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- Emmert, Kirsten, et al.
(författare)
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Influence of Vascular Variant of the Posterior Cerebral Artery (PCA) on Cerebral Blood Flow, Vascular Response to CO2 and Static Functional Connectivity
- 2016
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Ingår i: PLOS ONE. - : Public Library of Science (PLoS). - 1932-6203. ; 11:8
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Tidskriftsartikel (refereegranskat)abstract
- Introduction The fetal origin of the posterior cerebral artery (fPCA) is a frequent vascular variant in 11-29% of the population. For the fPCA, blood flow in the PCA originates from the anterior instead of the posterior circulation. We tested whether this blood supply variant impacts the cerebral blood flow assessed by arterial spin labeling (ASL), cerebrovascular reserve as well as resting-state static functional connectivity (sFC) in the sense of a systematic confound. Methods The study included 385 healthy, elderly subjects (mean age: 74.18 years [range: 68.9-90.4]; 243 female). Participants were classified into normal vascular supply (n = 296, 76.88%), right fetal origin (n = 23, 5.97%), left fetal origin (n = 16, 4.16%), bilateral fetal origin (n = 4, 1.04%), and intermediate (n = 46, 11.95%, excluded from further analysis) groups. ASL-derived relative cerebral blood flow (relCBF) maps and cerebrovascular reserve (CVR) maps derived from a CO2 challenge with blocks of 7% CO2 were compared. Additionally, sFC between 90 regions of interest (ROIs) was compared between the groups. Results CVR was significantly reduced in subjects with ipsilateral fPCA, most prominently in the temporal lobe. ASL yielded a non-significant trend towards reduced relCBF in bilateral posterior watershed areas. In contrast, conventional atlas-based sFC did not differ between groups. Conclusions In conclusion, fPCA presence may bias the assessment of cerebrovascular reserve by reducing the response to CO2. In contrast, its effect on ASL-assessed baseline perfusion was marginal. Moreover, fPCA presence did not systematically impact resting-state sFC. Taken together, this data implies that perfusion variables should take into account the vascularization patterns.
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| 2. |
- Haller, Sven, et al.
(författare)
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Radiologic-Histopathologic Correlation of Cerebral Microbleeds Using Pre-Mortem and Post-Mortem MRI
- 2016
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Ingår i: PLOS ONE. - : Public Library of Science (PLoS). - 1932-6203. ; 11:12
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Tidskriftsartikel (refereegranskat)abstract
- INTRODUCTION: Cerebral microbleeds (CMB), also known as cerebral microhemorrhages, are small areas of susceptibility on brain magnetic resonance imaging (MRI), that are increasingly detected due to the higher availability of high-field MRI systems and dedicated pulse sequences. The prevalence of CMBs increases in cases with cognitive decline. The current investigation assessed the poorly investigated radiologic-histopathologic correlation of CMBs on MRI.METHODS: The local ethical committee approved the current investigation. We retrospectively assessed a consecutive series of 1303 autopsy cases hospitalized in Geneva University Hospitals between 2000-2014. Of 112 cases with pre-mortem T2* sequences, we included 25 cases (mean age 77.3 ± 9.6, 9 females) with at least one CMB. We compared pre-mortem CMBs with targeted histopathology and post-mortem MRI.RESULTS: 25 cases had 31 CMB lesions detected by pre-mortem MRI. 25 additional CMB were detected on histopathology. 4 CMBs on pre-mortem MRI were false positives, resulting in a total of 52 CMBs. 27 CMBs on pre-mortem MRI were confirmed on histopathology, corresponding to a sensitivity or true positive rate of 51.9% (95% CI 37.6-66.0%). The false negative rate of pre-mortem MRI was 48.1% (95% CI 34.0-62.4%). Post-mortem MRI showed only 3 cases with additional CMBs. Overall, pre-mortem MRI significantly underestimated CMBs (p = 0.0001).CONCLUSIONS: Routine clinical brain MRI underestimates the prevalence of CMBs by approximately 50%, and 12% of radiologic pre-mortem MRI CMBs were false positives. Post-mortem MRI confirmed that this discordance is not explained by microbleeds occurring after the pre-mortem MRI.
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| 3. |
- Meskaldji, Djalel-Eddine, et al.
(författare)
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Prediction of long-term memory scores in MCI based on resting-state fMRI
- 2016
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Ingår i: NeuroImage. - : Elsevier BV. - 2213-1582. ; 12, s. 785-795
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Tidskriftsartikel (refereegranskat)abstract
- Resting-state functional MRI (rs-fMRI) opens a window on large-scale organization of brain function. However, establishing relationships between resting-state brain activity and cognitive or clinical scores is still a difficult task, in particular in terms of prediction as would be meaningful for clinical applications such as early diagnosis of Alzheimer's disease. In this work, we employed partial least square regression under cross-validation scheme to predict episodic memory performance from functional connectivity (FC) patterns in a set of fifty-five MCI subjects for whom rs-fMRI acquisition and neuropsychological evaluation was carried out. We show that a newly introduced FC measure capturing the moments of anti-correlation between brain areas, discordance, contains key information to predict long-term memory scores in MCI patients, and performs better than standard measures of correlation to do so. Our results highlighted that stronger discordance within default mode network (DMN) areas, as well as across DMN, attentional and limbic networks, favor episodic memory performance in MCI.
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| 4. |
- Zhang, Han, et al.
(författare)
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Topographical Information-Based High-Order Functional Connectivity and Its Application in Abnormality Detection for Mild Cognitive Impairment
- 2016
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Ingår i: Journal of Alzheimer's Disease. - 1387-2877 .- 1875-8908. ; 54:3, s. 1095-1112
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Tidskriftsartikel (refereegranskat)abstract
- Temporal synchronization-based functional connectivity (FC) has long been used by the neuroscience community. However, topographical FC information may provide additional information to characterize the advanced relationship between two brain regions. Accordingly, we proposed a novel method, namely high-order functional connectivity (HOFC), to capture this second-level relationship using inter-regional resemblance of the FC topographical profiles. Specifically, HOFC first calculates an FC profile for each brain region, notably between the given brain region and other brain regions. Based on these FC profiles, a second layer of correlations is computed between all pairs of brain regions (i.e., correlation's correlation). On this basis, we generated an HOFC network, where "high-order" network properties were computed. We found that HOFC was discordant with the traditional FC in several links, indicating additional information being revealed by the new metrics. We applied HOFC to identify biomarkers for early detection of Alzheimer's disease by comparing 77 mild cognitive impairment patients with 89 healthy individuals (control group). Sensitivity in detection of group difference was consistently improved by similar to 25% using HOFC compared to using FC. An HOFC network analysis also provided complementary information to an FC network analysis. For example, HOFC between olfactory and orbitofrontal cortices was found significantly reduced in patients, besides extensive alterations in HOFC network properties. In conclusion, our results showed promise in using HOFC to comprehensively map the human brain connectome.
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