Midlife hypertension confers increased risk for cognitive impairment in late life. The sensitive period for risk exposure and extent that risk is mediated through amyloid or vascular-related ...mechanisms are poorly understood. We aimed to identify if, and when, blood pressure or change in blood pressure during adulthood were associated with late-life brain structure, pathology, and cognition.
Participants were from Insight 46, a neuroscience substudy of the ongoing longitudinal Medical Research Council National Survey of Health and Development, a birth cohort that initially comprised 5362 individuals born throughout mainland Britain in one week in 1946. Participants aged 69–71 years received T1 and FLAIR volumetric MRI, florbetapir amyloid-PET imaging, and cognitive assessment at University College London (London, UK); all participants were dementia-free. Blood pressure measurements had been collected at ages 36, 43, 53, 60–64, and 69 years. We also calculated blood pressure change variables between ages. Primary outcome measures were white matter hyperintensity volume (WMHV) quantified from multimodal MRI using an automated method, amyloid-β positivity or negativity using a standardised uptake value ratio approach, whole-brain and hippocampal volumes quantified from 3D-T1 MRI, and a composite cognitive score—the Preclinical Alzheimer Cognitive Composite (PACC). We investigated associations between blood pressure and blood pressure changes at and between 36, 43, 53, 60–64, and 69 years of age with WMHV using generalised linear models with a gamma distribution and log link function, amyloid-β status using logistic regression, whole-brain volume and hippocampal volumes using linear regression, and PACC score using linear regression, with adjustment for potential confounders.
Between May 28, 2015, and Jan 10, 2018, 502 individuals were assessed as part of Insight 46. 465 participants (238 51% men; mean age 70·7 years SD 0·7; 83 18% amyloid-β-positive) were included in imaging analyses. Higher systolic blood pressure (SBP) and diastolic blood pressure (DBP) at age 53 years and greater increases in SBP and DBP between 43 and 53 years were positively associated with WMHV at 69–71 years of age (increase in mean WMHV per 10 mm Hg greater SBP 7%, 95% CI 1–14, p=0·024; increase in mean WMHV per 10 mm Hg greater DBP 15%, 4–27, p=0·0057; increase in mean WMHV per one SD change in SBP 15%, 3–29, p=0·012; increase in mean WMHV per 1 SD change in DBP 15%, 3–30, p=0·017). Higher DBP at 43 years of age was associated with smaller whole-brain volume at 69–71 years of age (−6·9 mL per 10 mm Hg greater DBP, −11·9 to −1·9, p=0·0068), as were greater increases in DBP between 36 and 43 years of age (−6·5 mL per 1 SD change, −11·1 to −1·9, p=0·0054). Greater increases in SBP between 36 and 43 years of age were associated with smaller hippocampal volumes at 69–71 years of age (−0·03 mL per 1 SD change, −0·06 to −0·001, p=0·043). Neither absolute blood pressure nor change in blood pressure predicted amyloid-β status or PACC score at 69–71 years of age.
High and increasing blood pressure from early adulthood into midlife seems to be associated with increased WMHV and smaller brain volumes at 69–71 years of age. We found no evidence that blood pressure affected cognition or cerebral amyloid-β load at this age. Blood pressure monitoring and interventions might need to start around 40 years of age to maximise late-life brain health.
Alzheimer's Research UK, Medical Research Council, Dementias Platform UK, Wellcome Trust, Brain Research UK, Wolfson Foundation, Weston Brain Institute, Avid Radiopharmaceuticals.
Attenuation correction is an essential requirement for quantification of positron emission tomography (PET) data. In PET/CT acquisition systems, attenuation maps are derived from computed tomography ...(CT) images. However, in hybrid PET/MR scanners, magnetic resonance imaging (MRI) images do not directly provide a patient-specific attenuation map. The aim of the proposed work is to improve attenuation correction for PET/MR scanners by generating synthetic CTs and attenuation maps. The synthetic images are generated through a multi-atlas information propagation scheme, locally matching the MRI-derived patient's morphology to a database of MRI/CT pairs, using a local image similarity measure. Results show significant improvements in CT synthesis and PET reconstruction accuracy when compared to a segmentation method using an ultrashort-echo-time MRI sequence and to a simplified atlas-based method.
In functional magnetic resonance imaging, the brain's response to experimental manipulation is almost always assumed to be independent of endogenous oscillations. To test this, we addressed the ...possible interaction between cognitive task performance and endogenous fMRI oscillations in an experiment designed to answer two questions: 1) Does performance of a cognitively effortful task significantly change fractal scaling properties of fMRI time series compared to their values before task performance? 2) If so, can we relate the extent of task-related perturbation to the difficulty of the task?
Using a novel continuous acquisition "rest-task-rest" design, we found that endogenous dynamics tended to recover their pre-task parameter values relatively slowly, over the course of several minutes, following completion of one of two versions of the n-back working memory task and that the rate of recovery was slower following completion of the more demanding (n = 2) version of the task.
