Practices to support co-design processes: A case-study of co-designing a program for children with parents with a mental health problem in the Austrian region of Tyrol.

Forms of collaborative knowledge production, such as community-academic partnerships (CAP), have been increasingly used in health care. However, instructions on how to deliver such processes are lacking. We aim to identify practice ingredients for one element within a CAP, a 6-month co-design process, during which 26 community- and 13 research-partners collaboratively designed an intervention programme for children whose parent have a mental illness. Using 22 published facilitating and hindering factors for CAP as the analytical framework, eight community-partners reflected on the activities which took place during the co-design process. From a qualitative content analysis of the data, we distilled essential practices for each CAP factor. Ten community- and eight research-partners revised the results and co-authored this article. We identified 36 practices across the 22 CAP facilitating or hindering factors. Most practices address more than one factor. Many practices relate to workshop design, facilitation methods, and relationship building. Most practices were identified for facilitating 'trust among partners', 'shared visions, goals and/or missions', 'effective/frequent communication', and 'well-structured meetings'. Fewer practices were observed for 'effective conflict resolution', 'positive community impact' and for avoiding 'excessive funding pressure/control struggles' and 'high burden of activities'. Co-designing a programme for mental healthcare is a challenging process that requires skills in process management and communication. We provide practice steps for delivering co-design activities. However, practitioners may have to adapt them to different cultural contexts. Further research is needed to analyse whether co-writing with community-partners results in a better research output and benefits for participants.

A deep learning pipeline for the automated segmentation of posterior limb of internal capsule in preterm neonates.

Segmentation of specific brain tissue from MRI volumes is of great significance for brain disease diagnosis, progression assessment, and monitoring of neurological conditions. Manual segmentation is time-consuming, laborious, and subjective, which significantly amplifies the need for automated processes. Over the last decades, the active development in the field of deep learning, especially convolutional neural networks (CNNs), and the associated performance improvements have increased the demand for the application of CNN-based methods to provide consistent measurements and quantitative analyses. In this paper, we present an efficient deep learning approach for the segmentation of brain tissue. More specifically, we address the problem of segmentation of the posterior limb of the internal capsule (PLIC) in preterm neonates. To this end, we propose a CNN-based pipeline comprised of slice-selection modules and a multi-view segmentation model, which exploits the 3D information contained in the MRI volumes to improve segmentation performance. One special feature of the proposed method is its ability to identify one desired slice out of the whole image volume, which is relevant for pediatricians in terms of prognosis. To increase computational efficiency, we apply a strategy that automatically reduces the information contained in the MRI volumes to its relevant parts. Finally, we conduct an expert rating alongside standard evaluation metrics, such as dice score, to evaluate the performance of the proposed framework. We demonstrate the benefit of the multi-view technique by comparing it with its single-view counterparts, which reveals that the proposed method strikes a good balance between exploiting the available image information and reducing the required computing power compared to 3D segmentation networks. Standard evaluation metrics as, well as expert-based assessment, confirm the good performance of the proposed framework, with the latter being more relevant in terms of clinical applicability. We demonstrate that the proposed deep learning pipeline can compete with the experts in terms of accuracy. To prove the generalisability of the proposed method, we additionally assess our deep learning pipeline to data from the Developing Human Connectome Project (dHCP).

Magnetic Resonance Spectroscopy in Diagnosis and Follow-Up of Gliomas: State-of-the-Art.

Preoperative grade prediction is important in diagnostics of glioma. Even more important can be follow-up after chemotherapy and radiotherapy of high grade gliomas. In this review we provide an overview of MR-spectroscopy (MRS), technical aspects, and different clinical scenarios in the diagnostics and follow-up of gliomas in pediatric and adult populations. Furthermore, we provide a recap of the current research utility and possible future strategies regarding proton- and phosphorous-MRS in glioma research.

The association of allergic asthma and carotid intima-media thickness in adolescence: data of the prospective early vascular ageing (EVA)-Tyrol cohort study.

BACKGROUND: In recent years, there has been increasing evidence that asthma is associated with atherosclerosis and cardiovascular disease. However, data in children and adolescents are scarce and conflicting. We aimed to assess the impact of asthma with and without an allergic component on the carotid intima-media thickness in a large pediatric population. METHODS: The community-based early vascular ageing-Tyrol cohort study was performed between May 2015 and July 2018 in North, East (Austria) and South Tyrol (Italy) and recruited youngster aged 14 years and above. Medical examinations included anthropometric measurements, fasting blood analysis, measurement of the carotid intima-media thickness by high-resolution ultrasound, and a physician guided interview. RESULTS: The mean age of the 1506 participants was 17.8 years (standard deviation 0.90). 851 (56.5%) participants were female. 22 subjects had a physician diagnosis of non-allergic asthma, 268 had inhalative allergies confirmed by a positive radio-allergo-sorbent-test and/or prick test, and 58 had allergic asthma. Compared to healthy controls, participants with non-allergic asthma (411.7 vs. 411.7 µm; p = 0.932) or inhalative allergy (420.0 vs. 411.7 µm; p = 0.118) did not have significantly higher carotid intima-media thickness (cIMT). However, participants with allergic asthma had significantly higher cIMT (430.8 vs. 411.7; p = 0.004) compared to those without and this association remained significant after multivariable adjustment for established cardiovascular risk factors. CONCLUSION: Allergic asthma in the youth is associated with an increased carotid intima-media thickness. Physicians should therefore be aware of allergic asthma as a potential cardiovascular risk factor in children and adolescents. Trial Registration Number The EVA-Tyrol Study has been retrospectively registered at clinicaltrials.gov under NCT03929692 since April 29, 2019.