| 1. |
- Coenen, Mirthe, et al.
(författare)
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Spatial distributions of white matter hyperintensities on brain MRI: A pooled analysis of individual participant data from 11 memory clinic cohorts
- 2023
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Ingår i: NeuroImage. Clinical. - 2213-1582. ; 40
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Tidskriftsartikel (refereegranskat)abstract
- INTRODUCTION: The spatial distribution of white matter hyperintensities (WMH) on MRI is often considered in the diagnostic evaluation of patients with cognitive problems. In some patients, clinicians may classify WMH patterns as "unusual", but this is largely based on expert opinion, because detailed quantitative information about WMH distribution frequencies in a memory clinic setting is lacking. Here we report voxel wise 3D WMH distribution frequencies in a large multicenter dataset and also aimed to identify individuals with unusual WMH patterns. METHODS: Individual participant data (N = 3525, including 777 participants with subjective cognitive decline, 1389 participants with mild cognitive impairment and 1359 patients with dementia) from eleven memory clinic cohorts, recruited through the Meta VCI Map Consortium, were used. WMH segmentations were provided by participating centers or performed in Utrecht and registered to the Montreal Neurological Institute (MNI)-152 brain template for spatial normalization. To determine WMH distribution frequencies, we calculated WMH probability maps at voxel level. To identify individuals with unusual WMH patterns, region-of-interest (ROI) based WMH probability maps, rule-based scores, and a machine learning method (Local Outlier Factor (LOF)), were implemented. RESULTS: WMH occurred in 82% of voxels from the white matter template with large variation between subjects. Only a small proportion of the white matter (1.7%), mainly in the periventricular areas, was affected by WMH in at least 20% of participants. A large portion of the total white matter was affected infrequently. Nevertheless, 93.8% of individual participants had lesions in voxels that were affected in less than 2% of the population, mainly located in subcortical areas. Only the machine learning method effectively identified individuals with unusual patterns, in particular subjects with asymmetric WMH distribution or with WMH at relatively rarely affected locations despite common locations not being affected. DISCUSSION: Aggregating data from several memory clinic cohorts, we provide a detailed 3D map of WMH lesion distribution frequencies, that informs on common as well as rare localizations. The use of data-driven analysis with LOF can be used to identify unusual patterns, which might serve as an alert that rare causes of WMH should be considered.
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| 2. |
- Altomare, Daniele, et al.
(författare)
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Prognostic value of Alzheimer’s biomarkers in mild cognitive impairment : the effect of age at onset
- 2019
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Ingår i: Journal of Neurology. - : Springer Science and Business Media LLC. - 0340-5354 .- 1432-1459. ; 266:10, s. 2535-2545
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Tidskriftsartikel (refereegranskat)abstract
- Objective: The aim of this study is to assess the impact of age at onset on the prognostic value of Alzheimer’s biomarkers in a large sample of patients with mild cognitive impairment (MCI). Methods: We measured Aβ42, t-tau, hippocampal volume on magnetic resonance imaging (MRI) and cortical metabolism on fluorodeoxyglucose–positron emission tomography (FDG-PET) in 188 MCI patients followed for at least 1 year. We categorised patients into earlier and later onset (EO/LO). Receiver operating characteristic curves and corresponding areas under the curve (AUCs) were performed to assess and compar the biomarker prognostic performances in EO and LO groups. Linear Model was adopted for estimating the time-to-progression in relation with earlier/later onset MCI groups and biomarkers. Results: In earlier onset patients, all the assessed biomarkers were able to predict cognitive decline (p < 0.05), with FDG-PET showing the best performance. In later onset patients, all biomarkers but t-tau predicted cognitive decline (p < 0.05). Moreover, FDG-PET alone in earlier onset patients showed a higher prognostic value than the one resulting from the combination of all the biomarkers in later onset patients (earlier onset AUC 0.935 vs later onset AUC 0.753, p < 0.001). Finally, FDG-PET showed a different prognostic value between earlier and later onset patients (p = 0.040) in time-to-progression allowing an estimate of the time free from disease. Discussion: FDG-PET may represent the most universal tool for the establishment of a prognosis in MCI patients and may be used for obtaining an onset-related estimate of the time free from disease.
