Structural magnetic resonance imaging for the early diagnosis of dementia due to Alzheimer's disease in people with mild cognitive impairment
Gemma Lombardi,Giada Crescioli,Enrica Cavedo,Ersilia Lucenteforte,Giovanni Casazza,Alessandro Giacco Bellatorre,Chiara Lista,Giorgio Costantino,Giovanni B. Frisoni,Gianni Virgili,Graziella Filippini +10 more
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TLDR
To assess the diagnostic accuracy of structural magnetic resonance imaging for the early diagnosis of dementia due to Alzheimer's disease in people with MCI, Cochrane Dementia and Cognitive Improvement's Specialised Register and the databases was searched and overall measures of relative accuracy in subgroup analyses were obtained.Abstract:
Background Mild cognitive impairment (MCI) due to Alzheimer's disease is the symptomatic predementia phase of Alzheimer's disease dementia, characterised by cognitive and functional impairment not severe enough to fulfil the criteria for dementia. In clinical samples, people with amnestic MCI are at high risk of developing Alzheimer's disease dementia, with annual rates of progression from MCI to Alzheimer's disease estimated at approximately 10% to 15% compared with the base incidence rates of Alzheimer's disease dementia of 1% to 2% per year. Objectives To assess the diagnostic accuracy of structural magnetic resonance imaging (MRI) for the early diagnosis of dementia due to Alzheimer's disease in people with MCI versus the clinical follow-up diagnosis of Alzheimer's disease dementia as a reference standard (delayed verification). To investigate sources of heterogeneity in accuracy, such as the use of qualitative visual assessment or quantitative volumetric measurements, including manual or automatic (MRI) techniques, or the length of follow-up, and age of participants. MRI was evaluated as an add-on test in addition to clinical diagnosis of MCI to improve early diagnosis of dementia due to Alzheimer's disease in people with MCI. Search methods On 29 January 2019 we searched Cochrane Dementia and Cognitive Improvement's Specialised Register and the databases, MEDLINE, Embase, BIOSIS Previews, Science Citation Index, PsycINFO, and LILACS. We also searched the reference lists of all eligible studies identified by the electronic searches. Selection criteria We considered cohort studies of any size that included prospectively recruited people of any age with a diagnosis of MCI. We included studies that compared the diagnostic test accuracy of baseline structural MRI versus the clinical follow-up diagnosis of Alzheimer's disease dementia (delayed verification). We did not exclude studies on the basis of length of follow-up. We included studies that used either qualitative visual assessment or quantitative volumetric measurements of MRI to detect atrophy in the whole brain or in specific brain regions, such as the hippocampus, medial temporal lobe, lateral ventricles, entorhinal cortex, medial temporal gyrus, lateral temporal lobe, amygdala, and cortical grey matter. Data collection and analysis Four teams of two review authors each independently reviewed titles and abstracts of articles identified by the search strategy. Two teams of two review authors each independently assessed the selected full-text articles for eligibility, extracted data and solved disagreements by consensus. Two review authors independently assessed the quality of studies using the QUADAS-2 tool. We used the hierarchical summary receiver operating characteristic (HSROC) model to fit summary ROC curves and to obtain overall measures of relative accuracy in subgroup analyses. We also used these models to obtain pooled estimates of sensitivity and specificity when sufficient data sets were available. Main results We included 33 studies, published from 1999 to 2019, with 3935 participants of whom 1341 (34%) progressed to Alzheimer's disease dementia and 2594 (66%) did not. Of the participants who did not progress to Alzheimer's disease dementia, 2561 (99%) remained stable MCI and 33 (1%) progressed to other types of dementia. The median proportion of women was 53% and the mean age of participants ranged from 63 to 87 years (median 73 years). The mean length of clinical follow-up ranged from 1 to 7.6 years (median 2 years). Most studies were of poor methodological quality due to risk of bias for participant selection or the index test, or both. Most of the included studies reported data on the volume of the total hippocampus (pooled mean sensitivity 0.73 (95% confidence interval (CI) 0.64 to 0.80); pooled mean specificity 0.71 (95% CI 0.65 to 0.77); 22 studies, 2209 