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Objectives Further survival benefits may be gained from low-dose chest computed tomography (CT) by assessing vertebral fractures and bone density. We sought to assess the association between CT-measured vertebral fractures and bone density with all-cause mortality in lung cancer screening participants. Methods Following a case-cohort design, lung cancer screening trial participants ( N  = 3,673) who died ( N  = 196) during a median follow-up of 6 years (inter-quartile range: 5.7–6.3) were identified and added to a random sample of N  = 383 from the trial. We assessed vertebral fractures using Genant´s semiquantative method on sagittal reconstructions and measured bone density (Hounsfield Units (HU)) in vertebrae. Cox proportional hazards modelling was used to determine if vertebral fractures or bone density were independently predictive of mortality. Results The prevalence of vertebral fractures was 35 % (95 % confidence interval 30–40 %) among survivors and 51 % (44–58 %) amongst cases. After adjusting for age, gender, smoking status, pack years smoked, coronary and aortic calcium volume and pulmonary emphysema, the adjusted hazard ratio (HR) for vertebral fracture was 2.04 (1.43–2.92). For each 10 HU decline in trabecular bone density, the adjusted HR was 1.08 (1.02–1.15). Conclusions Vertebral fractures and bone density are independently associated with all-cause mortality. Key Points • Lung cancer screening chest computed tomography contains additional, potentially useful information. • Vertebral fractures and bone density are independently predictive of mortality. • This finding has implications for screening and management decisions.

BackgroundEmphysema and small airway disease both contribute to chronic obstructive pulmonary disease (COPD), a disease characterised by accelerated decline in lung function. The association between the extent of emphysema in male current and former smokers and lung function decline was investigated.MethodsCurrent and former heavy smokers participating in a lung cancer screening trial were recruited to the study and all underwent CT. Spirometry was performed at baseline and at 3-year follow-up. The 15th percentile (Perc15) was used to assess the severity of emphysema.Results2085 men of mean age 59.8 years participated in the study. Mean (SD) baseline Perc15 was −934.9 (19.5) HU. A lower Perc15 value correlated with a lower forced expiratory volume in 1 s (FEV1) at baseline (r=0.12, p<0.001). Linear mixed model analysis showed that a lower Perc15 was significantly related to a greater decline in FEV1 after follow-up (p<0.001). Participants without baseline airway obstruction who developed it after follow-up had significantly lower mean (SD) Perc15 values at baseline than those who did not develop obstruction (−934.2 (17.1) HU vs −930.2 (19.7) HU, p<0.001).ConclusionGreater baseline severity of CT-detected emphysema is related to lower baseline lung function and greater rates of lung function decline, even in those without airway obstruction. CT-detected emphysema aids in identifying non-obstructed male smokers who will develop airflow obstruction.

Background Machine learning (ML) allows the exploration and progressive improvement of very complex high-dimensional data patterns that can be utilised to optimise specific classification and prediction tasks, outperforming traditional statistical approaches. An enormous acceleration of ready-to-use tools and artificial intelligence (AI) applications, shaped by the emergence, refinement, and application of powerful ML algorithms in several areas of knowledge, is ongoing. Although such progress has begun to permeate the medical sciences and clinical medicine, implementation in cardiovascular medicine and research is still in its infancy. Objectives To lay out the theoretical framework, purpose, and structure of a novel AI consortium. Methods We have established a new Dutch research consortium, the CVON-AI, supported by the Netherlands Heart Foundation, to catalyse and facilitate the development and utilisation of AI solutions for existing and emerging cardiovascular research initiatives and to raise AI awareness in the cardiovascular research community. CVON-AI will connect to previously established CVON consortia and apply a cloud-based AI platform to supplement their planned traditional data-analysis approach. Results A pilot experiment on the CVON-AI cloud was conducted using cardiac magnetic resonance data. It demonstrated the feasibility of the platform and documented excellent correlation between AI-generated ventricular function estimates as compared to expert manual annotations. The resulting AI solution was then integrated in a web application. Conclusion CVON-AI is a new consortium meant to facilitate the implementation and raise awareness of AI in cardiovascular research in the Netherlands. CVON-AI will create an accessible cloud-based platform for cardiovascular researchers, demonstrate the clinical applicability of AI, optimise the analytical methodology of other ongoing CVON consortia, and promote AI awareness through education and training.

