Introduction: The integration of artificial intelligence (AI) systems into medical imaging is advancing the practice and patient care. It is thought to further revolutionise the entire field in the near future. This study explored Ghanaian radiographers’ perspectives on the integration of AI into medical imaging.Methods: A cross‐sectional online survey of registered Ghanaian radiographers was conducted within a 3‐month period (February‐April, 2020). The survey sought information relating to demography, general perspectives on AI and implementation issues. Descriptive and inferential statistics were used for data analyses.Results: A response rate of 64.5% (151/234) was achieved. Majority of the respondents (n = 122, 80.8%) agreed that AI technology is the future of medical imaging. A good number of them (n = 131, 87.4%) indicated that AI would have an overall positive impact on medical imaging practice. However, some expressed fears about AI‐related errors (n = 126, 83.4%), while others expressed concerns relating to job security (n = 35, 23.2%). High equipment cost, lack of knowledge and fear of cyber threats were identified as some factors hindering AI implementation in Ghana.Conclusions: The radiographers who responded to this survey demonstrated a positive attitude towards the integration of AI into medical imaging. However, there were concerns about AI‐related errors, job displacement and salary reduction which need to be addressed. Lack of knowledge, high equipment cost and cyber threats could impede the implementation of AI in medical imaging in Ghana. These findings are likely comparable to most low resource countries and we suggest more education to promote credibility of AI in practice.

Purpose: Studies have documented the clinical potentials of artificial intelligence (AI) in medical imaging practice to improving patient care. This study aimed to qualitatively explore the perception of radiographers relating to the integration of AI in medical imaging practice in Africa.Methods: The study employed a qualitative design using an open-ended online instrument administered between March and August 2020. Participants consisted of radiographers working within Africa during the time of the study. Data obtained were analysed using qualitative content analysis. Six themes of concerns were generated: expectant tool; career insecurity; cost of new technology, equipment preservation and data insecurity; service delivery quality; need for expanding AI awareness.Results: A total of 475 valid responses were obtained. Participants demonstrated a positive outlook about AI in relation to clinical quality improvement, competent diagnosis, radiation dose reduction and improvement in research. They however expressed concerns relating to the implementation of this technology, including job security and loss of core professional radiographer skills and roles. In addition, concerns regarding AI equipment maintenance, lack of awareness about AI and education and training opportunities were evident.Conclusion: Awareness of the importance of AI in medical imaging practice was acknowledged; however, concerns relating to job security, data protection must be given critical attention for successful implementation of these advanced technologies in medical imaging in Africa. Inclusion of AI modules in the training of future radiographers is highly recommended.

Urgent global action is required to combat climate change, with radiographers poised to play a significant role in reducing healthcare's environmental impact. This paper explores radiography-related activities and factors in resource-limited departments contributing to the carbon footprint and proposes strategies for mitigation. The rationale is to discuss the literature regarding these contributing factors and to raise awareness about how to promote sustainability activities in clinical radiography practice and education in resource-limited countries. The radiography-related activities and factors contributing to the carbon footprint in resource-limited countries include the use of old equipment and energy inefficiency, insufficient clean energy to power equipment, long-distance commuting for radiological examinations, high film usage and waste, inadequate training and research on sustainable practices, as well as limited policies to drive support for sustainability. Addressing these issues requires a multifaceted approach. Firstly, financial assistance and partnerships are needed to adopt eco-friendly technologies and clean energy sources to power equipment, thus tackling issues related to old equipment and energy inefficiency. Transitioning to digital radiography can mitigate the environmental impact of high film usage and waste, while collaboration between governments, healthcare organisations, and international stakeholders can improve access to radiological services, reducing long-distance commuting. Additionally, promoting education programmes and research efforts in sustainability will empower radiographers with the knowledge to practice sustainably, complemented by clear policies such as green imaging practices to guide and incentivise the adoption of sustainable practices. These integrated solutions can significantly reduce the carbon footprint of radiography activities in resource-limited settings while enhancing healthcare delivery. Radiography-related activities and factors in resource-limited departments contributing to the carbon footprint are multifaceted but can be addressed through concerted efforts. Addressing the challenges posed by old equipment, energy inefficiency, high film usage, and inadequate training through collaborative efforts and robust policy implementation is essential for promoting sustainable radiography practices in resource-limited countries. Radiographers in these countries need to be aware of these factors contributing to the carbon footprint and begin to work with the relevant stakeholders to mitigate them. Furthermore, there is a need for them to engage in education programmes and research efforts in sustainability to empower them with the right knowledge and understanding to practice sustainably.

Pelvis X-ray examinations inevitably involve exposure of the gonads to ionizing radiation. In line with the principle of keeping doses as low as reasonably practicable (ALARP), accurate patient dose measurement is vital if we are to ascertain that these exposures are fully optimized. The study aimed to provide patient dose estimates for pelvis examination being undertaken at 10 separate hospitals in Ghana in order to provide an initial quantitative indication of each site's typically achievable radiation safety and quality standards. The method employed was adapted from established methods and peer reviewed literature, such as the International Atomic Energy Agency (IAEA) publications on optimization of the radiological protection of patients undergoing radiography, fluoroscopy, and computed tomography examinations in some countries in Africa, Asia, and Eastern Europe. Dose measurements were calculated on 323 patients (137 (42%) male, 186 (58%) female, ages, 38.56 yr ?9.0 ; range 20–68). The entrance surface dose (ESD) was determined by an indirect method, using the patient's anatomical data and exposure parameters utilized for the specific examination. The Quality Assurance Dose Database software (QADDs) developed by Integrated Radiological Services Ltd. in Liverpool, UK was used to generate the ESD values. The study identified variations in the technique factors used compared with the recommendations in the European Commission (EC) quality criteria. Eighty percent of the hospitals recorded lower ESD values below IAEA recommended diagnostic reference levels (10 mGy) and 40% of the hospitals exceeded the UK national reference value (4 mGy). However, one hospital consistently recorded higher ESDs than the other hospitals. The variations in the data recorded demonstrate the importance of creating awareness by the radiographic staff on quality assurance and standardization of protocols to ensure satisfactory standards and optimized radiation dose to patients and staff. PACS number: 87.59.B