Dementia is common in Parkinson's disease, but the underlying brain pathology is not yet fully understood.
To examine the changes in the brain of patients with Parkinson's disease with mild cognitive impairment (MCI) and dementia, using structural magnetic resonance imaging.
Using voxel‐based morphometry, the grey matter atrophy on brain images of patients with Parkinson's disease and dementia (PDD; n = 16) and Parkinson's disease without dementia (PDND; n = 20), and healthy elderly subjects (n = 20) was studied. In the PDND group, 12 subjects had normal cognitive status and 8 had MCI. Standardised rating scales for motor, cognitive and psychiatric symptoms were used.
Widespread areas of cortical atrophy were found in patients with PDD compared with normal controls (in both temporal and frontal lobes and in the left parietal lobe). Grey matter reductions were found in frontal, parietal, limbic and temporal lobes in patients with PDD compared with those with PDND. In patients with PDND with MCI, areas of reduced grey matter in the left frontal and both temporal lobes were found.
These findings show that dementia in Parkinson's disease is associated with structural neocortical changes in the brain, and that cognitive impairment in patients with PDND may be associated with structural changes in the brain. Further studies with larger groups of patients are needed to confirm these findings.
Cortical changes associated with cognitive decline in Parkinson's disease (PD) are not fully explored and require investigations with established diagnostic classification criteria.
We used MRI source-based morphometry to evaluate specific differences in grey matter volume patterns across 4 groups of subjects: healthy controls (HC), PD with normal cognition (PD-NC), PD with mild cognitive impairment (MCI-PD) and PD with dementia (PDD).
We examined 151 consecutive subjects: 25 HC, 75 PD-NC, 29 MCI-PD, and 22 PDD at an Italian and Czech movement disorder centre. Operational diagnostic criteria were applied to classify MCI-PD and PDD. All structural MRI images were processed together in the Czech centre. The spatial independent component analysis was used to assess group differences of local grey matter volume.
We identified two independent patterns of grey matter volume deviations: a) Reductions in the hippocampus and temporal lobes; b) Decreases in fronto-parietal regions and increases in the midbrain/cerebellum. Both patterns differentiated PDD from all other groups and correlated with visuospatial deficits and letter verbal fluency, respectively. Only the second pattern additionally differentiated PD-NC from HC.
Grey matter changes in PDD involve areas associated with Alzheimer-like pathology while fronto-parietal abnormalities are possibly an early marker of PD cognitive decline. These findings are consistent with a non-linear cognitive progression in PD.
Spatial patterns of brain atrophy in mild cognitive impairment (MCI) and Alzheimer’s disease (AD) were measured via methods of computational neuroanatomy. These patterns were spatially complex and involved many brain regions. In addition to the hippocampus and the medial temporal lobe gray matter, a number of other regions displayed significant atrophy, including orbitofrontal and medial-prefrontal grey matter, cingulate (mainly posterior), insula, uncus, and temporal lobe white matter. Approximately 2/3 of the MCI group presented patterns of atrophy that overlapped with AD, whereas the remaining 1/3 overlapped with cognitively normal individuals, thereby indicating that some, but not all, MCI patients have significant and extensive brain atrophy in this cohort of MCI patients. Importantly, the group with AD-like patterns presented much higher rate of MMSE decline in follow-up visits; conversely, pattern classification provided relatively high classification accuracy (87%) of the individuals that presented relatively higher MMSE decline within a year from baseline. High-dimensional pattern classification, a nonlinear multivariate analysis, provided measures of structural abnormality that can potentially be useful for individual patient classification, as well as for predicting progression and examining multivariate relationships in group analyses.
Alzheimer’s disease; early detection; mild cognitive impairment; MCI; pattern classification; structural MRI
Type 2 diabetes (T2DM) is associated with brain atrophy and cerebrovascular disease. We aimed to define the regional distribution of brain atrophy in T2DM and to examine whether atrophy or cerebrovascular lesions are feasible links between T2DM and cognitive function.
RESEARCH DESIGN AND METHODS
This cross-sectional study used magnetic resonance imaging (MRI) scans and cognitive tests in 350 participants with T2DM and 363 participants without T2DM. With voxel-based morphometry, we studied the regional distribution of atrophy in T2DM. We measured cerebrovascular lesions (infarcts, microbleeds, and white matter hyperintensity [WMH] volume) and atrophy (gray matter, white matter, and hippocampal volumes) while blinded to T2DM status. With use of multivariable regression, we examined for mediation or effect modification of the association between T2DM and cognitive measures by MRI measures.
T2DM was associated with more cerebral infarcts and lower total gray, white, and hippocampal volumes (all P < 0.05) but not with microbleeds or WMH. T2DM-related gray matter loss was distributed mainly in medial temporal, anterior cingulate, and medial frontal lobes, and white matter loss was distributed in frontal and temporal regions. T2DM was associated with poorer visuospatial construction, planning, visual memory, and speed (P ≤ 0.05) independent of age, sex, education, and vascular risk factors. The strength of these associations was attenuated by almost one-half when adjusted for hippocampal and total gray volumes but was unchanged by adjustment for cerebrovascular lesions or white matter volume.
