Development of size-specific dose estimates for common computed tomography examinations: a study in Ghana.

This study determined the size-specific dose estimate (SSDE) of computed tomography (CT) examinations and derived mathematical expressions for dose output estimation and optimization in a teaching hospital in Ghana. Demographic and scanner output indices, including CT dose index (CTDIvol) and dose length product for adult head, chest and abdominopelvic (ABP) CT examinations carried out at the hospital from 2018 to 2020, were retrieved from the picture archiving and communication system of the CT scanner machine. Other indices such as the antero-posterior diameter (DAP), lateral diameter (DL) and diagonal diameter (Ddia) of the patients' bodies were measured on the mid-slice axial image using a digital caliper. The effective diameter (Deff) was then calculated as the square root of the product of theDAPandDL. The SSDEs were calculated as the product of the CTDIvoland the size-specific conversion factors obtained from Report 204 of the American Association of Physicists in Medicine. Regression analyses were performed to find the relationship between SSDE and the various parameters to derive mathematical equations for the dose estimations. There were more female samples (n= 468, 56.3%) than male samples (n= 364, 43.7%) for each CT procedure. The SSDEs and size-specific diagnostic reference levels (SSDRLs) were: head (83.9 mGy; 86.9 mGy), chest (8.1 mGy; 8.7 mGy) and ABP (8.4 mGy; 9.2 mGy). The variations between CTDIvoland SSDEs for head (2.50%), chest (25.9%), and ABP (26.2%) showed an underestimation of radiation dose to patients, especially in chest and ABP examinations, if CTDIvolis used to report patient doses. The SSDEs of the chest and ABP CT examinations showed linear correlations with the CTDIvol. The estimated values could be used to optimize radiation doses in the CT facility. The SSDE and SSDRLs for head, chest and ABP CT examinations have been developed at a teaching hospital in Ghana. The SSDEs of chest and ABP examinations showed linear correlations with the CTDIvoland hence can be calculated using the mathematically derived equations in the study.

Complicated left isolated internal iliac artery aneurysm (IIIAA) in a young man - An unusual presentation in a Tertiary Hospital in Ghana: Case report.

Generally, an aneurysm is a disease of the elderly due to the degenerative aetiological factor. Isolated internal iliac artery aneurysm (IIIAA) is rare, representing 0.3-0.5 % of all intra-abdominal aneurysms. It is a focal dilatation of the internal iliac artery alone with a threshold for surgical intervention set at 8 mm. Herein, we present an unusual presentation of a rare condition of a huge left internal iliac artery aneurysm in a young man with no identifiable risk factor complicated by left ilio-femoral deep vein thrombosis. Even though this is an interesting case study, the lack of facilities to do anaerobic cultures remains a major limitation in our setting.

Examining moral distress and injury resulting from the COVID-19 pandemic: Insights from the Ghanaian radiography workforce.

BACKGROUND: Moral distress has been an issue under consideration in healthcare practice. The COVID-19 pandemic became a critical factor that contributed to heightened moral distress and injury among healthcare professionals, including radiographers. Despite the substantial engagement of radiographers in the management of COVID-19 patients, the consequent moral distress and injury states experienced by this critical frontline workforce have not been widely explored. This study investigated the level of moral distress and the coping mechanisms employed by radiographers in Ghana during the pandemic to provide valuable information to support radiographers and prepare the workforce better against any future pandemics. METHODS: Utilising a cross-sectional design, a survey approach was employed for data collection between June 2023 and August 2023 from clinically-active radiographers who worked before and during the pandemic in Ghana. Both descriptive and inferential statistics were generated using Microsoft Excel 2019 and the Statistical Package for the Social Sciences (v.26). RESULTS: Hundred (100) radiographers participated in the study. The result demonstrated that the COVID-19 pandemic escalated the risk of moral distress among radiographers from 22 % (n = 22) to 43 % (n = 43), with 33 % (n = 33) exhibiting signs of moral injury. This escalation impacted the mental health of 12 % (n = 12) of respondents and was reported as a contributor to career-changing decisions among radiographers. Notably, many of those affected did not seek formal support but relied on personal coping strategies and family support. Inadequate resources (69 %, n = 69), particularly regarding consumables, emerged as the primary cause of moral distress. The study underscored that the most effective means of mitigating moral distress in radiographers was through the provision of resources and additional staff support (66 %, n = 66). CONCLUSION: This study sheds light on the state of moral distress and injury among radiographers during the COVID-19 pandemic, impacting the mental health of a minority and contributing to career-changing decisions. The findings emphasise the importance for healthcare institutions to proactively implement systems, such as resource provision, improved staffing, and emotional support, now and during similar future pandemics. This is crucial to address moral distress and cater to the mental health needs of radiographers, ensuring a resilient clinical radiography workforce.

The drivers of migration of Ghanaian radiographers to high-income countries.

