104 research outputs found
Reflections and Experiences of a Co-Researcher involved in a Renal Research Study
Background Patient and Public Involvement (PPI) is seen as a prerequisite for health research. However, current Patient and public involvement literature has noted a paucity of recording of patient and public involvement within research studies. There have been calls for more recordings and reflections, specifically on impact. Renal medicine has also had similar criticisms and any reflections on patient and public involvement has usually been from the viewpoint of the researcher. Roles of patient and public involvement can vary greatly from sitting on an Advisory Group to analysing data. Different PPI roles have been described within studies; one being a co-researcher. However, the role of the co-researcher is largely undefined and appears to vary from study to study. Methods The aims of this paper are to share one first time co-researcher's reflections on the impact of PPI within a mixed methods (non-clinical trial) renal research study. A retrospective, reflective approach was taken using data available to the co-researcher as part of the day-to-day research activity. Electronic correspondence and documents such as meeting notes, minutes, interview thematic analysis and comments on documents were re-examined. The co-researcher led on writing this paper. Results This paper offers a broad definition of the role of the co-researcher. The co-researcher reflects on undertaking and leading on the thematic analysis of interview transcripts, something she had not previously done before. The co-researcher identified a number of key themes; the differences in time and responsibility between being a coresearcher and an Advisory Group member; how the role evolved and involvement activities could match the co-researchers strengths (and the need for flexibility); the need for training and support and lastly, the time commitment. It was also noted that it is preferable that a co-researcher needs to be involved from the very beginning of the grant application. Conclusions The reflections, voices and views of those undertaking PPI has been largely underrepresented in the literature. The role of co-researcher was seen to be rewarding but demanding, requiring a large time commitment. It is hoped that the learning from sharing this experience will encourage others to undertake this role, and encourage researchers to reflect on the needs of those involved.Peer reviewedFinal Published versio
Multi-task learning for joint weakly-supervised segmentation and aortic arch anomaly classification in fetal cardiac MRI
Congenital Heart Disease (CHD) is a group of cardiac malformations present
already during fetal life, representing the prevailing category of birth
defects globally. Our aim in this study is to aid 3D fetal vessel topology
visualisation in aortic arch anomalies, a group which encompasses a range of
conditions with significant anatomical heterogeneity. We present a multi-task
framework for automated multi-class fetal vessel segmentation from 3D black
blood T2w MRI and anomaly classification. Our training data consists of binary
manual segmentation masks of the cardiac vessels' region in individual subjects
and fully-labelled anomaly-specific population atlases. Our framework combines
deep learning label propagation using VoxelMorph with 3D Attention U-Net
segmentation and DenseNet121 anomaly classification. We target 11 cardiac
vessels and three distinct aortic arch anomalies, including double aortic arch,
right aortic arch, and suspected coarctation of the aorta. We incorporate an
anomaly classifier into our segmentation pipeline, delivering a multi-task
framework with the primary motivation of correcting topological inaccuracies of
the segmentation. The hypothesis is that the multi-task approach will encourage
the segmenter network to learn anomaly-specific features. As a secondary
motivation, an automated diagnosis tool may have the potential to enhance
diagnostic confidence in a decision support setting. Our results showcase that
our proposed training strategy significantly outperforms label propagation and
a network trained exclusively on propagated labels. Our classifier outperforms
a classifier trained exclusively on T2w volume images, with an average balanced
accuracy of 0.99 (0.01) after joint training. Adding a classifier improves the
anatomical and topological accuracy of all correctly classified double aortic
arch subjects.Comment: Accepted for publication at the Journal of Machine Learning for
Biomedical Imaging (MELBA) https://melba-journal.org/2023:01
Fetal whole-heart 4D imaging using motion-corrected multi-planar real-time MRI
Purpose: To develop a MRI acquisition and reconstruction framework for
volumetric cine visualisation of the fetal heart and great vessels in the
presence of maternal and fetal motion.
