Impact of the COVID-19 pandemic on radiography practice: findings from a UK radiography workforce survey

OBJECTIVES: Radiographers are key patient-facing healthcare professionals involved in many aspects of patient care. The working patterns and professional practice of the radiography workforce (RW) has been altered during the COVID-19 pandemic. This survey aimed to assess the impact of the pandemic on radiography practice in the United Kingdom (UK). METHODS: An online cross-sectional survey of the UK RW was performed (March 25th to April 26th, 2020). The survey sought information regarding 1. Demographics 2. Impact of the pandemic on professional practice 3. Infection prevention/control and 4. COVID-19 related stress. Data collected was analysed using the Statistical Package for Social Sciences (v.26). RESULTS: A total of 522 responses were received, comprising n = 412 (78.9%) diagnostic and n = 110 (21.1%) therapeutic RW categories from across the UK. 12.5% (65/522) of the respondents were redeployed. Redeployment did not appear to contribute (p = 0.31) to work-related stress. However, fear of contracting the infection and perceived inadequate personal protective equipment (PPE) were identified as key contributors to stress during the study period. Compared to the therapeutic RW, a significantly higher proportion of the diagnostic RW identified fear of being infected as a major stressor (166/412 (40.3%) vs 30/110 (27.3%), p = 0.01). CONCLUSION: This survey has demonstrated changes to clinical practice, in particular to working patterns, service delivery and infection prevention and control were key contributors to workplace-related stress during the pandemic. ADVANCES IN KNOWLEDGE: Timely and adequate staff training and availability of PPE as well as psychosocial support during future pandemics would enhance quality patient and staff safety

Explaining the practicum experiences of diagnostic radiography undergraduates in Australia and Ethiopia using the theory of human relatedness

Introduction Practice learning is critical to the development of clinical skills; hence placements are a major component of all pre-registration radiography programmes. Nonetheless, dissatisfaction with practicum experiences is a common reason why students consider leaving such programmes. Providing effective placements which promote retention may not only require better appreciation of students’ clinical reflections, but also a more fundamental understanding of the implicit criteria they use to appraise a practicum. This study applied the theory of human relatedness (THR) to the placement experiences of radiography undergraduates to identify the evaluative mechanisms which may underpin these experiences. Methods A critical realist investigative approach was employed to reanalyse data regarding the practicum experiences of stakeholders involved in undergraduate diagnostic radiography programmes at two universities in Australia and Ethiopia against the eight core THR concepts, namely connectedness, disconnectedness, parallelism, enmeshment, belonging, reciprocity, mutuality, and synchrony. Results The findings identified all states of relatedness and processes/social competencies of the THR within the placement experiences of these stakeholders. The degree of positive relatedness a radiography student experiences within a practicum, irrespective of the setting, may affect their clinical performance. Conclusion The findings support the argument that the THR may reflect an implicit set of criteria stakeholders use to evaluate clinical encounters. Additionally, these results are congruent with earlier investigations regarding the practicum reflections of other undergraduate healthcare students. Implications for practice To enhance student placement experiences, it is necessary to recognise the effect a student's sense of relatedness may have on their self-efficacy and proficiency, modifying pre-practicum preparation and assessment arrangements to inhibit disconnectedness and enmeshment, avoid the need for parallelism, and better cultivate connectedness, belonging, reciprocity, mutuality, and synchrony

The radiology workforce’s response to the COVID-19 pandemic in the Middle East, North Africa and India

Introduction This study aimed to investigate the response of the radiology workforce to the impact of the coronavirus disease 2019 (COVID-19) pandemic on professional practice in India and eight other Middle Eastern and North African countries. It further investigated the levels of fear and anxiety among this workforce during the pandemic. Methods A quantitative cross-sectional study was conducted using an online survey from 22 May-2 June 2020 among radiology workers employed during the COVID-19 pandemic. The survey collected information related to the following themes: (1) demographic characteristics, (2) the impact of COVID-19 on radiology practice, and (3) fear and (4) anxiety emanating from the global pandemic. Results We received 903 responses. Fifty-eight percent had completed training on infection control required for handling COVID-19 patients. A large proportion (79.5%) of the respondents strongly agreed or agreed that personal protective equipment (PPE) was adequately available at work during the pandemic. The respondents reported experiences of work-related stress (42.9%), high COVID-19 fear score (83.3%) and anxiety (10%) during the study period. Conclusion There was a perceived workload increase in general x-ray and Computed Tomography imaging procedures because they were the key modalities for the initial and follow-up investigations of COVID-19. However, there was adequate availability of PPE during the study period. Most radiology workers were afraid of being infected with the virus. Fear was predominant among workers younger than 30 years of age and also in temporary staff. Anxiety occurred completely independent of gender, age, experience, country, place of work, and work status. Implications for practice It is important to provide training and regular mental health support and evaluations for healthcare professionals, including radiology workers, during similar future pandemics

Cognitive and Clinical Predictors of Prefrontal Cortical Thickness Change Following First-Episode of Psychosis

