Atormac
Neurology India
menu-bar5 Open access journal indexed with Index Medicus
  Users online: 3744  
 Home | Login 
About Editorial board Articlesmenu-bullet NSI Publicationsmenu-bullet Search Instructions Online Submission Subscribe Videos Etcetera Contact
  Navigate Here 
 Search
 
  
 Resource Links
  »  Similar in PUBMED
 »  Search Pubmed for
 »  Search in Google Scholar for
 »Related articles
  »  Article in PDF (1,107 KB)
  »  Citation Manager
  »  Access Statistics
  »  Reader Comments
  »  Email Alert *
  »  Add to My List *
* Registration required (free)  

 
  In this Article
 »  Abstract
 » Patients and Methods
 » Results
 » Discussion
 » Conclusion
 »  References
 »  Article Figures
 »  Article Tables

 Article Access Statistics
    Viewed2731    
    Printed47    
    Emailed0    
    PDF Downloaded47    
    Comments [Add]    

Recommend this journal

 


 
Table of Contents    
ORIGINAL ARTICLE
Year : 2018  |  Volume : 66  |  Issue : 2  |  Page : 370-376

Structural correlates of mild cognitive impairment: A clinicovolumetric study


1 Cognition and Behavioural Neurology Section, Department of Neurology, Sree ChitraTirunal Institute for Medical Sciences and Technology, Trivandrum, Kerala, India
2 Department of Imaging Sciences and Interventional Radiology, Biostatistics Sree ChitraTirunal Institute for Medical Sciences and Technology, Trivandrum, Kerala, India
3 Biostatistics Sree ChitraTirunal Institute for Medical Sciences and Technology, Trivandrum, Kerala, India

Date of Web Publication15-Mar-2018

Correspondence Address:
Dr. Ramshekhar Menon
Department of Neurology, Cognition and Behavioural Neurology Section, Sree Chitra Tirunal Institute for Medical Sciences and Technology, Trivandrum - 695 011, Kerala
India
Login to access the Email id

Source of Support: None, Conflict of Interest: None


DOI: 10.4103/0028-3886.227298

Rights and Permissions

 » Abstract 


Context: Annually 10–12% of patients with mild cognitive impairment (MCI) are likely to progress to Alzheimer's Disease (AD). The morphometric profile in stable non-converters has not been adequately characterized.
Aims: To determine the structural differences between amnestic MCI and early AD using volumetric magnetic resonance imaging (MRI) and its correlation with neuropsychological test performances.
Settings and Design: This was a hospital-based case-control study.
Materials and Methods: Twenty-four patients classified as having “non-progressor” MCI, 13 as having an early AD, and 25 controls, and assessed using neuropsychological evaluation, and three-dimensional T1-weighted 1.5T magnetic resonance maging (MRI) were included in the study. We used both voxel-based morphometry and automated regional volumetry to assess the topographical patterns of volume loss.
Statistical Analysis Used: Post-hoc analysis of variance was done for comparison between means, and partial correlation analysis was done for correlating volumetric and cognitive measures.
Results: Consistently, significant atrophy of the superior temporal gyrus, left hippocampus, and mesial frontoparietal regions were identified in patients with MCI in comparison to controls. Increased atrophy in the limbic regions, temporal neocortex, and precuneus was identified in patients with early AD in comparison to patients with MCI. While differences in retention and recall scores between the groups were independent of age and volumetric variables, significant correlations were observed between the learning and recall scores and the volume of hippocampus in patients with MCI as well as temporal neocortex in patients with AD. Atrophy of the superior temporal gyrus and mesial neocortical regions represents the structural correlate of amnestic MCI parallel to the development of hippocampal atrophy.
Conclusions: Identification of the pattern of volumetric abnormalities in patients with amnestic MCI in addition to atrophy of the medial temporal lobes necessitates a close follow up to continuously assess these patients for their progression to early AD.


