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BackgroundA lack of in utero imaging data hampers our understanding of the connections in the human fetal brain. Generalizing observations from postmortem subjects and premature newborns is inaccurate due to technical and biological differences. PurposeTo evaluate changes in fetal brain structural connectivity between 23 and 35 weeks postconceptional age using a spatiotemporal atlas of diffusion tensor imaging (DTI). Study TypeRetrospective. PopulationPublicly available diffusion atlases, based on 60 healthy women (age 18–45 years) with normal prenatal care, from 23 and 35 weeks of gestation. Field Strength/Sequence3.0 Tesla/DTI acquired with diffusion‐weighted echo planar imaging (EPI). AssessmentWe performed whole‐brain fiber tractography from DTI images. The cortical plate of each diffusion atlas was segmented and parcellated into 78 regions derived from the Edinburgh Neonatal Atlas (ENA33). Connectivity matrices were computed, representing normalized fiber connections between nodes. We examined the relationship between global efficiency (GE), local efficiency (LE), small‐worldness (SW), nodal efficiency (NE), and betweenness centrality (BC) with gestational age (GA) and with laterality. Statistical TestsLinear regression was used to analyze changes in GE, LE, NE, and BC throughout gestation, and to assess changes in laterality. Thet‐tests were used to assess SW.P‐values were corrected using Holm‐Bonferroni method. A correctedP‐value <0.05 was considered statistically significant. ResultsNetwork analysis revealed a significant weekly increase in GE (5.83%/week, 95% CI 4.32–7.37), LE (5.43%/week, 95% CI 3.63–7.25), and presence of SW across GA. No significant hemisphere differences were found in GE (P = 0.971) or LE (P = 0.458). Increasing GA was significantly associated with increasing NE in 41 nodes, increasing BC in 3 nodes, and decreasing BC in 2 nodes. Data ConclusionExtensive network development and refinement occur in the second and third trimesters, marked by a rapid increase in global integration and local segregation. Level of Evidence3 Technical EfficacyStage 2
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Community action on FAIR data will fuel a revolution in materials research
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BackgroundWater content is a key parameter for simulating tissue swelling and nutrient diffusion. Accurately measuring water content throughout the intervertebral disc (NP = nucleus pulposus; AF = annulus fibrosus) is important for developing patient‐specific models. Water content is measured using destructive techniques, Quantitative MRI has been used to estimate water content and detect early degeneration, but it is dependent on scan parameters, concentration of free water molecules, and fiber architecture. PurposeTo directly measure disc‐tissue water content using quantitative MRI and compare MRI‐based measurements with biochemical assays, and to quantify changes in disc geometry due to compression. Study TypeBasic science, controlled. SpecimenTwenty bone‐disc‐bone motion segments from skeletally mature bovines. Field Strength/Sequence7T/3D fast low angle shot (FLASH) pulse sequence and a T2rapid imaging with refocused echoes (RARE) sequence. AssessmentDisc volumes, NP and AF volumetric water content, and T2relaxation times were measured through MRI; NP and AF tissue gravimetric water content, mass density, and glycosaminoglycan content were measured through a biochemical assay. Statistical TestsCorrelations between MRI‐based measurement and biochemical composition were evaluated using Pearson's linear regression. ResultsMechanical dehydration resulted in a decrease in disc volume by up to 20% and a decrease in disc height by up to 35%. Direct water content measurements for the NP was achieved by normalizing MRI‐based spin density by NP mass density (1.10 ± 0.03 g/cm3). However, the same approach underestimated water content in the AF by ~10%, which may be due to a higher concentration of collagen fibers and bound water molecules. Data ConclusionSpin density or spin density normalized by mass density to estimate NP and AF water content was more accurate than correlations between water content and relaxation times. Mechanical dehydration decreased disc volume and disc height, and increased maximum cross‐sectional area. Level of Evidence Technical Efficacy Stage J. Magn. Reson. Imaging 2020;52:1152–1162.more » « less