The association of neuroanatomical progression with cognitive and clinical deterioration after first-episode of psychosis remains uncertain. This longitudinal study aims to assess whether i)impaired executive functioning and emotional intelligence at first presentation are associated with progressive prefrontal and orbitofrontal cortical thinning ii)negative symptom severity is linked to progressive prefrontal cortical thinning. 1.5T MRI images were acquired at baseline and after 3.5 years for 20 individuals with first-episode psychosis and 18 controls. The longitudinal pipeline of Freesurfer was employed to parcellate prefrontal cortex at two time points. Baseline cognitive performance was compared between diagnostic groups using MANCOVA. Partial correlations investigated relationships between cognition and negative symptoms at baseline and cortical thickness change over time. Patients displayed poorer performance than controls at baseline in working memory, reasoning/problem solving and emotional intelligence. In patients, loss of prefrontal and orbitofrontal thickness over time was predicted by impaired working memory and emotional intelligence respectively at baseline. Moreover, exploratory analyses revealed that the worsening of negative symptoms over time was significantly related to prefrontal cortical thinning. Results indicate that specific cognitive deficits at the onset of psychotic illness are markers of progressive neuroanatomical deficits and that worsening of negative symptoms occurs with prefrontal thickness reduction as the illness progresses

White Matter Microstructure and Structural Networks in Treatment-Resistant Schizophrenia Patients After Commencing Clozapine Treatment: A Longitudinal Diffusion Imaging Study

This study investigates changes on white matter microstructure and neural networks after 6 months of switching to clozapine in schizophrenia patients compared to controls, and whether any changes are related to clinical variables. T1 and diffusion-weighted MRI images were acquired at baseline before commencing clozapine and after 6 months of treatment for 22 patients with treatment-resistant schizophrenia and 23 controls. The Tract-based spatial statistics approach was used to compare changes over time between groups in fractional anisotropy (FA). Changes in structural network organisation weighted by FA and number of streamlines were assessed using graph theory. Patients displayed a significant reduction of FA over time (p<0.05) compared to controls in the genu and body of the corpus callosum and bilaterally in the anterior and superior corona radiata. There was no correlation between FA change in patients and changes in clinical variables or serum level of clozapine. There was no changes in structural network organisation between groups (F(7,280)=2.80;p = 0.187). This longitudinal study demonstrated progressive focal FA abnormalities in key anterior tracts, but preserved brain structural network organisation in patients. The FA reduction was independent of any clinical measures and may reflect progression of the underlying pathophysiology of this malignant form of schizophrenia illness

Progression of neuroanatomical abnormalities after first-episode of psychosis: A 3-year longitudinal sMRI study

The location, extent and progression of longitudinal morphometric changes after first-episode of psychosis (FEP) remains unclear. We investigated ventricular and cortico-subcortical regions over a 3-year period in FEP patients compared with healthy controls. High resolution 1.5T T1-weighted MR images were obtained at baseline from 28 FEP patients at presentation and 28 controls, and again after 3-years. The longitudinal FreeSurfer pipeline (v.5.3.0) was used for regional volumetric and cortical reconstruction image analyses. Repeated-measures ANCOVA and vertex-wise linear regression analyses compared progressive changes between groups in subcortical structures and cortical thickness respectively. Compared with controls, patients displayed progressively reduced volume of the caudate [F (1,51)=5.86, p=0.02, Hedges’ g=0.66], putamen [F (1,51)=6.06, p=0.02, g=0.67], thalamus [F (1,51)=6.99, p=0.01, g=0.72] and increased right lateral ventricular volume [F (1, 51)=4.03, p=0.05], and significantly increased rate of cortical thinning [F (1,52)=5.11, p=0.028)] at a mean difference of 0.84% [95% CI (0.10, 1.59)] in the left lateral orbitofrontal region over the 3-year period. In patients, greater reduction in putamen volume over time was associated with lower cumulative antipsychotic medication dose (r=0.49, p=0.01), and increasing lateral ventricular volume over time was associated with worsening negative symptoms (r=0.41, p=0.04) and poorer global functioning (r= −0.41, p=0.04). This study demonstrates localised progressive structural abnormalities in the cortico-striato-thalamo-cortical circuit after the onset of psychosis, with increasing ventricular volume noted as a neuroanatomical marker of poorer clinical and functional outcome

The integration of artificial intelligence in medical imaging practice: Perspectives of African radiographers

Introduction The current technological developments in medical imaging are centred largely on the increasing integration of artificial intelligence (AI) into all equipment modalities. This survey assessed the perspectives of African radiographers on the integration of AI in medical imaging in order to offer unique recommendations to support the training of the radiography workforce. Methods An exploratory cross-sectional online survey of radiographers working within Africa was conducted from March to August 2020. The survey obtained data about their demographics and perspectives on AI implementation and usage. Data obtained were analysed using both descriptive and inferential statistics. Results A total of 1020 valid responses were obtained. Majority of the respondents (n = 883,86.6%) were working in general X-ray departments. Of the respondents, 84.9% (n = 866) indicated that AI technology would improve radiography practice and quality assurance for efficient diagnosis and improved clinical care. Fear of job losses following the implementation of AI was a key concern of most radiographers (n = 625,61.3%). Conclusion Generally, radiographers were delighted about the integration of AI into medical imaging, however; there were concerns about job security and lack of knowledge. There is an urgent need for stakeholders in medical imaging infrastructure development and practices in Africa to start empowering radiographers through training programmes, funding, motivational support, and create clear roadmaps to guide the adoption and integration of AI in medical imaging in Africa. Implication for practice The current study offers unique suggestions and recommendations to support the training of the African radiography workforce and others in similar resource-limited settings to provide quality care using AI-integrated imaging modalities

