| 1. |
- Salvadó, Gemma, et al.
(author)
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The protective gene dose effect of the APOE ε2 allele on gray matter volume in cognitively unimpaired individuals
- 2022
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In: Alzheimer's and Dementia. - : Wiley. - 1552-5260 .- 1552-5279. ; 18:7, s. 1383-1395
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Journal article (peer-reviewed)abstract
- Introduction: Harboring two copies of the apolipoprotein E (APOE) ε2 allele strongly protects against Alzheimer's disease (AD). However, the effect of this genotype on gray matter (GM) volume in cognitively unimpaired individuals has not yet been described. Methods: Multicenter brain magnetic resonance images (MRIs) from cognitively unimpaired ε2 homozygotes were matched (1:1) against all other APOE genotypes for relevant confounders (n = 223). GM volumes of ε2 genotypic groups were compared to each other and to the reference group (APOE ε3/ε3). Results: Carrying at least one ε2 allele was associated with larger GM volumes in brain areas typically affected by AD and also in areas associated with cognitive resilience. APOE ε2 homozygotes, but not APOE ε2 heterozygotes, showed larger GM volumes in areas related to successful aging. Discussion: In addition to the known resistance against amyloid-β deposition, the larger GM volumes in key brain regions may confer APOE ε2 homozygotes additional protection against AD-related cognitive decline.
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| 2. |
- Lerch, Ondrej, et al.
(author)
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Predicting progression from subjective cognitive decline to mild cognitive impairment or dementia based on brain atrophy patterns
- 2024
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In: Alzheimer's Research and Therapy. - 1758-9193. ; 16:1
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Journal article (peer-reviewed)abstract
- Background: Alzheimer’s disease (AD) is a progressive neurodegenerative disorder where pathophysiological changes begin decades before the onset of clinical symptoms. Analysis of brain atrophy patterns using structural MRI and multivariate data analysis are an effective tool in identifying patients with subjective cognitive decline (SCD) at higher risk of progression to AD dementia. Atrophy patterns obtained from models trained to classify advanced AD versus normal subjects, may not be optimal for subjects at an early stage, like SCD. In this study, we compared the accuracy of the SCD progression prediction using the ‘severity index’ generated using a standard classification model trained on patients with AD dementia versus a new model trained on β-amyloid (Aβ) positive patients with amnestic mild cognitive impairment (aMCI). Methods: We used structural MRI data of 504 patients from the Swedish BioFINDER-1 study cohort (cognitively normal (CN), Aβ-negative = 220; SCD, Aβ positive and negative = 139; aMCI, Aβ-positive = 106; AD dementia = 39). We applied multivariate data analysis to create two predictive models trained to discriminate CN individuals from either individuals with Aβ positive aMCI or AD dementia. Models were applied to individuals with SCD to classify their atrophy patterns as either high-risk “disease-like” or low-risk “CN-like”. Clinical trajectory and model accuracy were evaluated using 8 years of longitudinal data. Results: In predicting progression from SCD to MCI or dementia, the standard, dementia-based model, reached 100% specificity but only 10.6% sensitivity, while the new, aMCI-based model, reached 72.3% sensitivity and 60.9% specificity. The aMCI-based model was superior in predicting progression from SCD to MCI or dementia, reaching a higher receiver operating characteristic area under curve (AUC = 0.72; P = 0.037) in comparison with the dementia-based model (AUC = 0.57). Conclusion: When predicting conversion from SCD to MCI or dementia using structural MRI data, prediction models based on individuals with milder levels of atrophy (i.e. aMCI) may offer superior clinical value compared to standard dementia-based models.
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| 3. |
- Mårtensson, Gustav, et al.
