Joint analysis of structural and perfusion MRI for cognitive assessment and classification of Alzheimer's disease and normal aging

Arterial spin labeling perfusion MRI in the Alzheimer's Disease Neuroimaging Initiative: Past, present, and future

On the 20th anniversary of the Alzheimer's Disease Neuroimaging Initiative (ADNI), this paper provides a comprehensive overview of the role of arterial spin labeling (ASL) magnetic resonance imaging (MRI) in understanding perfusion changes in the aging brain and the relationship with Alzheimer's disease (AD) pathophysiology and its comorbid conditions. We summarize previously used acquisition protocols, available data, and the motivation for adopting a multi-post-labeling delay (PLD) acquisition scheme in the latest ADNI MRI protocol (ADNI 4). We also detail the process of setting up this scheme on different scanners, emphasizing the potential of ASL imaging in future AD research. HIGHLIGHTS: The Alzheimer's Disease Neuroimaging Initiative (ADNI) adopted multimodal arterial spin labeling magnetic resonance imaging (ASL MRI) to meet evolving biomarker requirements. The ADNI provides one of the largest multisite, multi-vendor ASL data collections. The ADNI 4 incorporates multi-post-labeling delay ASL techniques to jointly quantify cerebral blood flow and arterial transit time. ADNI 4 ASL MRI protocol is apt for detecting early Alzheimer's disease with cerebrovascular pathology.

Comparing single- and multi-post labeling delays for the measurements of resting cerebral and hippocampal blood flow for cerebrovascular testing in midlife adults

Objectives

To assess the reliability and validity of measuring resting cerebral blood flow (CBF) and hippocampal CBF using a single-post-labeling delay (PLD) and a multi-PLD pseudo-continuous arterial spin labeling (pCASL) protocol for cerebrovascular reactivity (CVR) testing.

Methods

25 healthy, midlife adults (57 ± 4 years old) were imaged in a Siemens Prisma 3T magnetic resonance imaging (MRI) scanner. Resting CBF and hippocampal CBF were assessed using two pCASL protocols, our modified single-PLD protocol (pCASL-MOD) to accommodate the needs for CVR testing and the multi-PLD Human Connectome Project (HCP) Lifespan protocol to serve as the reference control (pCASL-HCP). During pCASL-MOD, CVR was calculated as the change in CBF from rest to hypercapnia (+9 mmHg increase in end-tidal partial pressure of carbon dioxide [PETCO2]) and then normalized for PETCO2. The reliability and validity in resting gray matter (GM) CBF, white matter (WM) CBF, and hippocampal CBF between pCASL-MOD and pCASL-HCP protocols were examined using correlation analyses, paired t-tests, and Bland Altman plots.

Results

The pCASL-MOD and pCASL-HCP protocols were significantly correlated for resting GM CBF [r = 0.72; F (1, 23) = 25.24, p < 0.0001], WM CBF [r = 0.57; F (1, 23) = 10.83, p = 0.003], and hippocampal CBF [r = 0.77; F (1, 23) = 32.65, p < 0.0001]. However, pCASL-MOD underestimated resting GM CBF (pCASL-MOD: 53.7 ± 11.1 v. pCASL-HCP: 69.1 ± 13.1 mL/100 g/min; p < 0.0001), WM CBF (pCASL-MOD: 32.4 ± 4.8 v. pCASL-HCP: 35.5 ± 6.9 mL/100 g/min; p = 0.01), and hippocampal CBF (pCASL-MOD: 50.5 ± 9.0 v. pCASL-HCP: 68.1 ± 12.5 mL/100 g/min; p < 0.0001). PETCO2 increased by 8.0 ± 0.7 mmHg to induce CVR (GM CBF: 4.8% ± 2.6%; WM CBF 2.9% ± 2.5%; and hippocampal CBF: 3.4% ± 3.8%).

Conclusion

Our single-PLD pCASL-MOD protocol reliably measured CBF and hippocampal CBF at rest given the significant correlation with the multi-PLD pCASL-HCP protocol. Despite the lower magnitude relative to pCASL-HCP, we recommend using our pCASL-MOD protocol for CVR testing in which an exact estimate of CBF is not required such as the assessment of relative change in CBF to hypercapnia.

The Utility of Arterial Spin Labeling MRI in Medial Temporal Lobe as a Vascular Biomarker in Alzheimer's Disease Spectrum: A Systematic Review and Meta-Analysis

We sought to systematically review and meta-analy the role of cerebral blood flow (CBF) in the medial temporal lobe (MTL) using arterial spin labeling magnetic resonance imaging (ASL-MRI) and compare this in patients with Alzheimer's disease (AD), individuals with mild cognitive impairment (MCI), and cognitively normal adults (CN). The prevalence of AD is increasing and leading to high healthcare costs. A potential biomarker that can identify people at risk of developing AD, whilst cognition is normal or only mildly affected, will enable risk-stratification and potential therapeutic interventions in the future. All studies investigated the role of CBF in the MTL and compared this among AD, MCI, and CN participants. A total of 26 studies were included in the systematic review and 11 in the meta-analysis. Three separate meta-analyses were conducted. Four studies compared CBF in the hippocampus of AD compared with the CN group and showed that AD participants had 2.8 mL/min/100 g lower perfusion compared with the CN group. Eight studies compared perfusion in the hippocampus of MCI vs. CN group, which showed no difference. Three studies compared perfusion in the MTL of MCI vs. CN participants and showed no statistically significant differences. CBF measured via ASL-MRI showed impairment in AD compared with the CN group in subregions of the MTL. CBF difference was significant in hippocampus between the AD and CN groups. However, MCI and CN group showed no significant difference in subregions of MTL.