Cortical atrophy in T2DM resembles patterns seen in preclinical Alzheimer disease. Neurodegeneration rather than cerebrovascular lesions may play a key role in T2DM-related cognitive impairment.
Alzheimer’s disease (AD) is generally considered to be characterized by pathology in gray matter of the brain, but convergent evidence suggests that white matter degradation also plays a vital role in its pathogenesis. The evolution of white matter deterioration and its relationship with gray matter atrophy remains elusive in amnestic mild cognitive impairment (aMCI), a prodromal stage of AD.
We studied 155 cognitively normal (CN) and 27 ‘late’ aMCI individuals with stable diagnosis over 2 years, and 39 ‘early’ aMCI individuals who had converted from CN to aMCI at 2-year follow up. Diffusion tensor imaging (DTI) tractography was used to reconstruct six white matter tracts three limbic tracts critical for episodic memory function - the fornix, the parahippocampal cingulum, and the uncinate fasciculus; two cortico-cortical association fiber tracts - superior longitudinal fasciculus and inferior longitudinal fasciculus; and one projection fiber tract - corticospinal tract. Microstructural integrity as measured by fractional anisotropy (FA), mean diffusivity (MD), radial diffusivity (RD) and axial diffusivity (AxD) was assessed for these tracts.
Compared with CN, late aMCI had lower white matter integrity in the fornix, the parahippocampal cingulum, and the uncinate fasciculus, while early aMCI showed white matter damage in the fornix. In addition, fornical measures were correlated with hippocampal atrophy in late aMCI, whereas abnormality of the fornix in early aMCI occurred in the absence of hippocampal atrophy and did not correlate with hippocampal volumes.
Limbic white matter tracts are preferentially affected in the early stages of cognitive dysfunction. Microstructural degradation of the fornix preceding hippocampal atrophy may serve as a novel imaging marker for aMCI at an early stage.
Cognitive impairment is very common in patients with Parkinson's disease (PD). Brain changes accompanying cognitive decline in PD are still not fully established.
We applied cortical pattern matching and cortical thickness analyses to the three-dimensional T1-weighted brain MRI scans of 14 age-matched cognitively normal elderly (NC), 12 cognitively normal PD (PDC), and 11 PD dementia (PDD) subjects. We used linear regression models to investigate the effect of diagnosis on cortical thickness. All maps were adjusted for multiple comparisons using permutation testing with a threshold p < 0.01.
PDD showed significantly thinner bilateral sensorimotor, perisylvian, lateral parietal, as well as right posterior cingulate, parieto-occipital, inferior temporal and lateral frontal cortices relative to NC (left pcorrected = 0.06, right pcorrected = 0.009). PDD showed significantly thinner bilateral sensorimotor, right frontal and right parietal-occipital cortices relative to PDC (right pcorrected = 0.05). The absolute difference in cortical thickness between PDD and the other diagnostic groups ranged from 3% to 19%.
Our data shows that cognitive decline in PD is associated with cortical atrophy. PDD subjects have the most widespread gray matter atrophy suggesting more cortical involvement as PD patients progress to dementia.
Parkinson's disease; dementia; magnetic resonance imaging; MRI; brain atrophy; cortical atrophy; gray matter atrophy
White matter (WM) microstructural declines have been demonstrated in Alzheimer’s disease and amnestic mild cognitive impairment (aMCI). However, the pattern of WM microstructural changes in aMCI after controlling for WM atrophy is unknown. Here, we address this issue through joint consideration of aMCI alterations in fractional anisotropy, mean diffusivity, axial diffusivity, and radial diffusivity, as well as macrostructural volume in WM and gray matter compartments. Participants were 18 individuals with aMCI and 24 healthy seniors. Voxelwise analyses of diffusion tensor imaging data was carried out using tract-based spatial statistics (TBSS) and voxelwise analyses of high-resolution structural data was conducted using voxel based morphometry. After controlling for WM atrophy, the main pattern of TBSS findings indicated reduced fractional anisotropy with only small alterations in mean diffusivity/radial diffusivity/axial diffusivity. These WM microstructural declines bordered and/or were connected to gray matter structures showing volumetric declines. However, none of the potential relationships between WM integrity and volume in connected gray matter structures was significant, and adding fractional anisotropy information improved the classificatory accuracy of aMCI compared to the use of hippocampal atrophy alone. These results suggest that WM microstructural declines provide unique information not captured by atrophy measures that may aid the magnetic resonance imaging contribution to aMCI detection.
Alzheimer’s disease; atrophy; diffusion tensor imaging; mild cognitive impairment
To investigate whether baseline CSF biomarkers are associated with hippocampal atrophy rate as a measure of disease progression in patients with Alzheimer disease (AD), patients with mild cognitive impairment (MCI), and controls, controlling for baseline neuropsychological and MRI findings.
We assessed data from 31 patients with AD, 25 patients with MCI, and 19 controls (mean age 68 ± 8 years; 39 [52%] female) who visited our memory clinic and had received serial MRI scanning (scan interval 1.7 ± 0.7 years). At baseline, CSF biomarkers (amyloid β 1-42, tau, and tau phosphorylated at threonine 181 [p-tau]) were obtained, as well as neuropsychological data. Baseline MRI scans were assessed using visual rating scales for medial temporal lobe atrophy (MTA), global cortical atrophy, and white matter hyperintensities. Hippocampal atrophy rates were estimated using regional nonlinear “fluid” registration of follow-up scan to baseline scan.