Background: The brain drain of Ghanaian radiographers is a growing concern for the Ghana Health Service and patient care in the country. Unfortunately, this is affecting the quality of radiology services in Ghana. This study investigated the determinants of radiographers' brain drain from Ghana and identified potential mitigating factors. Methods: A cross-sectional survey was conducted using a semi-structured questionnaire which was administered online to Ghanaian radiographers. The questionnaire gathered data on push and pull factors that influenced brain drain. Statistical analysis was performed using SPSS version 29. Results: A total of 128 radiographers participated in the study. The findings indicated that 92.2 % of Ghanaian radiographers expressed intentions to work abroad. The estimated means and standard deviations on a five-point Likert Scale demonstrated that poor salary (4.47 ± 0.1) and poor working conditions (4.17 ± 1.1) were the main push factors, while improved living conditions (4.62 ± 0.9) and better health infrastructure (4.55 ± 0.9) were the influential pull/attractive factors. Although there are variations in participants' demographics, comparative analyses of push and pull factors indicated that respondents did not significantly differ in their migration decisions intentions (p < 0.05). To mitigate brain drain, respondents emphasised the need for better salaries (97.7 %) and comprehensive health insurance for radiographers and their families (92.2 %) among other factors. Conclusion: This study highlights the multifaceted factors that drive Ghanaian radiographers abroad and their consequences on the healthcare system. A comprehensive strategy encompassing financial incentives, career development, improved working conditions, and personal satisfaction was identified as a mitigating approach to addressing these challenges. Implementation of these recommendations by policymakers is necessary to create an environment that retains and empowers radiographers and ultimately enhances patient care and healthcare advancement in Ghana.

Sustainability in radiography: Knowledge, practices, and barriers among radiographers in Zimbabwe and Zambia.

INTRODUCTION: As the global demand for radiography services increases, departments need to be aware of the environmental impact of their practices and strive to reduce their carbon footprint. However, sustainability in radiography, particularly in low-resource settings, remains underexplored. This study aimed to investigate the knowledge, practices, and barriers to sustainability in radiography practice among radiographers in Zimbabwe and Zambia. METHODS: A quantitative cross-sectional study involving 216 consecutively sampled radiographers who completed an online questionnaire was conducted. Data analysis was performed using descriptive statistics, the Chi-square test, and exploratory factor analysis using principal component analysis. RESULTS: Overall, 81.49 % of the radiographers had some familiarity with the concept of sustainability. The radiography educational curriculum was singled out as lacking sufficient content on sustainability (44.44 %). More than half of the radiographers reported the absence of deliberate sustainable practices in place in their respective departments (Zambia 51.02 %, Zimbabwe 54.69 %). The top reported barriers to sustainability include; a lack of priority for sustainability from leadership and organization (73.61 %), a lack of incentives for sustainability (75.46 %), and a lack of partnerships between suppliers and consumers on ways to improve diagnosis, patient safety and sustainability (82.4 %). CONCLUSION: This study offers valuable insights into the current state of sustainability in radiography in Zambia and Zimbabwe, highlighting the need for academic reforms, intentional departmental practices, and systemic changes to drive sustainable efforts in the field. Future research should aim to enhance the sustainability of radiographic examinations and procedures, thereby advancing the core practice of radiographers.

Estimation of organ-specific cancer and mortality risks associated with common indication-specific CT examinations of the abdominopelvic region.

INTRODUCTION: There is a paucity of large-scale studies reporting organ doses and cancer risks in patients who undergo indication-specific CT examinations. This study estimated organ-specific lifetime attributable risk (LAR) of cancer incidence and mortality among patients who underwent indication-based computed tomography (CT) examinations [(involving abdominopelvic lesion, kidney stones and computed tomography-intravenous urography (CT-IVU)] in about 70% of the functioning CT facilities in Ghana. METHODS: With a total of 1,100 data sets, organ doses were first determined using the National Cancer Institute Dosimetry System for CT (NCICTX) software version 2.1, and LAR values were predicted using the BEIR VII model. RESULTS: The estimated radiation-induced colon cancer risks were likely in 39.4-59.8 out of 100,000 patients who underwent CT because of abdominopelvic lesion. The risk was even higher in CT-IVU examinations (53.3-66.4 patients in 100,000 procedures) but was relatively less (16.8-26.3 patients) in kidney stone procedures. Accordingly, the risk of radiation-induced colon mortality was more common in CT-IVU than in kidney stone procedures (22.7-28.2 versus 7.2-12.5 patients in 100,000 procedures). CONCLUSION: These results call for further optimisation actions for indication-specific CT examinations to appropriately reduce the potential risk levels for patients' protection and safety.

Generalisability of fetal ultrasound deep learning models to low-resource imaging settings in five African countries.

Most artificial intelligence (AI) research and innovations have concentrated in high-income countries, where imaging data, IT infrastructures and clinical expertise are plentiful. However, slower progress has been made in limited-resource environments where medical imaging is needed. For example, in Sub-Saharan Africa, the rate of perinatal mortality is very high due to limited access to antenatal screening. In these countries, AI models could be implemented to help clinicians acquire fetal ultrasound planes for the diagnosis of fetal abnormalities. So far, deep learning models have been proposed to identify standard fetal planes, but there is no evidence of their ability to generalise in centres with low resources, i.e. with limited access to high-end ultrasound equipment and ultrasound data. This work investigates for the first time different strategies to reduce the domain-shift effect arising from a fetal plane classification model trained on one clinical centre with high-resource settings and transferred to a new centre with low-resource settings. To that end, a classifier trained with 1792 patients from Spain is first evaluated on a new centre in Denmark in optimal conditions with 1008 patients and is later optimised to reach the same performance in five African centres (Egypt, Algeria, Uganda, Ghana and Malawi) with 25 patients each. The results show that a transfer learning approach for domain adaptation can be a solution to integrate small-size African samples with existing large-scale databases in developed countries. In particular, the model can be re-aligned and optimised to boost the performance on African populations by increasing the recall to [Formula: see text] and at the same time maintaining a high precision across centres. This framework shows promise for building new AI models generalisable across clinical centres with limited data acquired in challenging and heterogeneous conditions and calls for further research to develop new solutions for the usability of AI in countries with fewer resources and, consequently, in higher need of clinical support.