Keywords: Alzheimer's disease, amnestic mild cognitive impairment, automated regional volumetry, voxel-based morphometry
Key Messages: This is the first clinicovolumetric study on mild cognitive impairment from India. Realistic differences exist between apparently stable mild cognitive impairment, early Alzheimer′s disease, and cognitively normal healthy controls, irrespective of the methodology used in voxel-based morphometry. Learning and recall measures notably correlate with the hippocampal volume in patients with mild cognitive impairment, as well as with the temporal neocortex volume in patients with AD.


How to cite this article:
Sheelakumari R, Kesavadas C, Lekha V S, Justus S, Sarma P S, Menon R. Structural correlates of mild cognitive impairment: A clinicovolumetric study. Neurol India 2018;66:370-6

How to cite this URL:
Sheelakumari R, Kesavadas C, Lekha V S, Justus S, Sarma P S, Menon R. Structural correlates of mild cognitive impairment: A clinicovolumetric study. Neurol India [serial online] 2018 [cited 2019 Nov 17];66:370-6. Available from: http://www.neurologyindia.com/text.asp?2018/66/2/370/227298




Mild cognitive impairment (MCI) is considered to be a transitional stage between normal aging and Alzheimer's Disease (AD),[1] and its rate of progression varies between individuals. The longitudinal risk of developing AD in amnestic MCI (a-MCI) can be estimated by measures of memory performance and subjective level of cognitive functioning.[2],[3],[4] Neuropsychology tests such as vernacular adaptations of Addenbrooke's Cognitive Examination (ACE) and Rey Auditory Verbal Learning Test (RAVLT)[5],[6] have been found to be effective screening and definitive measures of cognitive impairment in a-MCI. Learning and retention measures, as assessed in RAVLT, have been shown to be among the most comprehensive clinical predictors of conversion from a-MCI to AD.[6] While it is believed that roughly 12% of patients with MCI annually run the risk of conversion to AD, with approximately 80% converting to dementia by 6 years, other studies debate this conversion rate.[7] It is also well-known that a large subset of patients remains stable over the years or may clinically revert to normal cognitive status.[8]

The most well-known approaches employed in the analysis of gray matter (GM) loss in MCI and AD is voxel-based morphometry (VBM) and automated regional volumetry (ARV).[9] Not surprisingly, prominent studies till date have focused on MTL and amygdala volumes.[10] Little is known regarding the relationship between GM volume in other cortical regions and performance on the neuropsychological tests of patients with MCI or AD. Therefore, the aim of the present cohort study was to quantify the structural changes in cognitively stable a-MCI and AD patients compared to individuals with no cognitive impairment (NCI) in South India, employing quantitative volumetric magnetic resonance imaging (MRI) analysis tools such as ARV and VBM. The study also aimed to correlate the neuropsychological test performances using screening tests and definitive tools for memory impairment with morphometric variables in patients with MCI in comparison with a diseased group of patients suffering from an early AD.


 » Patients and Methods Top


Case selection

Sixty-two participants (NCI: 25, MCI: 24, AD: 13) were prospectively recruited from Memory and Behavioral Neurology clinic at a reputed centre in the city of Trivandrum, located in the southern state of Kerala, India. Early AD patients were selected using the standard NINCDS–ADRDA (National Institute of Neurological and Communicative Disorders and Stroke and the Alzheimer's Disease and Related Disorders Association) diagnostic criteria with a clinical dementia rating (CDR) score of <2.[11] Patients with a-MCI, aged between 55–80 years, diagnosed as per the modified Petersen's criteria [1] with a CDR of ≤0.5, who were still functioning independently in the community, and having a normal general cognition (i.e., MMSE >24) with normal performance on tests of other cognitive domains, viz., language, executive functions, visuospatial functions, praxis, and perception were included. The minimum duration of follow up of MCI patients required for inclusion into the study was 1.5 years. It was ensured prior to their inclusion that none of them had neuropsychological or CDR evidence of progression to dementia. The objective evidence of memory impairment required that an individual scored less than mean −1.5 standard deviation (SD) from the norm on at least two tests in the memory domain. This method has been validated previously.[6] The inclusion criteria for the cognitively normal healthy controls included an age range of 55–80 years, with formal education of more than 8 years, with no history of subjective memory complaints, and no major neurological, psychiatric, or medical comorbidities. All participants underwent a detailed, clinical, neuropsychological, and radiological evaluation after providing a written informed consent. The study was approved by the Institutional Ethics Committee.