(author)
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Medial temporal atrophy in preclinical dementia : Visual and automated assessment during six year follow-up
- 2020
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In: NeuroImage: Clinical. - : Elsevier BV. - 2213-1582. ; 27
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Journal article (peer-reviewed)abstract
- Medial temporal lobe (MTL) atrophy is an important morphological marker of many dementias and is closely related to cognitive decline. In this study we aimed to characterize longitudinal progression of MTL atrophy in 93 individuals with subjective cognitive decline and mild cognitive impairment followed up over six years, and to assess if clinical rating scales are able to detect these changes. All MRI images were visually rated according to Scheltens’ scale of medial temporal atrophy (MTA) by two neuroradiologists and AVRA, a software for automated MTA ratings. The images were also segmented using FreeSurfer's longitudinal pipeline in order to compare the MTA ratings to volumes of the hippocampi and inferior lateral ventricles. We found that MTL atrophy rates increased with CSF biomarker abnormality, used to define preclinical stages of Alzheimer's Disease. Both AVRA's and the radiologists’ MTA ratings showed similar longitudinal trends as the subcortical volumes, suggesting that visual rating scales provide a valid alternative to automatic segmentations. Our results further showed that it took more than 8 years on average for individuals with mild cognitive impairment, and an Alzheimer's disease biomarker profile, to increase the MTA score by one. This suggests that discrete MTA ratings are too coarse for tracking individual MTL atrophy in short time spans. While the MTA scores from each radiologist showed strong correlations to subcortical volumes, the inter-rater agreement was low. We conclude that the main limitation of quantifying MTL atrophy with visual ratings in clinics is the subjectiveness of the assessment.
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| 4. |
- Pereira, Joana B., et al.
(author)
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Abnormal structural brain connectome in individuals with preclinical Alzheimer's disease
- 2018
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In: Cerebral Cortex. - : Oxford University Press (OUP). - 1047-3211 .- 1460-2199. ; 28:10, s. 3638-3649
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Journal article (peer-reviewed)abstract
- Alzheimer's disease has a long preclinical phase during which amyloid pathology and neurodegeneration accumulate in the brain without producing overt cognitive deficits. It is currently unclear whether these early disease stages are associated with a progressive disruption in the communication between brain regions that subsequently leads to cognitive decline and dementia. In this study we assessed the organization of structural networks in cognitively normal (CN) individuals harboring amyloid pathology (A+N-), neurodegeneration (A-N+), or both (A+N+) from the prospective and longitudinal Swedish BioFINDER study. We combined graph theory with diffusion tensor imaging to investigate integration, segregation, and centrality measures in the brain connectome in the previous groups. At baseline, our findings revealed a disrupted network topology characterized by longer paths, lower efficiency, increased clustering and modularity in CN A-N+ and CN A+N+, but not in CN A+N-. After 2 years, CN A+N+ showed significant abnormalities in all global network measures, whereas CN A-N+ only showed abnormalities in the global efficiency. Network connectivity and organization were associated with memory in CN A+N+ individuals. Altogether, our findings suggest that amyloid pathology is not sufficient to disrupt structural network topology, whereas neurodegeneration is.
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| 5. |
- Pereira, Joana B., et al.
(author)
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Amyloid network topology characterizes the progression of Alzheimer's disease during the predementia stages
- 2018
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In: Cerebral Cortex. - : Oxford University Press (OUP). - 1047-3211 .- 1460-2199. ; 28:1, s. 340-349
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Journal article (peer-reviewed)abstract
- There is increasing evidence showing that the accumulation of the amyloid-β (Aβ) peptide into extracellular plaques is a central event in Alzheimer's disease (AD). These abnormalities can be detected as lowered levels of Aβ42 in the cerebrospinal fluid (CSF) and are followed by increased amyloid burden on positron emission tomography (PET) several years before the onset of dementia. The aim of this study was to assess amyloid network topology in nondemented individuals with early stage Aβ accumulation, defined as abnormal CSF Aβ42 levels and normal Florbetapir PET (CSF+/PET-), and more advanced Aβ accumulation, defined as both abnormal CSF Aβ42 and Florbetapir PET (CSF+/PET+). The amyloid networks were built using correlations in the mean 18F-florbetapir PET values between 72 brain regions and analyzed using graph theory analyses. Our findings showed an association between early amyloid stages and increased covariance as well as shorter paths between several brain areas that overlapped with the default-mode network (DMN). Moreover, we found that individuals with more advanced amyloid accumulation showedmore widespread changes in brain regions both within and outside the DMN. These findings suggest that amyloid network topology could potentially be used to assess disease progression in the predementia stages of AD.
