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1.
Pediatr Res ; 2021 Feb 24.
Artigo em Inglês | MEDLINE | ID: mdl-33627820

RESUMO

BACKGROUND: This study aimed to identify which MRI and clinical assessments, alone or in combination, from (i) early (32 weeks postmenstrual age, PMA), (ii) term equivalent age (TEA) and (iii) 3 months corrected age (CA) are associated with motor or cognitive outcomes at 2 years CA in infants born <31 weeks gestation. METHODS: Prospective cohort study of 98 infants who underwent early and TEA MRI (n = 59 males; median birth gestational age 28 + 5 weeks). Hammersmith Neonatal Neurological Examination (HNNE), NICU Neonatal Neurobehavioural Scale and General Movements Assessment (GMs) were performed early and at TEA. Premie-Neuro was performed early and GMs, Test of Infant Motor Performance and visual assessment were performed at TEA and 3 months CA. Neurodevelopmental outcomes were determined using Bayley Scales of Infant and Toddler Development 3rd edition. RESULTS: The best combined motor outcome model included 3-month GMs (ß = -11.41; 95% CI = -17.34, -5.49), TEA MRI deep grey matter score (ß = -6.23; 95% CI = -9.47, -2.99) and early HNNE reflexes (ß = 3.51; 95% CI = 0.86, 6.16). Combined cognitive model included 3-month GMs (ß = -10.01; 95% CI = -15.90, -4.12) and TEA HNNE score (ß = 1.33; 95% CI = 0.57, 2.08). CONCLUSION: Early neonatal neurological assessment improves associations with motor outcomes when combined with term MRI and 3-month GMs. Term neurological assessment combined with 3-month GMs improves associations with cognitive outcomes. IMPACT: We present associations between 32- and 40-week MRI, comprehensive clinical assessments and later 2-year motor and cognitive outcomes for children born <31 weeks gestation. MRI and clinical assessment of motor, neurological and neurobehavioural function earlier than term equivalent age in very preterm infants is safe and becoming more available in clinical settings. Most of these children are discharged from hospital before term age and so completing assessments prior to discharge can assist with follow up. MRI and neurological assessment prior to term equivalent age while the child is still in hospital can provide earlier identification of children at highest risk of adverse outcomes and guide follow-up screening and intervention services.

2.
IEEE Trans Med Imaging ; PP2021 Feb 03.
Artigo em Inglês | MEDLINE | ID: mdl-33534704

RESUMO

In clinics, the information about the appearance and location of brain tumors is essential to assist doctors in diagnosis and treatment. Automatic brain tumor segmentation on the images acquired by magnetic resonance imaging (MRI) is a common way to attain this information. However, MR images are not quantitative and can exhibit significant variation in signal depending on a range of factors, which increases the difficulty of training an automatic segmentation network and applying it to new MR images. To deal with this issue, this paper proposes to learn a sample-adaptive intensity lookup table (LuT) that dynamically transforms the intensity contrast of each input MR image to adapt to the following segmentation task. Specifically, the proposed deep SA-LuT-Net framework consists of a LuT module and a segmentation module, trained in an end-to-end manner: the LuT module learns a sample-specific nonlinear intensity mapping function through communication with the segmentation module, aiming at improving the final segmentation performance. In order to make the LuT learning sample-adaptive, we parameterize the intensity mapping function by exploring two families of non-linear functions (i.e., piece-wise linear and power functions) and predict the function parameters for each given sample. These sample-specific parameters make the intensity mapping adaptive to samples. We develop our SA-LuT-Nets separately based on two backbone networks for segmentation, i.e., DMFNet and the modified 3D Unet, and validate them on BRATS2018 and BRATS2019 datasets for brain tumor segmentation. Our experimental results clearly demonstrate the superior performance of the proposed SA-LuT-Nets using either single or multiple MR modalities. It not only significantly improves the two baselines (DMFNet and the modified 3D Unet), but also wins a set of state-of-the-art segmentation methods. Moreover, we show that, the LuTs learnt using one segmentation model could also be applied to improving the performance of another segmentation model, indicating the general segmentation information captured by LuTs.