Objectives To determine inter-observer and inter-examination variability for aortic valve calcification (AVC) and mitral valve and annulus calcification (MC) in low-dose unenhanced ungated lung cancer screening chest computed tomography (CT). Methods We included 578 lung cancer screening trial participants who were examined by CT twice within 3 months to follow indeterminate pulmonary nodules. On these CTs, AVC and MC were measured in cubic millimetres. One hundred CTs were examined by five observers to determine the inter-observer variability. Reliability was assessed by kappa statistics (κ) and intra-class correlation coefficients (ICCs). Variability was expressed as the mean difference ± standard deviation (SD). Results Inter-examination reliability was excellent for AVC (κ = 0.94, ICC = 0.96) and MC (κ = 0.95, ICC = 0.90). Inter-examination variability was 12.7 ± 118.2 mm 3 for AVC and 31.5 ± 219.2 mm 3 for MC. Inter-observer reliability ranged from κ = 0.68 to κ = 0.92 for AVC and from κ = 0.20 to κ = 0.66 for MC. Inter-observer ICC was 0.94 for AVC and ranged from 0.56 to 0.97 for MC. Inter-observer variability ranged from -30.5 ± 252.0 mm 3 to 84.0 ± 240.5 mm 3 for AVC and from -95.2 ± 210.0 mm 3 to 303.7 ± 501.6 mm 3 for MC. Conclusions AVC can be quantified with excellent reliability on ungated unenhanced low-dose chest CT, but manual detection of MC can be subject to substantial inter-observer variability. Lung cancer screening CT may be used for detection and quantification of cardiac valve calcifications. Key points • Low - dose unenhanced ungated chest computed tomography can detect cardiac valve calcifications . • However , calcified cardiac valves are not reported by most radiologists . • Inter - observer and inter - examination variability of aortic valve calcifications is sufficient for longitudinal studies . • Volumetric measurement variability of mitral valve and annulus calcifications is substantial .

Background and aimEarly brain activity is crucial for neuronal growth. It is well known that the cerebral cortex develops rapidly in the last trimester of pregnancy. We investigated whether early brain activity was related to the rate of cortical development over the 10 wks before term equivalent age in preterm infants.Methods35 infants (GA: 27.1 plus or minus 0.7; BW: 937 plus or minus 172) without morphine, were monitored with EEG/aEEG. Three periods were selected at 20-24 h, 32-36 h, 44-48 h. Minimum amplitude,% of timeResultsIncreased SATrate was positively associated with deltaGMv, inner and outer surface (resp beta :7.4, p:0.001; beta :46.6,p:0.002; beta :57.5, p:0.001). Consistent with these findings, ISI was negatively associated with changes in GMv, inner and outer surface ( beta :-3.4, p: 0.007; beta :-17.8, p: 0.034; beta :-27.7, p: 0.006). Min aEEG and% of time <5 mu V were associated with inner and outer surface at 40 wks (respectively: beta :46.2, p:0.043; beta :53.0, p:0.041; and beta :-2.9, p:0.025; beta :-3.5, p:0.019). No effect on thickness and gyrification was found.ConclusionsEarly brain activity seems to be associated with cortical development suggesting that adequate brain activity in the early neuronal networks is necessary to lead to growth and development of neonatal cerebral cortical brain, measured by structural MRI.

Background and aimOur aim was to analyse the development of cortical morphology in preterm infants, as alterations in cortical folding affect functional development.MethodsMRI was performed at 30 and 40 weeks corrected age in 19 preterm born infants (gestational age (GA) 24.71-27.86 wks, 11 males). After automatic brain tissue segmentation,1 a 3D reconstruction of the inner cortical surface was computed and cortical sulci were labelled with Brainvisa software.2 We measured global sulcal index (SI=folded/unfolded surface areas), and per sulcus surface area (SA, mm2) and mean geodesic depth (MGD, mm), all corrected for scan-age.ResultsIn 10 weeks, SI increased from 0.18 to 1.08 (6 times, 40 wks: right > left). Central sulcus, lateral fissure, and insula increased more in SA (resp. 2.3, 2.6, 1.7-times) than in MGD (resp.1.2, 1.1, 1.3-times). The superior temporal sulcus (STS) expanded in SA with factor 16.3 left and 12.6 right (30 wks: right > left), and factor 1.6 in MGD (30 and 40 wks: right > left). White matter injury in these infants (9 IVH,1 PVHI, 4 treated for PHVD) or GA did not significantly influence cortical morphology changes.ConclusionOver this short period, cortical folding is immense in preterm newborns, and shows inter-hemispherical asymmetries. Sulci increased more in surface area than in depth, STS showed the largest increase. The influence of brain injury on cortical morphology needs to be elucidated in a larger cohort.ReferencesChita S, et al. Medical Imaging (2013) Perrot M, et al. Medical Image Analysis (2011)

