A Nordic survey on artificial intelligence in the radiography profession - Is the profession ready for a culture change?

INTRODUCTION: The impact of artificial intelligence (AI) on the radiography profession remains uncertain. Although AI has been increasingly used in clinical radiography, the perspectives of the radiography professionals in Nordic countries have yet to be examined. The primary aim was to examine views of Nordic radiographers 'on AI, with focus on perspectives, engagement, and knowledge of AI. METHODS: Radiographers from Denmark, Norway, Sweden, Iceland, Greenland, and the Faroe Island were invited through social media platforms to participate in an online survey from March to June 2023. The survey encompassed 29-items and included 4 sections a) demographics, b) barriers and enablers on AI, c) perspectives and experiences of AI and d) knowledge of AI in radiography. Edgars Schein's model of organizational culture was employed to analyse Nordic radiographers' perspectives on AI. RESULTS: Overall, a total of 421 respondents participated in the survey. A majority were positive/somewhat positive towards AI in radiography e.g., 77.9 % (n = 342) thought that AI would have a positive effect on the profession, and 26% thought that AI would reduce the administrative workload. Most radiographers agreed or strongly agreed that clinicians may have access to AI generated reports (76.8 %, n = 297). Nevertheless, a total of 86 (20.1%) agree or somewhat agreed that AI a potential risk for radiography. CONCLUSION: Nordic radiographers are generally positive towards AI, yet uncertainties regarding its implementation persist. The findings underscore the importance of understanding these challenges for the responsible integration of AI systems. Carefully weighing the expected influence of AI against key incentives will support a seamless integration of AI for the benefit not just of the patients, but also of the radiography profession. IMPLICATIONS FOR PRACTICE: Understanding incentives factors and barriers can help address uncertainties during implementation of AI in clinical practice.

Nordic radiographers' and students' perspectives on artificial intelligence - A cross-sectional online survey.

INTRODUCTION: The integration of artificial intelligence (AI) into the domain of radiography holds substantial potential in various aspects including workflow efficiency, image processing, patient positioning, and quality assurance. The successful implementation of AI within a Radiology department necessitates the participation of key stakeholders, particularly radiographers. The study aimed to provide a comprehensive investigation about Nordic radiographers' perspectives and attitudes towards AI in radiography. METHODS: An online 29-item survey was distributed via social media platforms to Nordic students and radiographers working in Denmark, Norway, Sweden, Iceland, Greenland, and the Faroe Islands including items on demographics, specialization, educational background, place of work and perspectives and knowledge on AI. The items were a mix of closed-type and scaled questions, with the option for free-text responses when relevant. RESULTS: The survey received responses from all Nordic countries with 586 respondents, 26.8% males, 72.1% females, and 1.1% non-binary/self-defined or preferred not to say. The mean age was 37.2 with a standard deviation (SD) of ±12.1 years, and the mean number of years since qualification was 14.2 SD ± 10.3 years. A total of 43% (n = 254) of the respondents had not received any AI training in clinical practice. Whereas 13% (n = 76) had received AI during radiography undergrad training. A total of 77.9% (n = 412) expressed interest in pursuing AI education. The majority of respondents were aware of the potential use of AI (n = 485, 82.8%) and 39.1% (n = 204) had no reservations about AI. CONCLUSION: Overall, this study found that Nordic radiographers have a positive attitude toward AI. Very limited training or education has been provided to the radiographers. Especially since 82.8% reports on plans to implement AI in clinical practice. In general, awareness of AI applications is high, but the educational level is low for Nordic radiographers. IMPLICATION FOR PRACTICE: This study emphasises the favourable view of AI held by students and Nordic radiographers. However, there is a need for continuous professional development to facilitate the implementation and effective utilization of AI tools within the field of radiography.

AI implementation in the UK landscape: Knowledge of AI governance, perceived challenges and opportunities, and ways forward for radiographers.

