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1.
Sci Rep ; 9(1): 16742, 2019 Nov 14.
Artigo em Inglês | MEDLINE | ID: mdl-31727919

RESUMO

White matter hyperintensities (WMHs) are a common manifestation of cerebral small vessel disease, that is increasingly studied with large, pooled multicenter datasets. This data pooling increases statistical power, but poses challenges for automated WMH segmentation. Although there is extensive literature on the evaluation of automated WMH segmentation methods, such evaluations in a multicenter setting are lacking. We performed WMH segmentations in sixty patients scanned on six different magnetic resonance imaging (MRI) scanners (10 patients per scanner) using five freely available and fully-automated WMH segmentation methods (Cascade, kNN-TTP, Lesion-TOADS, LST-LGA and LST-LPA). Different MRI scanner vendors and field strengths were included. We compared these automated WMH segmentations with manual WMH segmentations as a reference. Performance of each method both within and across scanners was assessed using spatial and volumetric correspondence with the reference segmentations by Dice's similarity coefficient (DSC) and intra-class correlation coefficient (ICC) respectively. We found the best performance, both within and across scanners, for kNN-TTP, followed by LST-LPA and LST-LGA, with worse performance for Lesion-TOADS and Cascade. Our findings can serve as a guide for choosing a method and also highlight the importance to further improve and evaluate consistency of methods in a multicenter setting.

2.
Artigo em Inglês | MEDLINE | ID: mdl-31705174

RESUMO

PURPOSE: The novel PET tracer [11C]SMW139 binds with high affinity to the P2X7 receptor, which is expressed on pro-inflammatory microglia. The purposes of this first in-man study were to characterise pharmacokinetics of [11C]SMW139 in patients with active relapsing remitting multiple sclerosis (RRMS) and healthy controls (HC) and to evaluate its potential to identify in vivo neuroinflammation in RRMS. METHODS: Five RRMS patients and 5 age-matched HC underwent 90-min dynamic [11C]SMW139 PET scans, with online continuous and manual arterial sampling to generate a metabolite-corrected arterial plasma input function. Tissue time activity curves were fitted to single- and two-tissue compartment models, and the model that provided the best fits was determined using the Akaike information criterion. RESULTS: The optimal model for describing [11C]SMW139 kinetics in both RRMS and HC was a reversible two-tissue compartment model with blood volume parameter and with the dissociation rate k4 fixed to the whole-brain value. Exploratory group level comparisons demonstrated an increased volume of distribution (VT) and binding potential (BPND) in RRMS compared with HC in normal appearing brain regions. BPND in MS lesions was decreased compared with non-lesional white matter, and a further decrease was observed in gadolinium-enhancing lesions. In contrast, increased VT was observed in enhancing lesions, possibly resulting from disruption of the blood-brain barrier in active MS lesions. In addition, there was a high correlation between parameters obtained from 60- to 90-min datasets, although analyses using 60-min data led to a slight underestimation in regional VT and BPND values. CONCLUSIONS: This first in-man study demonstrated that uptake of [11C]SMW139 can be quantified with PET using BPND as a measure for specific binding in healthy controls and RRMS patients. Additional studies are warranted for further clinical evaluation of this novel neuroinflammation tracer.

3.
Ann Neurol ; 2019 Nov 06.
Artigo em Inglês | MEDLINE | ID: mdl-31693200

RESUMO

OBJECTIVE: Clinical outcomes in multiple sclerosis (MS) are highly variable. We aim to determine the long-term clinical outcomes in MS, and to identify early prognostic features of these outcomes. METHODS: One hundred thirty-two people presenting with a clinically isolated syndrome were prospectively recruited between 1984 and 1987, and followed up clinically and radiologically 1, 5, 10, 14, 20, and now 30 years later. All available notes and magnetic resonance imaging scans were reviewed, and MS was defined according to the 2010 McDonald criteria. RESULTS: Clinical outcome data were obtained in 120 participants at 30 years. Eighty were known to have developed MS by 30 years. Expanded Disability Status Scale (EDSS) scores were available in 107 participants, of whom 77 had MS; 32 (42%) remained fully ambulatory (EDSS scores ≤3.5), all of whom had relapsing-remitting MS (RRMS), 3 (4%) had RRMS and EDSS scores >3.5, 26 (34%) had secondary progressive MS (all had EDSS scores >3.5), and MS contributed to death in 16 (20%). Of those with MS, 11 received disease-modifying therapy. The strongest early predictors (within 5 years of presentation) of secondary progressive MS at 30 years were presence of baseline infratentorial lesions and deep white matter lesions at 1 year. INTERPRETATION: Thirty years after onset, in a largely untreated cohort, there was a divergence of MS outcomes; some people accrued substantial disability early on, whereas others ran a more favorable long-term course. These outcomes could, in part, be predicted by radiological findings from within 1 year of first presentation. ANN NEUROL 2019.

