Cristelle Rodriguez

Individual Prediction of Cognitive Decline in Mild Cognitive Impairment Using Support Vector Machine-Based Analysis of Diffusion Tensor Imaging Data

Although cross-sectional diffusion tensor imaging (DTI) studies revealed significant white matter changes in mild cognitive impairment (MCI), the utility of this technique in predicting further cognitive decline is debated. Thirty-five healthy controls (HC) and 67 MCI subjects with DTI baseline data were neuropsychologically assessed at one year. Among them, there were 40 stable (sMCI; 9 single domain amnestic, 7 single domain frontal, 24 multiple domain) and 27 were progressive (pMCI; 7 single domain amnestic, 4 single domain frontal, 16 multiple domain). Fractional anisotropy (FA) and longitudinal, radial, and mean diffusivity were measured using Tract-Based Spatial Statistics. Statistics included group comparisons and individual classification of MCI cases using support vector machines (SVM). FA was significantly higher in HC compared to MCI in a distributed network including the ventral part of the corpus callosum, right temporal and frontal pathways. There were no significant group-level differences between sMCI versus pMCI or between MCI subtypes after correction for multiple comparisons. However, SVM analysis allowed for an individual classification with accuracies up to 91.4% (HC versus MCI) and 98.4% (sMCI versus pMCI). When considering the MCI subgroups separately, the minimum SVM classification accuracy for stable versus progressive cognitive decline was 97.5% in the multiple domain MCI group. SVM analysis of DTI data provided highly accurate individual classification of stable versus progressive MCI regardless of MCI subtype, indicating that this method may become an easily applicable tool for early individual detection of MCI subjects evolving to dementia.

Cerebral Microhemorrhage and Iron Deposition in Mild Cognitive Impairment: Susceptibility-weighted MR Imaging Assessment

PURPOSE To test whether susceptibility-weighted magnetic resonance imaging at baseline may help predict cognitive decline. MATERIALS AND METHODS This prospective study was approved by the institutional review board, and written informed consent was obtained from all participants. Thirty-five healthy control subjects and 69 patients with mild cognitive impairment were included. Patients with mild cognitive impairment underwent neuropsychologic follow-up after 1 year (40 patients with stable mild cognitive impairment, 27 with progressive mild cognitive impairment, and two lost to follow-up). Cerebral microhemorrhages were visually analyzed by two experienced neuroradiologists in consensus. Iron deposition in deep gray matter was assessed with voxel-wise and region-of-interest analysis after nonlinear spatial registration. In addition, individual classification of mild cognitive impairment was analyzed by using a support vector machine (SVM). RESULTS At baseline, the number of cerebral microhemorrhages was significantly higher in the mild cognitive impairment group than in the control group (P < .01) but did not differ between the patients with stable and those with progressive mild cognitive impairment. Compared with the control group, patients with mild cognitive impairment had increased iron concentration in the right pallidum (P < .01) and right substantia nigra (P < .01) but decreased concentration in the right red nucleus (P < .05). The classification based on the SVM successfully helped discriminate patients with mild cognitive impairment from the healthy control subjects (accuracy, 84%; sensitivity, 89%; specificity, 85%) and those with stable from those with progressive mild cognitive impairment (accuracy, 85%; sensitivity, 84%; specificity, 83%). CONCLUSION The findings reveal an accumulation of cerebral microhemorrhage in patients with mild cognitive impairment that is present at baseline, independent of subsequent cognitive decline, as well as an altered iron distribution in subcortical nuclei between the healthy control subjects and patients with mild cognitive impairment. Analysis of iron deposition at baseline performed with an SVM might help identify individual patients with mild cognitive impairment at risk for cognitive decline. SUPPLEMENTAL MATERIAL http://radiology.rsna.org/lookup/suppl/doi:10.1148/radiol.10100612/-/DC1.