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| 3. |
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| 4. |
- Caroli, Anna, et al.
(författare)
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Mild cognitive impairment with suspected nonamyloid pathology (SNAP) Prediction of progression
- 2015
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Ingår i: Neurology. - 0028-3878 .- 1526-632X. ; 84:5, s. 508-515
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Tidskriftsartikel (refereegranskat)abstract
- Objectives:The aim of this study was to investigate predictors of progressive cognitive deterioration in patients with suspected non-Alzheimer disease pathology (SNAP) and mild cognitive impairment (MCI).Methods:We measured markers of amyloid pathology (CSF -amyloid 42) and neurodegeneration (hippocampal volume on MRI and cortical metabolism on [F-18]-fluorodeoxyglucose-PET) in 201 patients with MCI clinically followed for up to 6 years to detect progressive cognitive deterioration. We categorized patients with MCI as A+/A- and N+/N- based on presence/absence of amyloid pathology and neurodegeneration. SNAPs were A-N+ cases.Results:The proportion of progressors was 11% (8/41), 34% (14/41), 56% (19/34), and 71% (60/85) in A-N-, A+N-, SNAP, and A+N+, respectively; the proportion of APOE epsilon 4 carriers was 29%, 70%, 31%, and 71%, respectively, with the SNAP group featuring a significantly different proportion than both A+N- and A+N+ groups (p 0.005). Hypometabolism in SNAP patients was comparable to A+N+ patients (p = 0.154), while hippocampal atrophy was more severe in SNAP patients (p = 0.002). Compared with A-N-, SNAP and A+N+ patients had significant risk of progressive cognitive deterioration (hazard ratio = 2.7 and 3.8, p = 0.016 and p < 0.001), while A+N- patients did not (hazard ratio = 1.13, p = 0.771). In A+N- and A+N+ groups, none of the biomarkers predicted time to progression. In the SNAP group, lower time to progression was correlated with greater hypometabolism (r = 0.42, p = 0.073).Conclusions:Our findings support the notion that patients with SNAP MCI feature a specific risk progression profile.
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| 5. |
- Leijenaar, Jolien F., et al.
(författare)
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Comorbid amyloid-β pathology affects clinical and imaging features in VCD
- 2020
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Ingår i: Alzheimer's and Dementia. - : Wiley. - 1552-5260 .- 1552-5279. ; 16:2, s. 354-364
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Tidskriftsartikel (refereegranskat)abstract
- Introduction: To date, the clinical relevance of comorbid amyloid-β (Aβ) pathology in patients with vascular cognitive disorders (VCD) is largely unknown. Methods: We included 218 VCD patients with available cerebrospinal fluid Aβ42 levels. Patients were divided into Aβ+ mild-VCD (n = 84), Aβ− mild-VCD (n = 68), Aβ+ major-VCD (n = 31), and Aβ− major-VCD (n = 35). We measured depression with the Geriatric Depression Scale, cognition with a neuropsychological test battery and derived white matter hyperintensities (WMH) and gray matter atrophy from MRI. Results: Aβ− patients showed more depressive symptoms than Aβ+. In the major-VCD group, Aβ− patients performed worse on attention (P =.02) and executive functioning (P =.008) than Aβ+. We found no cognitive differences in patients with mild VCD. In the mild-VCD group, Aβ− patients had more WMH than Aβ+ patients, whereas conversely, in the major-VCD group, Aβ+ patients had more WMH. Atrophy patterns did not differ between Aβ+ and Aβ− VCD group. Discussion: Comorbid Aβ pathology affects the manifestation of VCD, but effects differ by severity of VCD.
