to metabolism, and arterial transit time (ATT), related to vascular health. Our aim was to investigate the spatial coefficient of variation (sCoV) of CBF maps as a surrogate for ATT, in volunteers meeting criteria for subjective cognitive decline (SCD), amnestic mild cognitive impairment (MCI) and probable Alzheimer's dementia (AD). Whole-brain pseudo continuous ASL MRI was performed at 3 T in 122 participants (controls = 20, SCD = 44, MCI = 45 and AD = 13) across three sites in New Zealand. From CBF maps that included all grey matter, sCoV progressively increased across each group with increased cognitive deficit. A similar overall trend was found when examining sCoV solely in the temporal lobe. We conclude that sCoV, a simple to compute imaging metric derived from ASL MRI, is sensitive to varying degrees of cognitive changes and supports the view that vascular health contributes to cognitive decline associated with Alzheimer's disease.