Altered cerebral hemodyamics and cortical thinning in asymptomatic carotid artery stenosis

Cortical thinning is a potentially important biomarker, but the pathophysiology in cerebrovascular disease is unknown. We investigated the association between regional cortical blood flow and regional cortical thickness in patients with asymptomatic unilateral high-grade internal carotid artery disease without stroke. Twenty-nine patients underwent high resolution anatomical and single-delay, pseudocontinuous arterial spin labeling magnetic resonance imaging with partial volume correction to assess gray matter baseline flow. Cortical thickness was estimated using Freesurfer software, followed by co-registration onto each patient's cerebral blood flow image space. Paired t-tests assessed regional cerebral blood flow in motor cortex (supplied by the carotid artery) and visual cortex (indirectly supplied by the carotid) on the occluded and unoccluded side. Pearson correlations were calculated between cortical thickness and regional cerebral blood flow, along with age, hypertension, diabetes and white matter hyperintensity volume. Multiple regression and generalized estimating equation were used to predict cortical thickness bilaterally and in each hemisphere separately. Cortical blood flow correlated with thickness in motor cortex bilaterally (p = 0.0002), and in the occluded and unoccluded sides individually; age (p = 0.002) was also a predictor of cortical thickness in the motor cortex. None of the variables predicted cortical thickness in visual cortex. Blood flow was significantly lower on the occluded versus unoccluded side in the motor cortex (p<0.0001) and in the visual cortex (p = 0.018). On average, cortex was thinner on the side of occlusion in motor but not in visual cortex. The association between cortical blood flow and cortical thickness in carotid arterial territory with greater thinning on the side of the carotid occlusion suggests that altered cerebral hemodynamics is a factor in cortical thinning.

Dependency criterion based brain pathological age estimation of Alzheimer's disease patients with MR scans

Objectives

Traditional brain age estimation methods are based on the idea that uses the real age as the training label. However, these methods ignore that there is a deviation between the real age and the brain age due to the accelerated brain aging.

Methods

This paper considers this deviation and obtains it by maximizing the correlation between the estimated brain age and the class label rather than by minimizing the difference between the estimated brain age and the real age. Firstly, set the search range of the deviation as the deviation candidates according to the prior knowledge. Secondly, use the support vector regression as the age estimation model to minimize the difference between the estimated age and the real age plus deviation rather than the real age itself. Thirdly, design the fitness function based on the correlation criterion. Fourthly, conduct age estimation on the validation dataset using the trained age estimation model, put the estimated age into the fitness function, and obtain the fitness value of the deviation candidate. Fifthly, repeat the iteration until all the deviation candidates are involved and get the optimal deviation with maximum fitness values. The real age plus the optimal deviation is taken as the brain pathological age.

Results

The experimental results showed that the separability of the samples was apparently improved. For normal control- Alzheimer’s disease (NC-AD), normal control- mild cognition impairment (NC-MCI), and mild cognition impairment—Alzheimer’s disease (MCI-AD), the average improvements were 0.164 (31.66%), 0.1284 (34.29%), and 0.0206 (7.1%), respectively. For NC-MCI-AD, the average improvement was 0.2002 (50.39%). The estimated brain pathological age could be not only more helpful for the classification of AD but also more precisely reflect the accelerated brain aging.

Conclusion

In conclusion, this paper proposes a new kind of brain age—brain pathological age and offers an estimation method for it that can distinguish different states of AD, thereby better reflecting accelerated brain aging. Besides, the brain pathological age is most helpful for feature reduction, thereby simplifying the relevant classification algorithm.

Estimating the brain pathological age of Alzheimer's disease patients from MR image data based on the separability distance criterion

Traditional age estimation methods are based on the same idea that uses the real age as the training label. However, these methods ignore that there is a deviation between the real age and the brain age due to accelerated brain aging. This paper considers this deviation and searches for it by maximizing the separability distance value rather than by minimizing the difference between the estimated brain age and the real age. Firstly, set the search range of the deviation as the deviation candidates according to prior knowledge. Secondly, use the support vector regression (SVR) as the age estimation model to minimize the difference between the estimated age and the real age plus deviation rather than the real age itself. Thirdly, design the fitness function based on the separability distance criterion. Fourthly, conduct age estimation on the validation dataset using the trained age estimation model, put the estimated age into the fitness function, and obtain the fitness value of the deviation candidate. Fifthly, repeat the iteration until all the deviation candidates are involved and get the optimal deviation with maximum fitness values. The real age plus the optimal deviation is taken as the brain pathological age. The experimental results showed that the separability was apparently improved. For normal control-Alzheimer's disease (NC-AD), normal control-mild cognition impairment (NC-MCI), and MCI-AD, the average improvements were 0.178 (35.11%), 0.033 (14.47%), and 0.017 (39.53%), respectively. For NC-MCI-AD, the average improvement was 0.2287 (64.22%). The estimated brain pathological age could be not only more helpful to the classification of AD but also more precisely reflect accelerated brain aging. In conclusion, this paper offers a new method for brain age estimation that can distinguish different states of AD and can better reflect the extent of accelerated aging.