participants). This evidence was of low certainty due to risk of bias and inconsistency. Seven studies reported data on the atrophy of the medial temporal lobe (mean sensitivity 0.64 (95% CI 0.53 to 0.73); mean specificity 0.65 (95% CI 0.51 to 0.76); 1077 participants) and five studies on the volume of the lateral ventricles (mean sensitivity 0.57 (95% CI 0.49 to 0.65); mean specificity 0.64 (95% CI 0.59 to 0.70); 1077 participants). This evidence was of moderate certainty due to risk of bias. Four studies with 529 participants analysed the volume of the total entorhinal cortex and four studies with 424 participants analysed the volume of the whole brain. We did not estimate pooled sensitivity and specificity for the volume of these two regions because available data were sparse and heterogeneous. We could not statistically evaluate the volumes of the lateral temporal lobe, amygdala, medial temporal gyrus, or cortical grey matter assessed in small individual studies. We found no evidence of a difference between studies in the accuracy of the total hippocampal volume with regards to duration of follow-up or age of participants, but the manual MRI technique was superior to automatic techniques in mixed (mostly indirect) comparisons. We did not assess the relative accuracy of the volumes of different brain regions measured by MRI because only indirect comparisons were available, studies were heterogeneous, and the overall accuracy of all regions was moderate. Authors' conclusions The volume of hippocampus or medial temporal lobe, the most studied brain regions, showed low sensitivity and specificity and did not qualify structural MRI as a stand-alone add-on test for an early diagnosis of dementia due to Alzheimer's disease in people with MCI. This is consistent with international guidelines, which recommend imaging to exclude non-degenerative or surgical causes of cognitive impairment and not to diagnose dementia due to Alzheimer's disease. In view of the low quality of most of the included studies, the findings of this review should be interpreted with caution. Future research should not focus on a single biomarker, but rather on combinations of biomarkers to improve an early diagnosis of Alzheimer's disease dementia.read more
Citations
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Heterogeneous data fusion for predicting mild cognitive impairment conversion
TL;DR: A novel sparse regression method to fuse the auxiliary data into the predictor data for the pMCI/sMCI classification and shows the proposed method achieved the best classification performance, compared to the best comparison method, in terms of four evaluation metrics.
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European Stroke Organisation and European Academy of Neurology joint guidelines on post-stroke cognitive impairment:
Terence J. Quinn,Edo Richard,Yvonne Teuschl,Thomas Gattringer,Melanie Hafdi,John T. O'Brien,Niamh A. Merriman,Celine Gillebert,Hanne Huyglier,Ana Verdelho,Reinhold Schmidt,Emma Ghaziani,Hysse Forchammer,Sarah T. Pendlebury,Rose Bruffaerts,Milija Mijajlovic,Bogna A Drozdowska,Emily L Ball,Hugh S. Markus +18 more
TL;DR: The optimal management of post-stroke cognitive impairment remains controversial as mentioned in this paper, and these joint European Stroke Organisation (ESO) and European Academy of Neurology (EAN) guidelines provide evidence-based guidelines.
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Prediction Model of Dementia Risk Based on XGBoost Using Derived Variable Extraction and Hyper Parameter Optimization
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Preliminary Assessment of Intravoxel Incoherent Motion Diffusion‐Weighted MRI (IVIM‐DWI) Metrics in Alzheimer's Disease
Maurizio Bergamino,Ashley Nespodzany,Leslie C. Baxter,Leslie C. Baxter,Anna D. Burke,Richard J. Caselli,Marwan N. Sabbagh,Ryan R. Walsh,Ashley M. Stokes +8 more
TL;DR: In this article, the authors investigated the connection between cognitive assessments and neuroimaging metrics, including voxel-based morphometry (VBM), apparent diffusion coefficient (ADC), and intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) metrics in aging populations.
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Significance of Blood and Cerebrospinal Fluid Biomarkers for Alzheimer's Disease: Sensitivity, Specificity and Potential for Clinical Use.
TL;DR: The role of current and hypothetical biomarkers of Alzheimer’s disease, their specificity, and the caveats of current high-sensitivity platforms for their peripheral detection are discussed.
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