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This article, published in the journal "Ultrasound in Obstetrics & Gynecology," explores the experiences and perceptions of women who may participate in antenatal research in the United Kingdom. The study used a mixed methods approach, including a survey and qualitative analysis, to examine the motivators and enablers for participation in research. The results showed increased willingness to participate in research among certain groups, such as healthcare professionals and those who had previous experience with NHS research. The study also identified three meta themes related to research participation: perceptions and experience of safety, lived experience and education, and sociocultural differences. The authors recommend strategies to promote inclusive research design, including facilitative research designs, effective communication strategies, and participant education about research. [Extracted from the article]

This article discusses a study that aimed to develop a protocol for using fetal MRI to assess craniofacial biometrics in both healthy control subjects and those with Trisomy 21 (Down syndrome). The researchers performed a systematic literature review to determine appropriate anatomical landmarks for the MRI scans and then used a template atlas to calculate biometrics. They found differences in biometry between the control and Trisomy 21 groups, which correlated with known dysmorphology in Trisomy 21 phenotypes. The study also compared manual measurements to automated measurements and found that automated methodologies were faster but had a higher margin of error. The researchers concluded that future work should focus on optimizing MRI sequences, deep learning methods, and validation in syndromic cohorts. [Extracted from the article]

Objectives: Radiographers use advanced medical imaging and radiotherapy (MIRT) equipment. They are also a digitally mature and digitally resilient workforce in healthcare. Artificial intelligence is already changing their clinical practice and roles in data acquisition, post-processing, and workflow management. It is therefore vital to understand the impact of AI on the careers, roles and professional identity of radiographers, as key stakeholders of the digital transformation of healthcare within the medical imaging ecosystem., Methods: A European radiographer survey, endorsed by the European Federation of Radiographer Societies (EFRS), was distributed online. It was piloted with twelve radiographers and translated into eight languages. Although this study included both qualitative and quantitative results, this paper emphasises the quantitative aspect., Results: A total of 2206 European radiographers have responded from 37 different countries. Despite some concerns around workforce deskilling, future professional identity, and job prospects, participants showed overall optimistic views about the use of AI in healthcare. This was particularly strong for those with prior AI education (mean: 2.15 vs. 1.89; p-value: < 0.001), hands-on experience with AI (correlation: 0.047; p-value: 0.038), from countries with higher digital literacy (mean: 2.00 vs.1.93; p-value: 0.027) and a higher academic level of radiography education (mean: 3.28 vs. 3.15; p-value: 0.002). Men appeared slightly more enthused about the development of technological skills and women about the honing of patient-centred care skills. Finally, interprofessional collaboration was seen as essential not only for the seamless clinical integration of AI but also for supporting patient benefit., Conclusion: While AI implementation advances, AI education needs to keep at pace to ensure acceptability, trust, and safe use of this technology by healthcare professionals, minimising their concerns around professional role changes and enabling them to see the opportunities of service transformation., Critical Relevance Statement: This paper aims to map out the perceived impact of AI on the professional identity and careers of European radiographers., Key Points: AI is impacting radiographers' clinical practice and changing their professional identity. Despite increasing AI awareness, AI education is still lacking across Europe. AI education is key for AI acceptability and trust by radiographers, which facilitates AI implementation and service transformation., Competing Interests: Declarations. Ethics approval and consent to participate: Ethical approval was obtained from City St George’s, University of London School of Health and Psychological Sciences Ethics Committee (ETH2223-1346). All participants were informed about the aim and objectives of this study on the introductory page of the online survey. In addition, consent was explicitly obtained by asking respondents to physically tick a dedicated consent box. Consent for publication: Not applicable. Competing interests: M.Z. is a member of the Scientific Editorial Board of Insights into Imaging. As such, they did not participate in the selection nor review processes for this article. The authors declare that they have no competing interests., (© 2025. The Author(s).)