This result supports the model that endogenous low frequency oscillatory dynamics are relevant to the brain's response to exogenous stimulation. Moreover, it suggests that large-scale neurocognitive systems measured using fMRI, like the heart and other physiological systems subjected to external demands for enhanced performance, can take a considerable period of time to return to a stable baseline state.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
The release of
Tamarixia triozae
(Burks) (Hymenoptera: Eulophidae), a parasitoid of the potato psyllid,
Bactericera cockerelli
(Šulc) (Hemiptera: Triozidae)
,
resulted in the successful establishment ...of the parasitoid in New Zealand. The parasitoid was released at more than 30 sites by the final year of the three-year study throughout New Zealand. Its continued presence over the three-year study was confirmed in two regions (Hawke’s Bay and Canterbury). At one site in Canterbury, the parasitoid was released only in the first summer of this study (Nov. 2017–Feb. 2018). It was recovered from potato psyllid infested African boxthorn (
Lycium ferocissimum
Miers) foliage in the second and third summers at this site, demonstrating the parasitoid’s ability to survive over successive winters. We found
T. triozae
parasitized nymphs at 24 sites of the 86 potato psyllid host plant sites surveyed within a 25 km radius of known release sites in Hawke’s Bay. The parasitoid was found up to 24 km from the nearest known release site in Hawke’s Bay. In Canterbury, the parasitoid was found up to 0.6 km from a known release site. Parasitism rates of 13.7–15.6% were estimated based on two post-release survey methods employed in this study. The parasitoid also feeds on psyllid nymphs so its establishment may lead to helping to reduce or delay potato psyllid populations from reaching damaging levels. Long-term monitoring is needed to determine the consequences of importing
T. triozae
on populations of potato psyllid.
Purpose
To assess the quantitative accuracy of current MR attenuation correction (AC) methods in neurological PET, in comparison to data derived using CT AC.
Methods
This retrospective study included ...25 patients who were referred for a neurological FDG PET examination and were imaged sequentially by PET/CT and simultaneous PET/MR. Differences between activity concentrations derived using Dixon and ultrashort echo time (UTE) MR-based AC and those derived from CT AC were compared using volume of interest and voxel-based approaches. The same comparisons were also made using PET data represented as SUV ratios (SUVr) using grey matter cerebellum as the reference region.
Results
Extensive and statistically significant regional underestimations of activity concentrations were found with both Dixon AC (
P
< 0.001) and UTE AC (
P
< 0.001) in all brain regions when compared to CT AC. The greatest differences were found in the cortical grey matter (Dixon AC 21.3 %, UTE AC 15.7 %) and cerebellum (Dixon AC 19.8 %, UTE AC 17.3 %). The underestimation using UTE AC was significantly less than with Dixon AC (
P
< 0.001) in most regions. Voxel-based comparisons showed that all cortical grey matter and cerebellum uptake was underestimated with Dixon AC compared to CT AC. Using UTE AC the extent and significance of these differences were reduced. Inaccuracies in cerebellar activity concentrations led to a mixture of predominantly cortical underestimation and subcortical overestimation in SUVr PET data for both MR AC methodologies.
Conclusion
MR-based AC results in significant underestimation of activity concentrations throughout the brain, which makes the use of SUVr data difficult. These effects limit the quantitative accuracy of neurological PET/MR.
The differential diagnosis of parkinsonian disorders can be challenging, especially early in the disease course. PET imaging with
18F-fluorodeoxyglucose (FDG) has been used to identify ...characteristic patterns of regional glucose metabolism in patient cohorts with idiopathic Parkinson's disease (PD), as well as variant forms of parkinsonism such as multiple system atrophy (MSA), progressive supranuclear palsy (PSP), and corticobasal degeneration (CBGD). In this study, we assessed the utility of FDG PET in the differential diagnosis of individual patients with clinical parkinsonism.
135 parkinsonian patients were referred for FDG PET to determine whether their diagnosis could be made accurately based upon their scans. Imaging-based diagnosis was obtained by visual assessment of the individual scans and also by computer-assisted interpretation. The results were compared with 2-year follow-up clinical assessments made by independent movement disorders specialists who were blinded to the original PET findings.
We found that blinded computer assessment agreed with clinical diagnosis in 92.4% of all subjects (97.7% early PD, 91.6% late PD, 96% MSA, 85% PSP, 90.1% CBGD, 86.5% healthy control subjects). Concordance of visual inspection with clinical diagnosis was achieved in 85.4% of the patients scanned (88.4% early PD, 97.2% late PD, 76% MSA, 60% PSP, 90.9% CBGD, 90.9% healthy control subjects).
This study demonstrates that FDG PET performed at the time of initial referral for parkinsonism accurately predicted the clinical diagnosis of individual patients made at subsequent follow-up. Computer-assisted methodologies may be particularly helpful in situations where experienced readers of FDG PET images are not readily available.
•Preoperative glioma molecular subtyping impacts on the prognosis, surgical strategy and adjuvant therapy.•Filtration-histogram texture analysis to identify glioma IDH and 1p19q status could be ...suitable for clinical application.•T1+Gad, T2 and ADC texture parameters may support the distinction of glioma types.