4.
Neuroimage Clin ; 24: 102011, 2019 Oct 22.
Artigo em Inglês | MEDLINE | ID: mdl-31734524

RESUMO

Machine learning classification is an attractive approach to automatically differentiate patients from healthy subjects, and to predict future disease outcomes. A clinically isolated syndrome (CIS) is often the first presentation of multiple sclerosis (MS), but it is difficult at onset to predict who will have a second relapse and hence convert to clinically definite MS. In this study, we thus aimed to distinguish CIS converters from non-converters at onset of a CIS, using recursive feature elimination and weight averaging with support vector machines. We also sought to assess the influence of cohort size and cross-validation methods on the accuracy estimate of the classification. We retrospectively collected 400 patients with CIS from six European MAGNIMS MS centres. Patients underwent brain MRI at onset of a CIS according to local standard-of-care protocols. The diagnosis of clinically definite MS at one-year follow-up was the standard against which the accuracy of the model was tested. For each patient, we derived MRI-based features, such as grey matter probability, white matter lesion load, cortical thickness, and volume of specific cortical and white matter regions. Features with little contribution to the classification model were removed iteratively through an interleaved sample bootstrapping and feature averaging approach. Classification of CIS outcome at one-year follow-up was performed with 2-fold, 5-fold, 10-fold and leave-one-out cross-validation for each centre cohort independently and in all patients together. The estimated classification accuracy across centres ranged from 64.9% to 88.1% using 2-fold cross-validation and from 73% to 92.9% using leave-one-out cross-validation. The classification accuracy estimate was higher in single-centre, smaller data sets than in combinations of data sets, being the lowest when all patients were merged together. Regional MRI features such as WM lesions, grey matter probability in the thalamus and the precuneus or cortical thickness in the cuneus and inferior temporal gyrus predicted the occurrence of a second relapse in patients at onset of a CIS using support vector machines. The increased accuracy estimate of the classification achieved with smaller and single-centre samples may indicate a model bias (overfitting) when data points were limited, but also more homogeneous. We provide an overview of classifier performance from a range of cross-validation schemes to give insight into the variability across schemes. The proposed recursive feature elimination approach with weight averaging can be used both in single- and multi-centre data sets in order to bridge the gap between group-level comparisons and making predictions for individual patients.

5.
Stroke ; : STROKEAHA119026170, 2019 Nov 08.
Artigo em Inglês | MEDLINE | ID: mdl-31699021

RESUMO

Background and Purpose- Cerebral small vessel disease is characterized by a wide range of focal and global brain changes. We used a magnetic resonance imaging segmentation tool to quantify multiple types of small vessel disease-related brain changes and examined their individual and combined predictive value on cognitive and functional abilities. Methods- Magnetic resonance imaging scans of 560 older individuals from LADIS (Leukoaraiosis and Disability Study) were analyzed using automated atlas- and convolutional neural network-based segmentation methods yielding volumetric measures of white matter hyperintensities, lacunes, enlarged perivascular spaces, chronic cortical infarcts, and global and regional brain atrophy. The subjects were followed up with annual neuropsychological examinations for 3 years and evaluation of instrumental activities of daily living for 7 years. Results- The strongest predictors of cognitive performance and functional outcome over time were the total volumes of white matter hyperintensities, gray matter, and hippocampi (P<0.001 for global cognitive function, processing speed, executive functions, and memory and P<0.001 for poor functional outcome). Volumes of lacunes, enlarged perivascular spaces, and cortical infarcts were significantly associated with part of the outcome measures, but their contribution was weaker. In a multivariable linear mixed model, volumes of white matter hyperintensities, lacunes, gray matter, and hippocampi remained as independent predictors of cognitive impairment. A combined measure of these markers based on Z scores strongly predicted cognitive and functional outcomes (P<0.001) even above the contribution of the individual brain changes. Conclusions- Global burden of small vessel disease-related brain changes as quantified by an image segmentation tool is a powerful predictor of long-term cognitive decline and functional disability. A combined measure of white matter hyperintensities, lacunar, gray matter, and hippocampal volumes could be used as an imaging marker associated with vascular cognitive impairment.