Background: Preterm birth (< 37 weeks' gestation) alters cerebrovascular development due to the premature transition from a foetal to postnatal circulatory system, with potential implications for future cerebrovascular health. This study aims to explore potential differences in the Circle of Willis (CoW), a key arterial ring that perfuses the brain, of healthy adults born preterm., Methods: A total of 255 participants (108 preterm, 147 full-term) were included in the analysis. High-resolution three-dimensional Time-of-Flight Magnetic Resonance Angiography (3D TOF MRA) datasets were analysed, measuring vessel diameters and classifying segments into different groups of CoW anatomical variations. Statistical comparisons assessed the prevalence of each variant group between preterm and full-term populations, as well as the relationship between CoW variability, sex, and degree of prematurity., Results: We identified 164 participants with variant CoW configurations. Unilateral segment hypoplasia (30%) and unilateral segment absence (29%) were the most common variations, with over 50% related to the posterior communicating artery (PComA). However, the incidence of absent segments was lower in preterm adults, who were more likely to exhibit variants associated with complete CoW configurations compared to full-term adults (p = 0.025). Preterm males had a higher probability of a group 1 variant (circles with one or more hypoplastic segments only) than the full-term group (p = 0.024). In contrast, preterm females showed higher odds of a group 4a variant (circles with one or more accessory segments, without any absent segments) in comparison to their full-term counterparts (p = 0.020)., Conclusions: Preterm birth is linked to a distinct vascular phenotype of CoW in adults born preterm, with a higher likelihood of a CoW configuration with hypoplastic segments but a lower likelihood of absent segments. Future work should focus on larger prospective studies and explore the implications of these findings for normal development and cerebrovascular disease. Furthermore, TOF MRA might be a useful adjunct in the neurovascular assessment of preterm-born individuals., Competing Interests: Declarations. Ethics approval and consent to participate: Data for this research were derived from two studies: the ‘Young Adult Cardiovascular Health Study (YACHT)’ (trial registration number: NCT02103231) and the ‘Trial of Exercise to Prevent Hypertension in Young Adults (TEPHRA)’ (trial registration number: NCT02723552). Ethical approvals for these studies were granted by the South-Central Berkshire Research Ethics Committee (14/SC/0275) and the University of Oxford as the host institution along with the South-Central Research Ethics Committee (Reference 16/SC/0016), respectively. It was the requirement of the trials that written informed consent was obtained prior to the enrolment of the participants. The investigators ensured that the two studies were conducted in accordance with the principles of the Declaration of Helsinki. The investigators ensured that the two studies were conducted in accordance with relevant regulations and Good Clinical Practice. This research is a secondary analysis of data from the “YACHT” and “TEPHRA” trials and does not require a separate clinical trial registration. Consent for publication: The images used are entirely unidentifiable, and there are no details on individuals reported within the manuscript. Competing interests: The authors declare no competing interests., (© 2025. The Author(s).)

Introduction: Artificial Intelligence (AI) has the potential to transform medical imaging and radiotherapy; both fields where radiographers' use of AI tools is increasing. This study aimed to explore the views of those professionals who are now using AI tools., Methods: A small-scale exploratory research process was employed, where qualitative data was obtained from five UK-based participants; all professionals working in medical imaging and radiotherapy who use AI in clinical practice. Five semi-structured interviews were conducted online. Verbatim transcription was performed using an open-source automatic speech recognition model. Conceptual content analysis was performed to analyse the data and identify common themes., Results: Participants spoke about the possibility of AI deskilling staff and changing their roles, they discussed issues around data protection and data sharing strategies, the important role of effective leadership of AI teams, and the seamless integration into workflows. Participants thought that the benefits of adopting AI were smoother clinical workflows, support for the workforce in decision-making, and enhanced patient safety/care. They also highlighted the need for tailored AI education/training, multidisciplinary teamwork and support., Conclusion: Participants who are now using AI tools felt that clinical staff should be empowered to support AI implementation by adopting new and clearly defined roles and responsibilities. They suggest that attention to patient care and safety is a key to successful AI adoption. Despite the increasing adoption of AI, participants in the UK described a gap in knowledge with professionals still needing clear guidance, education and training regarding AI in preparation for more widespread adoption., (Copyright © 2024. Published by Elsevier Inc.)