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| 6. |
- Pereira, Joana B., et al.
(author)
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Longitudinal degeneration of the basal forebrain predicts subsequent dementia in Parkinson's disease
- 2020
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In: Neurobiology of Disease. - : Elsevier BV. - 0969-9961 .- 1095-953X. ; 139
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Journal article (peer-reviewed)abstract
- Objectives: Cholinergic dysfunction plays a prominent role in cognitive impairment in Parkinson's disease (PD). The aim of this study was to assess the relationship of baseline and longitudinal basal forebrain atrophy with cognitive decline and dementia in PD. Methods: We included 106 non-demented PD patients, 19 PD dementia (PDD) patients and 42 controls with longitudinal structural MRI and cognitive testing. After 4.2 ± 1.8 years, 20 non-demented PD patients were diagnosed with dementia (PD-dementia converters), whereas the rest of PD patients remained non-demented (stable-PD). We compared MRI volumes of the medial septum/diagonal band (Ch1/Ch2) and nucleus basalis of Meynert (Ch4) between groups. Cox regression analyses were applied to test whether Ch1/Ch2 or Ch4 atrophy could predict future dementia and linear mixed models assessed their association with cognitive decline. Results: Compared to controls, we found reduced Ch4 baseline volumes in PD-dementia converters (p =.003) and those who already had PDD (p <.001) but not in stable-PD. Over time, there was a greater loss in Ch1/Ch2 volumes in PD-dementia converters and PDD compared to the other groups (p =.004). Baseline and longitudinal Ch4 volumes were associated with cognition (p <.002) and longitudinal Ch4 atrophy predicted future dementia (p =.009). Conclusions: Atrophy of Ch4 precedes and predicts future dementia in PD and is followed by changes in Ch1/Ch2, reflecting a posterior-anterior pattern of basal forebrain atrophy. This pattern could be used to track the spread of cholinergic degeneration and identify patients at risk of developing dementia.
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| 7. |
- Sjöström, Henrik, et al.
(author)
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Putaminal T1/T2-weighted ratio is increased in PSP compared to PD and healthy controls, a multi-cohort study
- 2024
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In: Parkinsonism and Related Disorders. - 1353-8020 .- 1873-5126. ; 121
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Journal article (peer-reviewed)abstract
- Introduction: Differentiating Parkinson's disease (PD) from progressive supranuclear palsy (PSP) and multiple system atrophy (MSA) is a common clinical problem. We aimed to apply the T1-/T2-weighted ratio imaging technique, based on standard clinical MRI, to reveal differences in neurodegeneration in three large cohorts. Methods: Three cohorts, with a total of 405 participants (269 PD, 44 PSP, 38 MSA, 54 controls), were combined and T1/T2-weighted ratio image analyses were carried out. A combination of automatic segmentation and atlas-based ROI were used in this study. The cohorts were combined using the ComBat batch correction procedure. Results: Group differences were found in the putamen (p = 0.040), with higher T1/T2-weighted ratio in this region in PSP compared to PD and healthy controls (p-values 0.010 and 0.007 respectively). Using putaminal T1/T2-weighted ratio for diagnostic separation, a fair performance was found in separating PSP from healthy controls, with an area under the receiver operating characteristic curve of 0.701. Conclusion: Different patterns of T1/T2-weighted ratio, reflecting differences in underlying pathophysiology, were found between the groups. Since T1/T2-weighted ratio can be applied to standard clinical MRI sequences to allow more quantitative analyses, this seems to be a promising biomarker for diagnostics and treatment evaluation of parkinsonian disorders for clinical trials.