6.
Neuroimage Clin ; 24: 102051, 2019 Oct 25.
Artigo em Inglês | MEDLINE | ID: mdl-31734530

RESUMO

Prion diseases are a group of rare neurodegenerative conditions characterised by a high rate of progression and highly heterogeneous phenotypes. Whilst the most common form of prion disease occurs sporadically (sporadic Creutzfeldt-Jakob disease, sCJD), other forms are caused by prion protein gene mutations, or exposure to prions in the diet or by medical procedures, such us surgeries. To date, there are no accurate quantitative imaging biomarkers that can be used to predict the future clinical diagnosis of a healthy subject, or to quantify the progression of symptoms over time. Besides, CJD is commonly mistaken for other forms of dementia. Due to the heterogeneity of phenotypes and the lack of a consistent geometrical pattern of disease progression, the approaches used to study other types of neurodegenerative diseases are not satisfactory to capture the progression of human form of prion disease. In this paper, using a tailored framework, we aim to classify and stratify patients with prion disease, according to the severity of their illness. The framework is initialised with the extraction of subject-specific imaging biomarkers. The extracted biomakers are then combined with genetic and demographic information within a Gaussian Process classifier, used to calculate the probability of a subject to be diagnosed with prion disease in the next year. We evaluate the effectiveness of the proposed method in a cohort of patients with inherited and sporadic forms of prion disease. The model has shown to be effective in the prediction of both inherited CJD (92% of accuracy) and sporadic CJD (95% of accuracy). However the model has shown to be less effective when used to stratify the different stages of the disease, in which the average accuracy is 85%, whilst the recall is 59%. Finally, our framework was extended as a differential diagnosis tool to identify both forms of CJD among another neurodegenerative disease. In summary we have developed a novel method for prion disease diagnosis and prediction of clinical onset using multiple sources of features, which may have use in other disorders with heterogeneous imaging features.

7.
Hum Brain Mapp ; 2019 Nov 28.
Artigo em Inglês | MEDLINE | ID: mdl-31778002

RESUMO

White matter hyperintensities (WMH) have been extensively associated with cognitive impairment and reductions in gray matter volume (GMv) independently. This study explored whether WMH lesion volume mediates the relationship between cerebral patterns of GMv and cognition in 521 (mean age 57.7 years) cognitively unimpaired middle-aged individuals. Episodic memory (EM) was measured with the Memory Binding Test and executive functions (EF) using five WAIS-IV subtests. WMH were automatically determined from T2 and FLAIR sequences and characterized using diffusion-weighted imaging (DWI) parameters. WMH volume was entered as a mediator in a voxel-wise mediation analysis relating GMv and cognitive performance (with both EM and EF composites and the individual tests independently). The mediation model was corrected by age, sex, education, number of Apolipoprotein E (APOE)-ε4 alleles and total intracranial volume. We found that even at very low levels of WMH burden in the cohort (median volume of 3.2 mL), higher WMH lesion volume was significantly associated with a widespread pattern of lower GMv in temporal, frontal, and cerebellar areas. WMH mediated the relationship between GMv and EF, mainly driven by processing speed, but not EM. DWI parameters in these lesions were compatible with incipient demyelination and axonal loss. These findings lead to the reflection on the relevance of the control of cardiovascular risk factors in middle-aged individuals as a valuable preventive strategy to reduce or delay cognitive decline.

8.
J Clin Invest ; 129(11): 4758-4768, 2019 Nov 01.
Artigo em Inglês | MEDLINE | ID: mdl-31566584

RESUMO

Multiple sclerosis (MS) is a disabling disease of the CNS. Inflammatory features of MS include lymphocyte accumulations in the CNS and cerebrospinal fluid (CSF). The preclinical events leading to established MS are still enigmatic. Here we compared gene expression patterns of CSF cells from MS-discordant monozygotic twin pairs. Six "healthy" co-twins, who carry a maximal familial risk for developing MS, showed subclinical neuroinflammation (SCNI) with small MRI lesions. Four of these subjects had oligoclonal bands (OCBs). By single-cell RNA sequencing of 2752 CSF cells, we identified clonally expanded CD8+ T cells, plasmablasts, and, to a lesser extent, CD4+ T cells not only from MS patients but also from subjects with SCNI. In contrast to nonexpanded T cells, clonally expanded T cells showed characteristics of activated tissue-resident memory T (TRM) cells. The TRM-like phenotype was detectable already in cells from SCNI subjects but more pronounced in cells from patients with definite MS. Expanded plasmablast clones were detected only in MS and SCNI subjects with OCBs. Our data provide evidence for very early concomitant activation of 3 components of the adaptive immune system in MS, with a notable contribution of clonally expanded TRM-like CD8+ cells.