INTRODUCTION: Despite the rapid increase of AI-enabled applications deployed in clinical practice, many challenges exist around AI implementation, including the clarity of governance frameworks, usability of validation of AI models, and customisation of training for radiographers. This study aimed to explore the perceptions of diagnostic and therapeutic radiographers, with existing theoretical and/or practical knowledge of AI, on issues of relevance to the field, such as AI implementation, including knowledge of AI governance and procurement, perceptions about enablers and challenges and future priorities for AI adoption. METHODS: An online survey was designed and distributed to UK-based qualified radiographers who work in medical imaging and/or radiotherapy and have some previous theoretical and/or practical knowledge of working with AI. Participants were recruited through the researchers' professional networks on social media with support from the AI advisory group of the Society and College of Radiographers. Survey questions related to AI training/education, knowledge of AI governance frameworks, data privacy procedures, AI implementation considerations, and priorities for AI adoption. Descriptive statistics were employed to analyse the data, and chi-square tests were used to explore significant relationships between variables. RESULTS: In total, 88 valid responses were received. Most radiographers (56.6 %) had not received any AI-related training. Also, although approximately 63 % of them used an evaluation framework to assess AI models' performance before implementation, many (36.9 %) were still unsure about suitable evaluation methods. Radiographers requested clearer guidance on AI governance, ample time to implement AI in their practice safely, adequate funding, effective leadership, and targeted support from AI champions. AI training, robust governance frameworks, and patient and public involvement were seen as priorities for the successful implementation of AI by radiographers. CONCLUSION: AI implementation is progressing within radiography, but without customised training, clearer governance, key stakeholder engagement and suitable new roles created, it will be hard to harness its benefits and minimise related risks. IMPLICATIONS FOR PRACTICE: The results of this study highlight some of the priorities and challenges for radiographers in relation to AI adoption, namely the need for developing robust AI governance frameworks and providing optimal AI training.

"It's not just the medical aspects that are important": A qualitative exploration of first-time parents' experiences of antenatal imaging and their influence on parent-fetal bonding.

INTRODUCTION: Antenatal imaging provides clinical information regarding fetal growth and development. The additional benefit afforded by imaging for expectant parents in developing an emotional connection (bond) to the unborn baby is also acknowledged. However, the relationship between imaging and bonding is not fully understood, particularly where there are differing parental and pregnancy circumstances, for example use of advanced imaging techniques or the prenatal diagnosis of a congenital fetal condition. This study aimed to explore the role of antenatal imaging in enhancing the developing parent-fetal bond in first-time parents. METHODS: A descriptive, qualitative methodology was used. Semi-structured telephone interviews were conducted with first-time expectant parents attending a London hospital for clinical ultrasound (n = 20) or research MRI (n = 8) imaging during pregnancy. The sample included parents receiving specialist antenatal care for a diagnosed fetal cardiac condition (n = 8). Thematic analysis was conducted. RESULTS: The analysis generated three themes: 1) Our baby, our scan too; 2) Destination parenthood; and 3) Being in the dark, then finding the light. These themes highlight the important, but transient role of antenatal imaging in enhancing parent-fetal bonding, as well as the differing care needs of expectant parents. The integral role of healthcare professionals in providing a personalised, supportive, imaging experience to facilitate bonding is also reflected. CONCLUSION: Adopting parent-centred care approaches which involve expectant parents in fetal imaging influences bonding by helping parents to consider the reality of their impending parenthood. Knowledge acquired during scans is used to create an identity for the unborn baby, which parents can develop an emotional connection to. IMPLICATIONS FOR PRACTICE: To optimise the potential for enhanced parent-fetal bonding, care provision in fetal imaging should be tailored to the individual needs of expectant parents.

"It has been the most difficult time in my career": A qualitative exploration of UK obstetric sonographers' experiences during the COVID-19 pandemic.

INTRODUCTION: Substantial changes were made to the provision of pregnancy ultrasound services during the COVID-19 pandemic with the intention of minimising virus transmission and maintaining service continuity. Published literature describing the impact of the pandemic on obstetric sonographers is predominantly quantitative in nature, however statistics cannot fully convey sonographers' voices. This study aimed to gain a deeper understanding of the lived experiences of UK obstetric sonographers performing pregnancy ultrasound scans during the pandemic. METHODS: A UK-wide, online, anonymous cross-sectional survey on Qualtrics XM™ was open to responses between 9th March and 6th May 2021. Whilst this survey contained some quantitative elements, open questions were included to capture additional qualitative detail from respondents about their perceptions and experiences of scanning during the pandemic. Key themes were generated from free text responses using thematic analysis. RESULTS: Written responses were received from 111/138 sonographers participating in the survey. Five themes were generated, depicting the impact of the pandemic on obstetric sonographers: 1) continuity in a crisis; 2) decisions about me, without me; 3) battle scars - the lasting damage of COVID-19; 4) what people think I do vs. what I really do; and 5) the human touch. A cross-cutting theme was sonographers' feelings of disconnection from senior figures and expectant parents which created a sense of abandonment and distrust. CONCLUSION: Survey respondents' self-reported experiences of ineffective leadership and management, and perceived lack of understanding of the complexity of the sonographer role are potential contributory factors in the high levels of moral injury and occupational burnout reported within the workforce during the pandemic.