Cognitive assessments

The participants underwent cognitive screening by the vernacular adaptation of ACE, which has been validated previously.[5] This battery has a measure of global cognition (mini-mental state examination, MMSE), and also includes tests for memory (immediate and delayed recall of a seven-item address list), verbal fluency (initial letter P and categories of animals), confrontation naming (ten items), and constructional praxis (copying two line-drawings). It also assesses executive functions and constructional ability (clock-drawing), remote memory, and language. Registration/learning is scored on a 24-point scale which has 3 points for registration of 3 words and 21 points for 3-trial learning of an address. The recall score was drawn from a 10-point scoring which included a 5-min recall of the three items presented previously and a 7-point recall of the address. Participants were required to have a depression score on the Hospital Anxiety Depression Scale (HADS) of less than 7. The measures of learning and recall studied in this cohort were the cumulative learning trials and delayed recall scores in the vernacular adaptation of Rey Auditory Verbal Learning Test (RAVLT) and memory subsets of ACE. Multidomain involvement in MCI was excluded as diagnosis of a-MCI necessitated normal performance on the language, executive, and visuospatial domains. A semantic battery employing confrontation naming for language; trail making A and B, and Wisconsin card sorting test (WCST) for executive functions; and, visual objective space perception battery, and judgement of line orientation for visuospatial functions were the tests used to exclude the presence of patients with either a multidomain involvement, or having the presence of non-a-MCI.

Image acquisition

Participants were scanned with a 1.5T (Seimens Magnetom-Avanto SQ engine, Erlangen, Germany) MRI scanner in the Department of Radiology. The three-dimensional (3D) T1 weighted anatomical scans were acquired using a flash-spoiled gradient echo sequence with 1mm slice thickness, 176 sagittal slices, 1 × 1 × 1mm voxel size, 11 ms repetition time, 4.95 ms echotime, 15° flip angle, matrix size of 256 × 256 with a total scan time of 6 min 21 s.

Image processing

Whole brain analysis

VBM8 toolbox in Statistical Parametric Mapping (SPM8- Wellcome Department of Imaging Neuroscience, London) was applied to investigate the cortical GM changes across the entire brain without any prior knowledge of the region of interest (ROI). All the images were oriented in the anterior commissure-posterior commissure (AC-PC) line. The images were segmented into GM, white matter (WM), and cerebrospinal fluid (CSF), and spatially normalized into the Montreal Neurological Institute (MNI) space using VBM8 DARTEL procedure with custom settings. The segmentation was followed by modulation for preserving the volume of a particular tissue in a fixed voxel, and volumes of GM, WM, CSF, and total intracranial volume (TIV) were calculated. The resulting images were smoothed with an isotropic Gaussian kernel of 8mm full width half maximum (FWHM).

Group comparison among MCI, AD, and controls were performed by one-way analysis of variance (ANOVA) within the Statistical Parametric Mapping 8 (SPM8) general linear model. Group comparisons were tested with a corrected threshold of P < 0.001, which determines the clusters with significant differences in GM concentration. Three separate contrasts (NCI vs MCI, NCI vs AD, and MCI vs AD) with age, sex, and total intracranial volume (TIV) as covariates were used to compare the GM density between participants. The significant atrophic regions were overlaid on T1-weighted standard brain images, allowing the localization of areas of significant GM loss. The atrophic regions are reported in Montreal Neurological Institute (MNI) coordinates with the help of xjview toolbox (http://www.alivelearn.net/xjview/).