Diagnostic utility of ASL-MRI and FDG-PET in the behavioral variant of FTD and AD

Objective

To compare the values of arterial spin‐labeled (ASL) MRI and fluorodeoxyglucose (FDG) PET in the diagnosis of behavioral variant of frontotemporal dementia (bvFTD) and Alzheimer's disease (AD).

Methods

Partial least squares logistic regression was used to identify voxels with diagnostic value in cerebral blood flow (CBF) and cerebral metabolic rate of glucose (CMRgl) maps from patients with bvFTD (n = 32) and AD (n = 28), who were compared with each other and with cognitively normal controls (CN, n = 15). Diagnostic values of these maps were compared with each other.

Results

Regions that differentiated each disorder from controls were similar for CBF and CMRgl. For differentiating AD from CN, the areas under the curve (AUC) for CBF (0.89) and CMRgl (0.91) were similar, with similar sensitivity (CBF: 86%, CMRgl: 78%) and specificity (CBF: 92%, CMRgl: 100%). Likewise, for differentiating bvFTD from CN performances of CBF (AUC = 0.83) and CMRgl (AUC = 0.85) were equivalent, with similar sensitivity (CBF: 78%, CMRgl: 79%) and specificity (CBF: 92%, CMRgl: 100%). In differentiating bvFTD from AD, classification was again similar for CBF (AUC = 0.87) and CMRgl (AUC = 0.79), as were sensitivity (CBF: 83%, CMRgl: 89%) and specificity (CBF: 93%, CMRgl: 78%). None of the differences in any performance measure were statistically significant.

Interpretation

ASL‐MRI has similar diagnostic utility as FDG‐PET in the diagnosis of AD and bvFTD. Continued development of ASL‐MRI as a diagnostic tool for neurodegenerative dementias is warranted.

Magnetic resonance imaging in Alzheimer's Disease Neuroimaging Initiative 2

INTRODUCTION

Alzheimer's Disease Neuroimaging Initiative (ADNI) is now in its 10th year. The primary objective of the magnetic resonance imaging (MRI) core of ADNI has been to improve methods for clinical trials in Alzheimer's disease (AD) and related disorders.

METHODS

We review the contributions of the MRI core from present and past cycles of ADNI (ADNI-1, -Grand Opportunity and -2). We also review plans for the future-ADNI-3.

RESULTS

Contributions of the MRI core include creating standardized acquisition protocols and quality control methods; examining the effect of technical features of image acquisition and analysis on outcome metrics; deriving sample size estimates for future trials based on those outcomes; and piloting the potential utility of MR perfusion, diffusion, and functional connectivity measures in multicenter clinical trials.

DISCUSSION

Over the past decade the MRI core of ADNI has fulfilled its mandate of improving methods for clinical trials in AD and will continue to do so in the future.

Association of Insulin Resistance With Cerebral Glucose Uptake in Late Middle-Aged Adults at Risk for Alzheimer Disease

IMPORTANCE

Converging evidence suggests that Alzheimer disease (AD) involves insulin signaling impairment. Patients with AD and individuals at risk for AD show reduced glucose metabolism, as indexed by fludeoxyglucose F 18-labeled positron emission tomography (FDG-PET).

OBJECTIVES

To determine whether insulin resistance predicts AD-like global and regional glucose metabolism deficits in late middle-aged participants at risk for AD and to examine whether insulin resistance-predicted variation in regional glucose metabolism is associated with worse cognitive performance.

DESIGN, SETTING, AND PARTICIPANTS

This population-based, cross-sectional study included 150 cognitively normal, late middle-aged (mean [SD] age, 60.7 [5.8] years) adults from the Wisconsin Registry for Alzheimer's Prevention (WRAP) study, a general community sample enriched for AD parental history. Participants underwent cognitive testing, fasting blood draw, and FDG-PET at baseline. We used the homeostatic model assessment of peripheral insulin resistance (HOMA-IR). Regression analysis tested the statistical effect of HOMA-IR on global glucose metabolism. We used a voxelwise analysis to determine whether HOMA-IR predicted regional glucose metabolism. Finally, predicted variation in regional glucose metabolism was regressed against cognitive factors. Covariates included age, sex, body mass index, apolipoprotein E ε4 genotype, AD parental history status, and a reference region used to normalize regional uptake.

MAIN OUTCOMES AND MEASURES

Regional glucose uptake determined using FDG-PET and neuropsychological factors.

RESULTS

Higher HOMA-IR was associated with lower global glucose metabolism (β = -0.29; P < .01) and lower regional glucose metabolism across large portions of the frontal, lateral parietal, lateral temporal, and medial temporal lobes (P < .05, familywise error corrected). The association was especially robust in the left medial temporal lobe (R2 = 0.178). Lower glucose metabolism in the left medial temporal lobe predicted by HOMA-IR was significantly related to worse performance on the immediate memory (β = 0.317; t148 = 4.08; P < .001) and delayed memory (β = 0.305; t148 = 3.895; P < .001) factor scores.

CONCLUSIONS AND RELEVANCE

Our results show that insulin resistance, a prevalent and increasingly common condition in developed countries, is associated with significantly lower regional cerebral glucose metabolism, which in turn may predict worse memory performance. Midlife may be a critical period for initiating treatments to lower peripheral insulin resistance to maintain neural metabolism and cognitive function.