Background: To determine if filtration-histogram based texture analysis (MRTA) of clinical MR imaging can non-invasively identify molecular subtypes of untreated gliomas.
Methods: Post Gadolinium T1-weighted (T1+Gad) images, T2-weighted (T2) images and apparent diffusion coefficient (ADC) maps of 97 gliomas (54 = WHO II, 20 = WHO III, 23 = WHO IV) between 2010 and 2016 were studied. Whole-tumor segmentations were performed on a proprietary texture analysis research platform (TexRAD, Cambridge, UK) using the software’s freehand drawing tool. MRTA commences with a filtration step, followed by quantification of texture using histogram texture parameters. Results were correlated using non-parametric statistics with a logistic regression model generated.
Results: T1+Gad performed best for IDH typing of glioblastoma (sensitivity 91.9%, specificity 100%, AUC 0.945) and ADC for non-Gadolinium-enhancing gliomas (sensitivity 85.7%, specificity 78.4%, AUC 0.877). T2 was moderately precise (sensitivity 83.1%, specificity 78.9%, AUC 0.821). Excellent results for IDH typing were achieved from a combination of the three sequences (sensitivity 90.5%, specificity 94.5%, AUC = 0.98). For discriminating 1p19q genotypes, ADC produced the best results using unfiltered textures (sensitivity 80.6%, specificity 89.3%, AUC 0.811).
Conclusion: Preoperative glioma genotyping with MRTA appears valuable with potential for clinical translation. The optimal choice of texture parameters is influenced by sequence choice, tumour morphology and segmentation method.
•Novel methodology and software for MR-PET registration uncertainty analysis.•Registration software had the biggest effect on MR-PET registration precision, followed by reconstruction parameters ...(i.e., iterations, smoothing) and PET count level.•PVC can significantly improve the PET signal, but since it relies on precise MR-PET registration, it also increases PET signal variability and hence care should be taken when using it.
Accurate regional brain quantitative PET measurements, particularly when using partial volume correction, rely on robust image registration between PET and MR images. We argue here that the precision, and hence the uncertainty, of MR-PET image registration is mainly driven by the registration implementation and the quality of PET images due to their lower resolution and higher noise compared to the structural MR images. We propose a dedicated uncertainty analysis for quantifying the precision of MR-PET registration, centred around the bootstrap resampling of PET list-mode events to generate multiple PET image realisations with different noise (count) levels. The effects of PET image reconstruction parameters, such as the use of attenuation and scatter corrections and different number of iterations, on the precision and accuracy of MR-PET registration were investigated. In addition, the performance of four software packages with their default settings for rigid inter-modality image registration were considered: NiftyReg, Vinci, FSL and SPM. Four distinct PET image distributions made of two early time frames (similar to cortical FDG) and two late frames using two amyloid PET dynamic acquisitions of one amyloid positive and one amyloid negative participants were investigated.
For the investigated four PET frames, the biggest impact on the uncertainty was observed between registration software packages (up to 10-fold difference in precision) followed by the reconstruction parameters. On average, the lowest uncertainty for different PET frames and brain regions was observed with SPM and two iterations of fully quantitative image reconstruction. The observed uncertainty for the varying PET count-level (from 5% to 60%) was slightly lower than for the reconstruction parameters. We also observed that the registration uncertainty in quantitative PET analysis depends on amyloid status of the considered PET frames, with increased uncertainty (up to three times) when using post-reconstruction partial volume correction. This analysis is applicable for PET data obtained from either PET/MR or PET/CT scanners.
We present a standalone, scalable and high-throughput software platform for PET image reconstruction and analysis. We focus on high fidelity modelling of the acquisition processes to provide high ...accuracy and precision quantitative imaging, especially for large axial field of view scanners. All the core routines are implemented using parallel computing available from within the Python package
NiftyPET
, enabling easy access, manipulation and visualisation of data at any processing stage. The pipeline of the platform starts from MR and raw PET input data and is divided into the following processing stages: (1) list-mode data processing; (2) accurate attenuation coefficient map generation; (3) detector normalisation; (4) exact forward and back projection between sinogram and image space; (5) estimation of reduced-variance random events; (6) high accuracy fully 3D estimation of scatter events; (7) voxel-based partial volume correction; (8) region- and voxel-level image analysis. We demonstrate the advantages of this platform using an amyloid brain scan where all the processing is executed from a single and uniform computational environment in Python. The high accuracy acquisition modelling is achieved through span-1 (no axial compression) ray tracing for true, random and scatter events. Furthermore, the platform offers uncertainty estimation of any image derived statistic to facilitate robust tracking of subtle physiological changes in longitudinal studies. The platform also supports the development of new reconstruction and analysis algorithms through restricting the axial field of view to any set of rings covering a region of interest and thus performing fully 3D reconstruction and corrections using real data significantly faster. All the software is available as open source with the accompanying wiki-page and test data.
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