Volumes of cortical gray matter structures using automated regional volumetry

The segmentation algorithm in SPM8 and Automated Anatomic Labelling (AAL),[12] (http://www.cyceron.fr/web/aal) template was used to estimate the bilateral volumes of eight anterior and medial temporal structures, namely, inferior temporal gyrus, superior temporal gyrus, entorhinal cortex, middle temporal pole, superior temporal pole, parahippocampus, hippocampus, and amygdala, one deep gray matter structure (thalamus), and two parietal structures (precuneus and posterior cingulate). After segmentation, the volume of each region was obtained by writing scripts in MATLAB window.

Statistical analysis

Demographic data, neuropsychological measures, and cortical GM volumes between study groups were analyzed using the Statistical Package for the Social Sciences Statistics for Windows version 21 (SPSS, IBM. Armonk, NY, USA). The demographic and cognitive variables were compared across the groups, NCI, MCI, and AD, using univariate analysis of variance (ANOVA). Bonferroni post-hoc procedure with age correction was applied to compare means of the independent variables of volume with diagnosis. Partial correlation was used to assess the relationship between independent volumes and neuropsychological test measures in each study group. In all comparisons, the level of statistical significance was set at P < 0.05.


 » Results Top


Demographics, cognitive function, and memory

Demographic and neuropsychometric measures between the three groups are depicted in [Table 1]. The mean duration of subjective memory complaints in the MCI group was 5.8 ± 3.7 years and the mean disease duration in the AD group was 4.2 ± 1.5 years. The mean duration of follow-up since the time of diagnosis to the time of inclusion into the study was 3.5 ± 1.9 years in the MCI group, and 2.2 ± 0.7 years in the AD group. After adjusting for age, patients with both MCI and AD were significantly impaired on ACE recall, ACE total, RAVLT cumulative learning, and delayed recall compared to individuals with NCI (P< 0.001). Similarly, the AD group performed poorly in comparison to the MCI group on all components of cognitive and memory scores [ACE recall, ACE total, RAVLT recall (P< 0.001) and RAVLT learning scores (P = 0.013)]. None of the MCI patients had progressed to early AD during the minimum 1.5-year period of follow-up at the time of inclusion into the study.
Table 1: Demographics and Cognitive test scores each in the groups [mean±SD and pairwise post-hoc Bonferroni results]. Test scores represent raw scores

Click here to view


Whole brain findings

The participant groups were contrasted to reveal the patterns of GM atrophy on VBM group analysis. Compared to controls, MCI patients revealed predominant atrophy in bilateral superior temporal gyri. Significant atrophic patterns were also observed in the hippocampus, inferior temporal gyrus, middle frontal gyrus, cuneus and lingual gyrus in the left hemisphere, the middle occipital gyrus and cingulate gyrus in the right hemisphere [Figure 1] and [Supplementary Table 1]. For AD patients, most significant GM loss was detected in the left parahippocampal gyrus. In addition, AD patients had significant GM loss in bilateral hippocampi, bilateral precunei, bilateral fusiform gyri, bilateral middle temporal gyri, bilateral anterior cingulate regions, right inferior temporal gyri, right superior temporal pole, right posterior cingulate, right rolandic operculum, right thalamus, right inferior parietal lobule, right middle occipital gyri, left middle frontal, and orbitofrontal gyri [Figure 2] and [Supplementary Table 2]. Moreover, a direct comparison of the patient groups revealed greater cerebral atrophy in AD patients [Figure 3] and [Supplementary Table 3] in bilateral parahippocampi, hippocampi, amygdalae, fusiform gyri, superior and middle temporal poles, inferior temporal gyri, and medial orbitofrontal regions along with atrophy in the right precuneus and left angular regions.
Figure 1: VBM comparison between patients with MCI and normal healthy volunteers. Projection of SPM T-map on the customized MRI template showing the atrophic patterns with an uncorrected threshold of P < 0.001

Click here to view
Figure 2: VBM comparison between patients with AD and normal healthy volunteers. Projection of SPM T-map on the customized MRI template showing the atrophic patterns with an uncorrected threshold of P < 0.001

Click here to view
Figure 3: VBM comparison between patients with AD and MCI patients. Projection of SPM T-map on the customized MRI template showing the atrophic patterns with an uncorrected threshold of P < 0.001