Arterial Spin Labeling May Contribute to the Prediction of Cognitive Deterioration in Healthy Elderly Individuals

PURPOSE To explore whether arterial spin labeling (ASL) imaging in cognitively intact elderly individuals may be used to predict subsequent early neuropsychological decline. MATERIALS AND METHODS The local ethics committee approved this prospective study, and written informed consent was obtained from all participants. A total of 148 consecutive control subjects were included, 75 of whom had stable cognitive function (sCON) (mean age, 75.9 years ± 3.4 [standard deviation]; 43 female) and 73 of whom had deteriorated cognitive function (dCON) at 18-month clinical follow-up (mean age, 76.8 years ± 4.1; 44 female). An additional 65 patients with mild cognitive impairment (MCI) (mean age, 76.2 years ± 6.1; 25 female) were also included. Two-dimensional pulsed ASL was performed at the baseline visit. Statistical analysis included whole-brain voxelwise analysis of the ASL relative cerebral blood flow (CBF) data, receiver operating characteristic (ROC) curve analysis of the posterior cingulate cortex (PCC), and voxel-based morphometry analysis of gray matter. RESULTS The voxelwise comparison of ASL revealed decreased relative CBF in the dCON group compared with that in the sCON group and slightly more pronounced relative CBF in the MCI group compared with that in the sCON group, most notably in the PCC (P < .05 corrected). Comparison of the dCON group with the MCI group revealed no significant differences. ROC analysis of relative CBF in the PCC enabled discrimination of dCON (P < .001; area under the ROC curve, 0.66). There was no confounding focal gray matter atrophy. CONCLUSION Reduced ASL in the PCC at baseline is associated with the development of subsequent subtle neuropsychological deficits in healthy elderly control subjects. At a group level, ASL patterns in subjects with dCON are similar to those in patients with MCI at baseline, indicating that these subjects may initially maintain their cognitive status via mobilization of their neurocognitive reserve at baseline; however, they are likely to develop subsequent subtle cognitive deficits.

Individual Classification of Mild Cognitive Impairment Subtypes by Support Vector Machine Analysis of White Matter DTI

BACKGROUND AND PURPOSE: MCI was recently subdivided into sd-aMCI, sd-fMCI, and md-aMCI. The current investigation aimed to discriminate between MCI subtypes by using DTI. MATERIALS AND METHODS: Sixty-six prospective participants were included: 18 with sd-aMCI, 13 with sd-fMCI, and 35 with md-aMCI. Statistics included group comparisons using TBSS and individual classification using SVMs. RESULTS: The group-level analysis revealed a decrease in FA in md-aMCI versus sd-aMCI in an extensive bilateral, right-dominant network, and a more pronounced reduction of FA in md-aMCI compared with sd-fMCI in right inferior fronto-occipital fasciculus and inferior longitudinal fasciculus. The comparison between sd-fMCI and sd-aMCI, as well as the analysis of the other diffusion parameters, yielded no significant group differences. The individual-level SVM analysis provided discrimination between the MCI subtypes with accuracies around 97%. The major limitation is the relatively small number of cases of MCI. CONCLUSIONS: Our data show that, at the group level, the md-aMCI subgroup has the most pronounced damage in white matter integrity. Individually, SVM analysis of white matter FA provided highly accurate classification of MCI subtypes.

Acute caffeine administration impact on working memory-related brain activation and functional connectivity in the elderly: a BOLD and perfusion MRI study

