Volumetric MRI Measurements Can Differentiate Alzheimers Disease, Mild Cognitive Impairment, and Normal Aging (original) (raw)
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Neurobiology of Aging, 2011
To study the ability of neuropsychological tests, manual MRI hippocampal volume measures, regional volume and cortical thickness measures to identify subjects with Alzheimer's disease (AD), mild cognitive impairment (MCI), and healthy age-matched controls. Neuropsychological tests, manual hippocampal volume, automated regional volume and regional cortical thickness measures were performed in 120 AD patients, 120 MCI subjects, and 111 controls. The regional cortical thickness and volumes in MCI subjects were significantly decreased in limbic/paralimbic areas and temporal lobe compared to controls. Atrophy was much more extensive in the AD patients compared to MCI subjects and controls. The combination of neuropsychological tests and volumes revealed the highest accuracy (82% AD vs. MCI; 94% AD vs. control; 83% MCI vs. control). Adding regional cortical thicknesses into the discriminate analysis did not improve accuracy. We conclude that regional cortical thickness and volume measures provide a panoramic view of brain atrophy in AD and MCI subjects. A combination of neuropsychological tests and regional volumes are important when discriminating AD from healthy controls and MCI.
Arquivos de Neuro-Psiquiatria, 2013
Objective: To evaluate the volumetric and spectroscopy aspects of hippocampus in patients with mild Alzheimer's disease (AD) and mild cognitive impairment (MCI). Methods: A series of patients older than 65 years and with memory deficit were studied. Results: The evocation of words test presented a significant reduction in the number of words recalled by the patients with MCI and mild AD as compared with the control group. Bilateral reduction of the hippocampus volume in the AD group was observed when compared to the control group. There were no statistical differences in the values of NAA/Cr, mI/Cr, Cho/Cr and mI/NAA between the groups. Conclusions: Magnetic resonance imaging study failed to individually distinguish patients with MCI, mild AD and normal aging. However, patients with mild AD presented loss of asymmetry between the right and left hippocampus, and a reduction in hippocampus volume.
IEEE Reviews in Biomedical Engineering, 2018
Classifying and predicting Alzheimer's disease (AD) in individuals with memory disorders through clinical and psychometric assessment is challenging especially in Mild Cognitive Impairment (MCI) subjects. Quantitative structural Magnetic Resonance Imaging (MRI) acquisition methods in combination with Computer-Aided Diagnosis (CAD) are currently being used for the assessment AD. These acquisitions methods include: i) Voxel-based Morphometry (VBM), ii) volumetric measurements in specific Regions of Interest (ROIs), iii) cortical thickness measurements, iv) shape analysis and v) texture analysis. This review evaluates the aforementioned methods in the classification of cases into one of the following 3 groups: Normal Controls (NC), MCI and AD subjects. Furthermore, the performance of the methods is assessed on the prediction of conversion from MCI to AD. In parallel, it is also assessed which ROIs are preferred in both classification and prognosis through the different states of the disease. Structural changes in the early stages of the disease are more pronounced in the Medial Temporal Lobe (MTL) especially in the entorhinal cortex, whereas with disease progression both entorhinal cortex and hippocampus offer similar discriminative power. However, for the conversion from MCI subjects to AD, entorhinal cortex provides better predictive accuracies rather than other structures, such as the hippocampus.