Click here to view



Gray matter volumes using automated regional volumetry

The regional volumes of GM structures estimated by using ARV are summarized in [Table 2]. Post-hoc Bonferroni procedure showed significant volume differences for the left hippocampus, right precuneus, and bilateral superior temporal gyri in the MCI patients compared to individuals with NCI. In patients with AD, bilateral hippocampi, precunei, superior temporal gyri, parahippocampi, right amygdala, and right superior temporal pole revealed significant GM volume loss compared to controls. Only the total GM and left hippocampal volume discriminated the patient groups, with lower volumes detectable in AD patients.
Table 2: Anatomical structures with significant group differences of volume in MCI and AD patients compared with normal healthy non-demented controls. Each group shows mean (SD) values in cu.mm, and pairwise posthoc Bonferroni correction results with age as covariate

Click here to view


Correlation between neuropsychology parameters and automated lobar volumetry

Partial correlation analysis with age as the controlling variable showed that RAVLT delayed recall positively correlated with reduced volumes of left (rp= 0.42, P < 0.04) and right (rp= 0.38, P < 0.05) hippocampi in MCI patients. A similar observation was noted between RAVLT total learning and the hippocampal volume (rp= 0.42, P < 0.04) in the left hemisphere; whereas, in AD, a significant correlation was observed between RAVLT total learning and the right hemisphere volume of the middle temporal pole (rp= 0.66, P < 0.01) and superior temporal pole (rp= 0.84, P < 0.001). In addition, ACE total score significantly correlated with volume of the right superior temporal pole (rp= 0.73, P < 0.006).


 » Discussion Top


Our study was designed to quantify the GM differences in stable “non-progressor” a-MCI patients compared to early AD patients and NCI individuals using VBM group analysis and ARV. Further, the study compared the cognitive measures that were deemed clinically relevant for tracking the progression of MCI to AD. Previous studies have demonstrated variable results using these two methods, predominantly favouring VBM over ARV for assessing GM volume differences between the groups.[13],[14] The features unique to a-MCI patients who are clinically stable are crucial to determining structural measures of stability in what is usually considered to be a pre-AD status. To the best of our knowledge, this is the first study in the Indian population that utilized automated software tools to discriminate MCI and AD population from individuals with NCI, as well as to correlate the GM loss in specific anatomical regions with cognitive measures. A recent Indian study addressed the relationship between regional morphometric brain changes and cognitive deficits in AD patients in relation to NCI.[15]

As VBM analysis is a practical tool for whole-brain group comparisons, identifying regions which can be subsequently analyzed using ARV, we identified certain regions of interest (ROIs) in each comparative model. Considering the MCI patients, GM volume loss was detected in the superior temporal gyrus and left hippocampus, and variably over the mesial brain regions (cuneus, precuneus, and cingulate cortex), in comparison to individuals with NCI. The observation of hippocampal atrophy is in line with previous reports [16],[17],[18] and is established as a marker of future progression in MCI. Atrophy identified in the mesial cortical regions, especially the precuneus, as identified on ARV, is a unique finding in this study and represents an avenue for future research considering the role of precuneus in episodic memory retrieval and visuospatial awareness, and from a network perspective, in the default mode network.[19] This highlights the added functional significance of the posteromedial regions of the cortex in MCI in addition to atrophy of the temporal lobe. The inferior frontal gyrus atrophy identified in the MCI group is in line with the findings of Whitwell et al.,[20] as an indicator of faster disease progression. Only a longitudinal follow-up would indicate the significance of these results in our stable MCI group.