Background and aimOur aim was to analyse the development of cortical morphology in preterm infants, as alterations in cortical folding affect functional development.MethodsMRI was performed at 30 and 40 weeks corrected age in 19 preterm born infants (gestational age (GA) 24.71–27.86 wks, 11 males). After automatic brain tissue segmentation,1 a 3D reconstruction of the inner cortical surface was computed and cortical sulci were labelled with Brainvisa software.2 We measured global sulcal index (SI=folded/unfolded surface areas), and per sulcus surface area (SA, mm2) and mean geodesic depth (MGD, mm), all corrected for scan-age.ResultsIn 10 weeks, SI increased from 0.18 to 1.08 (6 times, 40 wks: right > left). Central sulcus, lateral fissure, and insula increased more in SA (resp. 2.3, 2.6, 1.7-times) than in MGD (resp.1.2, 1.1, 1.3-times). The superior temporal sulcus (STS) expanded in SA with factor 16.3 left and 12.6 right (30 wks: right > left), and factor 1.6 in MGD (30 and 40 wks: right > left). White matter injury in these infants (9 IVH,1 PVHI, 4 treated for PHVD) or GA did not significantly influence cortical morphology changes.ConclusionOver this short period, cortical folding is immense in preterm newborns, and shows inter-hemispherical asymmetries. Sulci increased more in surface area than in depth, STS showed the largest increase. The influence of brain injury on cortical morphology needs to be elucidated in a larger cohort.ReferencesChita S, et al. Medical Imaging (2013)Perrot M, et al. Medical Image Analysis (2011)

ObjectivesTo assess the association of brain tissue volumes at term-equivalent age (TEA) with long-term neurodevelopment.Methods108 preterm infants (median GA 28.6 weeks; 25.0–30.9 weeks) were prospectively studied at TEA (median 41.6 weeks PMA; 39.7–43.6). Volumes of eight different tissue types were quantified using an automatic segmentation method (Anbeek, PLOSOne2013)and related to neurodevelopmental outcome using cognitive (CCs), fine motor (FMss), and gross motor scaled scores (GMss) of the BSITD-III at two years corrected age, Griffiths Mental Development Scales (DQ) at age 3.5, and WPPSI at age 5.5. Corrections were made for PMA at scan, intracranial volume and maternal education.ResultsSignificant results are presented in the table. Both ventricular (Vent) and cortical grey matter volume (CoGM) were inversely related to all included subscales of the BSITD-III and DQ. However, the association at age 3.5 was lost after excluding infants with severe brain lesions (venous infarction, PHVD with neurosurgical intervention, and severe cerebellar haemorrhages). CoGM volume demonstrated a borderline significant inverse correlation with performal IQ at age 5.5 (coefficient-3.2;-6.6–0.08), that did not change after adjustment for severe brain lesions. Cerebellar volume was related to cognitive outcome at 2 and 3.5 years, but the association was mediated by cerebellar injury.ConclusionVent and CoGM volumes at TEA may serve as biomarkers for long-term neurodevelopmental outcome in preterm infants. The relationship between larger CoGM volumes and adverse neurodevelopment may reflect disturbances in white matter-CoGM boundaries and warrants further investigation.Abstract PS-332 Table 1CCs (n = 108)FMss (n = 108)GMss (n = 108)DQ (n = 94)Ventricles-3.5;-6.1--0.9-0.8;-1.3--0.2-0.5;-0.9--0.1-2.1;-3.8--0.4Cerebellum5.4;1.0–9.7nsns4.0;1.5–6.5CoGM-1.6;-2.8--0.5-0.4;-0.7--0.2-0.4;-0.5--0.2-0.9;-1.7--0.2Numbers reflect coefficients and 95%-confidence intervals