Objectives: Evaluating craniofacial phenotype-genotype correlations prenatally is increasingly important; however, it is subjective and challenging with 3D ultrasound. We developed an automated label propagation pipeline using 3D motion- corrected, slice-to-volume reconstructed (SVR) fetal MRI for craniofacial measurements., Methods: A literature review and expert consensus identified 31 craniofacial biometrics for fetal MRI. An MRI atlas with defined anatomical landmarks served as a template for subject registration, auto-labelling, and biometric calculation. We assessed 108 healthy controls and 24 fetuses with Down syndrome (T21) in the third trimester (29-36 weeks gestational age, GA) to identify meaningful biometrics in T21. Reliability and reproducibility were evaluated in 10 random datasets by four observers., Results: Automated labels were produced for all 132 subjects with a 0.3% placement error rate. Seven measurements, including anterior base of skull length and maxillary length, showed significant differences with large effect sizes between T21 and control groups (ANOVA, p<0.001). Manual measurements took 25-35 minutes per case, while automated extraction took approximately 5 minutes. Bland-Altman plots showed agreement within manual observer ranges except for mandibular width, which had higher variability. Extended GA growth charts (19-39 weeks), based on 280 control fetuses, were produced for future research., Conclusion: This is the first automated atlas-based protocol using 3D SVR MRI for fetal craniofacial biometrics, accurately revealing morphological craniofacial differences in a T21 cohort. Future work should focus on improving measurement reliability, larger clinical cohorts, and technical advancements, to enhance prenatal care and phenotypic characterisation., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Matthew et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Introduction: Artificial Intelligence (AI) is revolutionizing medical imaging and radiation therapy. AI-powered applications are being deployed to aid Medical Radiation Technologists (MRTs) in clinical workflows, decision-making, dose optimisation, and a wide range of other tasks. Exploring the levels of AI education provided across the United States is crucial to prepare future graduates to deliver the digital future. This study aims to assess educators' levels of AI knowledge, the current state of AI educational provisions, the perceived challenges around AI education, and important factors for future advancements., Methods: An online survey was electronically administered to all radiologic technologists in the American Society of Radiologic Technologists (ASRT) database who indicated that they had an educator role in the United States. This was distributed through the membership of the ASRT, from February to April 2023. All quantitative data was analysed using frequency and descriptive statistics. The survey's open-ended questions were analysed using a conceptual content analysis approach., Results: Out of 5,066 educators in the ASRT database, 373 valid responses were received, resulting in a response rate of 7.4%. Despite 84.5% of educators expressing the importance of teaching AI, 23.7% currently included AI in academic curricula. Of the 76.3% that did not include AI in their curricula, lack of AI knowledge among educators was the top reason for not integrating AI in education (59.1%). Similarly, AI-enabled tools were utilised by only 11.1% of the programs to assist teaching. The levels of trust in AI varied among educators., Conclusion: The study found that although US educators of MRTs have a good baseline knowledge of general concepts regarding AI, they could improve on the teaching and use of AI in their curricula. AI training and guidance, adequate time to develop educational resources, and funding and support from higher education institutions were key priorities as highlighted by educators., (Copyright © 2024. Published by Elsevier Inc.)

Introduction: Artificial Intelligence (AI) is increasingly implemented in medical imaging practice, however, its impact on radiographers practice is not well studied. The aim of this study was to explore the perceived impact of AI on radiographers' activities and profession in Switzerland., Methods: A survey conducted in the UK, translated into French and German, was disseminated through professional bodies and social media. The participants were Swiss radiographers (clinical/educators/ researchers/students) and physicians working within the medical imaging profession (radiology/nuclear medicine/radiation-oncology). The survey covered five sections: demographics, AI-knowledge, skills, confidence, perceptions about the AI impact. Descriptive, association statistics and qualitative thematic analysis were conducted., Results: A total of 242 responses were collected (89% radiographers; 11% physicians). AI is being used by 43% of participants in clinical practice, but 64% of them did not feel confident with AI-terminology. Participants viewed AI as an opportunity (57%), while 19% considered it as a threat. The opportunities were associated with streamlining repetitive tasks, minimizing errors, increasing time towards patient-centered care, research, and patient safety. The significant threats identified were reduction on work positions (23%), decrease of the radiographers' expertise level due to automation bias (16%). Participants (68%) did not feel well trained/prepared to implement AI in their practice, highlighting the non-availability of specific training (88%). 93% of the participants mentioned that AI education should be included at undergraduate education program., Conclusion: Although most participants perceive AI as an opportunity, this study identified areas for improvement including lack of knowledge, educational supports/training, and confidence in radiographers. Customised training needs to be implemented to improve clinical practice and understanding of how AI can benefit radiographers., (Copyright © 2024. Published by Elsevier Inc.)

