The Sub-Classification of Amnestic Mild Cognitive Impairment Using MRI-Based Cortical Thickness Measures

Raamana, Pradeep Reddy; Wang, Wen; Kochan, Nicole A.; Brodaty, Henry; Sachdev, Perminder S.; Wang, Lei; Beg, Mirza Faisal

doi:10.3389/fneur.2014.00076

Cited by 13 publications

(14 citation statements)

References 35 publications

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“…In addition to bilateral MTL atrophy, multidomain amnestic MCI typically involves widespread thinning within parietal, temporal, and frontal regions. 17,18,20,21 However, the pattern of thinning in the dysexecutive/ mixed MCI group was less consistent with previous studies of the conventional nonamnestic MCI subtype, in which heterogeneous patterns of gray matter loss and less MTL focus have been noted. 17,18 The current study did not include a purely dysexecutive group, as all subtypes demonstrated memory impairment, limiting our ability to examine nonamnestic forms of MCI.…”

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confidence: 32%

Heterogeneous cortical atrophy patterns in MCI not captured by conventional diagnostic criteria

et al. 2016

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Objective: We investigated differences in regional cortical thickness between previously identified empirically derived mild cognitive impairment (MCI) subtypes (amnestic MCI, dysnomic MCI, dysexecutive/mixed MCI, and cluster-derived normal) in order to determine whether these cognitive subtypes would show different patterns of cortical atrophy.Methods: Participants were 485 individuals diagnosed with MCI and 178 cognitively normal individuals from the Alzheimer's Disease Neuroimaging Initiative. Cortical thickness estimates were computed for 32 regions of interest per hemisphere. Statistical group maps compared each MCI subtype to cognitively normal participants and to one another. Results:The pattern of cortical thinning observed in each MCI subtype corresponded to their cognitive profile. No differences in cortical thickness were found between the cluster-derived normal MCI subtype and the cognitively normal group. Direct comparison between MCI subtypes suggested that the cortical thickness patterns reflect increasing disease severity. Conclusions:There is an ordered pattern of cortical atrophy among patients with MCI that coincides with their profiles of increasing cognitive dysfunction. This heterogeneity is not captured when patients are grouped by conventional diagnostic criteria. Results in the cluster-derived normal group further support the premise that the conventional MCI diagnostic criteria are highly susceptible to false-positive diagnostic errors. Findings suggest a need to (1) improve the diagnostic criteria by reducing reliance on conventional screening measures, rating scales, and a single memory measure in order to avoid false-positive errors; and (2) divide MCI samples into meaningful subgroups based on cognitive and biomarkers profiles-a method that may provide better staging of MCI and inform prognosis. Mild cognitive impairment (MCI), a prodromal state between normal aging and dementia, 1 is typically divided into amnestic or nonamnestic subtypes, with single-domain or multi-domain distinctions.2,3 A limitation of this conventional classification system is that it combines patients with very different cognitive profiles. Previous research has identified considerable heterogeneity beyond the amnestic/nonamnestic distinction with respect to neuropsychological performance in MCI samples. [4][5][6][7] In a recent study, 7 cluster analysis was performed on 825 individuals with MCI from the Alzheimer's Disease Neuroimaging Initiative (ADNI). Although nearly all participants (99.8%) were originally classified simply as amnestic MCI by conventional criteria, 2,8 results showed 4 cognitive phenotypes. This included 3 impaired subtypes: amnestic MCI (34.9%), dysnomic MCI (18.5%), and dysexecutive/mixed MCI (12.5%). A large fourth cluster

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confidence: 32%

Heterogeneous cortical atrophy patterns in MCI not captured by conventional diagnostic criteria

et al. 2016

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“…Various types of cortical morphological features, such as cortical thickness, GM volume, metric distortion, and GM densities, have shown promising capacities for the classification between aMCI and controls [43][44][45]. Our study revealed the relatively high classification accuracy by using each of parameters extracted from the whole brain (GM volume and density), which was in line with previous studies.…”

Section: The Reliability Of Combined Visual Rating Scalessupporting

confidence: 90%

Combining visual rating scales of medial temporal lobe atrophy and posterior atrophy to identify amnestic mild cognitive impairment from cognitively normal older adults: evidence based on two datasets