9.
Alzheimers Dement ; 15(11): 1458-1467, 2019 Nov.
Artigo em Inglês | MEDLINE | ID: mdl-31594684

RESUMO

INTRODUCTION: The objective of this study was to assess the usefulness of the appropriate use criteria (AUC) for amyloid imaging in an unselected cohort. METHODS: We calculated sensitivity and specificity of appropriate use (increased confidence and management change), as defined by Amyloid Imaging Taskforce in the AUC, and other clinical utility outcomes. Furthermore, we compared differences in post-positron emission tomography diagnosis and management change between "AUC-consistent" and "AUC-inconsistent" patients. RESULTS: Almost half (250/507) of patients were AUC-consistent. In both AUC-consistent and AUC-inconsistent patients, post-positron emission tomography diagnosis (28%-21%) and management (32%-17%) change was substantial. The Amyloid Imaging Taskforce's definition of appropriate use occurred in 55/507 (13%) patients, detected by the AUC with a sensitivity of 93%, and a specificity of 56%. Diagnostic changes occurred independently of AUC status (sensitivity: 57%, specificity: 53%). DISCUSSION: The current AUC are not sufficiently able to discriminate between patients who will benefit from amyloid positron emission tomography and those who will not.

10.
Neurology ; 93(20): e1906-e1916, 2019 Nov 12.
Artigo em Inglês | MEDLINE | ID: mdl-31594857

RESUMO

OBJECTIVE: In the phase II, randomized, double-blind, placebo-controlled Supplementation of Vigantol Oil versus Placebo Add-on in Patients with Relapsing-Remitting Multiple Sclerosis (RRMS) Receiving Rebif Treatment (SOLAR) study (NCT01285401), we assessed the efficacy and safety of add-on vitamin D3 in patients with RRMS. METHODS: Eligible patients with RRMS treated with SC interferon-ß-1a (IFN-ß-1a) 44 µg 3 times weekly and serum 25(OH)D levels <150 nmol/L were included. From February 15, 2011, to May 11, 2015, 229 patients were included and randomized 1:1 to receive SC IFN-ß-1a plus placebo (n = 116) or SC IFN-ß-1a plus oral high-dose vitamin D3 14,007 IU/d (n = 113). The revised primary outcome was the proportion of patients with no evidence of disease activity (NEDA-3) at week 48. RESULTS: At 48 weeks, 36.3% of patients who received high-dose vitamin D3 had NEDA-3, without a statistically significant difference in NEDA-3 status between groups (placebo 35.3%; odds ratio 0.93; 95% confidence interval [CI] 0.53-1.63; p = 0.80). Compared with placebo, the high-dose vitamin D3 group had better MRI outcomes for combined unique active lesions (incidence rate ratio 0.68; 95% CI 0.52-0.89; p = 0.0045) and change from baseline in total volume of T2 lesions (difference in mean ranks: -0.074; p = 0.035). CONCLUSIONS: SOLAR did not establish a benefit for high-dose vitamin D3 as add-on to IFN-ß-1a, based on the primary outcome of NEDA-3, but findings from exploratory outcomes suggest protective effects on development of new MRI lesions in patients with RRMS. CLINICALTRIALSGOV IDENTIFIER: NCT01285401. CLASSIFICATION OF EVIDENCE: This study provides Class II evidence that for patients with RRMS treated with SC IFN-ß-1a, 48 weeks of cholecalciferol supplementation did not promote NEDA-3 status.

11.
Neurology ; 93(20): e1852-e1866, 2019 Nov 12.
Artigo em Inglês | MEDLINE | ID: mdl-31611336

RESUMO

OBJECTIVE: To characterize the distribution and regional evolution of cervical cord atrophy in patients with multiple sclerosis (MS) in a multicenter dataset. METHODS: MRI and clinical evaluations were acquired from 179 controls and 435 patients (35 clinically isolated syndromes [CIS], 259 relapsing-remitting multiple sclerosis [RRMS], 99 secondary progressive multiple sclerosis [SPMS], and 42 primary progressive multiple sclerosis [PPMS]). Sixty-nine controls and 178 patients underwent a 1-year MRI and clinical follow-up. Patients were classified as clinically stable/worsened according to their disability change. Longitudinal changes of cord atrophy were investigated with linear mixed-effect models. Sample size calculations were performed using age-, sex- and site-adjusted annualized percentage normalized cord cross-sectional area (CSAn) changes. RESULTS: Baseline CSAn was lower in patients with MS vs controls (p < 0.001), but not different between controls and patients with CIS or between patients with early RRMS (disease duration ≤5 years) and patients with CIS. Patients with late RRMS (disease duration >5 years) showed significant cord atrophy vs patients with early RRMS (p = 0.02). Patients with progressive MS had decreased CSAn (p < 0.001) vs patients with RRMS. Atrophy was located between C1/C2 and C5 in patients with RRMS vs patients with CIS, and widespread along the cord in patients with progressive MS vs patients with RRMS, with an additional C5/C6 involvement in patients with SPMS vs patients with PPMS. At follow-up, CSAn decreased in all phenotypes (p < 0.001), except CIS. Cord atrophy rates were highest in patients with early RRMS and clinically worsened patients, who had a more widespread cord involvement than stable patients. The sample size per arm required to detect a 50% treatment effect was 118 for patients with early RRMS. CONCLUSIONS: Cord atrophy increased in MS during 1 year, except for CIS. Faster atrophy contributed to explain clinical worsening.