3.
Artigo em Inglês | MEDLINE | ID: mdl-33495928

RESUMO

PURPOSE: Previous studies have shown that Aß-amyloid (Aß) likely promotes tau to spread beyond the medial temporal lobe. However, the Aß levels necessary for tau to spread in the neocortex is still unclear. METHODS: Four hundred sixty-six participants underwent tau imaging with [18F]MK6420 and Aß imaging with [18F]NAV4694. Aß scans were quantified on the Centiloid (CL) scale with a cut-off of 25 CL for abnormal levels of Aß (A+). Tau scans were quantified in three regions of interest (ROI) (mesial temporal (Me); temporoparietal neocortex (Te); and rest of neocortex (R)) and four mesial temporal region (entorhinal cortex, amygdala, hippocampus, and parahippocampus). Regional tau thresholds were established as the 95%ile of the cognitively unimpaired A- subjects. The prevalence of abnormal tau levels (T+) along the Centiloid continuum was determined. RESULTS: The plots of prevalence of T+ show earlier and greater increase along the Centiloid continuum in the medial temporal area compared to neocortex. Prevalence of T+ was low but associated with Aß level between 10 and 40 CL reaching 23% in Me, 15% in Te, and 11% in R. Between 40 and 70 CL, the prevalence of T+ subjects per CL increased fourfold faster and at 70 CL was 64% in Me, 51% in Te, and 37% in R. In cognitively unimpaired, there were no T+ in R below 50 CL. The highest prevalence of T+ were found in the entorhinal cortex, reaching 40% at 40 CL and 80% at 60 CL. CONCLUSION: Outside the entorhinal cortex, abnormal levels of cortical tau on PET are rarely found with Aß below 40 CL. Above 40 CL prevalence of T+ accelerates in all areas. Moderate Aß levels are required before abnormal neocortical tau becomes detectable.

4.
Neuroimage Clin ; 29: 102527, 2021.
Artigo em Inglês | MEDLINE | ID: mdl-33341723

RESUMO

This prospective cohort study, "Prospective Imaging Study of Ageing: Genes, Brain and Behaviour" (PISA) seeks to characterise the phenotype and natural history of healthy adult Australians at high future risk of Alzheimer's disease (AD). In particular, we are recruiting midlife and older Australians with high and low genetic risk of dementia to discover biological markers of early neuropathology, identify modifiable risk factors, and establish the very earliest phenotypic and neuronal signs of disease onset. PISA utilises genetic prediction to recruit and enrich a prospective cohort and follow them longitudinally. Online surveys and cognitive testing are used to characterise an Australia-wide sample currently totalling over 3800 participants. Participants from a defined at-risk cohort and positive controls (clinical cohort of patients with mild cognitive impairment or early AD) are invited for onsite visits for detailed functional, structural and molecular neuroimaging, lifestyle monitoring, detailed neurocognitive testing, plus blood sample donation. This paper describes recruitment of the PISA cohort, study methodology and baseline demographics.

5.
J Biomech ; 115: 110163, 2021 Jan 22.
Artigo em Inglês | MEDLINE | ID: mdl-33338974

RESUMO

Finite element analysis (FEA) provides a powerful approach for estimating the in-vivo loading characteristics of the hip joint during various locomotory and functional activities. However, time-consuming procedures, such as the generation of high-quality FE meshes and setup of FE simulation, typically make the method impractical for rapid applications which could be used in clinical routine. Alternatively, discrete element analysis (DEA) has been developed to quantify mechanical conditions of the hip joint in a fraction of time compared to FEA. Although DEA has proven effective in the estimation of contact stresses and areas in various complex applications, it has not yet been well characterised by its ability to evaluate contact mechanics for the hip joint during gait cycle loading using data from several individuals. The objective of this work was to compare DEA modelling against well-established FEA for analysing contact mechanics of the hip joint during walking gait. Subject-specific models were generated from magnetic resonance images of the hip joints in five asymptomatic subjects. The DEA and FEA models were then simulated for 13 loading time-points extracted from a full gait cycle. Computationally, DEA was substantially more efficient compared to FEA (simulation times of seconds vs. hours). The DEA and FEA methods had similar predictions for contact pressure distribution for the hip joint during normal walking. In all 13 simulated loading time-points across five subjects, the maximum difference in average contact pressures between DEA and FEA was within ±0.06 MPa. Furthermore, the difference in contact area ratio computed using DEA and FEA was less than ±6%.

