Structural magnetic resonance imaging for the early diagnosis of dementia due to Alzheimer's disease in people with mild cognitive impairment

Lombardi, Gemma; Crescioli, Giada; Cavedo, Enrica; Lucenteforte, Ersilia; Casazza, Giovanni; Bellatorre, Alessandro Giacco; Lista, Chiara; Costantino, Giorgio; Frisoni, Giovanni B.; Virgili, Gianni; Filippini, Graziella

doi:10.1002/14651858.cd009628.pub2

Cited by 112 publications

(99 citation statements)

References 383 publications

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“…1,4 However, conventional MRI methods alone are often limited in their sensitivity to underlying neuropathological changes. 4 In particular, standard structural imaging demonstrates brain atrophy on a gross tissue level, although more advanced analysis with voxel-based morphometry (VBM) can highlight subtle brain volumetric changes. 5 Advanced multimodal neuroimaging approaches, including diffusion-weighted MRI, can provide novel metrics related to functional changes associated with AD.…”

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confidence: 99%

Preliminary Assessment of Intravoxel Incoherent Motion Diffusion‐Weighted MRI (IVIM‐DWI) Metrics in Alzheimer's Disease

Bergamino

Nespodzany

Baxter

et al. 2020

Magnetic Resonance Imaging

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Background: Alzheimer's disease (AD) is a progressive neurodegenerative disease that affects aging populations. Current MRI techniques are often limited in their sensitivity to underlying neuropathological changes. Purpose: To characterize differences in voxel-based morphometry (VBM), apparent diffusion coefficient (ADC), and intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) metrics in aging populations. Additionally, to investigate the connection between cognitive assessments and neuroimaging metrics. Study Type: Prospective/cross-sectional. Population: In all, 49 subjects, including 13 with AD dementia, 12 with mild cognitive impairment (MCI), and 24 healthy controls (HC). Field Strength/Sequence: 3T/magnetization-prepared rapid acquisition gradient echo (MP-RAGE) and IVIM-DWI Assessment: All participants completed a cognitive screening battery prior to MRI. IVIM-DWI maps (pure diffusion coefficient [D], pseudodiffusion coefficient [D*], and perfusion fraction [f]) were generated from a biexponential fit of diffusion MRI data. VBM was performed on the standard T 1-weighted MP-RAGE structural images. Group-wise templates were used to compare across groups. Statistical Tests: Analysis of covariance (ANCOVA) with gender and age as covariates (familywise error [FWE] corrected, post-hoc comparisons using Bonferroni correction) for group comparisons. Partial-η 2 and Hedges' g were used for effectsize analysis. Spearman's correlations (false discovery rate [FDR]-corrected) for the relationship between cognitive scores and imaging. Results: Clusters of significant group-wise differences were found mainly in the temporal lobe, hippocampus, and amygdala using all VBM and IVIM methods (P < 0.05 FWE). While VBM showed significant changes between MCI and AD groups and between HC and AD groups, no significant clusters were observed between HC and MCI using VBM. ADC and IVIM-D demonstrated significant changes, at P < 0.05 FWE, between HC and MCI, notably in the amygdala and hippocampus. Several voxel-based correlations were observed between neuroimaging metrics and cognitive tests within the cognitively impaired groups (P < 0.05 FDR). Data Conclusion: These findings suggest that IVIM-DWI metrics may be earlier biomarkers for AD-related changes than VBM. The use of these techniques may provide novel insight into subvoxel neurodegenerative processes. Level of Evidence: 2 Technical Efficacy Stage: 2

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confidence: 99%

Preliminary Assessment of Intravoxel Incoherent Motion Diffusion‐Weighted MRI (IVIM‐DWI) Metrics in Alzheimer's Disease

Bergamino

Nespodzany

Baxter

et al. 2020

Magnetic Resonance Imaging

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“…The validation of biomarkers is imperfect, and they might not be sufficiently sensitive or specific for the clinical syndrome [49]. In research cohorts, the classification accuracy of MRI biomarkers varies, but appears to improve when using multiple MRI biomarkers combined or quantitative methods instead of visual MRI ratings [21,[90][91][92]. CSF biomarkers appear to have better sensitivity than specificity proposing greater utility to exclude AD etiology than include [93,94].…”