Stepwise multiple linear regression, adjusted for age and sex, showed that increased CSF p-tau levels (β [standard error]: −0.79 [0.35]) at baseline was independently associated with higher subsequent hippocampal atrophy rates (p < 0.05), together with poorer memory performance (0.09 [0.04]) and more severe MTA (−0.60 [0.21]). The association of memory function with hippocampal atrophy rate was explained by the link with diagnosis, because it disappeared from the model after we additionally corrected for diagnosis.
Baseline CSF levels of tau phosphorylated at threonine 181 are independently associated with subsequent disease progression, as reflected by hippocampal atrophy rate. This effect is independent of baseline neuropsychological and MRI predictors. Our results imply that predicting disease progression can best be achieved by combining information from different modalities.
= amyloid β 1-42;
= Alzheimer disease;
= field of view;
= global cortical atrophy;
= lumbar puncture;
= mild cognitive impairment;
= Mini-Mental State Examination;
= medial temporal lobe atrophy;
= tau phosphorylated at threonine 181;
= echo time;
= inversion time;
= Trail Making Test;
= repetition time;
= Visual Association Test;
= white matter hyperintensities.
To examine the neural basis of cognitive complaints in healthy older adults in the absence of memory impairment and to determine whether there are medial temporal lobe (MTL) gray matter (GM) changes as reported in Alzheimer disease (AD) and amnestic mild cognitive impairment (MCI).
Participants were 40 euthymic individuals with cognitive complaints (CCs) who had normal neuropsychological test performance. The authors compared their structural brain MRI scans to those of 40 patients with amnestic MCI and 40 healthy controls (HCs) using voxel-based morphometry and hippocampal volume analysis.
The CC and MCI groups showed similar patterns of decreased GM relative to the HC group on whole brain analysis, with differences evident in the MTL, frontotemporal, and other neocortical regions. The degree of GM loss was associated with extent of both memory complaints and performance deficits. Manually segmented hippocampal volumes, adjusted for age and intracranial volume, were significantly reduced only in the MCI group, with the CC group showing an intermediate level.
Cognitive complaints in older adults may indicate underlying neurodegenerative changes even when unaccompanied by deficits on formal testing. The cognitive complaint group may represent a pre–mild cognitive impairment stage and may provide an earlier therapeutic opportunity than mild cognitive impairment. MRI analysis approaches incorporating signal intensity may have greater sensitivity in early preclinical stages than volumetric methods.
Dementia is a frequent and devastating complication in Parkinson’s disease (PD). There is an intensive search for biomarkers that may predict the progression from normal cognition (PD-NC) to dementia (PDD) in PD. Mild cognitive impairment in PD (PD-MCI) seems to represent a transitional state between PD-NC and PDD. Few studies have explored the structural changes that differentiate PD-NC from PD-MCI and PDD patients.
Objectives and Methods
We aimed to analyze changes in cortical thickness on 3.0T Magnetic Resonance Imaging (MRI) across stages of cognitive decline in a prospective sample of PD-NC (n = 26), PD-MCI (n = 26) and PDD (n = 20) patients, compared to a group of healthy subjects (HC) (n = 18). Cortical thickness measurements were made using the automatic software Freesurfer.
In a sample of 72 PD patients, a pattern of linear and progressive cortical thinning was observed between cognitive groups in cortical areas functionally specialized in declarative memory (entorhinal cortex, anterior temporal pole), semantic knowledge (parahippocampus, fusiform gyrus), and visuoperceptive integration (banks of the superior temporal sulcus, lingual gyrus, cuneus and precuneus). Positive correlation was observed between confrontation naming and thinning in the fusiform gyrus, parahippocampal gyrus and anterior temporal pole; clock copy with thinning of the precuneus, parahippocampal and lingual gyrus; and delayed memory with thinning of the bilateral anteromedial temporal cortex.
The pattern of regional decreased cortical thickness that relates to cognitive deterioration is present in PD-MCI patients, involving areas that play a central role in the storage of prior experiences, integration of external perceptions, and semantic processing.
Structural neuroimaging studies have consistently shown a pattern of extra‐hippocampal atrophy in patients with left and right drug‐refractory medial temporal lobe epilepsy (MTLE). However, it is not yet completely understood how extra‐hippocampal atrophy is related to hippocampal atrophy. Moreover, patients with left MTLE often exhibit more intense cognitive impairment, and subtle brain asymmetries have been reported in patients with left MTLE versus right MTLE but have not been explored in a controlled study.
To investigate the association between extra‐hippocampal and hippocampal atrophy in patients with MTLE, and the effect of side of hippocampal atrophy on extra‐hippocampal atrophy.
Voxel‐based morphometry analyses of magnetic resonance images of the brain were performed to determine the correlation between regional extra‐hippocampal grey matter volume and hippocampal grey matter volume. The results from 36 patients with right and left MTLE were compared, and results from the two groups were compared with those from 49 healthy controls.