Caveat of measuring perfusion indexes using intravoxel incoherent motion magnetic resonance imaging in the human brain

OBJECTIVES

To numerically and experimentally investigate the robustness of intravoxel incoherent motion (IVIM) magnetic resonance imaging in measuring perfusion indexes in the human brain.

METHODS

Eighteen healthy volunteers were imaged on a 3 T clinical system. Data of IVIM imaging (12 b-values ranging from 0 to 1000 s/mm(2), 12 repetitions) were fitted with a bi-exponential model to extract blood volume fraction (f) and pseudo-diffusion coefficient (D*). The robustness of measurement was assessed by bootstrapping. Dynamic susceptibility contrast (DSC) imaging and arterial spin-labelling (ASL) imaging were performed for cross-modal comparison. Numerical simulations were performed to assess the accuracy and precision of f and D* estimates at varied signal-to-noise ratio (SNRb1000).

RESULTS

Based on our experimental setting (SNRb1000 ~ 30), the average error/variability is ~5 %/25 % for f and ~100 %/30 % for D* in gray matter, and ~10 %/50 % for f and ~300 %/60 % for D* in white matter. Correlation was found between f and DSC-derived cerebral blood volume in gray matter (r = 0.29 - 0.48 across subjects, p < 10(-5)), but not in white matter. No correlation was found between f-D* product and ASL-derived cerebral blood flow.

CONCLUSIONS

f may provide noninvasive measurement of cerebral blood volume, particularly in gray matter. D* has limited robustness and should be interpreted with caution.

KEY POINTS

• A minimum SNR b1000 of 30 is recommended for reliable IVIM imaging. • f may provide noninvasive measurement of cerebral blood volume. • f correlates with CBV DSC in gray matter. • There is no correlation between fD* and CBF ASL . • D* has limited robustness and should be interpreted with caution.

Comparison of Regional Brain Perfusion Levels in Chronically Smoking and Non-Smoking Adults

Chronic cigarette smoking is associated with numerous abnormalities in brain neurobiology, but few studies specifically investigated the chronic effects of smoking (compared to the acute effects of smoking, nicotine administration, or nicotine withdrawal) on cerebral perfusion (i.e., blood flow). Predominately middle-aged male (47 ± 11 years of age) smokers (n = 34) and non-smokers (n = 27) were compared on regional cortical perfusion measured by continuous arterial spin labeling magnetic resonance studies at 4 Tesla. Smokers showed significantly lower perfusion than non-smokers in the bilateral medial and lateral orbitofrontal cortices, bilateral inferior parietal lobules, bilateral superior temporal gyri, left posterior cingulate, right isthmus of cingulate, and right supramarginal gyrus. Greater lifetime duration of smoking (adjusted for age) was related to lower perfusion in multiple brain regions. The results indicated smokers showed significant perfusion deficits in anterior cortical regions implicated in the development, progression, and maintenance of all addictive disorders. Smokers concurrently demonstrated reduced blood flow in posterior brain regions that show morphological and metabolic aberrations as well as elevated beta amyloid deposition demonstrated by those with early stage Alzheimer disease. The findings provide additional novel evidence of the adverse effects of cigarette smoking on the human brain.

Brain perfusion in polysubstance users: relationship to substance and tobacco use, cognition, and self-regulation

BACKGROUND

Brain perfusion is altered in both alcohol dependence and stimulant dependence. Although most substance users also abuse/depend on alcohol concurrently (polysubstance users; PSU), rigorous perfusion research in PSU is limited. Also, the relationships of perfusion abnormalities with cognition, impulsivity, or decision making are not well known.

METHODS

Arterial spin labeling MRI and neuropsychological measures assessed perfusion levels and neurocognition in 20 alcohol-dependent individuals with comorbid-stimulant dependence (PSU), 26 individuals dependent on alcohol only (ALC), and 31 light/non-drinking controls (LD). The patient groups included smokers and non-smokers.

RESULTS

ALC had lower perfusion than LD in subcortical and cortical brain regions including the brain reward/executive oversight system (BREOS). Contrary to our hypothesis, regional perfusion was generally not lower in PSU than ALC. However, smoking PSU had lower perfusion than smoking ALC in several regions, including BREOS. Lower BREOS perfusion related to greater drinking severity in smoking substance users and to greater smoking severity in smoking ALC. Lower regional perfusion in ALC and PSU correlated with worse performance in different cognitive domains; smoking status affected perfusion-cognition relationships in ALC only. Lower BREOS perfusion in both substance using groups related to higher impulsivity.

CONCLUSION

Although regional perfusion was not decreased in PSU as a group, the combination of cigarette smoking and polysubstance use is strongly related to hypoperfusion in important cortical and subcortical regions. As lower perfusion relates to greater smoking severity, worse cognition and higher impulsivity, smoking cessation is warranted for treatment-seeking PSU and ALC.