The Egyptian Journal of Radiology and Nuclear Medicine, 2014
Background: Structural neuroimaging MR volumetric changes can predict progression of MCI to AD. Early effective treatment of MCI has been shown to delay institutionalization and improve cognition and behavioral symptoms. Aim of the work: To evaluate the role of volumetric MRI to identify a pattern of regional atrophy characteristic in differentiation between Alzheimer's disease, Mild Cognitive Impairment, and Normal elderly control. Material and methods: The regional ethics committee approved the study and written informed consent was obtained from all participants. Between April 2012 and May 2013, prospective study was conducted on 25 patients (18 males and 7 females) and 15 healthy elderly controls (9 males and 6 females) referred to the Radiodiagnosis Department from the Neuropsychiatry Department that had clinical manifestations of suspected cognitive impairment, we used the Mini Mental State Examination (MMSE) as a measure of general cognitive function and the total learning from the
The role of volumetric MRI in understanding mild cognitive impairment and similar classifications
Aging & Mental Health, 2003
We review nineteen empirical studies of mild cognitive impairment (MCI), age-associated memory impairment (AAMI) and related classifications reporting volumetric data on the hippocampus, entorhinal cortex and amygdala. Studies varied considerably in terms of the selection of participants, sample characteristics, the definitions of regions of interest and normalization techniques. Effect sizes for differences in left hippocampal volume and right hippocampal volumes of AAMI, MCI and pre-clinical dementia groups compared with controls ranged from 0.47 to 1.34. Effect sizes for left and right hippocampal volumes for Alzheimer's disease (AD) versus control were 1.88 and 1.75 respectively. Longitudinal results confirm that initial hippocampal volume is predictive of conversion to AD. Greater standardization in methodology and the development of normative age-referenced databases of regional brain volumes is required.
Neurobiology of Aging, 2010
We determined predictors of conversion to Alzheimer's disease (AD) from mild cognitive impairment (MCI) with automated magnetic resonance imaging (MRI) regional cortical volume and thickness measures. One hundred amnestic MCI subjects, 118 AD patients, and 94 age-matched healthy controls were selected from AddNeuroMed study. Twenty-four regional cortical volumes and 34 cortical thicknesses were measured with automated image processing software at baseline. Twenty-one subjects converted from MCI to AD determined with the cognitive tests at baseline and 1 year later. The hippocampus, amygdala, and caudate volumes were significantly smaller in progressive MCI subjects than in controls and stable MCI subjects. The cortical volumes achieved higher predictive accuracy than did cognitive tests or cortical thickness. Combining the volumes, thicknesses, and cognitive tests did not improve the accuracy. The volume of amygdala and caudate were independent variables in predicting conversion from MCI to AD. We conclude that regional cortical volume measures are more powerful than those common cognitive tests we used in identifying AD patients at the very earliest stage of the disease.
Alzheimer Disease & Associated Disorders, 2010
The aim of this study was to analyze the combined contribution of magnetic resonance imaging and magnetoencephalography (MEG) to the diagnosis of mild cognitive impairment (MCI) and AD. To whole-head MEG recordings were obtained from three diagnosis groups: Alzheimer disease (AD), MCI, and control. Magnetic resonance imaging volumetric data of global brain, temporal lobe, and hippocampal volumes, were also obtained. Results indicated that a reduction of volume in the hippocampal structure allowed the discrimination between AD and MCI patients as compared with controls. The percentage of correct classification was 91.3% when AD versus controls was compared, and 83.3% when we compared MCI versus control. MEG data showed that AD patients exhibit higher y and d activity than MCI and controls. Such higher activity was significant in parietal, temporal, and occipital areas. Left parietal theta classified controls versus MCIs with 78.3% rate of correct classification. Right occipital theta and the left parietal delta allowed the discrimination of controls versus ADs, with 81.8% rate of correct classification. Left parietal theta discriminated between ADs and MCIs with 56.6% rate of correct classification. In addition, the combination of both techniques significantly improved the rate of correct classification, thus indicating that a multidisciplinary perspective of techniques may improve the diagnostic capabilities.