Compared with controls, patients with MTLE showed a more intense correlation between hippocampal grey matter volume and regional grey matter volume in locations such as the contralateral hippocampus, bilateral parahippocampal gyri and frontal and parietal areas. Compared with right MTLE, patients with left MTLE exhibited a wider area of atrophy related to hippocampal grey matter loss, encompassing both the contralateral and ipsilateral hemispheres, particularly affecting the contralateral hippocampus.
Our results suggest that left hippocampal atrophy is associated with a larger degree of extra‐hippocampal atrophy. This may help to explain the more intense cognitive impairment usually observed in these patients.
In one of the largest brain MRI studies to date, we used tensor-based morphometry (TBM) to create 3D maps of structural atrophy in 676 subjects with Alzheimer’s disease (AD), mild cognitive impairment (MCI), and healthy elderly controls, scanned as part of the Alzheimer’s Disease Neuroimaging Initiative (ADNI). Using inverse-consistent 3D non-linear elastic image registration, we warped 676 individual brain MRI volumes to a population mean geometric template. Jacobian determinant maps were created, revealing the 3D profile of local volumetric expansion and compression. We compared the anatomical distribution of atrophy in 165 AD patients (age: 75.6 ± 7.6 years), 330 MCI subjects (74.8 ± 7.5), and 181 controls (75.9 ± 5.1). Brain atrophy in selected regions-of-interest was correlated with clinical measurements - the sum-of-boxes clinical dementia rating (CDR-SB), mini-mental state examination (MMSE), and the logical memory test scores - at voxel level followed by correction for multiple comparisons. Baseline temporal lobe atrophy correlated with current cognitive performance, future cognitive decline, and conversion from MCI to AD over the following year; it predicted future decline even in healthy subjects. Over half of the AD and MCI subjects carried the ApoE4 (apolipoprotein E4) gene, which increases risk for AD; they showed greater hippocampal and temporal lobe deficits than non-carriers. ApoE2 gene carriers - 1/6 of the normal group - showed reduced ventricular expansion, suggesting a protective effect. As an automated image analysis technique, TBM reveals 3D correlations between neuroimaging markers, genes, and future clinical changes, and is highly efficient for large-scale MRI studies.
Late-life depression (LLD) and amnestic mild cognitive impairment (aMCI) are associated with medial temporal lobe structural abnormalities. However, the hippocampal functional connectivity (HFC) similarities and differences related to these syndromes when they occur alone or coexist are unclear. Resting-state functional connectivity MRI (R-fMRI) technique was used to measure left and right HFC in 72 elderly participants (LLD [n = 18], aMCI [n = 17], LLD with comorbid aMCI [n = 12], and healthy controls [n = 25]). The main and interactive relationships of LLD and aMCI on the HFC networks were determined, after controlling for age, gender, education and gray matter volumes. The effects of depressive symptoms and episodic memory deficits on the hippocampal functional connections also were assessed. While increased and decreased left and right HFC with several cortical and subcortical structures involved in mood regulation were related to LLD, aMCI was associated with globally diminished connectivity. Significant LLD–aMCI interactions on the right HFC networks were seen in the brain regions critical for emotion processing and higher-order cognitive functions. In the interactive brain regions, LLD and aMCI were associated with diminished hippocampal functional connections, whereas the comorbid group demonstrated enhanced connectivity. Main and interactive effects of depressive symptoms and episodic memory performance were also associated with bilateral HFC network abnormalities. In conclusion, these findings indicate that discrete hippocampal functional network abnormalities are associated with LLD and aMCI when they occur alone. However, when these conditions coexist, more pronounced vulnerabilities of the hippocampal networks occur, which may be a marker of disease severity and impending cognitive decline. By utilizing R-fMRI technique, this study provides novel insights into the neural mechanisms underlying LLD and aMCI in the functional network level.
•Effects of late-life depression and MCI on hippocampal memory network using R-fMRI•Distinct hippocampal functional network correlates in late-life depression and MCI.•Late-life depression and MCI interact on hippocampal functional network level.•Hippocampal functional network correlates with neuropsychological measures.•Novel insights into functional network vulnerability underlying depression and MCI
Depression; Mild cognitive impairment; Hippocampus; Functional connectivity; MRI; Episodic memory; Depressive symptoms; Elderly
To investigate the added value of hippocampal atrophy rates over whole brain volume measurements on MRI in patients with Alzheimer disease (AD), patients with mild cognitive impairment (MCI), and controls.
We included 64 patients with AD (67 ± 9 years; F/M 38/26), 44 patients with MCI (71 ± 6 years; 21/23), and 34 controls (67 ± 9 years; 16/18). Two MR scans were performed (scan interval: 1.8 ± 0.7 years; 1.0 T), using a coronal three-dimensional T1-weighted gradient echo sequence. At follow-up, 3 controls and 23 patients with MCI had progressed to AD. Hippocampi were manually delineated at baseline. Hippocampal atrophy rates were calculated using regional, nonlinear fluid registration. Whole brain baseline volumes and atrophy rates were determined using automated segmentation and registration tools.