12.
Neurology ; 93(17): e1635-e1646, 2019 Oct 22.
Artigo em Inglês | MEDLINE | ID: mdl-31597710

RESUMO

OBJECTIVE: To apply the ATN scheme to memory clinic patients, to assess whether it discriminates patient populations with specific features. METHODS: We included 305 memory clinic patients (33% subjective cognitive decline [SCD]: 60 ± 9 years, 61% M; 19% mild cognitive impairment [MCI]: 68 ± 9 years, 68% M; 48% dementia: 66 ± 10 years, 58% M) classified for positivity (±) of amyloid (A) ([18F]Florbetaben PET), tau (T) (CSF p-tau), and neurodegeneration (N) (medial temporal lobe atrophy). We assessed ATN profiles' demographic, clinical, and cognitive features at baseline, and cognitive decline over time. RESULTS: The proportion of A+T+N+ patients increased with syndrome severity (from 1% in SCD to 14% in MCI and 35% in dementia), while the opposite was true for A-T-N- (from 48% to 19% and 6%). Compared to A-T-N-, patients with the Alzheimer disease profiles (A+T+N- and A+T+N+) were older (both p < 0.05) and had a higher prevalence of APOE ε4 (both p < 0.05) and lower Mini-Mental State Examination (MMSE) (both p < 0.05), memory (both p < 0.05), and visuospatial abilities (both p < 0.05) at baseline. Non-Alzheimer profiles A-T-N+ and A-T+N+ showed more severe white matter hyperintensities (both p < 0.05) and worse language performance (both p < 0.05) than A-T-N-. A linear mixed model showed faster decline on MMSE over time in A+T+N- and A+T+N+ (p = 0.059 and p < 0.001 vs A-T-N-), attributable mainly to patients without dementia. CONCLUSIONS: The ATN scheme identified different biomarker profiles with overlapping baseline features and patterns of cognitive decline. The large number of profiles, which may have different implications in patients with vs without dementia, poses a challenge to the application of the ATN scheme.

13.
PLoS One ; 14(9): e0222939, 2019.
Artigo em Inglês | MEDLINE | ID: mdl-31560705

RESUMO

PURPOSE: During resections of brain tumors, neurosurgeons have to weigh the risk between residual tumor and damage to brain functions. Different perspectives on these risks result in practice variation. We present statistical methods to localize differences in extent of resection between institutions which should enable to reveal brain regions affected by such practice variation. METHODS: Synthetic data were generated by simulating spheres for brain, tumors, resection cavities, and an effect region in which a likelihood of surgical avoidance could be varied between institutions. Three statistical methods were investigated: a non-parametric permutation based approach, Fisher's exact test, and a full Bayesian Markov chain Monte Carlo (MCMC) model. For all three methods the false discovery rate (FDR) was determined as a function of the cut-off value for the q-value or the highest density interval, and receiver operating characteristic and precision recall curves were created. Sensitivity to variations in the parameters of the synthetic model were investigated. Finally, all these methods were applied to retrospectively collected data of 77 brain tumor resections in two academic hospitals. RESULTS: Fisher's method provided an accurate estimation of observed FDR in the synthetic data, whereas the permutation approach was too liberal and underestimated FDR. AUC values were similar for Fisher and Bayes methods, and superior to the permutation approach. Fisher's method deteriorated and became too liberal for reduced tumor size, a smaller size of the effect region, a lower overall extent of resection, fewer patients per cohort, and a smaller discrepancy in surgical avoidance probabilities between the different surgical practices. In the retrospective patient data, all three methods identified a similar effect region, with lower estimated FDR in Fisher's method than using the permutation method. CONCLUSIONS: Differences in surgical practice may be detected using voxel statistics. Fisher's test provides a fast method to localize differences but could underestimate true FDR. Bayesian MCMC is more flexible and easily extendable, and leads to similar results, but at increased computational cost.