Decomposing cerebral blood flow MRI into functional and structural components: a non-local approach based on prediction

We present RIPMMARC (Rotation Invariant Patch-based Multi-Modality Analysis aRChitecture), a flexible and widely applicable method for extracting information unique to a given modality from a multi-modal data set. We use RIPMMARC to improve the interpretation of arterial spin labeling (ASL) perfusion images by removing the component of perfusion that is predicted by the underlying anatomy. Using patch-based, rotation invariant descriptors derived from the anatomical image, we learn a predictive relationship between local neuroanatomical structure and the corresponding perfusion image. This relation allows us to produce an image of perfusion that would be predicted given only the underlying anatomy and a residual image that represents perfusion information that cannot be predicted by anatomical features. Our learned structural features are significantly better at predicting brain perfusion than tissue probability maps, which are the input to standard partial volume correction techniques. Studies in test-retest data show that both the anatomically predicted and residual perfusion signals are highly replicable for a given subject. In a pediatric population, both the raw perfusion and structurally predicted images are tightly linked to age throughout adolescence throughout the brain. Interestingly, the residual perfusion also shows a strong correlation with age in selected regions including the hippocampi (corr = 0.38, p-value <10(-6)), precuneus (corr = -0.44, p < 10(-5)), and combined default mode network regions (corr = -0.45, p < 10(-8)) that is independent of global anatomy-perfusion trends. This finding suggests that there is a regionally heterogeneous pattern of functional specialization that is distinct from that of cortical structural development.

Neuroimaging characteristics of dementia with Lewy bodies

This review summarises the findings and applications from neuroimaging studies in dementia with Lewy bodies (DLB), highlighting key differences between DLB and other subtypes of dementia. We also discuss the increasingly important role of imaging biomarkers in differential diagnosis and outline promising areas for future research in DLB. DLB shares common clinical, neuropsychological and pathological features with Parkinson’s disease dementia and other dementia subtypes, such as Alzheimer’s disease. Despite the development of consensus diagnostic criteria, the sensitivity for differential diagnosis of DLB in clinical practice remains low and many DLB patients will be misdiagnosed. The importance of developing accurate imaging markers in dementia is highlighted by the potential for treatments targeting specific molecular abnormalities as well as the responsiveness to cholinesterase inhibitors and marked neuroleptic sensitivity of DLB. We review various brain imaging techniques that have been applied to investigate DLB, including the characteristic nigrostriatal degeneration in DLB using positron emission tomography (PET) and single-photon emission computed tomography (SPECT) tracers. Dopamine transporter loss has proven to reliably differentiate DLB from other dementias and has been incorporated into the revised clinical diagnostic criteria for DLB. To date, this remains the 'gold standard' for diagnostic imaging of DLB. Regional cerebral blood flow, 18 F-fluorodeoxygluclose-PET and SPECT have also identified marked deficits in the occipital regions with relative sparing of the medial temporal lobe when compared to Alzheimer’s disease. In addition, structural, diffusion, and functional magnetic resonance imaging techniques have shown alterations in structure, white matter integrity, and functional activity in DLB. We argue that the multimodal identification of DLB-specific biomarkers has the potential to improve ante-mortem diagnosis and contribute to our understanding of the pathological background of DLB and its progression.

Multimodal MRI-based Imputation of the Aβ+ in Early Mild Cognitive Impairment

Objective

The primary goal of this study was to identify brain atrophy from structural MRI (magnetic resonance imaging) and cerebral blood flow (CBF) patterns from arterial spin labeling perfusion MRI that are best predictors of the Aβ-burden, measured as composite ¹⁸F-AV45-PET (positron emission tomography) uptake, in individuals with early mild cognitive impairment (MCI). Furthermore, another objective was to assess the relative importance of imaging modalities in classification of Aβ+/Aβ− early MCI.

Methods

Sixty-seven Alzheimer's Disease Neuroimaging Initiative (ADNI)-GO/2 participants with early MCI were included. Voxel-wise anatomical shape variation measures were computed by estimating the initial diffeomorphic mapping momenta from an unbiased control template. CBF measures normalized to average motor cortex CBF were mapped onto the template space. Using partial least squares regression, we identified the structural and CBF signatures of Aβ after accounting for normal cofounding effects of age, gender, and education.

Results

¹⁸F-AV45-positive early MCIs could be identified with 83% classification accuracy, 87% positive predictive value, and 84% negative predictive value by multidisciplinary classifiers combining demographics data, ApoE ε4-genotype, and a multimodal MRI-based Aβ score.

Interpretation

Multimodal MRI can be used to predict the amyloid status of early-MCI individuals. MRI is a very attractive candidate for the identification of inexpensive and noninvasive surrogate biomarkers of Aβ deposition. Our approach is expected to have value for the identification of individuals likely to be Aβ+ in circumstances where cost or logistical problems prevent Aβ detection using cerebrospinal fluid analysis or Aβ-PET. This can also be used in clinical settings and clinical trials, aiding subject recruitment and evaluation of treatment efficacy. Imputation of the Aβ-positivity status could also complement Aβ-PET by identifying individuals who would benefit the most from this assessment.

Measurement of cerebral white matter perfusion using pseudocontinuous arterial spin labeling 3T magnetic resonance imaging--an experimental and theoretical investigation of feasibility

PURPOSE

This study was aimed to experimentally and numerically investigate the feasibility of measuring cerebral white matter perfusion using pseudocontinuous arterial spin labeling (PCASL) 3T magnetic resonance imaging (MRI) at a relatively fine resolution to mitigate partial volume effect from gray matter.

MATERIALS AND METHODS

The Institutional Research Ethics Committee approved this study. On a clinical 3T MR system, ten healthy volunteers (5 females, 5 males, age = 28 ± 3 years) were scanned after providing written informed consent. PCASL imaging was performed with varied combinations of labeling duration (τ = 1000, 1500, 2000, and 2500 ms) and post-labeling delay (PLD = 1000, 1400, 1800, and 2200 ms), at a spatial resolution (1.56 x 1.56 x 5 mm(3)) finer than commonly used (3.5 x 3.5 mm(2), 5-8 mm in thickness). Computer simulations were performed to calculate the achievable perfusion-weighted signal-to-noise ratio at varied τ, PLD, and transit delay.