All MRI measures differed between groups (p < 0.005). For the distinction of MCI from controls, larger effect sizes of hippocampal measures were found compared to whole brain measures. Between MCI and AD, only whole brain atrophy rate differed significantly. Cox proportional hazards models (variables dichotomized by median) showed that within all patients without dementia, hippocampal baseline volume (hazard ratio [HR]: 5.7 [95% confidence interval: 1.5–22.2]), hippocampal atrophy rate (5.2 [1.9–14.3]), and whole brain atrophy rate (2.8 [1.1–7.2]) independently predicted progression to AD; the combination of low hippocampal volume and high atrophy rate yielded a HR of 61.1 (6.1–606.8). Within patients with MCI, only hippocampal baseline volume and atrophy rate predicted progression.
Hippocampal measures, especially hippocampal atrophy rate, best discriminate mild cognitive impairment (MCI) from controls. Whole brain atrophy rate discriminates Alzheimer disease (AD) from MCI. Regional measures of hippocampal atrophy are the strongest predictors of progression to AD.
= Alzheimer disease;
= brain extraction tool;
= confidence interval;
= degrees of freedom;
= frontotemporal lobar degeneration;
= hazard ratio;
= mild cognitive impairment;
= Mini-Mental State Examination;
= normalized brain volume;
= percentage brain volume change;
= region of interest;
= vascular dementia;
= visual association test.
Cognitively intact older individuals at risk for developing Alzheimer's disease frequently show increased functional magnetic resonance imaging (fMRI) brain activation presumably associated with compensatory recruitment, whereas mild cognitive impairment (MCI) patients tend not to show increased activation presumably due to reduced neural reserve. Previous studies, however, have typically used episodic memory activation tasks, placing MCI participants at a performance disadvantage relative to healthy elders. In this event-related fMRI study, we employed a low effort, high accuracy semantic memory task to determine if increased activation of memory circuits is preserved in amnestic MCI when task performance is controlled. Fifty-seven participants, aged 65–85 years, comprised three groups (n = 19 each): amnestic MCI patients; cognitively intact older participants at risk for developing Alzheimer's disease based on having at least one ApoE ε4 allele and a positive family history of Alzheimer's disease (At Risk); and cognitively intact participants without Alzheimer's disease risk factors (Control). fMRI was conducted on a 3T MR scanner while participants performed a famous name discrimination task. Participants also underwent neuropsychological testing outside the scanner; whole brain and hippocampal atrophy were assessed from anatomical MRI scans. The three groups did not differ on demographic variables or on fame discrimination performance (>87% correct for all groups). As expected, the amnestic MCI participants demonstrated reduced episodic memory performance. Spatial extent of activation (Fame—Unfamiliar subtraction) differentiated the three groups (Control = 0 ml, At Risk = 9.7 ml, MCI = 34.7 ml). The MCI and At Risk groups showed significantly greater per cent signal change than Control participants in 8 of 14 functionally defined regions, including the medial temporal lobe, temporoparietal junction, and posterior cingulate/precuneus. MCI participants also showed greater activation than Controls in two frontal regions. At Risk, but not MCI, participants showed increased activity in the left hippocampal complex; MCI participants, however, evidenced increased activity in this region when hippocampal atrophy was controlled. When performance is equated, MCI patients demonstrate functional compensation in brain regions subserving semantic memory systems that generally equals or exceeds that observed in cognitively intact individuals at risk for Alzheimer's disease. This hyperactivation profile in MCI is even observed in the left hippocampal complex, but only when the extent of hippocampal atrophy is taken into consideration.
Area under the curve (AUC); fMRI; semantic memory; mild cognitive impairment; APOE ε4
Alzheimer's disease (AD) and Parkinson's disease (PD) are among the most common neurodegenerative disorders affecting older populations. AD is characterized by impaired memory and cognitive decline while the primary symptoms of PD include resting tremor, bradykinesia and rigidity. In PD, mild cognitive changes are frequently present, which could progress to dementia (PD dementia (PDD)). PDD and AD dementias are different in pathology although the difference in microstructural changes remains unknown. To further understand these diseases, it is essential to understand the distinct mechanism of their microstructural changes. We used diffusion tensor imaging (DTI) to investigate white matter tract differences between early stage individuals with AD (n=14), PD (n=12), PDD (n=9), and healthy non-demented controls (CON) (n=13). We used whole brain tract based spatial statistics (TBSS) and a region of interest (ROI) analysis focused on the substantia nigra (SN). We found that individuals with PDD had more widespread white matter degeneration compared to PD, AD, and CON. Individuals with AD had few regional abnormalities in the anterior and posterior projections of the corpus callosum while PD and CON did not appear to have significant white matter degeneration when compared to other groups. ROI analyses showed that PDD had the highest diffusivity in the SN and were significantly different from CON. There were no significant ROI differences between CON, PD, or AD. In conclusion, global white matter microstructural deterioration is evident in individuals with PDD, and DTI may provide a means with which to tease out pathological differences between AD and PD dementias.