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| 8. |
- Srikrishna, Meera, et al.
(author)
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Deep learning from MRI-derived labels enables automatic brain tissue classification on human brain CT
- 2021
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In: NeuroImage. - : Elsevier BV. - 1053-8119 .- 1095-9572. ; 244
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Journal article (peer-reviewed)abstract
- Automatic methods for feature extraction, volumetry, and morphometric analysis in clinical neuroscience typically operate on images obtained with magnetic resonance (MR) imaging equipment. Although CT scans are less expensive to acquire and more widely available than MR scans, their application is currently limited to the visual assessment of brain integrity and the exclusion of co-pathologies. CT has rarely been used for tissue classification because the contrast between grey matter and white matter was considered insufficient. In this study, we propose an automatic method for segmenting grey matter (GM), white matter (WM), cerebrospinal fluid (CSF), and intracranial volume (ICV) from head CT images. A U-Net deep learning model was trained and validated on CT images with MRI-derived segmentation labels. We used data from 744 participants of the Gothenburg H70 Birth Cohort Studies for whom CT and T1-weighted MR images had been acquired on the same day. Our proposed model predicted brain tissue classes accurately from unseen CT images (Dice coefficients of 0.79, 0.82, 0.75, 0.93 and 0.98 for GM, WM, CSF, brain volume and ICV, respectively). To contextualize these results, we generated benchmarks based on established MR-based methods and intentional image degradation. Our findings demonstrate that CT-derived segmentations can be used to delineate and quantify brain tissues, opening new possibilities for the use of CT in clinical practice and research.
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| 9. |
- Voevodskaya, Olga, et al.
(author)
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Altered structural network organization in cognitively normal individuals with amyloid pathology
- 2018
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In: Neurobiology of Aging. - : Elsevier BV. - 0197-4580 .- 1558-1497. ; 64, s. 15-24
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Journal article (peer-reviewed)abstract
- Recent findings show that structural network topology is disrupted in Alzheimer’s disease (AD), with changes occurring already at the prodromal disease stages. Amyloid accumulation, a hallmark of AD, begins several decades before symptom onset and its effects on brain connectivity at the earliest disease stages is not fully known. We studied global and local network changes in a large cohort of cognitively healthy individuals (N=299, Swedish BioFINDER study) with and without β-amyloid (Aβ) pathology (based on cerebrospinal fluid Aβ42/Aβ40 levels). Structural correlation matrices were constructed based on MRI cortical thickness data. Despite the fact that no significant regional cortical atrophy was found in the Aβ-positive group, this group exhibited an altered global network organization, including decreased global efficiency and modularity. At the local level, Aβ-positive individuals displayed fewer and more disorganized modules as well as a loss of hubs. Our findings suggest that changes in network topology occur already at the presymptomatic (preclinical) stage of AD and may precede detectable cortical thinning.
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| 10. |
- Wahlund, Lars-Olof, et al.
(author)
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Strukturell hjärnavbildning kan förbättra diagnostiken vid demens
- 2013
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In: Läkartidningen. - 0023-7205 .- 1652-7518. ; 110:CEY4
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Journal article (peer-reviewed)abstract
- Ökad kunskap om demenssjukdomar leder till att de diagnostiska kriterierna förändras. Diagnostiken kan förbättras med hjälp av hjärnavbildningsfynd.Med datortomografi (DT) och magnetisk resonanstomografi (MRT) kan medial temporallobsatrofi, global cerebral atrofi och förändringar i vit substans visualiseras och kvantifieras.För att ge optimal information om dessa förändringar krävs ett strukturerat radiologiskt DT-/MR-utlåtande. Imaging Cognitive Impairment Network (ICINET) har som huvudmål att föreslå ett standardiserat MRT-protokoll och kliniska utvärderingsverktyg (visuella skattningsskalor för MRT och DT).
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