RESULTS

Based on experimental and numerical data, the optimal τ and PLD were found to be 2000 ms and 1500-1800 ms, respectively, yielding adequate SNR (~2) to support perfusion measurement in the majority (~60%) of white matter. The measurement variability was about 9% in a one-week interval. The measured white matter perfusion and perfusion ratio of gray matter to white matter were 15.8-27.5 ml/100ml/min and 1.8-4.0, respectively, depending on spatial resolution as well as the amount of deep white matter included.

CONCLUSION

PCASL 3T MRI is able to measure perfusion in the majority of cerebral white matter at an adequate signal-to-noise ratio by using appropriate tagging duration and post-labeling delay. Although pixel-wise comparison may not be possible, region-of-interest based flow quantification is feasible.

Identifying patients with poststroke mild cognitive impairment by pattern recognition of working memory load-related ERP

The early detection of subjects with probable cognitive deficits is crucial for effective appliance of treatment strategies. This paper explored a methodology used to discriminate between evoked related potential signals of stroke patients and their matched control subjects in a visual working memory paradigm. The proposed algorithm, which combined independent component analysis and orthogonal empirical mode decomposition, was applied to extract independent sources. Four types of target stimulus features including P300 peak latency, P300 peak amplitude, root mean square, and theta frequency band power were chosen. Evolutionary multiple kernel support vector machine (EMK-SVM) based on genetic programming was investigated to classify stroke patients and healthy controls. Based on 5-fold cross-validation runs, EMK-SVM provided better classification performance compared with other state-of-the-art algorithms. Comparing stroke patients with healthy controls using the proposed algorithm, we achieved the maximum classification accuracies of 91.76% and 82.23% for 0-back and 1-back tasks, respectively. Overall, the experimental results showed that the proposed method was effective. The approach in this study may eventually lead to a reliable tool for identifying suitable brain impairment candidates and assessing cognitive function.

Combined analysis of sMRI and fMRI imaging data provides accurate disease markers for hearing impairment

In this research, we developed a robust two-layer classifier that can accurately classify normal hearing (NH) from hearing impaired (HI) infants with congenital sensori-neural hearing loss (SNHL) based on their Magnetic Resonance (MR) images. Unlike traditional methods that examine the intensity of each single voxel, we extracted high-level features to characterize the structural MR images (sMRI) and functional MR images (fMRI). The Scale Invariant Feature Transform (SIFT) algorithm was employed to detect and describe the local features in sMRI. For fMRI, we constructed contrast maps and detected the most activated/de-activated regions in each individual. Based on those salient regions occurring across individuals, the bag-of-words strategy was introduced to vectorize the contrast maps. We then used a two-layer model to integrate these two types of features together. With the leave-one-out cross-validation approach, this integrated model achieved an AUC score of 0.90. Additionally, our algorithm highlighted several important brain regions that differentiated between NH and HI children. Some of these regions, e.g. planum temporale and angular gyrus, were well known auditory and visual language association regions. Others, e.g. the anterior cingulate cortex (ACC), were not necessarily expected to play a role in differentiating HI from NH children and provided a new understanding of brain function and of the disorder itself. These important brain regions provided clues about neuroimaging markers that may be relevant to the future use of functional neuroimaging to guide predictions about speech and language outcomes in HI infants who receive a cochlear implant. This type of prognostic information could be extremely useful and is currently not available to clinicians by any other means.

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We probe brain structural and functional changes in hearing impaired (HI) infants.

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We build a robust two-layer classifier that integrates sMRI and fMRI data.

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This integrated model accurately separates HI from normal infants (AUC 0.9).

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Our method detects important brain regions different between HI and normal infants.

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Our method can include diverse types of data and be applied to other diseases.

Low cerebral blood flow is associated with lower memory function in metabolic syndrome

BACKGROUND

Metabolic syndrome (MetS)--a cluster of cardiovascular risk factors--is linked with cognitive decline and dementia. However, the brain changes underlying this link are presently unknown. In this study, we tested the relationship between MetS, cerebral blood flow (CBF), white matter hyperintensity burden, and gray matter (GM) volume in cognitively healthy late middle-aged adults. Additionally, the extent to which MetS was associated with cognitive performance was assessed.

DESIGN AND METHODS

Late middle-aged adults from the Wisconsin Registry for Alzheimer's Prevention (N = 69, mean age = 60.4 years) underwent a fasting blood draw, arterial spin labeling perfusion MRI, T1-weighted MRI, T2FLAIR MRI, and neuropsychological testing. MetS was defined as abnormalities on three or more factors, including abdominal obesity, triglycerides, HDL-cholesterol, blood pressure, and fasting glucose.

RESULTS

Mean GM CBF was 15% lower in MetS compared to controls. Voxel-wise image analysis indicated that the MetS group had lower CBF across a large portion of the cortical surface, with the exception of medial and inferior parts of the occipital and temporal lobes. The MetS group also had lower immediate memory function; a mediation analysis indicated this relationship was partially mediated by CBF. Among the MetS factors, abdominal obesity and elevated triglycerides were most strongly associated with lower CBF.