Neurodegenerative disorders; Dementia; Corticospinal tract; Corpus callosum; Cingulum
Mild cognitive impairment (MCI) may represent an early stage of dementia conferring a particularly high annual risk of 15–20% of conversion to Alzheimer’s disease (AD). Recent findings suggest that not only gray matter (GM) loss but also a decline in white matter (WM) integrity may be associated with imminent conversion from MCI to AD.
In this study we used Voxel-based morphometry (VBM) to examine if gray matter loss and/or an increase of the apparent diffusion coefficient (ADC) reflecting mean diffusivity (MD) are an early marker of conversion from MCI to AD in a high risk population.
Retrospective neuropsychological and clinical data were collected for fifty-five subjects (MCI converters n = 13, MCI non-converters n = 14, healthy controls n = 28) at baseline and one follow-up visit. All participants underwent diffusion weighted imaging (DWI) and T1-weighted structural magnetic resonance imaging scans at baseline to analyse changes in GM density and WM integrity using VBM.
At baseline MCI converters showed impaired performance in verbal memory and naming compared to MCI non-converters. Further, MCI converters showed decreased WM integrity in the frontal, parietal, occipital, as well as the temporal lobe prior to conversion to AD. Multiple regression analysis showed a positive correlation of gray matter atrophy with specific neuropsychological test results.
Our results suggest that additionally to morphological changes of GM a reduced integrity of WM indicates an imminent progression from MCI stage to AD. Therefore, we suggest that DWI is useful in the early diagnosis of AD.
Recently, many researchers have used graph theory to study the aberrant brain structures in Alzheimer's disease (AD) and have made great progress. However, the characteristics of the cortical network in Mild Cognitive Impairment (MCI) are still largely unexplored. In this study, the gray matter volumes obtained from magnetic resonance imaging (MRI) for all brain regions except the cerebellum were parcellated into 90 areas using the automated anatomical labeling (AAL) template to construct cortical networks for 98 normal controls (NCs), 113 MCIs and 91 ADs. The measurements of the network properties were calculated for each of the three groups respectively. We found that all three cortical networks exhibited small-world properties and those strong interhemispheric correlations existed between bilaterally homologous regions. Among the three cortical networks, we found the greatest clustering coefficient and the longest absolute path length in AD, which might indicate that the organization of the cortical network was the least optimal in AD. The small-world measures of the MCI network exhibited intermediate values. This finding is logical given that MCI is considered to be the transitional stage between normal aging and AD. Out of all the between-group differences in the clustering coefficient and absolute path length, only the differences between the AD and normal control groups were statistically significant. Compared with the normal controls, the MCI and AD groups retained their hub regions in the frontal lobe but showed a loss of hub regions in the temporal lobe. In addition, altered interregional correlations were detected in the parahippocampus gyrus, medial temporal lobe, cingulum, fusiform, medial frontal lobe, and orbital frontal gyrus in groups with MCI and AD. Similar to previous studies of functional connectivity, we also revealed increased interregional correlations within the local brain lobes and disrupted long distance interregional correlations in groups with MCI and AD.
Understanding the progression of Alzheimer's disease (AD) is essential. We investigated networks of cortical connectivity along a continuum from normal to AD. Mild Cognitive Impairment (MCI) has been implicated as transitional between normal aging and AD. By investigating the characteristics of cortical networks in these three stages (normal, MCI and AD), we found that all three networks exhibited small-world properties. These properties indicate efficient information transfer in the human brain. We also found that the small-world measures of the MCI network were intermediate to those of the normal controls and the patients with AD. This supports the opinion that MCI is a transitional stage between normal aging and AD. Additionally, we found altered interregional correlations in patients with MCI and AD, which may indicate that a compensatory system interacts with cerebral atrophy. The presence of compensatory mechanisms in patients with MCI and AD may enable them to use additional cognitive resources to function on a more nearly normal level. In future, we need to integrate the multi-level network features obtained with various functional and anatomical brain imaging technologies on different scales to understand the pathophysiological mechanism of MCI and AD. We propose brainnetome to represent such integration framework.
Neuroimaging measures have potential as surrogate markers of disease through identification of consistent features that occur prior to clinical symptoms. Despite numerous investigations, especially in relation to the transition to clinical impairment, the regional pattern of brain changes in clinically normal older adults has not been established. We predict that the regions that show early pathologic changes in association with Alzheimer disease will show accelerated volume loss in mild cognitive impairment (MCI) compared to normal aging.
Through the Baltimore Longitudinal Study of Aging, we prospectively evaluated 138 nondemented individuals (age 64–86 years) annually for up to 10 consecutive years. Eighteen participants were diagnosed with MCI over the course of the study. Mixed-effects regression was used to compare regional brain volume trajectories of clinically normal individuals to those with MCI based on a total of 1,017 observations.
All investigated volumes declined with normal aging (p < 0.05). Accelerated change with age was observed for ventricular CSF (vCSF), frontal gray matter, superior, middle, and medial frontal, and superior parietal regions (p ≤ 0.04). The MCI group showed accelerated changes compared to normal controls in whole brain volume, vCSF, temporal gray matter, and orbitofrontal and temporal association cortices, including the hippocampus (p ≤ 0.04).