In the AD group, as in other studies, a significant GM atrophy was noted by both the techniques in the medial temporal (MTL) structures, i.e., the hippocampus, amygdala, parahippocampal gyrus,[21],[22],[23] and precuneus.[24] Similar to other studies, VBM identified atrophy of the anterior cingulate,[25],[26] the fusiform gyrus, and the frontal [25],[27] regions in AD compared to controls. Interestingly, in contrast to the literature,[28],[29] our study failed to reveal significant impairment of the posterior cingulate region on group analysis. Furthermore, our study detected greater atrophy of the hippocampus in patients with AD compared to those with MCI, in addition to the medial and neocortical temporal lobe, anterior cingulate region, insula, and precuneus identified on VBM comparison between patients with AD and MCI. As has been shown in another study,[7] atrophy in these regions, if observed in MCI, may be indicative of transition to early AD.

As expected, patients with MCI and AD significantly differed from individuals with NCI on cognitive measures. The observations were retained even after controlling for age and regional volumes. The direct comparison between patient groups revealed significant differences in ACE recall, ACE total, and RAVLT total learning. These results would imply the existence of genuine clinical and functional differences between the 3 groups, and the independent relevance of these neuropsychological measures as predictors of cognitive decline in the elderly.[30] Correlation between the cognitive scores and regional volume loss was very specific in the MCI and AD participants. Both RAVLT total learning and recall after 20 minutes significantly correlated with hippocampal atrophy in MCI participants; whereas, in AD, the decline in cognitive measures such as RAVLT total and ACE total significantly correlated with the volume of the superior temporal gyrus. These results indicate an association between cognitive functioning and regional morphometric brain changes, a probable epiphenomenon of pathological changes in MCI and AD considering the early deposition of amyloid plaques in neocortical areas preceding the limbic areas.[31],[32]

Even though our study came up with the above-mentioned promising findings, it had some limitations. In the technique of ARV, we only selected certain regions in the temporal, parietal, and limbic regions; however, we excluded the frontal and occipital cortex. Although we included only stable MCI patients who were non-progressors during the duration of follow-up, a follow-up of greater than 5 years would have added further strength to the current study. However, the findings represent an avenue to predict conversion or stability in patients with atrophic MCI using population-based studies and to earmark patients at risk of progression.


 » Conclusion Top


In summary, the present study indicates that genuine neuropsychological differences exist between patients with MCI and AD, and control subjects. These differences are independent of age as well as the total GM volume and the regional cortical volumes, thereby highlighting functional differences that occur independent of structural differences between the groups. The volumetric findings of the study highlight the characteristics of stable MCI patients, with demonstration of atrophy in the temporal neocortex, hippocampus, and mesial neocortical regions as a key finding. In addition, atrophy in these regions along with frontoinsular regions could predict MCI due to AD. As we observed more findings in VBM, it is a more useful method for group comparisons. However, future cross-sectional and longitudinal studies in larger samples with comprehensive neuropsychological evaluation are needed to confirm these findings.

Financial support and sponsorship

This work was supported in part by grants from Kerala State Council for Science, Technology & Environment (19SRSHS/2011) and Department of Science and technology (SR/CSI/90/2012(G)).

Conflicts of interest

There are no conflicts of interest.



 
 » References Top

1.
Petersen RC, Doody R, Kurz A, Mohs RC, Morris JC, Rabins PV, et al. Current concepts in mild cognitive impairment. Arch Neurol 2001;58:1985-92.  Back to cited text no. 1
    
2.
Bennett DA, Wilson RS, Schneider JA, Evans DA, Mendes de Leon CF, Arnold SE, et al. Education modifies the relation of AD pathology to level of cognitive function in older persons. Neurology 2003; 60:1909-15.  Back to cited text no. 2
    
3.
Jack CR, Shiung MM, Gunter JL, O'Brien PC, Weigand SD, Knopman DS, et al. Comparison of different MRI brain atrophy rate measures with clinical disease progression in AD. Neurology 2004;62:591-600.  Back to cited text no. 3
    
4.
Petersen RC, Smith GE, Waring SC, Ivnik RJ, Tangalos EG, Kokmen E. Mild cognitive impairment: Clinical characterization and outcome. Arch Neurol 1999;56:303-8.  Back to cited text no. 4
    
5.
Mathuranath PS, Hodges JR, Mathew R, Cherian PJ, George A, Bak TH. Adaptation of the ACE for a Malayalam speaking population in southern India. Int J Geriatr Psychiatry 2004;19:1188-94.  Back to cited text no. 5
    
