Both brain size and biological sex contribute to variation in white matter microstructure in middle-aged healthy adults

Whether head size and/or biological sex influence proxies of white matter (WM) microstructure such as fractional anisotropy (FA) and mean diffusivity (MD) remains controversial. Diffusion tensor imaging (DTI) indices are also associated with age, but there are large discrepancies in the spatial distribution and timeline of age-related differences reported. The aim of this study was to evaluate the associations between intracranial volume (ICV), sex, and age and DTI indices from WM in a population-based study of healthy individuals (n = 812) aged 50–66 in the Nord-Trøndelag health survey. Semiautomated tractography and tract-based spatial statistics (TBSS) analyses were performed on the entire sample and in an ICV-matched sample of men and women. The tractography results showed a similar positive association between ICV and FA in all major WM tracts in men and women. Associations between ICV and MD, radial diffusivity and axial diffusivity were also found, but to a lesser extent than FA. The TBSS results showed that both men and women had areas of higher and lower FA when controlling for age, but after controlling for age and ICV only women had areas with higher FA. The ICV matched analysis also demonstrated that only women had areas of higher FA. Age was negatively associated with FA across the entire WM skeleton in the TBSS analysis, independent of both sex and ICV. Combined, these findings demonstrated that both ICV and sex contributed to variation in DTI indices and emphasized the importance of considering ICV as a covariate in DTI analysis

MULTIDIMENSIONAL STRENGTH PROPERTIES IN CLEAR WOOD SAMPLES OF CULTIVATED NORWAY SPRUCE PRO LIGNO

Abstract: Variatio

Development of an augmented reality concept for icebreaker assistance and convoy operations

A vessel convoy is a complex and high‐risk operation completed during icebreaking operations in the Arctic. Icebreaker navigators need to continuously communicate with their crew while monitoring information such as speed, heading, and distance between vessels in the convoy. This paper presents an augmented reality user interface concept, which aims to support navigators by improving oversight and safety during convoy operations. The concept demonstrates how augmented reality can help to realize a situated user interface that adapts to user’s physical and operational contexts. The concept was developed through a human‐centered design process and tested through a virtual reality simulator in a usability study involving seven mariners. The results suggest that augmented reality has the potential to improve the safety of convoy operations by integrating distributed information with heads‐up access to operation‐critical information. However, the user interface concept is still novel, and further work is needed to develop the concept and safely integrate augmented reality into maritime operations

A review of augmented reality applications for ship bridges

We present a state-of-the art analysis of Augmented Reality (AR) applications for ship bridge operation. We compiled and reviewed what type of use cases were published, what type of maritime applications have been adapted to AR, how they were prototyped and evaluated and what type of technology was used. We also reviewed the user interaction mechanisms, information display and adaptation to maritime environmental conditions. Our analysis shows that although there are many examples of AR applications in ship bridges, there is still much work that needs to be done before these solutions can be suitably adapted to commercial settings. In addition, we argue there is a need to develop design requirements and regulations that can guide the safe development of AR

Utfordringer og mestring ved diabetes type 1 hos barn

Sammendrag Bakgrunn Omtrent 300 barn i Norge blir diagnosert med diabetes type 1 hvert år. Diabetes type 1 er en alvorlig kronisk sykdom som krever mye tid og oppmerksomhet til egenomsorg og behandling. Sykepleier har en viktig rolle i opplæring og kan bidra til mestring. Hensikt Hensikten med oppgaven er å belyse utfordringer barn står overfor med diabetes type 1 og hvordan sykepleier kan hjelpe barnet til å oppleve mestring i hverdagen. Metode Metoden vi har brukt i denne oppgaven er en integrativ litteraturoversikt som bygger på fire studier. Vi har analyserer studiene og brukt relevant teori sammen med studienes resultater samt egne refleksjoner for å besvare oppgavens hensikt. Resultat Etter analyse av studiene ble det trukket frem tre hovedfunn; mangelfull mestringsopplevelse, å føle seg annerledes og sykepleierens rolle. Sammen belyser disse funnene hvordan sykepleier kan fremme mestring hos barn. Nøkkelord: Sykepleie, diabetes type 1, barn, unge, mestring, egenomsorg, livsstil, utfordringer, opplæring, annerlede

Unsupervised supervoxel-based lung tumor segmentation across patient scans in hybrid PET/MRI