6.
Magn Reson Med ; 85(3): 1364-1378, 2021 Mar.
Artigo em Inglês | MEDLINE | ID: mdl-32989788

RESUMO

PURPOSE: To demonstrate that fluid and white matter suppression (FLAWS) imaging can be used for high-resolution T1 mapping with low transmitted bias field ( B 1 + ) sensitivity at 7T. METHODS: The FLAWS sequence was optimized for 0.8-mm isotropic resolution imaging. The theoretical accuracy and precision of the FLAWS T1 mapping was compared with the one of the magnetization-prepared two rapid gradient echoes (MP2RAGE) sequence optimized for low B 1 + sensitivity. FLAWS images were acquired at 7T on six healthy volunteers (21 to 48 years old; two women). MP2RAGE and saturation-prepared with two rapid gradient echoes (SA2RAGE) datasets were also acquired to obtain T1 mapping references and B 1 + maps. The contrast-to-noise ratio (CNR) between brain tissues was measured in the FLAWS-hco and MP2RAGE-uni images. The Pearson correlation was measured between the MP2RAGE and FLAWS T1 maps. The effect of B 1 + on FLAWS T1 mapping was assessed using the Pearson correlation. RESULTS: The FLAWS-hco images were characterized by a higher brain tissue CNR ( CNR WM / GM = 5.5 , CNR WM / CSF = 14.7 , CNR GM / CSF = 10.3 ) than the MP2RAGE-uni images ( CNR WM / GM = 4.9 , CNR WM / CSF = 6.6 , CNR GM / CSF = 3.7 ). The theoretical accuracy and precision of the FLAWS T1 mapping ( acc = 91.9 % ; prec = 90.2 % ) were in agreement with those provided by the MP2RAGE T1 mapping ( acc = 90.0 % ; prec = 86.8 % ). A good agreement was found between in vivo T1 values measured with the MP2RAGE and FLAWS sequences (r = 0.91). A weak correlation was found between the FLAWS T1 map and the B 1 + map within cortical gray matter and white matter segmentations ( r WM = - 0.026 ; r GM = 0.081 ). CONCLUSION: The results from this study suggest that FLAWS is a good candidate for high-resolution T1 -weighted imaging and T1 mapping at the field strength of 7T.

7.
Neurology ; 2020 Nov 12.
Artigo em Inglês | MEDLINE | ID: mdl-33184233

RESUMO

OBJECTIVE: To determine the effect of Aß level on progression risk to MCI or dementia and longitudinal cognitive change in cognitively normal (CN) older individuals. METHODS: All CN from the Australian Imaging Biomarkers and Lifestyle study (AIBL) with Aß PET and ≥3 years follow-up were included (n=534; age 72±6 yrs; 27% Aß positive; follow-up 5.3±1.7 yrs). Aß level was divided using the standardised 0-100 Centiloid scale: <15 CL negative, 15-25 CL uncertain, 26-50 CL moderate, 51-100 CL high, >100 CL very high, noting >25 CL approximates a positive scan. Cox proportional hazards analysis and linear mixed effect models were used to assess risk of progression and cognitive decline. RESULTS: Aß levels in 63% were negative, 10% uncertain, 10% moderate, 14% high and 3% very high. Fifty-seven (11%) progressed to MCI or dementia. Compared to negative Aß, the hazard ratio for progression for moderate Aß was 3.2 (95% CI 1.3-7.6; p<0.05), for high was 7.0 (95% CI 3.7-13.3; p<0.001) and for very high was 11.4 (95% CI 5.1-25.8; p<0.001). Decline in cognitive composite score was minimal in the moderate group (-0.02 SD/year, p=0.05) while the high and very high declined substantially (high -0.08 SD/year, p<0.001; very high -0.35 SD/year p<0.001). CONCLUSION: The risk of MCI or dementia over 5 years in older CN is related to Aß level on PET, 5% if negative vs 25% if positive but ranging from 12% if 26-50 CL to 28% if 51-100 CL and 50% if >100 CL. This information may be useful for dementia risk counselling and aid design of preclinical AD trials.

8.
Neuropsychology ; 34(8): 881-893, 2020 Nov.
Artigo em Inglês | MEDLINE | ID: mdl-33197200

RESUMO

Objective: White matter (WM) changes detected using diffusion tensor imaging (DTI) are reportedly related to cognitive outcomes following traumatic brain injury (TBI), but much existing research is underpowered or has only examined general outcomes, rather than cognitive functioning. Method: A large sample of adults who had sustained mild, moderate or severe TBIs seven months prior (N = 165) and a control group (N = 106) underwent DTI and cognitive testing. Fractional anisotropy and mean diffusivity were calculated for 5 regions (corpus callosum: genu, body, splenium; fornix; superior longitudinal fasciculus) that recent meta-analyses identified as being affected by TBI and related to cognition following TBI. Memory, attention and executive functioning, which are often affected by TBI, were assessed. Results: Overall, mild TBI did not show significant WM or cognitive changes, relative to controls, but moderate to severe TBI was associated with large WM alterations (all regions) and poorer cognitive performance. No significant correlations were found between DTI findings and cognition in the moderate to severe group. Conclusions: The findings have shown that moderate to severe TBI leads to considerable WM and cognitive changes. Early and ongoing examination of mild TBI is needed to determine whether WM and cognitive changes are initially present and, if so, when they resolve. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