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| 6. |
- Prestia, Annapaola, et al.
(författare)
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Prediction of dementia in MCI patients based on core diagnostic markers for Alzheimer disease
- 2013
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Ingår i: Neurology. - 0028-3878 .- 1526-632X. ; 80:11, s. 1048-1056
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Tidskriftsartikel (refereegranskat)abstract
- Objectives: The current model of Alzheimer disease (AD) stipulates that brain amyloidosis biomarkers turn abnormal earliest, followed by cortical hypometabolism, and finally brain atrophy ones. The aim of this study is to provide clinical evidence of the model in patients with mild cognitive impairment (MCI). Methods: A total of 73 patients with MCI from 3 European memory clinics were included. Brain amyloidosis was assessed by CSF A beta 42 concentration, cortical metabolism by an index of temporoparietal hypometabolism on FDG-PET, and brain atrophy by automated hippocampal volume. Patients were divided into groups based on biomarker positivity: 1) A beta 422- FDG-PET- Hippo-, 2) A beta 42+ FDG-PET- Hippo-, 3) A beta 42+ FDG-PET + Hippo-, 4) A beta 42+ FDG-PET+ Hippo+, and 5) any other combination not in line with the model. Measures of validity were prevalence of group 5, increasing incidence of progression to dementia with increasing biological severity, and decreasing conversion time. Results: When patients with MCI underwent clinical follow-up, 29 progressed to dementia, while 44 remained stable. A total of 26% of patients were in group 5. Incident dementia was increasing with greater biological severity in groups 1 to 5 from 4% to 27%, 64%, and 100% (p for trend, 0.0001), and occurred increasingly earlier (p for trend = 0.024). Conclusions: The core biomarker pattern is in line with the current pathophysiologic model of AD. Fully normal and fully abnormal pattern is associated with exceptional and universal development of dementia. Cases not in line might be due to atypical neurobiology or inaccurate thresholds for biomarker (ab) normality.
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| 7. |
- van Maurik, Ingrid S., et al.
(författare)
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Biomarker testing in MCI patients—deciding who to test
- 2021
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Ingår i: Alzheimer's Research and Therapy. - : Springer Science and Business Media LLC. - 1758-9193. ; 13:1
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Tidskriftsartikel (refereegranskat)abstract
- Background: We aimed to derive an algorithm to define the optimal proportion of patients with mild cognitive impairment (MCI) in whom cerebrospinal fluid (CSF) testing is of added prognostic value. Methods: MCI patients were selected from the Amsterdam Dementia Cohort (n = 402). Three-year progression probabilities to dementia were predicted using previously published models with and without CSF data (amyloid-beta1-42 (Abeta), phosphorylated tau (p-tau)). We incrementally augmented the proportion of patients undergoing CSF, starting with the 10% patients with prognostic probabilities based on clinical data around the median (percentile 45–55), until all patients received CSF. The optimal proportion was defined as the proportion where the stepwise algorithm showed similar prognostic discrimination (Harrell’s C) and accuracy (three-year Brier scores) compared to CSF testing of all patients. We used the BioFINDER study (n = 221) for validation. Results: The optimal proportion of MCI patients to receive CSF testing selected by the stepwise approach was 50%. CSF testing in only this proportion improved the performance of the model with clinical data only from Harrell’s C = 0.60, Brier = 0.198 (Harrell’s C = 0.61, Brier = 0.197 if the information on magnetic resonance imaging was available) to Harrell’s C = 0.67 and Brier = 0.190, and performed similarly to a model in which all patients received CSF testing. Applying the stepwise approach in the BioFINDER study would again select half of the MCI patients and yielded robust results with respect to prognostic performance. Interpretation: CSF biomarker testing adds prognostic value in half of the MCI patients. As such, we achieve a CSF saving recommendation while simultaneously retaining optimal prognostic accuracy.
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