Research ethics systems, processes, and awareness across Europe: Radiography research ethics standards for Europe (RRESFE).

INTRODUCTION: The Radiography Research Ethics Standards for Europe (RRESFE) project aims to provide a cross-sectional snapshot of current research ethics systems, processes, and awareness of such, across Europe together with identifying the associated challenges, education, and training needs. METHODS: A cross-sectional online survey targeting radiography researchers in Europe was conducted. Data collection took place between April 26 and July 12, 2021, using a snowball sampling approach. Descriptive and analytical statistics were used to identify trends in research ethics frameworks across Europe. RESULTS: 285 responses were received across 33 European and 23 non-European countries. Most (n = 221; 95%) European respondents stated ethics approval is required before commencing research in their country. Requirements around research ethics approval and awareness of such requirements varied by European region (X2 (2, n = 129) = 7.234, p = 0.013) and were found to differ depending on the type of research participant and study design. Additionally, European respondents reported ethics approval is a national requirement more often than their non-European counterparts (X2 (1, n = 282) = 4.316, p = 0.049). Requirements for ethics approval were also associated with the undergraduate programme duration (2-year vs. 3-year vs. 3.5 year vs. 4-year vs. multiple programme durations; X2 (4, n = 231) = 10.075, p = 0.016) and availability of postgraduate training (postgraduate training available vs. postgraduate training not available; X2 (1, n = 231) = 15.448, p = <0.001) within respondents' country. CONCLUSION: Respondents from countries with longer programme durations/availability of multiple programme lengths, availability of postgraduate training, and establishment of European Qualifications Framework Level 6 were generally associated with less uncertainty and more comprehensive research ethics requirements. IMPLICATIONS FOR PRACTICE: Results are informative of the current status of research ethics within evidence-based radiography.

Research ethics training, challenges, and suggested improvements across Europe: Radiography research ethics standards for Europe (RRESFE).

INTRODUCTION: The Radiography Research Ethics Standards for Europe (RRESFE) project aimed to provide a cross-sectional view of the current state of radiography research ethics across Europe. This included investigating education and training in research ethics, and identifying the key challenges and potential improvements associated with using existing research ethics frameworks. METHODS: This cross-sectional online survey targeting radiography researchers in Europe was conducted between April 26 and July 12, 2021. Descriptive and analytical statistics were used to identify research ethics education and training trends. Content analysis of qualitative responses was employed to identify significant challenges and proposed improvements in research ethics frameworks of practice. RESULTS: There were 232 responses received across 33 European countries. Most (n = 132; 57%) respondents had received some research ethics training; however, fewer participants had received training on safeguarding vulnerable patients (n = 72; 38%), diversity and inclusivity (n = 62; 33%), or research with healthy volunteers (n = 60; 32%). Training was associated with a greater perceived importance of the need for research ethics review (p = 0.031) and with the establishment of EQF Level 6 training (p = 0.038). The proportion of formally trained researchers also varied by region (p = <0.001). Time-to-ethics-approval was noted as the biggest challenge for professionals making research ethics applications. CONCLUSION: Early and universal integration of research-oriented teaching within the radiography education framework which emphasises research ethics is recommended. Additionally, study findings suggest research ethics committee application and approval processes could be further simplified and streamlined. IMPLICATIONS FOR PRACTICE: The survey contributes to a growing body of knowledge surrounding the importance of education and training in research ethics for assuring a high standard of research outputs in Radiography and has identified hurdles to obtaining research ethics approval for further investigation and address.

The gendered impact of the COVID-19 pandemic on academics working in medical imaging and radiation therapy.

