Relevance of Magnetic Resonance Imaging for Early Detection and Diagnosis of Alzheimer Disease

University Medicine Rostock, Rostock, Germany
The Medical clinics of North America (Impact Factor: 2.61). 05/2013; 97(3):399-424. DOI: 10.1016/j.mcna.2012.12.013
Source: PubMed


Magnetic resonance imaging (MRI)-based indicators of regional and global brain atrophy and more advanced measures of cortical functional and structural connectivity are among the most promising imaging biomarkers for the characterization of preclinical and prodromal stages of Alzheimer disease (AD). This review presents the current status of available and evolving MRI-based technologies for the early asymptomatic and predementia diagnosis of AD, including high-resolution structural MRI of global and regional brain atrophy, diffusion tensor imaging of structural cortical connectivity, and functional MRI during rest and task performance. The selection of an appropriate technique needs to consider its suitability for specific applications.

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Available from: Michel Grothe, May 13, 2014
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    • "The deposition of neurofibrillary tangles begins primarily in the limbic system structures, initially in the entorhinal cortex and the medial temporal regions, then progressively spread across the cerebral cortex. Hippocampal and entorhinal cortical atrophy assessed with MRI is well documented in patients with AD (Teipel et al., 2013), and in many with MCI (Pihlajamaki et al., 2009). Furthermore, this observation has extended the investigation of all limbic structures in relation to disease progression and cognitive performance. "
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    ABSTRACT: The fornix is a part of the limbic system and constitutes the major efferent and afferent white matter tracts from the hippocampi. The underdevelopment of or injuries to the fornix are strongly associated with memory deficits. Its role in memory impairments was suggested long ago with cases of surgical forniceal transections. However, recent advances in brain imaging techniques, such as diffusion tensor imaging have revealed that macrostructural and microstructural abnormalities of the fornix correlated highly with declarative and episodic memory performance. This structure appears to provide a robust and early imaging predictor for memory deficits not only in neurodegenerative and neuroinflammatory diseases, such as Alzheimer’s disease and multiple sclerosis, but also in schizophrenia and psychiatric disorders, and during neurodevelopment and “typical” aging. The objective of the manuscript is to present a systematic review regarding published brain imaging research on the fornix, including the development of its tracts, its role in various neurological diseases, and its relationship to neurocognitive performance in human studies.
    Frontiers in Aging Neuroscience 01/2015; DOI:10.3389/fnagi.2014.00343 · 4.00 Impact Factor
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    • "67 [42–85] 78 [60–92] ++++ 79 [64–91] ++++ MMSE: mean (range) 27 [6–30] 25 [16] [17] [18] [19] [20] [21] [22] [23] [24] [25] [26] [27] [28] [29] [30] 21 [13–29] Clock drawing test mean (range) 6 [0] [1] [2] [3] [4] [5] [6] [7] 5 [2] [3] [4] [5] [6] [7] 4 [0] [1] [2] [3] [4] [5] [6] [7] GMV [ml] "
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    ABSTRACT: Hippocampal volume is a promising biomarker to enhance the accuracy of the diagnosis of dementia due to Alzheimer's disease (AD). However, whereas hippocampal volume is well studied in patient samples from clinical trials, its value in clinical routine patient care is still rather unclear. The aim of the present study, therefore, was to evaluate fully automated atlas-based hippocampal volumetry for detection of AD in the setting of a secondary care expert memory clinic for outpatients. One-hundred consecutive patients with memory complaints were clinically evaluated and categorized into three diagnostic groups: AD, intermediate AD, and non-AD. A software tool based on open source software (Statistical Parametric Mapping SPM8) was employed for fully automated tissue segmentation and stereotactical normalization of high-resolution three-dimensional T1-weighted magnetic resonance images. Predefined standard masks were used for computation of grey matter volume of the left and right hippocampus which then was scaled to the patient's total grey matter volume. The right hippocampal volume provided an area under the receiver operating characteristic curve of 84% for detection of AD patients in the whole sample. This indicates that fully automated MR-based hippocampal volumetry fulfills the requirements for a relevant core feasible biomarker for detection of AD in everyday patient care in a secondary care memory clinic for outpatients. The software used in the present study has been made freely available as an SPM8 toolbox. It is robust and fast so that it is easily integrated into routine workflow.
    Journal of Alzheimer's disease: JAD 09/2014; 44(1). DOI:10.3233/JAD-141446 · 4.15 Impact Factor
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    • "Interestingly, the cerebellum is a common area that can be thought as a node of several RSNs including the DMN. Although previous works have suggested a cerebellar involvement in AD and MCI (Wang et al., 2007; Kaufmann et al., 2008; Thomann et al., 2008; Bai et al., 2009, 2011b; Solé-Padullés et al., 2009; Teipel et al., 2013), the alteration in FC in the cerebellum in AD and MCI remains unclear. "
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    ABSTRACT: In resting state fMRI (rs-fMRI), only functional connectivity (FC) reductions in the default mode network (DMN) are normally reported as a biomarker for Alzheimer's disease (AD). In this investigation we have developed a comprehensive strategy to characterize the FC changes occurring in multiple networks and applied it in a pilot study of subjects with AD and Mild Cognitive Impairment (MCI), compared to healthy controls (HC). Resting state networks (RSNs) were studied in 14 AD (70±6 years), 12 MCI (74±6 years) and 16 HC (69±5 years). RSN alterations were present in almost all the 15 recognized RSNs; overall, 474 voxels presented a reduced FC in MCI and 1244 in AD while 1627 voxels showed an increased FC in MCI and 1711 in AD. The RSNs were then ranked according to the magnitude and extension of FC changes (gFC), putting in evidence 6 RSNs with prominent changes: DMN, frontal cortical network (FCN), lateral visual network (LVN), basal ganglia network (BGN), cerebellar network (CBLN), and the anterior insula network (AIN). Nodes, or hubs, showing alterations common to more than one RSN were mostly localized within the prefrontal cortex and the mesial-temporal cortex. The cerebellum showed a unique behavior where voxels of decreased gFC were only found in AD while a significant gFC increase was only found in MCI. The gFC alterations showed strong correlations (p< 0.001) with psychological scores, in particular MMSE and attention/memory tasks. In conclusion, this analysis revealed that the DMN was affected by remarkable FC increases, that FC alterations extended over several RSNs, that derangement of functional relationships between multiple areas occurred already in the early stages of dementia. These results warrant future work to verify whether these represent compensatory mechanisms that exploit a pre-existing neural reserve through plasticity, which evolve in a state of lack of connectivity between different networks with the worsening of the pathology.
    Frontiers in Neuroscience 07/2014; 8:223. DOI:10.3389/fnins.2014.00223 · 3.66 Impact Factor
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