6.
Menon R, Lekha V, Justus S, Sarma Ps, Mathuranath P. A pilot study on utility of Malayalam version of Addenbrooke's Cognitive Examination in detection of amnestic mild cognitive impairment: A critical insight into utility of learning and recall measures. Ann Indian Acad Neurol 2014;17:420.  Back to cited text no. 6
    
7.
Chang Y-L, Bondi MW, Fennema-Notestine C, McEvoy LK, Hagler DJ, Jacobson MW, et al. Brain substrates of learning and retention in mild cognitive impairment diagnosis and progression to Alzheimer's disease. Neuropsychologia 2010;48:1237-47.  Back to cited text no. 7
    
8.
Tierney MC, Szalai JP, Snow WG, Fisher RH, Tsuda T, Chi H, et al. A prospective study of the clinical utility of ApoE genotype in the prediction of outcome in patients with memory impairment. Neurology1996;46:149-54.  Back to cited text no. 8
    
9.
Bowen J, Teri L, Kukull W, McCormick W, McCurry SM, Larson EB. Progression to dementia in patients with isolated memory loss. Lancet 1997;349:763-5.  Back to cited text no. 9
    
10.
Kantarci K, Weigand SD, Przybelski SA, Preboske GM, Pankratz VS, Vemuri P, et al. MRI and MRS predictors of mild cognitive impairment in a population-based sample. Neurology 2013;81:126-33.  Back to cited text no. 10
    
11.
O'Bryant SE, Waring SC, Cullum CM, Hall J, Lacritz L, Massman PJ, et al. Staging dementia using clinical dementia rating scale sum of boxes scores. Arch Neurol 2008;65:1091-5.  Back to cited text no. 11
    
12.
Tzourio-Mazoyer N, Landeau B, Papathanassiou D, Crivello F, Etard O, Delcroix N, et al. Automated anatomical labeling of activations in SPM using a macroscopic anatomical parcellation of the MNI MRI single-subject brain. NeuroImage 2002;15:273-89.  Back to cited text no. 12
    
13.
Cantor JM, Kabani N, Christensen BK, Zipursky RB, Barbaree HE, Dickey R, et al. Cerebral white matter deficiencies in pedophilic men. J Psychiatr Res 2008;42:167-83.  Back to cited text no. 13
    
14.
Voormolen EHJ, Wei C, Chow EWC, Bassett AS, Mikulis DJ, Crawley AP. Voxel-based morphometry and automated lobar volumetry: The trade-off between spatial scale and statistical correction. NeuroImage 2010;49:587-96.  Back to cited text no. 14
    
15.
Bagepally BS, John JP, Varghese M, Halahalli HN, Kota L, Sivakumar PT, et al. Relationship of clinical and cognitive variables with brain morphometric abnormalities in Alzheimer's disease: A voxel based morphometric study using 3-Tesla MRI. Aging Dis 2013;4:235-43.  Back to cited text no. 15
    
16.
Elshafey R, Hassanien O, Khalil M, Allah MR, Saad S, Baghdadi M, et al. Hippocampus, caudate nucleus and entorhinal cortex volumetric MRI measurements in discrimination between Alzheimer's disease, mild cognitive impairment, and normal aging. Egypt J RadiolNucl Med 2014;45:511-8.  Back to cited text no. 16
    
17.
Sánchez-Benavides G, Gómez-Ansón B, Sainz A, Vives Y, Delfino M, Peña-Casanova J. Manual validation of FreeSurfer's automated hippocampal segmentation in normal aging, mild cognitive impairment, and Alzheimer disease subjects. Psychiatry Res 2010;181:219-25.  Back to cited text no. 17
    
18.
Jhoo JH, Lee DY, Choo IH, Seo EH, Oh JS, Lee JS, et al. Discrimination of normal aging, MCI and AD with multimodal imaging measures on the medial temporal lobe. Psychiatry Res 2010;183:237-43.  Back to cited text no. 18
    