Although age-related regional volume loss is apparent and widespread in nondemented individuals, mild cognitive impairment is associated with a unique pattern of structural vulnerability reflected in differential volume loss in specific regions. Early identification of patterns of abnormality is of fundamental importance for detecting disease onset and tracking progression.
= Alzheimer disease;
= Blessed Information Memory Concentration Scale;
= Baltimore Longitudinal Study of Aging;
= gray matter;
= intracranial volume;
= mild cognitive impairment;
= Mini-Mental State Examination;
= ventricular CSF;
= white matter.
Amnestic mild cognitive impairment (aMCI) is recognized as the prodromal phase of Alzheimer’s disease (AD). Evidence showed that patients with multiple-domain (MD) aMCI were at higher risk of converting to dementia and exhibited more severe gray matter atrophy than single-domain (SD) aMCI. The investigation of the microstructural abnormalities of white matter (WM) among different subtypes of aMCI and their relations with cognitive performances can help to understand the variations among aMCI subtypes and to construct potential imaging based biomarkers to monitor the progression of aMCI. Diffusion-weighted MRI data were acquired from 40 patients with aMCI (aMCI-SD: n = 19; aMCI-MD: n= 21) and 37 healthy controls (HC). Voxel-wise and atlas-based analyses of whole-brain WM were performed among three groups. The correlations between the altered diffusion metrics of the WM tracts and the neuropsychological scores in each subtype of aMCI were assessed. The aMCI-MD patients showed disrupted integrity in multiple WM tracts across the whole-brain when compared with HCs or with aMCI-SD. In contrast, only few WM regions with diffusion changes were found in aMCI-SD as compared to HCs and with less significance. For neuropsychological correlations, only aMCI-MD patients exhibited significant associations between disrupted WM connectivity (in the body of the corpus callosum and the right anterior internal capsules) and cognitive impairments (MMSE and Digit Symb-Coding scores), whereas no such correlations were found in aMCI-SD. These findings indicate that the degeneration extensively exists in WM tracts in aMCI-MD that precedes the development of AD, whereas underlying WM pathology in aMCI-SD is imperceptible. The results are consistent with the view that aMCI is not a uniform disease entity and presents heterogeneity in the clinical progression.
Amnestic mild cognitive impairment; diffusion tensor imaging; multiple-domain; single-domain; TBSS; white matter
Mild cognitive impairment (MCI), particularly the amnestic subtype (aMCI), is considered as a transitional stage between normal aging and a diagnosis of clinically probable Alzheimer's disease (AD). The aMCI construct is particularly useful as it provides an opportunity to assess a clinical stage which in most subjects represents prodromal AD. The aim of this study was to assess the progression of cerebral atrophy over multiple serial MRI during the period from aMCI to conversion to AD. Thirty-three subjects were selected that fulfilled clinical criteria for aMCI and had three serial MRI scans: the first scan approximately three years before conversion to AD, the second scan approximately one year before conversion, and the third scan at the time of conversion from aMCI to AD. A group of 33 healthy controls were age and gender-matched to the study cohort. Voxel-based morphometry (VBM) was used to assess patterns of grey matter atrophy in the aMCI subjects at each time-point compared to the control group. Customized templates and prior probability maps were used to avoid normalization and segmentation bias. The pattern of grey matter loss in the aMCI subject scans that were three years before conversion was focused primarily on the medial temporal lobes, including the amygdala, anterior hippocampus and entorhinal cortex, with some additional involvement of the fusiform gyrus, compared to controls. The extent and magnitude of the cerebral atrophy further progressed by the time the subjects were one year before conversion. At this point atrophy in the temporal lobes spread to include the middle temporal gyrus, and extended into more posterior regions of the temporal lobe to include the entire extent of the hippocampus. The parietal lobe also started to become involved. By the time the subjects had converted to a clinical diagnosis of AD the pattern of grey matter atrophy had become still more widespread with more severe involvement of the medial temporal lobes and the temporoparietal association cortices and, for the first time, substantial involvement of the frontal lobes. This pattern of progression fits well with the Braak and Braak neurofibrillary pathological staging scheme in AD. It suggests that the earliest changes occur in the anterior medial temporal lobe and fusiform gyrus, and that these changes occur at least three years before conversion to AD. These results also suggest that 3-dimensional patterns of grey matter atrophy may help to predict the time to conversion in subjects with aMCI.
Alzheimer's disease; mild cognitive impairment; longitudinal; magnetic resonance imaging; voxel-based morphometry
We investigated progression of atrophy in vivo, in Alzheimer’s disease (AD), and mild cognitive impairment (MCI). We included 64 patients with AD, 44 with MCI and 34 controls with serial MRI examinations (interval 1.8 ± 0.7 years). A nonlinear registration algorithm (fluid) was used to calculate atrophy rates in six regions: frontal, medial temporal, temporal (extramedial), parietal, occipital lobes and insular cortex. In MCI, the highest atrophy rate was observed in the medial temporal lobe, comparable with AD. AD patients showed even higher atrophy rates in the extramedial temporal lobe. Additionally, atrophy rates in frontal, parietal and occipital lobes were increased. Cox proportional hazard models showed that all regional atrophy rates predicted conversion to AD. Hazard ratios varied between 2.6 (95% confidence interval (CI) = 1.1–6.2) for occipital atrophy and 15.8 (95% CI = 3.5–71.8) for medial temporal lobe atrophy. In conclusion, atrophy spreads through the brain with development of AD. MCI is marked by temporal lobe atrophy. In AD, atrophy rate in the extramedial temporal lobe was even higher. Moreover, atrophy rates also accelerated in parietal, frontal, insular and occipital lobes. Finally, in nondemented elderly, medial temporal lobe atrophy was most predictive of progression to AD, demonstrating the involvement of this region in the development of AD.