Objective: To examine the pattern of atrophy modifications in whole-brain and ventricular regions, using data from serial (multi-timepoint) magnetic resonance imaging (MRI) in Alzheimer’s patients, Mild Cognitive Impairment (MCI) and normal aging. To evaluate a published atrophy-measurement technique: Brain Boundary Shift Integral, determining suitable values for parameters which control the BBSI and investigate its stability over time. To test how brain volume tested with BBSI can identify group membership and progress over time and to examine the relationship between these parameters and the cognitive data available. Methods: The Brain Boundary Shift Integral was computed by the following stages: Image Pre-processing Brain extraction and brain segmentation Registration (alignment) of each pair of MRI scans BBSI Calibration Using Simulated Data: Establishing the optimum boundary region (morphological operators) Establishing the optimum intensity window for ventricular area Results: The AD patients differed primarily in the rates of brain atrophy and ventricular enlargement from elderly controls and Mild Cognitive Impairment. These results were analyzed according to time variation from baseline to 24 months by controlling for gender and group differences. The overall volumetric loss was correlated with the performance on cognitive scale. Conclusions: The pattern of brain volume atrophy has progressively decreased over time factor at both level of total and ventricular volume with a significant difference between AD and normal elderly. The correlation between brain atrophy, ventricular enlargement and cognitive scales reflected the correspondence between the measures of cerebral atrophy monitored in time and the global measures of cognitive scale.
Investigative Magnetic Resonance Imaging, 2021
Mild cognitive impairment (MCI) is a prodromal stage of Alzheimer's disease (AD). Brain atrophy in this disease spectrum begins in the medial temporal lobe structure, which can be recognized by magnetic resonance imaging. To overcome the unsatisfactory inter-observer reliability of visual evaluation, quantitative brain volumetry has been developed and widely investigated for the diagnosis of MCI and AD. The aim of this study was to assess the prediction accuracy of quantitative brain volumetry using a fully automated segmentation software package, NeuroQuant®, for the diagnosis of MCI. Materials and Methods: A total of 418 subjects from the Korean Brain Aging Study for Early Diagnosis and Prediction of Alzheimer's Disease cohort were included in our study. Each participant was allocated to either a cognitively normal old group (n = 285) or an MCI group (n = 133). Brain volumetric data were obtained from T1weighted images using the NeuroQuant software package. Logistic regression and receiver operating characteristic (ROC) curve analyses were performed to investigate relevant brain regions and their prediction accuracies. Results: Multivariate logistic regression analysis revealed that normative percentiles of the hippocampus (P < 0.001), amygdala (P = 0.003), frontal lobe (P = 0.049), medial parietal lobe (P = 0.023), and third ventricle (P = 0.012) were independent predictive factors for MCI. In ROC analysis, normative percentiles of the hippocampus and amygdala showed fair accuracies in the diagnosis of MCI (area under the curve: 0.739 and 0.727, respectively). Conclusion: Normative percentiles of the hippocampus and amygdala provided by the fully automated segmentation software could be used for screening MCI with a reasonable post-processing time. This information might help us interpret structural MRI in patients with cognitive impairment.
Journal of Neuropsychology, 2015
The construct of mild cognitive impairment (MCI) has been proposed to identify patients at risk of developing Alzheimer's disease (AD) in the pre-clinical stage. Although subjects with MCI have an increased risk of progressing to dementia, most remain stable or return to normality. The new criteria for diagnosing prodromal AD assume that, to increase the predictive value of the MCI, in addition to a defect of delayed recall there must also be the presence of abnormal biomarkers, investigating structural and molecular neuroimaging and cerebrospinal fluid (CSF) analysis of amyloid- or tau proteins. Although acknowledging that the use of CSF degeneration biomarkers is advisable not only for research, but also for clinical purposes, the present review is centered upon the neuropsychological markers of conversion to AD, which are equally clinically important. In particular, results of this review suggest the following: (a) measures of delayed recall are the best neuropsychological predictors of conversion from MCI to AD; (b) memory tests providing controlled encoding and cued recall are not necessarily better predictors than free recall tests; (c) stringent cutoff points are necessary to increase the specificity of these predictors; (d) multi-domain amnestic MCI patients are the best candidates for clinical trials, but not for treatment with disease-modifying drugs; and (e) not only episodic but also semantic memory is significantly impaired in patients who will convert to AD. These data and the underlying neural mechanisms will be discussed, trying to distinguish results obtained in MCI patients from those obtained in a pre-MCI stage of the AD progression.