9.
Neuroimage ; 226: 117593, 2020 Nov 26.
Artigo em Inglês | MEDLINE | ID: mdl-33248259

RESUMO

BACKGROUND: Centiloid was introduced to harmonise ß-Amyloid (Aß) PET quantification across different tracers, scanners and analysis techniques. Unfortunately, Centiloid still suffers from some quantification disparities in longitudinal analysis when normalising data from different tracers or scanners. In this work, we aim to reduce this variability using a different analysis technique applied to the existing calibration data. METHOD: All PET images from the Centiloid calibration dataset, along with 3762 PET images from the AIBL study were analysed using the recommended SPM pipeline. The PET images were SUVR normalised using the whole cerebellum. All SUVR normalised PiB images from the calibration dataset were decomposed using non-negative matrix factorisation (NMF). The NMF coefficients related to the first component were strongly correlated with global SUVR and were subsequently used as a surrogate for Aß retention. For each tracer of the calibration dataset, the components of the NMF were computed in a way such that the coefficients of the first component would match those of the corresponding PiB. Given the strong correlations between the SUVR and the NMF coefficients on the calibration dataset, all PET images from AIBL were subsequently decomposed using the computed NMF, and their coefficients transformed into Centiloids. RESULTS: Using the AIBL data, the correlation between the standard Centiloid and the novel NMF-based Centiloid was high in each tracer. The NMF-based Centiloids showed a reduction of outliers, and improved longitudinal consistency. Furthermore, it removed the effects of switching tracers from the longitudinal variance of the Centiloid measure, when assessed using a linear mixed effects model. CONCLUSION: We here propose a novel image driven method to perform the Centiloid quantification. The methods is highly correlated with standard Centiloids while improving the longitudinal reliability when switching tracers. Implementation of this method across multiple studies may lend to more robust and comparable data for future research.

10.
Neurology ; 95(18): e2577-e2585, 2020 11 03.
Artigo em Inglês | MEDLINE | ID: mdl-32887774

RESUMO

OBJECTIVE: To determine the extent to which deficits in learning over 6 days are associated with ß-amyloid-positive (Aß+) and hippocampal volume in cognitively normal (CN) adults. METHODS: Eighty CN older adults who had undergone PET neuroimaging to determine Aß status (n = 42 Aß- and 38 Aß+), MRI to determine hippocampal and ventricular volume, and repeated assessment of memory were recruited from the Australian Imaging, Biomarkers and Lifestyle (AIBL) study. Participants completed the Online Repeatable Cognitive Assessment-Language Learning Test (ORCA-LLT), which required they learn associations between 50 Chinese characters and their English language equivalents over 6 days. ORCA-LLT assessments were supervised on the first day and were completed remotely online for all remaining days. RESULTS: Learning curves in the Aß+ CN participants were significantly worse than those in matched Aß- CN participants, with the magnitude of this difference very large (d [95% confidence interval (CI)] 2.22 [1.64-2.75], p < 0.001), and greater than differences between these groups for memory decline since their enrollment in AIBL (d [95% CI] 0.52 [0.07-0.96], p = 0.021), or memory impairment at their most recent visit. In Aß+ CN adults, slower rates of learning were associated with smaller hippocampal and larger ventricular volumes. CONCLUSIONS: These results suggest that in CN participants, Aß+ is associated more strongly with a deficit in learning than any aspect of memory dysfunction. Slower rates of learning in Aß+ CN participants were associated with hippocampal volume loss. Considered together, these data suggest that the primary cognitive consequence of Aß+ is a failure to benefit from experience when exposed to novel stimuli, even over very short periods.