Alzheimer’s disease; Magnetic resonance imaging; Atrophy; Image processing; Computer-assisted
Lack of clear understanding remains on the overlapping atrophy patterns of aging and early Alzheimer disease (AD) pathology in gray matter (GM) of the brain in vivo.
To evaluate the independent and overlapping patterns of GM atrophy in normal aging and AD.
A total of 169 cognitively normal subjects and 33 persons with probable AD enrolled in the longitudinal Cardiovascular Health Study–Cognition Study underwent 3-dimensional volumetric MRI scans. Controls remained cognitively normal for at least 5 years after their MRI scans and the probable AD subjects were relatively early in their clinical course with an average modified Mini-Mental State Examination score of 76/100. The scans were analyzed using voxel-based morphometry adjusting for total intracranial volume, gender, education, and race.
With older age, GM volume was lower in the sensorimotor and heteromodal association areas in frontal, temporal, occipital, and parietal lobes, as well as in the cerebellum (false discovery rate p = 0.05). Additional atrophy was observed in the posterior hippocampus, thalamus, and middle cingulate gyrus. By contrast, atrophy was seen in subjects with AD in the anterior hippocampal/parahippocampal regions and the precuneus. Normal aging and AD overlapped in the hippocampal body and the entorhinal cortex.
Brain atrophy with aging was observed in supratentorial and infratentorial areas, as well in primary motor, sensory, and heteromodal association regions. Age and Alzheimer disease exert independent gray matter atrophy patterns but these effects overlapped substantially in the hippocampus and entorhinal cortex.
= Modified Mini-Mental State Examination;
= Alzheimer disease;
= Cardiovascular Health Study–Cognition Study;
= gray matter;
= spoiled gradient recalled acquisition;
= total intracranial volume;
= voxel-based morphometry;
= white matter.
To investigate whether APOE ε4 carriers have higher hippocampal atrophy rates than non-carriers in Alzheimer's disease (AD), mild cognitive impairment (MCI) and controls, and if so, whether higher hippocampal atrophy rates are still observed after adjusting for concurrent whole-brain atrophy rates.
MRI scans from all available visits in ADNI (148 AD, 307 MCI, 167 controls) were used. MCI subjects were divided into “progressors” (MCI-P) if diagnosed with AD within 36 months or “stable” (MCI-S) if a diagnosis of MCI was maintained. A joint multi-level mixed-effect linear regression model was used to analyse the effect of ε4 carrier-status on hippocampal and whole-brain atrophy rates, adjusting for age, gender, MMSE and brain-to-intracranial volume ratio. The difference in hippocampal rates between ε4 carriers and non-carriers after adjustment for concurrent whole-brain atrophy rate was then calculated.
Mean adjusted hippocampal atrophy rates in ε4 carriers were significantly higher in AD, MCI-P and MCI-S (p≤0.011, all tests) compared with ε4 non-carriers. After adjustment for whole-brain atrophy rate, the difference in mean adjusted hippocampal atrophy rate between ε4 carriers and non-carriers was reduced but remained statistically significant in AD and MCI-P.
These results suggest that the APOE ε4 allele drives atrophy to the medial-temporal lobe region in AD.
Tensor-based morphometry can recover three-dimensional longitudinal brain changes over time by nonlinearly registering baseline to follow-up MRI scans of the same subject. Here, we compared the anatomical distribution of longitudinal brain structural changes, over 12 months, using a subset of the ADNI dataset consisting of 20 patients with Alzheimer’s disease (AD), 40 healthy elderly controls, and 40 individuals with mild cognitive impairment (MCI). Each individual longitudinal change map (Jacobian map) was created using an unbiased registration technique, and spatially normalized to a geometrically-centered average image based on healthy controls. Voxelwise statistical analyses revealed regional differences in atrophy rates, and these differences were correlated with clinical measures and biomarkers. Consistent with prior studies, we detected widespread cerebral atrophy in AD, and a more restricted atrophic pattern in MCI. In MCI, temporal lobe atrophy rates were correlated with changes in mini-mental state exam (MMSE) scores, clinical dementia rating (CDR), and logical/verbal learning memory scores. In AD, temporal atrophy rates were correlated with several biomarker indices, including a higher CSF level of p-tau protein, and a greater CSF tau/beta amyloid 1-42 (ABeta42) ratio. Temporal lobe atrophy was significantly faster in MCI subjects who converted to AD than in non-converters. Serial MRI scans can therefore be analyzed with nonlinear image registration to relate ongoing neurodegeneration to a variety of pathological biomarkers, cognitive changes, and conversion from MCI to AD, tracking disease progression in 3-dimensional detail.