19.
Cavanna AE, Trimble MR. The precuneus: A review of its functional anatomy and behavioural correlates. Brain 2006;129:564-83.  Back to cited text no. 19
    
20.
Whitwell JL, Shiung MM, Przybelski SA, Weigand SD, Knopman DS, Boeve BF, et al. MRI patterns of atrophy associated with progression to AD in amnestic mild cognitive impairment. Neurology 2008;70:512-20.  Back to cited text no. 20
    
21.
Xie S, Xiao JX, Gong GL, Zang YF, Wang YH, Wu HK, et al. Voxel-based detection of white matter abnormalities in mild Alzheimer disease. Neurology 2006;66:1845-9.  Back to cited text no. 21
    
22.
Whitwell JL, Weigand SD, Shiung MM, Boeve BF, Ferman TJ, Smith GE, et al. Focal atrophy in dementia with Lewy bodies on MRI: A distinct pattern from Alzheimer's disease. Brain J Neurol 2007;130:708-19.  Back to cited text no. 22
    
23.
Josephs KA, Whitwell JL, Duffy JR, Vanvoorst WA, Strand EA, Hu WT, et al. Progressive aphasia secondary to Alzheimer disease vs FTLD pathology. Neurology 2008;70:25-34.  Back to cited text no. 23
    
24.
Shiino A, Watanabe T, Maeda K, Kotani E, Akiguchi I, Matsuda M. Four subgroups of Alzheimer's disease based on patterns of atrophy using VBM and a unique pattern for early onset disease. NeuroImage 2006;33:17-26.  Back to cited text no. 24
    
25.
Kawachi T, Ishii K, Sakamoto S, Sasaki M, Mori T, Yamashita F, et al. Comparison of the diagnostic performance of FDG-PET and VBM-MRI in very mild Alzheimer's disease. Eur J Nucl Med Mol Imaging 2006;33:801-9.  Back to cited text no. 25
    
26.
Kinkingnéhun S, Sarazin M, Lehéricy S, Guichart-Gomez E, Hergueta T, Dubois B. VBM anticipates the rate of progression of Alzheimer disease: A 3-year longitudinal study. Neurology 2008;70:2201-11.  Back to cited text no. 26
    
27.
Di Paola M, Macaluso E, Carlesimo GA, Tomaiuolo F, Worsley KJ, Fadda L, et al. Episodic memory impairment in patients with Alzheimer's disease is correlated with entorhinal cortex atrophy. A voxel-based morphometry study. J Neurol 2007;254:774-81.  Back to cited text no. 27
    
28.
Minoshima S, Giordani B, Berent S, Frey KA, Foster NL, Kuhl DE. Metabolic reduction in the posterior cingulate cortex in very early Alzheimer's disease. Ann Neurol 1997;42:85-94.  Back to cited text no. 28
    
29.
Vogt BA, Van Hoesen GW, Vogt LJ. Laminar distribution of neuron degeneration in posterior cingulate cortex in Alzheimer's disease. Acta Neuropathol 1990;80:581-9.  Back to cited text no. 29
    
30.
Mathuranath P, Sharma G, Alexander A, Ranjith N. Qualitative aspects of learning, recall, and recognition in dementia. Ann Indian Acad Neurol 2010;13:117.  Back to cited text no. 30
[PUBMED]  [Full text]  
31.
Sirály E, Szabó Á, Szita B, Kovács V, Fodor Z, Marosi C, et al. Monitoring the early signs of cognitive decline in elderly by computer games: An MRI study. PLoSOne 2015;10:e0117918.  Back to cited text no. 31
    
32.
Braak H, Braak E. Neuropathological staging of Alzheimer-related changes. Acta Neuropathol 1991;82:239-59.  Back to cited text no. 32
    


    Figures

  [Figure 1], [Figure 2], [Figure 3]
 
 
    Tables

  [Table 1], [Table 2]



 

Top
Print this article  Email this article
   
Online since 20th March '04
Published by Wolters Kluwer - Medknow