11.
J Alzheimers Dis ; 78(1): 321-334, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-32986666

RESUMO

BACKGROUND: Cerebrovascular disease often coexists with Alzheimer's disease (AD). While both diseases share common risk factors, their interrelationship remains unclear. Increasing the understanding of how cerebrovascular changes interact with AD is essential to develop therapeutic strategies and refine biomarkers for early diagnosis. OBJECTIVE: We investigate the prevalence and risk factors for the comorbidity of amyloid-ß (Aß) and cerebrovascular disease in the Australian Imaging, Biomarkers and Lifestyle Study of Ageing, and further examine their cross-sectional association. METHODS: A total of 598 participants (422 cognitively normal, 89 with mild cognitive impairment, 87 with AD) underwent positron emission tomography and structural magnetic resonance imaging for assessment of Aß deposition and cerebrovascular disease. Individuals were categorized based on the comorbidity status of Aß and cerebrovascular disease (V) as Aß-V-, Aß-V+, Aß+V-, or Aß+V+. RESULTS: Advancing age was associated with greater likelihood of cerebrovascular disease, high Aß load and their comorbidity. Apolipoprotein E ɛ4 carriage was only associated with Aß positivity. Greater total and regional WMH burden were observed in participants with AD. However, no association were observed between Aß and WMH measures after stratification by clinical classification, suggesting that the observed association between AD and cerebrovascular disease was driven by the common risk factor of age. CONCLUSION: Our observations demonstrate common comorbid condition of Aß and cerebrovascular disease in later life. While our study did not demonstrate a convincing cross-sectional association between Aß and WMH burden, future longitudinal studies are required to further confirm this.

12.
Alzheimers Dement ; 2020 Sep 13.
Artigo em Inglês | MEDLINE | ID: mdl-32920988

RESUMO

INTRODUCTION: Relationships between brain atrophy patterns of typical aging and Alzheimer's disease (AD), white matter disease, cognition, and AD neuropathology were investigated via machine learning in a large harmonized magnetic resonance imaging database (11 studies; 10,216 subjects). METHODS: Three brain signatures were calculated: Brain-age, AD-like neurodegeneration, and white matter hyperintensities (WMHs). Brain Charts measured and displayed the relationships of these signatures to cognition and molecular biomarkers of AD. RESULTS: WMHs were associated with advanced brain aging, AD-like atrophy, poorer cognition, and AD neuropathology in mild cognitive impairment (MCI)/AD and cognitively normal (CN) subjects. High WMH volume was associated with brain aging and cognitive decline occurring in an ≈10-year period in CN subjects. WMHs were associated with doubling the likelihood of amyloid beta (Aß) positivity after age 65. Brain aging, AD-like atrophy, and WMHs were better predictors of cognition than chronological age in MCI/AD. DISCUSSION: A Brain Chart quantifying brain-aging trajectories was established, enabling the systematic evaluation of individuals' brain-aging patterns relative to this large consortium.

13.
Ann Intern Med ; 173(11): 861-869, 2020 Dec 01.
Artigo em Inglês | MEDLINE | ID: mdl-32926799

RESUMO

BACKGROUND: Current pharmacologic therapies for patients with osteoarthritis are suboptimal. OBJECTIVE: To determine the efficacy of Curcuma longa extract (CL) for reducing knee symptoms and effusion-synovitis in patients with symptomatic knee osteoarthritis and knee effusion-synovitis. DESIGN: Randomized, double-blind, placebo-controlled trial. (Australian New Zealand Clinical Trials Registry: ACTRN12618000080224). SETTING: Single-center study with patients from southern Tasmania, Australia. PARTICIPANTS: 70 participants with symptomatic knee osteoarthritis and ultrasonography-defined effusion-synovitis. INTERVENTION: 2 capsules of CL (n = 36) or matched placebo (n = 34) per day for 12 weeks. MEASUREMENTS: The 2 primary outcomes were changes in knee pain on a visual analogue scale (VAS) and effusion-synovitis volume on magnetic resonance imaging (MRI). The key secondary outcomes were change in Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) pain and cartilage composition values. Outcomes were assessed over 12 weeks. RESULTS: CL improved VAS pain compared with placebo by -9.1 mm (95% CI, -17.8 to -0.4 mm [P = 0.039]) but did not change effusion-synovitis volume (3.2 mL [CI, -0.3 to 6.8 mL]). CL also improved WOMAC knee pain (-47.2 mm [CI, -81.2 to -13.2 mm]; P = 0.006) but not lateral femoral cartilage T2 relaxation time (-0.4 ms [CI, -1.1 to 0.3 ms]). The incidence of adverse events was similar in the CL (n = 14 [39%]) and placebo (n = 18 [53%]) groups (P = 0.16); 2 events in the CL group and 5 in the placebo group may have been treatment related. LIMITATION: Modest sample size and short duration. CONCLUSION: CL was more effective than placebo for knee pain but did not affect knee effusion-synovitis or cartilage composition. Multicenter trials with larger sample sizes are needed to assess the clinical significance of these findings. PRIMARY FUNDING SOURCE: University of Tasmania and Natural Remedies Private Limited.