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BackgroundHealthy articular cartilage presents structural gradients defined by distinct zonal patterns through the thickness, which may be disrupted in the pathogenesis of several disorders. Analysis of textural patterns using quantitative MRI data may identify structural gradients of healthy or degenerating tissue that correlate with early osteoarthritis (OA). PurposeTo quantify spatial gradients and patterns in MRI data, and to probe new candidate biomarkers for early severity of OA. Study TypeRetrospective study. SubjectsFourteen volunteers receiving total knee replacement surgery (eight males/two females/four unknown, average age ± standard deviation: 68.1 ± 9.6 years) and 10 patients from the OA Initiative (OAI) with radiographic OA onset (two males/eight females, average age ± standard deviation: 57.7 ± 9.4 years; initial Kellgren‐Lawrence [KL] grade: 0; final KL grade: 3 over the 10‐year study). Field Strength/Sequence3.0‐T and 14.1‐T, biomechanics‐based displacement‐encoded imaging, fast spin echo, multi‐slice multi‐echoT2mapping. AssessmentWe studied structure and strain in cartilage explants from volunteers receiving total knee replacement, or structure in cartilage of OAI patients with progressive OA. We calculated spatial gradients of quantitative MRI measures (eg, T2) normal to the cartilage surface to enhance zonal variations. We compared gradient values against histologically OA severity, conventional relaxometry, and/or KL grades. Statistical TestsMultiparametric linear regression for evaluation of the relationship between residuals of the mixed effects models and histologically determined OA severity scoring, with a significance threshold atα = 0.05. ResultsGradients of individual relaxometry and biomechanics measures significantly correlated with OA severity, outperforming conventional relaxometry and strain metrics. In human explants, analysis of spatial gradients provided the strongest relationship to OA severity (R2 = 0.627). Spatial gradients of T2 from OAI data identified variations in radiographic (KL Grade 2) OA severity in single subjects, while conventional T2 alone did not. Data ConclusionSpatial gradients of quantitative MRI data may improve the predictive power of noninvasive imaging for early‐stage degeneration. Evidence Level1 Technical EfficacyStage 1more » « less
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BackgroundCognitive training may partially reverse cognitive deficits in people with HIV (PWH). Previous functional MRI (fMRI) studies demonstrate that working memory training (WMT) alters brain activity during working memory tasks, but its effects on resting brain network organization remain unknown. PurposeTo test whether WMT affects PWH brain functional connectivity in resting‐state fMRI (rsfMRI). Study TypeProspective. PopulationA total of 53 PWH (ages 50.7 ± 1.5 years, two women) and 53HIV‐seronegative controls (SN, ages 49.5 ± 1.6 years, six women). Field Strength/SequenceAxial single‐shot gradient‐echo echo‐planar imaging at 3.0 T was performed at baseline (TL1), at 1‐month (TL2), and at 6‐months (TL3), after WMT. AssessmentAll participants had rsfMRI and clinical assessments (including neuropsychological tests) at TL1 before randomization to Cogmed WMT (adaptive training,n = 58: 28 PWH, 30 SN; nonadaptive training,n = 48: 25 PWH, 23 SN), 25 sessions over 5–8 weeks. All assessments were repeated at TL2 and at TL3. The functional connectivity estimated by independent component analysis (ICA) or graph theory (GT) metrics (eigenvector centrality, etc.) for different link densities (LDs) were compared between PWH and SN groups at TL1 and TL2. Statistical TestsTwo‐way analyses of variance (ANOVA) on GT metrics and two‐samplet‐tests on FC or GT metrics were performed. Cognitive (eg memory) measures were correlated with eigenvector centrality (eCent) using Pearson's correlations. The significance level was set atP < 0.05 after false discovery rate correction. ResultsThe ventral default mode network (vDMN) eCent differed between PWH and SN groups at TL1 but not at TL2 (P = 0.28). In PWH, vDMN eCent changes significantly correlated with changes in the memory ability in PWH (r = −0.62 at LD = 50%) and vDMN eCent before training significantly correlated with memory performance changes (r = 0.53 at LD = 50%). Data ConclusionICA and GT analyses showed that adaptive WMT normalized graph properties of the vDMN in PWH. Evidence Level1 Technical Efficacy1more » « less
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ObjectiveThe objective of this study was to assess nonresponse error in telephone health survey data based on an address‐based sample. Data SourcesTelephone and in‐person interviews in Greater Boston. Study Design/Data CollectionInterviewers attempted telephone interviews at addresses that were matched to telephone numbers using questions drawn from federal health surveys. In‐person household interviews were carried out with telephone nonrespondents and at addresses without matching telephone numbers. Principal FindingsAfter adjusting for demographic differences, only eight of 15 estimates based on the telephone interviews lay within two standard errors of the estimates when data from all three groups were included. ConclusionsFor health surveys of address‐based samples, many estimates based on telephone respondents differ from the total population in ways that cannot be corrected with simple demographic adjustments.more » « less