Section: Discussionmentioning

confidence: 99%

Cerebrospinal Fluid and MRI Biomarkers in Neurodegenerative Diseases: A Retrospective Memory Clinic-Based Study

Kaipainen

Jääskeläinen

Liu

et al. 2020

JAD

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Background: Cerebrospinal fluid (CSF) and magnetic resonance imaging (MRI) biomarkers of neurodegenerative diseases are relatively sensitive and specific in highly curated research cohorts, but proper validation for clinical use is mostly missing. Objective: We studied these biomarkers in a novel memory clinic cohort with a variety of different neurodegenerative diseases. Methods: This study consisted of 191 patients with subjective or objective cognitive impairment who underwent neurological, CSF biomarker (A␤ 42 , p-tau, and tau) and T1-weighted MRI examinations at Kuopio University Hospital. We assessed CSF and imaging biomarkers, including structural MRI focused on volumetric and cortical thickness analyses, across groups stratified based on different clinical diagnoses, including Alzheimer's disease (AD), frontotemporal dementia, dementia with Lewy bodies, Parkinson's disease, vascular dementia, and mild cognitive impairment (MCI), and subjects with no evidence of neurodegenerative disease underlying the cognitive symptoms. Imaging biomarkers were also studied by profiling subjects according to the novel amyloid, tau, and, neurodegeneration (AT(N)) classification. Results: Numerous imaging variables differed by clinical diagnosis, including hippocampal, amygdalar and inferior lateral ventricular volumes and entorhinal, lingual, inferior parietal and isthmus cingulate cortical thicknesses, at a false discovery rate (FDR)-corrected threshold for significance (analysis of covariance; p < 0.005). In volumetric comparisons by AT(N) profile, hippocampal volume significantly differed (p < 0.001) between patients with normal AD biomarkers and patients with amyloid pathology. Conclusion: Our analysis suggests that CSF and MRI biomarkers function well also in clinical practice across multiple clinical diagnostic groups in addition to AD, MCI, and cognitively normal groups.

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“…Despite its long history, relying on structural MRI for the early diagnosis of Alzheimer’s disease in the form of mild cognitive impairment (MCI) is not currently recommended. A recent Cochrane review found a high false negative rate of 27% and a false positive rate of 29% [ 10 ] based on data from 33 studies. Most of the data came from studies looking solely at the hippocampus although overall the data quality was sparse with insufficient data available to establish whether, for example, total brain volume could better differentiate between MCI and Alzheimer’s disease.…”

Section: Structural Imagingmentioning

confidence: 99%

Neurological update: neuroimaging in dementia

Rittman

2020

J Neurol

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Neuroimaging for dementia has made remarkable progress in recent years, shedding light on diagnostic subtypes of dementia, predicting prognosis and monitoring pathology. This review covers some updates in the understanding of dementia using structural imaging, positron emission tomography (PET), structural and functional connectivity, and using big data and artificial intelligence. Progress with neuroimaging methods allows neuropathology to be examined in vivo, providing a suite of biomarkers for understanding neurodegeneration and for application in clinical trials. In addition, we highlight quantitative susceptibility imaging as an exciting new technique that may prove to be a sensitive biomarker for a range of neurodegenerative diseases. There are challenges in translating novel imaging techniques to clinical practice, particularly in developing standard methodologies and overcoming regulatory issues. It is likely that clinicians will need to lead the way if these obstacles are to be overcome. Continued efforts applying neuroimaging to understand mechanisms of neurodegeneration and translating them to clinical practice will complete a revolution in neuroimaging.

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Structural magnetic resonance imaging for the early diagnosis of dementia due to Alzheimer's disease in people with mild cognitive impairment

Cited by 112 publications

References 383 publications

Preliminary Assessment of Intravoxel Incoherent Motion Diffusion‐Weighted MRI (IVIM‐DWI) Metrics in Alzheimer's Disease

Preliminary Assessment of Intravoxel Incoherent Motion Diffusion‐Weighted MRI (IVIM‐DWI) Metrics in Alzheimer's Disease

Cerebrospinal Fluid and MRI Biomarkers in Neurodegenerative Diseases: A Retrospective Memory Clinic-Based Study

Neurological update: neuroimaging in dementia

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