14.
Neurology ; 93(19): e1778-e1786, 2019 Nov 05.
Artigo em Inglês | MEDLINE | ID: mdl-31484710

RESUMO

OBJECTIVE: To assess the onset of ocrelizumab efficacy on brain MRI measures of disease activity in the phase II study in relapsing-remitting multiple sclerosis (RRMS), and relapse rate in the pooled phase III studies in relapsing multiple sclerosis (RMS). METHODS: Brain MRI activity was determined in the phase II trial at monthly intervals in patients with RRMS receiving placebo, ocrelizumab (600 mg), or intramuscular interferon (IFN) ß-1a (30 µg). Annualized relapse rate (ARR; over various epochs) and time to first relapse were analyzed in the pooled population of the phase III OPERA (A Study of Ocrelizumab in Comparison With Interferon Beta-1a [Rebif] in Participants With Relapsing Multiple Sclerosis) I and OPERA II trials in patients with RMS receiving ocrelizumab (600 mg) or subcutaneous IFN-ß-1a (44 µg). RESULTS: In patients with RRMS, ocrelizumab reduced the number of new T1 gadolinium-enhancing lesions by week 4 vs placebo (p = 0.042) and by week 8 vs intramuscular IFN-ß-1a (p < 0.001). Ocrelizumab also reduced the number of new or enlarging T2 lesions appearing between weeks 4 and 8 vs both placebo and IFN-ß-1a (both p < 0.001). In patients with RMS, ocrelizumab significantly reduced ARR (p = 0.005) and the probability of time to first protocol-defined relapse (p = 0.014) vs subcutaneous IFN-ß-1a within the first 8 weeks. CONCLUSION: Epoch analysis of MRI-measured lesion activity in the phase II study and relapse rate in the phase III studies consistently revealed a rapid suppression of acute MRI and clinical disease activity following treatment initiation with ocrelizumab in patients with RRMS and RMS, respectively. CLASSIFICATION OF EVIDENCE: This study provides Class II evidence that for patients with RRMS and RMS, ocrelizumab suppressed MRI activity within 4 weeks and clinical disease activity within 8 weeks.

15.
Alzheimers Dement ; 15(11): 1478-1488, 2019 Nov.
Artigo em Inglês | MEDLINE | ID: mdl-31495601

RESUMO

INTRODUCTION: Plasma proteins have been widely studied as candidate biomarkers to predict brain amyloid deposition to increase recruitment efficiency in secondary prevention clinical trials for Alzheimer's disease. Most such biomarker studies are targeted to specific proteins or are biased toward high abundant proteins. METHODS: 4001 plasma proteins were measured in two groups of participants (discovery group = 516, replication group = 365) selected from the European Medical Information Framework for Alzheimer's disease Multimodal Biomarker Discovery study, all of whom had measures of amyloid. RESULTS: A panel of proteins (n = 44), along with age and apolipoprotein E (APOE) ε4, predicted brain amyloid deposition with good performance in both the discovery group (area under the curve = 0.78) and the replication group (area under the curve = 0.68). Furthermore, a causal relationship between amyloid and tau was confirmed by Mendelian randomization. DISCUSSION: The results suggest that high-dimensional plasma protein testing could be a useful and reproducible approach for measuring brain amyloid deposition.