Methods: Four-dimensional depiction was achieved using a highly-accelerated
multi-planar real-time balanced steady state free precession acquisition
combined with retrospective image-domain techniques for motion correction,
cardiac synchronisation and outlier rejection. The framework was evaluated and
optimised using a numerical phantom, and evaluated in a study of 20 mid- to
late-gestational age human fetal subjects. Reconstructed cine volumes were
evaluated by experienced cardiologists and compared with matched ultrasound. A
preliminary assessment of flow-sensitive reconstruction using the velocity
information encoded in the phase of dynamic images is included.
Results: Reconstructed cine volumes could be visualised in any 2D plane
without the need for highly-specific scan plane prescription prior to
acquisition or for maternal breath hold to minimise motion. Reconstruction was
fully automated aside from user-specified masks of the fetal heart and chest.
The framework proved robust when applied to fetal data and simulations
confirmed that spatial and temporal features could be reliably recovered.
Expert evaluation suggested the reconstructed volumes can be used for
comprehensive assessment of the fetal heart, either as an adjunct to ultrasound
or in combination with other MRI techniques.
Conclusion: The proposed methods show promise as a framework for
motion-compensated 4D assessment of the fetal heart and great vessels
An initial consideration of silicon carbide devices in pressure-packages
Fast switching SiC Schottky diodes are known to exhibit significant output oscillations and electromagnetic emissions in the presence of parasitic inductance from the package/module connections. Furthermore, solder pad delamination and wirebond lift-off are common failure modes in high temperature applications. To this end, pressure packages, which obviate the need for wire-bonds and solder/die attach, have been developed for high power applications where reliability is critical like thyristor valves in HVDC line commutated converters. In this paper, SiC Schottky diodes in pressure-packages (press-pack) have been designed, developed and tested. The electrothermal properties of the SiC diode in press-pack have been tested as a function of the clamping force using different thermal contacts, namely molybdenum and Aluminum Graphite. Finite Element Simulations have been used to support the analysis
Impaired development of the cerebral cortex in infants with congenital heart disease is correlated to reduced cerebral oxygen delivery
Neurodevelopmental impairment is the most common comorbidity associated with complex congenital heart disease (CHD), while the underlying biological mechanism remains unclear. We hypothesised that impaired cerebral oxygen delivery in infants with CHD is a cause of impaired cortical development, and predicted that cardiac lesions most associated with reduced cerebral oxygen delivery would demonstrate the greatest impairment of cortical development. We compared 30 newborns with complex CHD prior to surgery and 30 age-matched healthy controls using brain MRI. The cortex was assessed using high resolution, motion-corrected T2-weighted images in natural sleep, analysed using an automated pipeline. Cerebral oxygen delivery was calculated using phase contrast angiography and pre-ductal pulse oximetry, while regional cerebral oxygen saturation was estimated using near-infrared spectroscopy. We found that impaired cortical grey matter volume and gyrification index in newborns with complex CHD was linearly related to reduced cerebral oxygen delivery, and that cardiac lesions associated with the lowest cerebral oxygen delivery were associated with the greatest impairment of cortical development. These findings suggest that strategies to improve cerebral oxygen delivery may help reduce brain dysmaturation in newborns with CHD, and may be most relevant for children with CHD whose cardiac defects remain unrepaired for prolonged periods after birth
Fully automated planning for anatomical fetal brain MRI on 0.55T
Purpose: Widening the availability of fetal MRI with fully automatic
real-time planning of radiological brain planes on 0.55T MRI. Methods: Deep
learning-based detection of key brain landmarks on a whole-uterus EPI scan
enables the subsequent fully automatic planning of the radiological single-shot
Turbo Spin Echo acquisitions. The landmark detection pipeline was trained on
over 120 datasets from varying field strength, echo times and resolutions and
quantitatively evaluated. The entire automatic planning solution was tested
prospectively in nine fetal subjects between 20 and 37 weeks. Comprehensive
evaluation of all steps, the distance between manual and automatic landmarks,