14.
Brain Commun ; 2(1): fcaa041, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-32954297

RESUMO

Plasma amyloid-ß peptide concentration has recently been shown to have high accuracy to predict amyloid-ß plaque burden in the brain. These amyloid-ß plasma markers will allow wider screening of the population and simplify and reduce screening costs for therapeutic trials in Alzheimer's disease. The aim of this study was to determine how longitudinal changes in blood amyloid-ß track with changes in brain amyloid-ß. Australian Imaging, Biomarker and Lifestyle study participants with a minimum of two assessments were evaluated (111 cognitively normal, 7 mild cognitively impaired, 15 participants with Alzheimer's disease). Amyloid-ß burden in the brain was evaluated through PET and was expressed in Centiloids. Total protein amyloid-ß 42/40 plasma ratios were determined using ABtest® assays. We applied our method for obtaining natural history trajectories from short term data to measures of total protein amyloid-ß 42/40 plasma ratios and PET amyloid-ß. The natural history trajectory of total protein amyloid-ß 42/40 plasma ratios appears to approximately mirror that of PET amyloid-ß, with both spanning decades. Rates of change of 7.9% and 8.8%, were observed for total protein amyloid-ß 42/40 plasma ratios and PET amyloid-ß, respectively. The trajectory of plasma amyloid-ß preceded that of brain amyloid-ß by a median value of 6 years (significant at 88% confidence interval). These findings, showing the tight association between changes in plasma and brain amyloid-ß, support the use of plasma total protein amyloid-ß 42/40 plasma ratios as a surrogate marker of brain amyloid-ß. Also, that plasma total protein amyloid-ß 42/40 plasma ratios has potential utility in monitoring trial participants, and as an outcome measure.

15.
Med Phys ; 47(10): 4939-4948, 2020 Oct.
Artigo em Inglês | MEDLINE | ID: mdl-32745260

RESUMO

PURPOSE: High resolution three-dimensional (3D) magnetic resonance (MR) images are well suited for automated cartilage segmentation in the human knee joint. However, volumetric scans such as 3D Double-Echo Steady-State (DESS) images are not routinely acquired in clinical practice which limits opportunities for reliable cartilage segmentation using (fully) automated algorithms. In this work, a method for generating synthetic 3D MR (syn3D-DESS) images with better contrast and higher spatial resolution from routine, low resolution, two-dimensional (2D) Turbo-Spin Echo (TSE) clinical knee scans is proposed. METHODS: A UNet convolutional neural network is employed for synthesizing enhanced artificial MR images suitable for automated knee cartilage segmentation. Training of the model was performed on a large, publically available dataset from the OAI, consisting of 578 MR examinations of knee joints from 102 healthy individuals and patients with knee osteoarthritis. RESULTS: The generated synthetic images have higher spatial resolution and better tissue contrast than the original 2D TSE, which allow high quality automated 3D segmentations of the cartilage. The proposed approach was evaluated on a separate set of MR images from 88 subjects with manual cartilage segmentations. It provided a significant improvement in automated segmentation of knee cartilages when using the syn3D-DESS images compared to the original 2D TSE images. CONCLUSION: The proposed method can successfully synthesize 3D DESS images from 2D TSE images to provide images suitable for automated cartilage segmentation.