Introduction: Magnetic resonance imaging (MRI) is a rapidly evolving modality, generally considered safe due to lack of ionising radiation. While MRI technology and techniques are improving, many of the safety concerns remain the same as when first established. Patient thermal injuries are the most frequently reported adverse event, accounting for 59% of MRI incidents to the Food and Drug Administration (FDA). Surveys indicate many incidents remain unreported. Patient thermal injuries are preventable and various methods for their mitigation have been published. However, recommendations can be variable, fragmented and confusing. The aim of this systematic review was to synthesise the evidence on MRI safety and associated skin injuries and offer comprehensive recommendations for radiographers to prevent skin thermal injuries., Methods: Four journal databases were searched for sources published January 2010-May 2023, presenting information on MRI safety and thermal injuries., Results: Of 26,801 articles returned, after careful screening and based on the eligibility criteria, only 79 articles and an additional 19 grey literature sources were included (n = 98). Included studies were examined using thematic analysis to determine if holistic recommendations can be provided to assist in preventing skin burns. This resulted in three simplified recommendations: Remove any electrically conductive items Insulate the patient to prevent any conductive loops or contact with objects Communicate regularly CONCLUSION: By implementing the above recommendations, it is estimated that 97% of skin burns could be prevented. With thermal injuries continuing to impact MRI safety, strategies to prevent skin burns and heating are essential. Assessing individual risks, rather than blanket policies, will help prevent skin thermal injuries occurring, improving patient care., (© 2024 The Author(s). Journal of Medical Radiation Sciences published by John Wiley & Sons Australia, Ltd on behalf of Australian Society of Medical Imaging and Radiation Therapy and New Zealand Institute of Medical Radiation Technology.)

Competing Interests: Competing interests: None declared.

Background: Medical Imaging and radiotherapy (MIRT) are at the forefront of artificial intelligence applications. The exponential increase of these applications has made governance frameworks necessary to uphold safe and effective clinical adoption. There is little information about how healthcare practitioners in MIRT in the UK use AI tools, their governance and associated challenges, opportunities and priorities for the future., Methods: This cross-sectional survey was open from November to December 2022 to MIRT professionals who had knowledge or made use of AI tools, as an attempt to map out current policy and practice and to identify future needs. The survey was electronically distributed to the participants. Statistical analysis included descriptive statistics and inferential statistics on the SPSS statistical software. Content analysis was employed for the open-ended questions., Results: Among the 245 responses, the following were emphasised as central to AI adoption: governance frameworks, practitioner training, leadership, and teamwork within the AI ecosystem. Prior training was strongly correlated with increased knowledge about AI tools and frameworks. However, knowledge of related frameworks remained low, with different professionals showing different affinity to certain frameworks related to their respective roles. Common challenges and opportunities of AI adoption were also highlighted, with recommendations for future practice., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Author(s). Published by Elsevier B.V. All rights reserved.)

Background: Prenatal bonding describes the emotional connection expectant parents form to their unborn child. Research acknowledges the association between antenatal imaging and enhanced bonding, but the influencing factors are not well understood, particularly for fathers or when using advanced techniques like fetal magnetic resonance imaging (MRI). This study aimed to identify variables which may predict increased bonding after imaging., Methods: First-time expectant parents (mothers = 58, fathers = 18) completed a two-part questionnaire (QualtricsXM™) about their expectations and experiences of ultrasound (n = 64) or fetal MRI (n = 12) scans in uncomplicated pregnancies. A modified version of the Prenatal Attachment Inventory (PAI) was used to measure bonding. Qualitative data were collected through open-ended questions. Multivariate linear regression models were used to identify significant parent and imaging predictors for bonding. Qualitative content analysis of free-text responses was conducted to further understand the predictors' influences., Results: Bonding scores were significantly increased after imaging for mothers and fathers (p < 0.05). MRI-parents reported significantly higher bonding than ultrasound-parents (p = 0.02). In the first regression model of parent factors (adjusted R 2  = 0.17, F = 2.88, p < 0.01), employment status (β = -0.38, p < 0.05) was a significant predictor for bonding post-imaging. The second model of imaging factors (adjusted R 2  = 0.19, F = 3.85, p < 0.01) showed imaging modality (β = -0.53), imaging experience (β = 0.42) and parental excitement after the scan (β = 0.29) were significantly (p < 0.05) associated with increased bonding. Seventeen coded themes were generated from the qualitative content analysis, describing how scans offered reassurance about fetal wellbeing and the opportunity to connect with the baby through quality interactions with imaging professionals. A positive scan experience helped parents to feel excited about parenthood. Fetal MRI was considered a superior modality to ultrasound., Conclusions: Antenatal imaging provides reassurance of fetal development which affirms parents' emotional investment in the pregnancy and supports the growing connection. Imaging professionals are uniquely positioned to provide parent-centred experiences which may enhance parental excitement and facilitate bonding., (© 2024. The Author(s).)