INTRODUCTION: Healthcare workers have been particularly impacted by the COVID-19 pandemic, as have those educating them, albeit differently. Several papers have identified a gendered difference in the impact of the pandemic. This study aims to determine impact of COVID-19 on the health and wellbeing of Medical Imaging and Radiation Therapy (MIRT) academics. METHODS: An electronic survey was designed in English on Qualtrics and distributed via email and online platforms to MIRT academics. Fifty-one questions were used; demographic (n = 9), work patterns (n = 11), general health (n = 8), mental health (n = 2), physical health (n = 10), and workload (n = 11). Overall, 46 were quantitative and five were qualitative 'open-ended' questions. The survey was open between 3rd March 2021 to 1st May 2021. Quantitative analysis was carried out using MS Excel v 16.61.1ss and SPSS v26. RESULTS: The survey reached 32 countries globally and 412 participants; 23.5% identified as men (n = 97) and 76.5% as women (n = 315). Women reported worse sleep quality than men and overwhelmingly felt they would not like to work remotely again if given a choice. A higher percentage of males, 73% versus 40.5% of females reported getting outdoors less. The CORE-10 validated questionnaire found that 10.3% of males (n = 42) and 2.7% of females (n = 11) experienced severe psychological distress the week immediately before the survey was conducted. CONCLUSION: While the study has identified some gender-related differences in the impact of COVID-19 on the mental and physical health of MIRT academics, both males and females have experienced significant deterioration in health and wellbeing due to the pandemic. IMPLICATION FOR PRACTICE: Developing mental health support for MIRT academics and defining optimum methods for raising awareness is recommended.

UK reporting radiographers' perceptions of AI in radiographic image interpretation - Current perspectives and future developments.

INTRODUCTION: Radiographer reporting is accepted practice in the UK. With a national shortage of radiographers and radiologists, artificial intelligence (AI) support in reporting may help minimise the backlog of unreported images. Modern AI is not well understood by human end-users. This may have ethical implications and impact human trust in these systems, due to over- and under-reliance. This study investigates the perceptions of reporting radiographers about AI, gathers information to explain how they may interact with AI in future and identifies features perceived as necessary for appropriate trust in these systems. METHODS: A Qualtrics® survey was designed and piloted by a team of UK AI expert radiographers. This paper reports the third part of the survey, open to reporting radiographers only. RESULTS: 86 responses were received. Respondents were confident in how an AI reached its decision (n = 53, 62%). Less than a third of respondents would be confident communicating the AI decision to stakeholders. Affirmation from AI would improve confidence (n = 49, 57%) and disagreement would make respondents seek a second opinion (n = 60, 70%). There is a moderate trust level in AI for image interpretation. System performance data and AI visual explanations would increase trust. CONCLUSIONS: Responses indicate that AI will have a strong impact on reporting radiographers' decision making in the future. Respondents are confident in how an AI makes decisions but less confident explaining this to others. Trust levels could be improved with explainable AI solutions. IMPLICATIONS FOR PRACTICE: This survey clarifies UK reporting radiographers' perceptions of AI, used for image interpretation, highlighting key issues with AI integration.

Autism-friendly MRI: Improving radiography practice in the UK, a survey of radiographer practitioners.

INTRODUCTION: Autistic individuals undergoing magnetic resonance imaging (MRI) examinations may face significant challenges, mainly due to sensory overload and MRI environment-related limitations. This study aimed to explore radiographers' perspectives and experiences regarding MRI scanning of autistic individuals. METHODS: Data collection was achieved using a specifically designed mixed methods questionnaire on Qualtrics. The snowball technique was used. This UK-wide survey was electronically distributed by three main recruitment agencies between December 2020 and February 2021. RESULTS: 130 valid responses were received. A lack of relevant training and knowledge related to autism was noted. Effective communication, optimisation and customisation of the MRI examination, and MRI environment adjustments facilitated the completion of a safe and effective MRI examination. Poor patient-radiographer communication, unavailability of Special Educational Needs (SEN) experts, lack of specialised radiographer training and lack of specific guidelines were identified as the main barriers to successful MRI examinations. CONCLUSION: Although routine MRI safety and patient care rules will apply, MRI scanning of autistic individuals requires customisation and reasonable adjustments in communication, environment, and training of clinical teams. In addition, guidelines should be established to be used as a reference point to improve clinical practice. The adjustments proposed by radiographers were all consistent with the interventions in the wider literature. IMPLICATIONS FOR PRACTICE: MRI practice for personalised care of autistic individuals should be aligned with current evidence, to customise communication and offer workflow and environmental adjustments. Formal training related to autism, integrated within radiography academic curricula and better co-ordination and communication of interdisciplinary teams would provide the necessary skill mix to deliver safe, high quality MRI scans with optimal experience for autistic service users and their carer(s).