In young individuals, caffeine-mediated blockade of adenosine receptors and vasoconstriction has direct repercussions on task-related activations, changes in functional connectivity, as well as global vascular effects. To date, no study has explored the effect of caffeine on brain activation patterns during highly demanding cognitive tasks in the elderly. This prospective, placebo-controlled crossover design comprises 24 healthy elderly individuals (mean age 68.8 ± 4.0 years, 17 females) performing a 2-back working memory (WM) task in functional magnetic resonance imaging (fMRI). Analyses include complimentary assessment of task-related activations (general linear model, GLM), functional connectivity (tensorial independent component analysis, TICA), and baseline perfusion (arterial spin labeling). Despite a reduction in whole-brain global perfusion (-22.7%), caffeine-enhanced task-related GLM activation in a local and distributed network is most pronounced in the bilateral striatum and to a lesser degree in the right middle and inferior frontal gyrus, bilateral insula, left superior and inferior parietal lobule as well as in the cerebellum bilaterally. TICA was significantly enhanced (+8.2%) in caffeine versus placebo in a distributed and task-relevant network including the pre-frontal cortex, the supplementary motor area, the ventral premotor cortex and the parietal cortex as well as the occipital cortex (visual stimuli) and basal ganglia. The inverse comparison of placebo versus caffeine had no significant difference. Activation strength of the task-relevant-network component correlated with response accuracy for caffeine yet not for placebo, indicating a selective cognitive effect of caffeine. The present findings suggest that acute caffeine intake enhances WM-related brain activation as well as functional connectivity of blood oxygen level-dependent fMRI in elderly individuals.

Age-associated modulations of cerebral oscillatory patterns related to attention control.

Visual attention depends on bottom-up sensory activation and top-down attentional guidance. Although aging is known to affect sensory processing, its impact on the top-down control of attention remains a matter of debate. We investigated age-related modulations of brain oscillatory activity during visual attention using a variant of the attention network test (ANT) in 20 young and 28 elderly adults. We examined the EEG oscillatory responses to warning and target signals, and explored the correlates of temporal and spatial orienting as well as conflict resolution at target presentation. Time-frequency analysis was performed between 4 and 30 Hz, and the relationship between behavioral and brain oscillatory responses was analyzed. Whereas temporal cueing and conflict had similar reaction time effects in both age groups, spatial cueing was more beneficial to older than younger subjects. In the absence of cue, posterior alpha activation was drastically reduced in older adults, pointing to an age-related decline in anticipatory attention. Following both cues and targets, older adults displayed pronounced motor-related activation in the low beta frequency range at the expense of attention-related posterior alpha activation prominent in younger adults. These findings support the recruitment of alternative motor-related circuits in the elderly, in line with the dedifferentiation hypothesis. Furthermore, older adults showed reduced midparietal alpha inhibition induced by temporal orienting as well as decreased posterior alpha activation associated with both spatial orienting and conflict resolution. Altogether, the results are consistent with an overall reduction of task-related alpha activity in the elderly, and provide functional evidence that younger and older adults engage distinct brain circuits at different oscillatory frequencies during attentional functions.

Neuroimaging of dementia in 2013: what radiologists need to know

AbstractThe structural and functional neuroimaging of dementia have substantially evolved over the last few years. The most common forms of dementia, Alzheimer disease (AD), Lewy body dementia (LBD) and fronto-temporal lobar degeneration (FTLD), have distinct patterns of cortical atrophy and hypometabolism that evolve over time, as reviewed in the first part of this article. The second part discusses unspecific white matter alterations on T2-weighted and fluid-attenuated inversion recovery (FLAIR) images as well as cerebral microbleeds, which often occur during normal aging and may affect cognition. The third part summarises molecular neuroimaging biomarkers recently developed to visualise amyloid deposits, tau protein deposits and neurotransmitter systems. The fourth section reviews the utility of advanced image analysis techniques as predictive biomarkers of cognitive decline in individuals with early symptoms compatible with mild cognitive impairment (MCI). As only about half of MCI cases will progress to clinically overt dementia, whereas the other half remain stable or might even improve, the discrimination of stable versus progressive MCI is of paramount importance for both individual patient treatment and patient selection for clinical trials. The fifth and final part discusses the inter-individual variation in the neurocognitive reserve, which is a potential constraint for all proposed methods. Key Points• Many forms of dementia have spatial atrophy patterns detectable on neuroimaging.• Early treatment of dementia is beneficial, indicating the need for early diagnosis.• Advanced image analysis techniques detect subtle anomalies invisible on radiological evaluation.• Inter-individual variation explains variable cognitive impairment despite the same degree of atrophy.

Aging effects on selective attention-related electroencephalographic patterns during face encoding.