Sheng

Sun

Wang

et al. 2019

Preprint

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Background: Structural magnetic resonance imaging (MRI)-based visual rating scales are considered as the primary method for rapid and cost-effective evaluation of regional brain atrophy in patients with Alzheimer’s disease (AD) in routine clinical practice. Both medial temporal lobe atrophy (MTA) and posterior atrophy (PA) visual rating scales have been reported to be useful in AD diagnosis. However, very few existing studies have investigated the efficacy of combined MTA and PA for identification of amnestic mild cognitive impairment (aMCI) from cognitively normal elderly.Methods: This study included T1-weighted MRI images acquired inXuanwu Hospital of Capital Medical University, Beijing, China from two different cohorts. In the first cohort, we recruited 73 patients with aMCI and 48 group-matched cognitively normal controls for the training and validation. Visual assessments of MTA and PA, including left MTA, right MTA, mean MTA, left PA, right PA and mean PA, were carried out from each participant. Global gray matter (GM) volume and density was estimated using voxel-based morphometry analysis as the objective reference. Based on the receiver operating characteristic (ROC) analysis, we investigated the discriminative power of single visual rating scale and the combination of MTA and PA for successful classification between the two diagnostic groups, respectively, and then compared them to GM measures. The second cohort, consisted of 33 aMCI patients and 45 NCs, was used to verify the reliability of the discriminative power of visual assessments.Results: In the first cohort, visual rating scales of MTA and PA showed different potential to distinguish aMCI from controls. Moreover, the combination of MTA and PA exhibited the best discriminative power, with the AUC of 0.818 ± 0.041, which was similar to the diagnostic accuracy of GM volumetric measures (0.857 ± 0.034). The discriminative power was verified in the second cohort when combining MTA and PA visual rating scales, with the AUC of 0.824 ± 0.058.Conclusion: The combined visual rating scales of MTA and PA demonstrated practical diagnostic values for distinguishing aMCI patients from controls, suggesting its potential to serve as a convenient and reproducible method to assess the degree of atrophy in the clinical setting.

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“…Mild cognitive impairment (MCI) is understood as a risk state for dementia [1][2][3][4][5]. MCI patients could progress to dementia (from 4 to 15% in clinical setting [6] and from 4 to as high as 17% in community-based studies [7]), could remain stable or could even revert to a normal cognition [4,[8][9][10][11][12]. It is a current target to identify those who hold a high risk of progressing to dementia to provide interventions that can prevent or slow further cognitive decline.…”

Section: Introductionmentioning

confidence: 99%

“…Supporting this notion is the subtype of MCI that presents with memory and other cognitive impairments (multidomain amnesic MCI, maMCI), with executive functions being those more commonly affected [9,25]. Some studies pointed out that maMCI exhibits the fastest progression to dementia in ACS in longitudinal studies [4,11,12]. Notwithstanding, the evidence remains mixed with some studies showing that dysexecutive MCI holds a higher risk to progress to dementia in ACS [2], while others concluded that amnestic and maMCI had a similar risk of conversion to that dementia [26].…”

Section: Introductionmentioning

confidence: 99%

Role of Executive Functions in the Conversion from Mild Cognitive Impairment to Dementia

Junquera

García-Zamora

Olazarán

et al. 2020

JAD

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Background: Recent research pointed to executive dysfunction as a potential early predictor of the progression of mild cognitive impairment (MCI) to dementia in Alzheimer’s clinical syndrome (ACS). Such cognitive impairments account for functional impairments in instrumental activities of daily living (IADL). Objective: The present study analyzes the contributions of executive functions to predict MCI–dementia progression in ACS. Methods: We assessed 145 participants, 51 cognitively unimpaired and 94 MCI. The latter were divided using the traditional, memory-based MCI classification (single domain amnestic, multidomain amnestic, and non-amnestic). Eight tests assessing executive functions were administered at baseline and at 1-year follow-up, together with cognitive screening tools and IADL measures. MCI patients were reclassified based on the outcomes from a K-mean cluster analysis which identified three groups. A simple lineal regression model was used to examine whether the classification based on executive functioning could more accurately predict progression to dementia a year later. Results: Clusters based on executive function deficits explained a significant proportion of the variance linked to MCI–dementia conversion, even after controlling for the severity of MCI at baseline (F(1, 68) = 116.25, p = 0.000, R2 = 0.63). Classical memory-based MCI classification failed to predict such a conversion (F(1, 68) = 5.09, p = 0.955, R2 = 0.07). Switching, categories generation, and planning were the executive functions that best distinguished between MCI converters and stable. Conclusion: MCI with a dysexecutive phenotype significantly predicts conversion to dementia in ACS a year later. Switching abilities and verbal fluency (categories) must be evaluated in MCI patients to assess risk of future dementia.

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The Sub-Classification of Amnestic Mild Cognitive Impairment Using MRI-Based Cortical Thickness Measures

Cited by 13 publications

References 35 publications

Heterogeneous cortical atrophy patterns in MCI not captured by conventional diagnostic criteria

Heterogeneous cortical atrophy patterns in MCI not captured by conventional diagnostic criteria

Combining visual rating scales of medial temporal lobe atrophy and posterior atrophy to identify amnestic mild cognitive impairment from cognitively normal older adults: evidence based on two datasets

Role of Executive Functions in the Conversion from Mild Cognitive Impairment to Dementia

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