CONCLUSIONS

The results underscore the importance of reducing the number of cardiovascular risk factors for maintaining CBF and cognition in an aging population.

Alzheimer disease: new concepts on its neurobiology and the clinical role imaging will play

Alzheimer disease (AD) is one of, if not the most, feared diseases associated with aging. The prevalence of AD increases exponentially with age after 60 years. Increasing life expectancy coupled with the absence of any approved disease-modifying therapies at present position AD as a dominant public health problem. Major advances have occurred in the development of disease biomarkers for AD in the past 2 decades. At present, the most well-developed AD biomarkers are the cerebrospinal fluid analytes amyloid-β 42 and tau and the brain imaging measures amyloid positron emission tomography (PET), fluorodeoxyglucose PET, and magnetic resonance imaging. CSF and imaging biomarkers are incorporated into revised diagnostic guidelines for AD, which have recently been updated for the first time since their original formulation in 1984. Results of recent studies suggest the possibility of an ordered evolution of AD biomarker abnormalities that can be used to stage the typical 20-30-year course of the disease. When compared with biomarkers in other areas of medicine, however, the absence of standardized quantitative metrics for AD imaging biomarkers constitutes a major deficiency. Failure to move toward a standardized system of quantitative metrics has substantially limited potential diagnostic usefulness of imaging in AD. This presents an important opportunity that, if widely embraced, could greatly expand the application of imaging to improve clinical diagnosis and the quality and efficiency of clinical trials.

Complex relationships between cerebral blood flow and brain atrophy in early Huntington's disease

Alterations in cerebral blood flow (CBF) may play an important role in the pathophysiology of neurodegenerative disorders such as Huntington's disease (HD). While a few reports have suggested reductions in CBF in HD, little is known about their extent and whether, or how, they might be related to atrophy and to clinical symptoms. We used pulsed arterial-spin labeling MRI in conjunction with high-resolution anatomical MRI to non-invasively measure regional CBF in 17 early stage HD subjects and 41 age- and gender-matched healthy controls. We found profound yet heterogeneous CBF reductions in the cortex, extending to the sensorimotor, paracentral, inferior temporal and lateral occipital regions, with sparing of the neighboring postcentral gyrus, insula and medial occipital areas. As expected, CBF in subcortical regions was also profoundly reduced, and to a similar degree. Unexpectedly, however, the association between CBF reductions and regional atrophy was complex, the two being directly associated in certain areas but not with others. In contrast, CBF was associated with performance on the Stroop, suggesting a potentially important role for alterations in CBF in cognitive deficits in HD. The work described here may have broad-reaching implications for our understanding of HD pathogenesis, progression and emerging therapies.

MRI patterns of atrophy and hypoperfusion associations across brain regions in frontotemporal dementia

Magnetic Resonance Imaging (MRI) provides various imaging modes to study the brain. We tested the benefits of a joint analysis of multimodality MRI data in combination with a large-scale analysis that involved simultaneously all image voxels using joint independent components analysis (jICA) and compared the outcome to results using conventional voxel-by-voxel unimodality tests. Specifically, we designed a jICA to decompose multimodality MRI data into independent components that explain joint variations between the image modalities as well as variations across brain regions. We tested the jICA design on structural and perfusion-weighted MRI data from 12 patients diagnosed with behavioral variant frontotemporal dementia (bvFTD) and 12 cognitively normal elderly individuals. While unimodality analyses showed widespread brain atrophy and hypoperfusion in the patients, jICA further revealed two significant joint components of variations between atrophy and hypoperfusion across brain regions. The 1st joint component revealed associated brain atrophy and hypoperfusion predominantly in the right brain hemisphere in behavioral variant frontotemporal dementia, and the 2nd joint component revealed greater atrophy relative to hypoperfusion affecting predominantly the left hemisphere in behavioral variant frontotemporal dementia. The patterns are consistent with the clinical symptoms of behavioral variant frontotemporal dementia that relate to asymmetric compromises of the left and right brain hemispheres. The joint components also revealed that that structural alterations can be associated with physiological alterations in spatially separated but potentially connected brain regions. Finally, jICA outperformed voxel-by-voxel unimodal tests significantly in terms of an effect size, separating the behavioral variant frontotemporal dementia patients from the controls. Taken together, the results demonstrate the benefit of multimodality MRI in conjunction with jICA for mapping neurodegeneration, which may lead ultimately to an improved diagnosis of behavioral variant frontotemporal dementia and other forms of neurodegenerative diseases.

Multimodal MRI neuroimaging biomarkers for cognitive normal adults, amnestic mild cognitive impairment, and Alzheimer's disease

Multimodal magnetic resonance imaging (MRI) techniques have been developed to noninvasively measure structural, metabolic, hemodynamic and functional changes of the brain. These advantages have made MRI an important tool to investigate neurodegenerative disorders, including diagnosis, disease progression monitoring, and treatment efficacy evaluation. This paper discusses recent findings of the multimodal MRI in the context of surrogate biomarkers for identifying the risk for AD in normal cognitive (NC) adults, brain anatomical and functional alterations in amnestic mild cognitive impairment (aMCI), and Alzheimer's disease (AD) patients. Further developments of these techniques and the establishment of promising neuroimaging biomarkers will enhance our ability to diagnose aMCI and AD in their early stages and improve the assessment of therapeutic efficacy in these diseases in future clinical trials.