Previous electrophysiological studies revealed that human faces elicit an early visual event-related potential (ERP) within the occipito-temporal cortex, the N170 component. Although face perception has been proposed to rely on automatic processing, the impact of selective attention on N170 remains controversial both in young and elderly individuals. Using early visual ERP and alpha power analysis, we assessed the influence of aging on selective attention to faces during delayed-recognition tasks for face and letter stimuli, examining 36 elderly and 20 young adults with preserved cognition. Face recognition performance worsened with age. Aging induced a latency delay of the N1 component for faces and letters, as well as of the face N170 component. Contrasting with letters, ignored faces elicited larger N1 and N170 components than attended faces in both age groups. This counterintuitive attention effect on face processing persisted when scenes replaced letters. In contrast with young, elderly subjects failed to suppress irrelevant letters when attending faces. Whereas attended stimuli induced a parietal alpha band desynchronization within 300-1000 ms post-stimulus with bilateral-to-right distribution for faces and left lateralization for letters, ignored and passively viewed stimuli elicited a central alpha synchronization larger on the right hemisphere. Aging delayed the latency of this alpha synchronization for both face and letter stimuli, and reduced its amplitude for ignored letters. These results suggest that due to their social relevance, human faces may cause paradoxical attention effects on early visual ERP components, but they still undergo classical top-down control as a function of endogenous selective attention. Aging does not affect the face bottom-up alerting mechanism but reduces the top-down suppression of distracting letters, possibly impinging upon face recognition, and more generally delays the top-down suppression of task-irrelevant information.

Acute Caffeine Administration Effect on Brain Activation Patterns in Mild Cognitive Impairment

Previous studies showed that acute caffeine administration enhances task-related brain activation in elderly individuals with preserved cognition. To explore the effects of this widely used agent on cognition and brain activation in early phases of cognitive decline, we performed a double-blinded, placebo-controlled functional magnetic resonance imaging (fMRI) study during an n-back working memory task in 17 individuals with mild cognitive impairment (MCI) compared to 17 age-matched healthy controls (HC). All individuals were regular caffeine consumers with an overnight abstinence and given 200 mg caffeine versus placebo tablets 30 minutes before testing. Analyses included assessment of task-related activation (general linear model), functional connectivity (tensorial-independent component analysis, TICA), baseline perfusion (arterial spin labeling, ASL), grey matter density (voxel-based morphometry, VBM), and white matter microstructure (tract-based spatial statistics, TBSS). Acute caffeine administration induced a focal activation of the prefrontal areas in HC with a more diffuse and posteromedial activation pattern in MCI individuals. In MCI, TICA documented a significant caffeine-related enhancement in the prefrontal cortex, supplementary motor area, ventral premotor and parietal cortex as well as the basal ganglia and cerebellum. The absence of significant group differences in baseline ASL perfusion patterns supports a neuronal rather than a purely vascular origin of these differences. The VBM and TBSS analyses excluded potentially confounding differences in grey matter density and white matter microstructure between MCI and HC. The present findings suggest a posterior displacement of working memory-related brain activation patterns after caffeine administration in MCI that may represent a compensatory mechanism to counterbalance a frontal lobe dysfunction.

Prediction of long-term memory scores in MCI based on resting-state fMRI

Resting-state functional MRI (rs-fMRI) opens a window on large-scale organization of brain function. However, establishing relationships between resting-state brain activity and cognitive or clinical scores is still a difficult task, in particular in terms of prediction as would be meaningful for clinical applications such as early diagnosis of Alzheimers disease. In this work, we employed partial least square regression under cross-validation scheme to predict episodic memory performance from functional connectivity (FC) patterns in a set of fifty-five MCI subjects for whom rs-fMRI acquisition and neuropsychological evaluation was carried out. We show that a newly introduced FC measure capturing the moments of anti-correlation between brain areas, discordance, contains key information to predict long-term memory scores in MCI patients, and performs better than standard measures of correlation to do so. Our results highlighted that stronger discordance within default mode network (DMN) areas, as well as across DMN, attentional and limbic networks, favor episodic memory performance in MCI.