16.
Brain ; 142(9): 2787-2799, 2019 Sep 01.
Artigo em Inglês | MEDLINE | ID: mdl-31497864

RESUMO

Chronic active and slowly expanding lesions with smouldering inflammation are neuropathological correlates of progressive multiple sclerosis pathology. T1 hypointense volume and signal intensity on T1-weighted MRI reflect brain tissue damage that may develop within newly formed acute focal inflammatory lesions or in chronic pre-existing lesions without signs of acute inflammation. Using a recently developed method to identify slowly expanding/evolving lesions in vivo from longitudinal conventional T2- and T1-weighted brain MRI scans, we measured the relative amount of chronic lesion activity as measured by change in T1 volume and intensity within slowly expanding/evolving lesions and non-slowly expanding/evolving lesion areas of baseline pre-existing T2 lesions, and assessed the effect of ocrelizumab on this outcome in patients with primary progressive multiple sclerosis participating in the phase III, randomized, placebo-controlled, double-blind ORATORIO study (n = 732, NCT01194570). We also assessed the predictive value of T1-weighted measures of chronic lesion activity for clinical multiple sclerosis progression as reflected by a composite disability measure including the Expanded Disability Status Scale, Timed 25-Foot Walk and 9-Hole Peg Test. We observed in this clinical trial population that most of total brain non-enhancing T1 hypointense lesion volume accumulation was derived from chronic lesion activity within pre-existing T2 lesions rather than new T2 lesion formation. There was a larger decrease in mean normalized T1 signal intensity and greater relative accumulation of T1 hypointense volume in slowly expanding/evolving lesions compared with non-slowly expanding/evolving lesions. Chronic white matter lesion activity measured by longitudinal T1 hypointense lesion volume accumulation in slowly expanding/evolving lesions and in non-slowly expanding/evolving lesion areas of pre-existing lesions predicted subsequent composite disability progression with consistent trends on all components of the composite. In contrast, whole brain volume loss and acute lesion activity measured by longitudinal T1 hypointense lesion volume accumulation in new focal T2 lesions did not predict subsequent composite disability progression in this trial at the population level. Ocrelizumab reduced longitudinal measures of chronic lesion activity such as T1 hypointense lesion volume accumulation and mean normalized T1 signal intensity decrease both within regions of pre-existing T2 lesions identified as slowly expanding/evolving and in non-slowly expanding/evolving lesions. Using conventional brain MRI, T1-weighted intensity-based measures of chronic white matter lesion activity predict clinical progression in primary progressive multiple sclerosis and may qualify as a longitudinal in vivo neuroimaging correlate of smouldering demyelination and axonal loss in chronic active lesions due to CNS-resident inflammation and/or secondary neurodegeneration across the multiple sclerosis disease continuum.

17.
Neurobiol Aging ; 2019 Aug 09.
Artigo em Inglês | MEDLINE | ID: mdl-31500909

RESUMO

White matter hyperintensities (WMHs) are a common manifestation of cerebral small vessel disease. WMHs are also frequently observed in patients with familial and sporadic Alzheimer's disease, often with a particular posterior predominance. Whether amyloid and tau pathologies are linked to WMH occurrence is still debated. We examined whether cerebral amyloid and tau burden, reflected in cerebrospinal fluid amyloid-beta 1-42 (Aß-42) and phosphorylated tau (p-tau), are related to WMH location in a cohort of 517 memory clinic patients. Two lesion mapping techniques were performed: voxel-based analyses and region of interest-based linear regression. Voxelwise associations were found between lower Aß-42 and parieto-occipital periventricular WMHs. Regression analyses demonstrated that lower Aß-42 correlated with larger WMH volumes in the splenium of the corpus callosum and posterior thalamic radiation, also after controlling for markers of vascular disease. P-tau was not consistently related to WMH occurrence. Our findings indicate that cerebral amyloid burden is associated with WMHs located in specific posterior white matter regions, possibly reflecting region-specific effects of amyloid pathology on the white matter.

18.
Neuro Oncol ; 2019 Sep 24.
Artigo em Inglês | MEDLINE | ID: mdl-31550353

RESUMO

BACKGROUND: Surgical resection and irradiation of diffuse glioma are guided by standard MRI: T2/FLAIR-weighted MRI for non-enhancing and T1-weighted gadolinium-enhanced (T1G) MRI for enhancing gliomas. Amino acid PET has been suggested as new standard. Imaging combinations may improve standard MRI and amino acid PET. The aim of the study was to determine the accuracy of imaging combinations to detect glioma infiltration. METHODS: We included 20 consecutive adults with newly-diagnosed non-enhancing (seven diffuse astrocytomas, IDH-mutant; one oligodendroglioma, IDH-mutant and1p/19q-codeleted; one glioblastoma IDH-wildtype) or enhancing glioma (glioblastoma, nine IDH-wildtype and two IDH-mutant). Standardized pre-operative imaging (T1-, T2-, FLAIR-weighted and T1G MRI, perfusion and diffusion MRI, MR spectroscopy and O-(2-[18F]-fluoroethyl)-L-tyrosine ([18F]FET) PET) was co-localized with multi-region stereotactic biopsies preceding resection. Tumor presence in the biopsies was assessed by two neuropathologists. Diagnostic accuracy was determined using receiver operating characteristic analysis. RESULTS: A total of 174 biopsies were obtained (63 from nine non-enhancing and 111 from 11 enhancing gliomas), of which 129 contained tumor (50 from non-enhancing and 79 from enhancing gliomas). In enhancing gliomas, the combination of Apparent Diffusion Coefficient (ADC) with [18F]FET PET (AUC, 95%CI: 0.89,0.79-0.99) detected tumor better than T1G MRI (0.56,0.39-0.72;P<.001) and [18F]FET PET (0.76,0.66-0.86;P=0.001). In non-enhancing gliomas, no imaging combination detected tumor significantly better than standard MRI. FLAIR-weighted MRI had an AUC of 0.81 (0.65-0.98) compared to 0.69 (0.56-0.81;P=0.019) for [18F]FET PET. CONCLUSION AND RELEVANCE: Combining ADC and [18F]FET PET detects glioma infiltration better than standard MRI and [18F]FET PET in enhancing gliomas, potentially enabling better guidance of local therapy.