16.
Neuroimage ; 221: 117163, 2020 Jul 11.
Artigo em Inglês | MEDLINE | ID: mdl-32663645

RESUMO

Very preterm-born infants are at risk of adverse neurodevelopmental outcomes. Brain magnetic resonance imaging (MRI) at term equivalent age (TEA) can probe tissue microstructure and morphology, and demonstrates potential in the early prediction of outcomes. In this study, we use the recently introduced fixel-based analysis method for diffusion MRI to investigate the association between microstructure and morphology at TEA, and motor and cognitive development at 1 and 2 years corrected age (CA). Eighty infants born <31 weeks' gestation successfully underwent diffusion MRI (3T; 64 directions; b â€‹= â€‹2000s/mm2) at term equivalent age, and had neurodevelopmental follow-up using the Bayley-III motor and cognitive assessments at 1 year (n â€‹= â€‹78) and/or 2 years (n â€‹= â€‹76) CA. Diffusion MRI data were processed using constrained spherical deconvolution (CSD) and aligned to a study-specific fibre orientation distribution template, yielding measures of fibre density (FD), fibre-bundle cross-section (FC), and fibre density and bundle cross-section (FDC). The association between FD, FC, and FDC at TEA, and motor and cognitive composite scores at 1 and 2 years CA, and change in composite scores from 1 to 2 years, was assessed using whole-brain fixel-based analysis. Additionally, the association between diffusion tensor imaging (DTI) metrics (fractional anisotropy FA, mean diffusivity MD, axial diffusivity AD, radial diffusivity RD) and outcomes was investigated. Motor function at 1 and 2 years CA was associated with CSD-based measures of the bilateral corticospinal tracts and corpus callosum. Cognitive function was associated with CSD-based measures of the midbody (1-year outcomes only) and splenium of the corpus callosum, as well as the bilateral corticospinal tracts. The change in motor/cognitive outcomes from 1 to 2 years was associated with CSD-based measures of the splenium of the corpus callosum. Analysis of DTI-based measures showed overall less extensive associations. Post-hoc analysis showed that associations were weaker for 2-year outcomes than they were for 1-year outcomes. Infants with better neurodevelopmental outcomes demonstrated higher FD, FC, and FDC at TEA, indicating better information transfer capacity which may be related to increased number of neurons, increased myelination, thicker bundles, and/or combinations thereof. The fibre bundles identified here may serve as the basis for future studies investigating the predictive ability of these metrics.

17.
Alzheimers Res Ther ; 12(1): 72, 2020 06 09.
Artigo em Inglês | MEDLINE | ID: mdl-32517787

RESUMO

BACKGROUND: Heme and iron homeostasis is perturbed in Alzheimer's disease (AD); therefore, the aim of the study was to examine the levels and association of heme with iron-binding plasma proteins in cognitively normal (CN), mild cognitive impairment (MCI), and AD individuals from the Australian Imaging, Biomarker and Lifestyle Flagship Study of Ageing (AIBL) and Kerr Anglican Retirement Village Initiative in Ageing Health (KARVIAH) cohorts. METHODS: Non-targeted proteomic analysis by high-resolution mass spectrometry was performed to quantify relative protein abundances in plasma samples from 144 CN individuals from the AIBL and 94 CN from KARVIAH cohorts and 21 MCI and 25 AD from AIBL cohort. ANCOVA models were utilized to assess the differences in plasma proteins implicated in heme/iron metabolism, while multiple regression modeling (and partial correlation) was performed to examine the association between heme and iron proteins, structural neuroimaging, and cognitive measures. RESULTS: Of the plasma proteins implicated in iron and heme metabolism, hemoglobin subunit ß (p = 0.001) was significantly increased in AD compared to CN individuals. Multiple regression modeling adjusted for age, sex, APOEε4 genotype, and disease status in the AIBL cohort revealed lower levels of transferrin but higher levels of hemopexin associated with augmented brain amyloid deposition. Meanwhile, transferrin was positively associated with hippocampal volume and MMSE performance, and hemopexin was negatively associated with CDR scores. Partial correlation analysis revealed lack of significant associations between heme/iron proteins in the CN individuals progressing to cognitive impairment. CONCLUSIONS: In conclusion, heme and iron dyshomeostasis appears to be a feature of AD. The causal relationship between heme/iron metabolism and AD warrants further investigation.

18.
Brain ; 143(7): 2312-2324, 2020 Jul 01.
Artigo em Inglês | MEDLINE | ID: mdl-32591831

RESUMO

Deep learning has emerged as a powerful approach to constructing imaging signatures of normal brain ageing as well as of various neuropathological processes associated with brain diseases. In particular, MRI-derived brain age has been used as a comprehensive biomarker of brain health that can identify both advanced and resilient ageing individuals via deviations from typical brain ageing. Imaging signatures of various brain diseases, including schizophrenia and Alzheimer's disease, have also been identified using machine learning. Prior efforts to derive these indices have been hampered by the need for sophisticated and not easily reproducible processing steps, by insufficiently powered or diversified samples from which typical brain ageing trajectories were derived, and by limited reproducibility across populations and MRI scanners. Herein, we develop and test a sophisticated deep brain network (DeepBrainNet) using a large (n = 11 729) set of MRI scans from a highly diversified cohort spanning different studies, scanners, ages and geographic locations around the world. Tests using both cross-validation and a separate replication cohort of 2739 individuals indicate that DeepBrainNet obtains robust brain-age estimates from these diverse datasets without the need for specialized image data preparation and processing. Furthermore, we show evidence that moderately fit brain ageing models may provide brain age estimates that are most discriminant of individuals with pathologies. This is not unexpected as tightly-fitting brain age models naturally produce brain-age estimates that offer little information beyond age, and loosely fitting models may contain a lot of noise. Our results offer some experimental evidence against commonly pursued tightly-fitting models. We show that the moderately fitting brain age models obtain significantly higher differentiation compared to tightly-fitting models in two of the four disease groups tested. Critically, we demonstrate that leveraging DeepBrainNet, along with transfer learning, allows us to construct more accurate classifiers of several brain diseases, compared to directly training classifiers on patient versus healthy control datasets or using common imaging databases such as ImageNet. We, therefore, derive a domain-specific deep network likely to reduce the need for application-specific adaptation and tuning of generic deep learning networks. We made the DeepBrainNet model freely available to the community for MRI-based evaluation of brain health in the general population and over the lifespan.