Tumor segmentation is a crucial but difficult task in treatment planning and follow-up of cancerous patients. The challenge of automating the tumor segmentation has recently received a lot of attention, but the potential of utilizing hybrid positron emission tomography (PET)/magnetic resonance imaging (MRI), a novel and promising imaging modality in oncology, is still under-explored. Recent approaches have either relied on manual user input and/or performed the segmentation patient-by-patient, whereas a fully unsupervised segmentation framework that exploits the available information from all patients is still lacking. We present an unsupervised across-patients supervoxel-based clustering framework for lung tumor segmentation in hybrid PET/MRI. The method consists of two steps: First, each patient is represented by a set of PET/ MRI supervoxel-features. Then the data points from all patients are transformed and clustered on a population level into tumor and non-tumor supervoxels. The proposed framework is tested on the scans of 18 non-small cell lung cancer patients with a total of 19 tumors and evaluated with respect to manual delineations provided by clinicians. Experiments study the performance of several commonly used clustering algorithms within the framework and provide analysis of (i) the effect of tumor size, (ii) the segmentation errors, (iii) the benefit of across-patient clustering, and (iv) the noise robustness. The proposed framework detected 15 out of 19 tumors in an unsupervised manner. Moreover, performance increased considerably by segmenting across patients, with the mean dice score increasing from 0.169 ± 0.295 (patient-by-patient) to 0.470 ± 0.308 (across-patients). Results demonstrate that both spectral clustering and Manhattan hierarchical clustering have the potential to segment tumors in PET/MRI with a low number of missed tumors and a low number of false-positives, but that spectral clustering seems to be more robust to noise

A comparison of FDG PET/MR and PET/CT for staging, response assessment, and prognostic imaging biomarkers in lymphoma

The aim of the current study was to investigate the diagnostic performance of FDG PET/MR compared to PET/CT in a patient cohort including Hodgkins lymphoma, diffuse large B-cell lymphoma, and high-grade B-cell lymphoma at baseline and response assessment. Sixty-one patients were examined with FDG PET/CT directly followed by PET/MR. Images were read by two pairs of nuclear medicine physicians and radiologists. Concordance for lymphoma involvement between PET/MR and the reference standard PET/CT was assessed at baseline and response assessment. Correlation of prognostic biomarkers Deauville score, criteria of response, SUVmax, SUVpeak, and MTV was performed between PET/MR and PET/CT. Baseline FDG PET/MR showed a sensitivity of 92.5% and a specificity 97.9% compared to the reference standard PET/CT (κ 0.91) for nodal sites. For extranodal sites, a sensitivity of 80.4% and a specificity of 99.5% were found (κ 0.84). Concordance in Ann Arbor was found in 57 of 61 patients (κ 0.92). Discrepancies were due to misclassification of region and not lesion detection. In response assessment, a sensitivity of 100% and a specificity 99.9% for all sites combined were found (κ 0.92). There was a perfect agreement on Deauville scores 4 and 5 and criteria of response between the two modalities. Intraclass correlation coefficient (ICC) for SUVmax, SUVpeak, and MTV values showed excellent reliability (ICC > 0.9). FDG PET/MR is a reliable alternative to PET/CT in this patient population, both in terms of lesion detection at baseline staging and response assessment, and for quantitative prognostic imaging biomarkers

Hvordan praktisere brukermedvirkning uten brukeren? Organisatoriske utfordringer for brukermedvirkning i helse og omsorgstjenester i rus og psykiatrifeltet

Brukermedvirkning i behandling er en lovfestet rett i Norge. Hvordan er helsepolitiske føringer implementert i praksis? Vi diskuterte medvirkning med brukere, pårørende og tjenesteytere i rus og psykisk helsevern i en norsk kommune og samarbeidende spesialisthelsetjenester. Data ble samlet fra to ulike arenaer. I tjeneste, bruker- og pårørendespesifikke grupper diskuterte deltakerne hvordan helsepolitiske føringer og et fragmentert tjenesteapparat satte ulike aktører opp mot hverandre og reduserte medvirkningen for alle. I mindre, tverrfaglige grupper som inkluderte brukere og pårørende, kom eksempler fram om tverrfaglig praksis som en arena for felles problemløsning. Artikkelen bidrar med teori, forskningsmetoder og praksis om tjenesteutvikling på lokalplan. Det er i denne konteksten brukere, pårørende og tjenesterepresentanter kan jobbe sammen for å realisere intensjonen i sentral helsepolitikk.publishedVersio

Pelvic PET/MR attenuation correction in the image space using deep learning

IntroductionThe five-class Dixon-based PET/MR attenuation correction (AC) model, which adds bone information to the four-class model by registering major bones from a bone atlas, has been shown to be error-prone. In this study, we introduce a novel method of accounting for bone in pelvic PET/MR AC by directly predicting the errors in the PET image space caused by the lack of bone in four-class Dixon-based attenuation correction.MethodsA convolutional neural network was trained to predict the four-class AC error map relative to CT-based attenuation correction. Dixon MR images and the four-class attenuation correction µ-map were used as input to the models. CT and PET/MR examinations for 22 patients ([18F]FDG) were used for training and validation, and 17 patients were used for testing (6 [18F]PSMA-1007 and 11 [68Ga]Ga-PSMA-11). A quantitative analysis of PSMA uptake using voxel- and lesion-based error metrics was used to assess performance.ResultsIn the voxel-based analysis, the proposed model reduced the median root mean squared percentage error from 12.1% and 8.6% for the four- and five-class Dixon-based AC methods, respectively, to 6.2%. The median absolute percentage error in the maximum standardized uptake value (SUVmax) in bone lesions improved from 20.0% and 7.0% for four- and five-class Dixon-based AC methods to 3.8%.ConclusionThe proposed method reduces the voxel-based error and SUVmax errors in bone lesions when compared to the four- and five-class Dixon-based AC models