19.
Neurology ; 93(14): e1348-e1359, 2019 Oct 01.
Artigo em Inglês | MEDLINE | ID: mdl-31484713

RESUMO

OBJECTIVE: To determine which pathologic process could be responsible for the acceleration of cognitive decline during the course of multiple sclerosis (MS), using longitudinal structural MRI, which was related to cognitive decline in relapsing-remitting MS (RRMS) and progressive MS (PMS). METHODS: A prospective cohort of 230 patients with MS (179 RRMS and 51 PMS) and 59 healthy controls was evaluated twice with 5-year (mean 4.9, SD 0.94) interval during which 22 patients with RRMS converted to PMS. Annual rates of cortical and deep gray matter atrophy as well as lesion volume increase were computed on longitudinal (3T) MRI data and correlated to the annual rate of cognitive decline as measured using an extensive cognitive evaluation at both time points. RESULTS: The deep gray matter atrophy rate did not differ between PMS and RRMS (-0.82%/year vs -0.71%/year, p = 0.11), while faster cortical atrophy was observed in PMS (-0.87%/year vs -0.48%/year, p < 0.01). Similarly, faster cognitive decline was observed in PMS compared to RRMS (p < 0.01). Annual cognitive decline was related to the rate of annual lesion volume increase in stable RRMS (r = -0.17, p = 0.03) to the rate of annual deep gray matter atrophy in converting RRMS (r = 0.50, p = 0.02) and annual cortical atrophy in PMS (r = 0.35, p = 0.01). CONCLUSIONS: These results indicate that cortical atrophy and cognitive decline accelerate together during the course of MS. Substrates of cognitive decline shifted from worsening lesional pathology in stable RRMS to deep gray matter atrophy in converting RRMS and to accelerated cortical atrophy in PMS only.

20.
Lancet Neurol ; 18(11): 1034-1044, 2019 Nov.
Artigo em Inglês | MEDLINE | ID: mdl-31526625

RESUMO

BACKGROUND: Biomarker-based risk predictions of dementia in people with mild cognitive impairment are highly relevant for care planning and to select patients for treatment when disease-modifying drugs become available. We aimed to establish robust prediction models of disease progression in people at risk of dementia. METHODS: In this modelling study, we included people with mild cognitive impairment (MCI) from single-centre and multicentre cohorts in Europe and North America: the European Medical Information Framework for Alzheimer's Disease (EMIF-AD; n=883), Alzheimer's Disease Neuroimaging Initiative (ADNI; n=829), Amsterdam Dementia Cohort (ADC; n=666), and the Swedish BioFINDER study (n=233). Inclusion criteria were a baseline diagnosis of MCI, at least 6 months of follow-up, and availability of a baseline Mini-Mental State Examination (MMSE) and MRI or CSF biomarker assessment. The primary endpoint was clinical progression to any type of dementia. We evaluated performance of previously developed risk prediction models-a demographics model, a hippocampal volume model, and a CSF biomarkers model-by evaluating them across cohorts, incorporating different biomarker measurement methods, and determining prognostic performance with Harrell's C statistic. We then updated the models by re-estimating parameters with and without centre-specific effects and evaluated model calibration by comparing observed and expected survival. Finally, we constructed a model combining markers for amyloid deposition, tauopathy, and neurodegeneration (ATN), in accordance with the National Institute on Aging and Alzheimer's Association research framework. FINDINGS: We included all 2611 individuals with MCI in the four cohorts, 1007 (39%) of whom progressed to dementia. The validated demographics model (Harrell's C 0·62, 95% CI 0·59-0·65), validated hippocampal volume model (0·67, 0·62-0·72), and updated CSF biomarkers model (0·72, 0·68-0·74) had adequate prognostic performance across cohorts and were well calibrated. The newly constructed ATN model had the highest performance (0·74, 0·71-0·76). INTERPRETATION: We generated risk models that are robust across cohorts, which adds to their potential clinical applicability. The models could aid clinicians in the interpretation of CSF biomarker and hippocampal volume results in individuals with MCI, and help research and clinical settings to prepare for a future of precision medicine in Alzheimer's disease. Future research should focus on the clinical utility of the models, particularly if their use affects participants' understanding, emotional wellbeing, and behaviour. FUNDING: ZonMW-Memorabel.

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