19.
Stat Med ; 39(21): 2695-2713, 2020 Sep 20.
Artigo em Inglês | MEDLINE | ID: mdl-32419227

RESUMO

The degeneration of the human brain is a complex process, which often affects certain brain regions due to healthy aging or disease. This degeneration can be evaluated on regions of interest (ROI) in the brain through probabilistic networks and morphological estimates. Current approaches for finding such networks are limited to analyses at discrete neuropsychological stages, which cannot appropriately account for connectivity dynamics over the onset of cognitive deterioration, and morphological changes are seldom unified with connectivity networks, despite known dependencies. To overcome these limitations, a probabilistic wombling model is proposed to simultaneously estimate ROI cortical thickness and covariance networks contingent on rates of change in cognitive decline. This proposed model was applied to analyze longitudinal data from healthy control (HC) and Alzheimer's disease (AD) groups and found connection differences pertaining to regions, which play a crucial role in lasting cognitive impairment, such as the entorhinal area and temporal regions. Moreover, HC cortical thickness estimates were significantly higher than those in the AD group across all ROIs. The analyses presented in this work will help practitioners jointly analyze brain tissue atrophy at the ROI-level conditional on neuropsychological networks, which could potentially allow for more targeted therapeutic interventions.

20.
BMJ Open ; 10(5): e036480, 2020 05 12.
Artigo em Inglês | MEDLINE | ID: mdl-32404396

RESUMO

INTRODUCTION: Infants born very preterm are at risk of adverse neurodevelopmental outcomes, including cognitive deficits, motor impairments and cerebral palsy. Earlier identification enables targeted early interventions to be implemented with the aim of improving outcomes. METHODS AND ANALYSIS: Protocol for 6-year follow-up of two cohorts of infants born <31 weeks gestational age (PPREMO: Prediction of Preterm Motor Outcomes; PREBO: Prediction of Preterm Brain Outcomes) and a small term-born reference sample in Brisbane, Australia. Both preterm cohorts underwent very early MRI and concurrent clinical assessment at 32 and 40 weeks postmenstrual age (PMA) and were followed up at 3, 12 and 24 months corrected age (CA). This study will perform MRI and electroencephalography (EEG). Primary outcomes include the Movement Assessment Battery for Children second edition and Full-Scale IQ score from the Wechsler Intelligence Scale for Children fifth edition (WISC-V). Secondary outcomes include the Gross Motor Function Classification System for children with cerebral palsy; executive function (Behavior Rating Inventory of Executive Function second edition, WISC-V Digit Span and Picture Span, Wisconsin Card Sorting Test 64 Card Version); attention (Test of Everyday Attention for Children second edition); language (Clinical Evaluation of Language Fundamentals fifth edition), academic achievement (Woodcock Johnson IV Tests of Achievement); mental health and quality of life (Development and Well-Being Assessment, Autism Spectrum Quotient-10 Items Child version and Child Health Utility-9D). AIMS: Examine the ability of early neonatal MRI, EEG and concurrent clinical measures at 32 weeks PMA to predict motor, cognitive, language, academic achievement and mental health outcomes at 6 years CA.Determine if early brain abnormalities persist and are evident on brain MRI at 6 years CA and the relationship to EEG and concurrent motor, cognitive, language, academic achievement and mental health outcomes. ETHICS AND DISSEMINATION: Ethical approval has been obtained from Human Research Ethics Committees at Children's Health Queensland (HREC/19/QCHQ/49800) and The University of Queensland (2019000426). Study findings will be presented at national and international conferences and published in peer-reviewed journals. TRIAL REGISTRATION NUMBER: ACTRN12619000155190p. WEB ADDRESS OF TRIAL: http://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?ACTRN=12619000155190p.

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