Using structural MRI to identify bipolar disorders - 13 site machine learning study in 3020 individuals from the ENIGMA Bipolar Disorders Working Group.

Bipolar disorders (BDs) are among the leading causes of morbidity and disability. Objective biological markers, such as those based on brain imaging, could aid in clinical management of BD. Machine learning (ML) brings neuroimaging analyses to individual subject level and may potentially allow for their diagnostic use. However, fair and optimal application of ML requires large, multi-site datasets. We applied ML (support vector machines) to MRI data (regional cortical thickness, surface area, subcortical volumes) from 853 BD and 2167 control participants from 13 cohorts in the ENIGMA consortium. We attempted to differentiate BD from control participants, investigated different data handling strategies and studied the neuroimaging/clinical features most important for classification. Individual site accuracies ranged from 45.23% to 81.07%. Aggregate subject-level analyses yielded the highest accuracy (65.23%, 95% CI = 63.47-67.00, ROC-AUC = 71.49%, 95% CI = 69.39-73.59), followed by leave-one-site-out cross-validation (accuracy = 58.67%, 95% CI = 56.70-60.63). Meta-analysis of individual site accuracies did not provide above chance results. There was substantial agreement between the regions that contributed to identification of BD participants in the best performing site and in the aggregate dataset (Cohen's Kappa = 0.83, 95% CI = 0.829-0.831). Treatment with anticonvulsants and age were associated with greater odds of correct classification. Although short of the 80% clinically relevant accuracy threshold, the results are promising and provide a fair and realistic estimate of classification performance, which can be achieved in a large, ecologically valid, multi-site sample of BD participants based on regional neurostructural measures. Furthermore, the significant classification in different samples was based on plausible and similar neuroanatomical features. Future multi-site studies should move towards sharing of raw/voxelwise neuroimaging data

Subcortical volumes across the lifespan: data from 18,605 healthy individuals aged 3-90 years

Age has a major effect on brain volume. However, the normative studies available are constrained by small sample sizes, restricted age coverage and significant methodological variability. These limitations introduce inconsistencies and may obscure or distort the lifespan trajectories of brain morphometry. In response, we capitalized on the resources of the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) Consortium to examine age-related trajectories inferred from cross-sectional measures of the ventricles, the basal ganglia (caudate, putamen, pallidum, and nucleus accumbens), the thalamus, hippocampus and amygdala using magnetic resonance imaging data obtained from 18,605 individuals aged 3-90 years. All subcortical structure volumes were at their maximum value early in life. The volume of the basal ganglia showed a monotonic negative association with age thereafter; there was no significant association between age and the volumes of the thalamus, amygdala and the hippocampus (with some degree of decline in thalamus) until the sixth decade of life after which they also showed a steep negative association with age. The lateral ventricles showed continuous enlargement throughout the lifespan. Age was positively associated with inter-individual variability in the hippocampus and amygdala and the lateral ventricles. These results were robust to potential confounders and could be used to examine the functional significance of deviations from typical age-related morphometric patterns.Education and Child Studie

Impact of artificial intelligence on clinical radiography practice: futuristic prospects in a low resource setting

Current trends in clinical radiography practice include the integration of artificial intelligence (AI) and related applications to improve patient care and enhance research. However, in low resource countries there are unique barriers to the process of AI integration. Using Ghana as a case study, this paper seeks to discuss the potential impact of AI on future radiographic practice in low-resource settings. The opportunities, challenges and the way forward to optimise the potential benefits of AI in future practice within these settings have been explored. Some of the barriers to AI integration into radiographic practice relate to lack of regulatory and legal policy frameworks and limited resource availability including unreliable internet connectivity and low expert skillset. These barriers notwithstanding, AI presents a great potential to the growth of medical imaging and subsequently improving quality of healthcare delivery in the near future. For example, AI-enabled radiographer reporting has a potential to improving quality of healthcare, especially in low-resource settings like Ghana with an acute shortage of radiologists. In addition, futuristic AI-enabled advancements such as synthetic crossmodality transfer where images from one modality are used as a baseline to generate a corresponding image of another modality without the need for additional scanning will be of particular benefit in low-resource settings. The urgent need for inclusion of AI modules for the training of the radiographer of the future has been suggested. Recommendations for development of AI strategies by national societies and regulatory bodies will harmonise the implementation efforts. Finally, there is need for collaboration between clinical practitioners and academia to ensure that the future radiography workforce is well prepared for the AI-enabled clinical environment