Cognitively preserved subjects with transitional cerebrospinal fluid ß-amyloid 1-42 values have thicker cortex in Alzheimer's disease vulnerable areas

BACKGROUND

Establishing the relationship between cerebrospinal fluid (CSF) ß-amyloid 1-42 (Aß) and cortical thickness (CTh) would represent a major step forward in the understanding of the Alzheimer's disease (AD) process. We studied this relationship in a group of healthy control subjects and subjects with subjective memory complaints with preserved cognitive function at neuropsychological testing.

METHODS

In this cross-sectional study, 33 individuals (17 healthy control subjects and 16 subjects with subjective memory complaints) underwent structural 3-Tesla magnetic resonance image scanning and a spinal tap. Cerebrospinal fluid Aß was measured by enzyme-linked immunosorbent assay. The relationship between CSF Aß values and CTh in several regions of interest, both susceptible and unrelated to AD pathology, was analyzed with a curve fit analysis and CTh difference maps were derived from group comparisons.

RESULTS

Dichotomizing the whole sample according to Aß values (cutoff 500 pg/mL), we found the expected cortical thinning in Aß positive subjects in temporoparietal areas (p < .05 corrected). When analyzing the relationship between CSF Aß and CTh in AD-susceptible regions, we found a significant inverted U-shaped relationship (quadratic). Therefore, the sample was further divided into tertiles (according to CSF Aß values) to perform subsequent subgroup comparisons. Increased CTh in temporoparietal areas and precuneus (p < .05 corrected) was found in the middle Aß tertile (CSF Aß between 416 and 597 pg/mL) when compared with the high Aß tertile (616-881 pg/mL).

CONCLUSIONS

The relationship between Aß and CTh in preclinical stages may not be linear. Cortical thickness in temporoparietal and precuneus regions is greater in subjects with transitional CSF Aß values.

Cortical thickness, surface area, and volume of the brain reward system in alcohol dependence: relationships to relapse and extended abstinence

BACKGROUND

At least 60% of those treated for an alcohol use disorder will relapse. Empirical study of the integrity of the brain reward system (BRS) is critical to understanding the mechanisms of relapse as this collection of circuits is implicated in the development and maintenance of all forms of addictive disorders. This study compared thickness, surface area, and volume in neocortical components of the BRS among nonsmoking light-drinking controls (controls), individuals who remained abstinent and those who relapsed after treatment.

METHODS

Seventy-five treatment-seeking alcohol-dependent individuals (abstinent for 7±3 days) and 43 controls completed 1.5T proton magnetic resonance imaging studies. Parcellated morphological data were obtained for following bilateral components of the BRS: rostral and caudal anterior cingulate cortex, insula, medial and lateral orbitofrontal cortex (OFC), rostral and caudal middle and superior frontal gyri, amygdala and hippocampus as well as for 26 other bilateral neocortical regions. Alcohol-dependent participants were followed over 12-months after baseline study and were classified as abstainers (no alcohol consumption; n=24) and relapsers (any alcohol consumption; n=51) at follow-up.

RESULTS

Relapsers and abstainers demonstrated lower cortical thickness in the vast majority of BRS regions as well as lower global thickness compared to controls. Relapsers had lower total BRS surface area than both controls and abstainers, but abstainers were not significantly different from controls on any surface area measure. Relapsers demonstrated lower volumes than controls in the majority of regions, while abstainers showed lower volumes than controls in the superior frontal gyrus, insula, amygdala, and hippocampus, bilaterally. Relapsers exhibited smaller volumes than abstainers in the right rostral middle and caudal middle frontal gyri and the lateral OFC, bilaterally. In relapsers, lower baseline volumes and surface areas in multiple regions were associated with a greater magnitude of post-treatment alcohol consumption.

CONCLUSIONS

Results suggest relapsers demonstrated morphological abnormalities in regions involved in the "top down" regulation/modulation of internal drive states, emotions, reward processing, and behavior, which may impart increased risk for the relapse/remit cycle that afflicts many with an alcohol use disorder. Results also highlight the importance of examining both cortical thickness and surface area to better understand the nature of regional volume loss frequently observed in alcohol use disorders. Results from this report are consistent with previous research implicating plastic neurobiological changes in the BRS in the maintenance of addictive disorders.

Age-associated reductions in cerebral blood flow are independent from regional atrophy

Prior studies have demonstrated decreasing cerebral blood flow (CBF) in normal aging, but the full spatial pattern and potential mechanism of changes in CBF remain to be elucidated. Specifically, existing data have not been entirely consistent regarding the spatial distribution of such changes, potentially a result of neglecting the effect of age-related tissue atrophy in CBF measurements. In this work, we use pulsed arterial-spin labelling to quantify regional CBF in 86 cognitively and physically healthy adults, aged 23 to 88 years. Surface-based analyses were utilized to map regional decline in CBF and cortical thickness with advancing age, and to examine the spatial associations and dissociations between these metrics. Our results demonstrate regionally selective age-related reductions in cortical perfusion, involving the superior-frontal, orbito-frontal, superior-parietal, middle-inferior temporal, insular, precuneus, supramarginal, lateral-occipital and cingulate regions, while subcortical CBF was relatively preserved in aging. Regional effects of age on CBF differed from that of grey-matter atrophy. In addition, the pattern of CBF associations with age displays an interesting similarity with the default-mode network. These findings demonstrate the dissociation between regional CBF and structural alterations specific to normal aging, and augment our understanding of mechanisms of pathology in older adults.