the planning quality and the resulting image quality was conducted. Results:
Prospective automatic planning was performed in real-time without latency in
all subjects. The landmark detection accuracy was 4.21+-2.56 mm for the fetal
eyes and 6.47+-3.23 for the cerebellum, planning quality was 2.44/3 (compared
to 2.56/3 for manual planning) and diagnostic image quality was 2.14 compared
to 2.07 for manual planning. Conclusions: Real-time automatic planning of all
three key fetal brain planes was successfully achieved and will pave the way
towards simplifying the acquisition of fetal MRI thereby widening the
availability of this modality in non-specialist centres.Comment: 17 pages, 8 figures, 1 table, MR
A Uniform Description of Perioperative Brain MRI Findings in Infants with Severe Congenital Heart Disease:Results of a European Collaboration
BACKGROUND AND PURPOSE: A uniform description of brain MR imaging findings in infants with severe congenital heart disease to assess risk factors, predict outcome, and compare centers is lacking. Our objective was to uniformly describe the spectrum of perioperative brain MR imaging findings in infants with congenital heart disease. MATERIALS AND METHODS: Prospective observational studies were performed at 3 European centers between 2009 and 2019. Brain MR imaging was performed preoperatively and/or postoperatively in infants with transposition of the great arteries, single-ventricle physiology, or left ventricular outflow tract obstruction undergoing cardiac surgery within the first 6 weeks of life. Brain injury was assessed on T1, T2, DWI, SWI, and MRV. A subsample of images was assessed jointly to reach a consensus. RESULTS: A total of 348 MR imaging scans (180 preoperatively, 168 postoperatively, 146 pre- and postoperatively) were obtained in 202 infants. Preoperative, new postoperative, and cumulative postoperative white matter injury was identified in 25%, 30%, and 36%; arterial ischemic stroke, in 6%, 10%, and 14%; hypoxic-ischemic watershed injury in 2%, 1%, and 1%; intraparenchymal cerebral hemorrhage, in 0%, 4%, and 5%; cerebellar hemorrhage, in 6%, 2%, and 6%; intraventricular hemorrhage, in 14%, 6%, and 13%; subdural hemorrhage, in 29%, 17%, and 29%; and cerebral sinovenous thrombosis, in 0%, 10%, and 10%, respectively. CONCLUSIONS: A broad spectrum of perioperative brain MR imaging findings was found in infants with severe congenital heart disease. We propose an MR imaging protocol including T1-, T2-, diffusion-, and susceptibility-weighted imaging, and MRV to identify ischemic, hemorrhagic, and thrombotic lesions observed in this patient group
A genome-wide meta-analysis of palmoplantar pustulosis implicates TH2 responses and cigarette smoking in disease pathogenesis
\ua9 2024 The AuthorsBackground: Palmoplantar pustulosis (PPP) is an inflammatory skin disorder that mostly affects smokers and manifests with painful pustular eruptions on the palms and soles. Although the disease can present with concurrent plaque psoriasis, TNF and IL-17/IL-23 inhibitors show limited efficacy. There is therefore a pressing need to uncover PPP disease drivers and therapeutic targets. Objectives: We sought to identify genetic determinants of PPP and investigate whether cigarette smoking contributes to disease pathogenesis. Methods: We performed a genome-wide association meta-analysis of 3 North-European cohorts (n = 1,456 PPP cases and 402,050 controls). We then used the scGWAS program to investigate the cell-type specificity of the association signals. We also undertook genetic correlation analyses to examine the similarities between PPP and other immune-mediated diseases. Finally, we applied Mendelian randomization to analyze the causal relationship between cigarette smoking and PPP. Results: We found that PPP is not associated with the main genetic determinants of plaque psoriasis. Conversely, we identified genome-wide significant associations with the FCGR3A/FCGR3B and CCHCR1 loci. We also observed 13 suggestive (P < 5
7 10−6) susceptibility regions, including the IL4/IL13 interval. Accordingly, we demonstrated a significant genetic correlation between PPP and TH2-mediated diseases such as atopic dermatitis and ulcerative colitis. We also found that genes mapping to PPP-associated intervals were preferentially expressed in dendritic cells and often implicated in T-cell activation pathways. Finally, we undertook a Mendelian randomization analysis, which supported a causal role of cigarette smoking in PPP. Conclusions: The first genome-wide association study of PPP points to a pathogenic role for deregulated TH2 responses and cigarette smoking
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