Artificial Intelligence: Guidance for clinical imaging and therapeutic radiography professionals, a summary by the Society of Radiographers AI working group.

INTRODUCTION: Artificial intelligence (AI) has started to be increasingly adopted in medical imaging and radiotherapy clinical practice, however research, education and partnerships have not really caught up yet to facilitate a safe and effective transition. The aim of the document is to provide baseline guidance for radiographers working in the field of AI in education, research, clinical practice and stakeholder partnerships. The guideline is intended for use by the multi-professional clinical imaging and radiotherapy teams, including all staff, volunteers, students and learners. METHODS: The format mirrored similar publications from other SCoR working groups in the past. The recommendations have been subject to a rapid period of peer, professional and patient assessment and review. Feedback was sought from a range of SoR members and advisory groups, as well as from the SoR director of professional policy, as well as from external experts. Amendments were then made in line with feedback received and a final consensus was reached. RESULTS: AI is an innovative tool radiographers will need to engage with to ensure a safe and efficient clinical service in imaging and radiotherapy. Educational provisions will need to be proportionately adjusted by Higher Education Institutions (HEIs) to offer the necessary knowledge, skills and competences for diagnostic and therapeutic radiographers, to enable them to navigate a future where AI will be central to patient diagnosis and treatment pathways. Radiography-led research in AI should address key clinical challenges and enable radiographers co-design, implement and validate AI solutions. Partnerships are key in ensuring the contribution of radiographers is integrated into healthcare AI ecosystems for the benefit of the patients and service users. CONCLUSION: Radiography is starting to work towards a future with AI-enabled healthcare. This guidance offers some recommendations for different areas of radiography practice. There is a need to update our educational curricula, rethink our research priorities, forge new strong clinical-academic-industry partnerships to optimise clinical practice. Specific recommendations in relation to clinical practice, education, research and the forging of partnerships with key stakeholders are discussed, with potential impact on policy and practice in all these domains. These recommendations aim to serve as baseline guidance for UK radiographers. IMPLICATIONS FOR PRACTICE: This review offers the most up-to-date recommendations for clinical practitioners, researchers, academics and service users of clinical imaging and therapeutic radiography services. Radiography practice, education and research must gradually adjust to AI-enabled healthcare systems to ensure gains of AI technologies are maximised and challenges and risks are minimised. This guidance will need to be updated regularly given the fast-changing pace of AI development and innovation.

Artificial intelligence in radiography: Where are we now and what does the future hold?

OBJECTIVES: This paper will outline the status and basic principles of artificial intelligence (AI) in radiography along with some thoughts and suggestions on what the future might hold. While the authors are not always able to separate the current status from future developments in this field, given the speed of innovation in AI, every effort has been made to give a view to the present with projections to the future. KEY FINDINGS: AI is increasingly being integrated within radiography and radiographers will increasingly be working with AI based tools in the future. As new AI tools are developed it is essential that robust validation is undertaken in unseen data, supported by more prospective interdisciplinary research. A framework of stronger, more comprehensive approvals are recommended and the involvement of service users, including practitioners, patients and their carers in the design and implementation of AI tools is essential. Clearer accountability and medicolegal frameworks are required in cases of erroneous results from the use of AI-powered software and hardware. Clearer career pathways and role extension provision for healthcare practitioners, including radiographers, are required along with education in this field where AI will be central. CONCLUSION: With the current growth rate of AI tools it is expected that many of the applications in medical imaging will continue to develop to more accurate, less expensive and more readily available versions moving from the bench to the bedside. The hope is that, alongside efficiency and increased patient throughput, patient centred care and precision medicine will find their way in, so we will not only deliver a faster, safer, seamless clinical service but also one that will have the patients at its heart. IMPACT FOR PRACTICE: AI is already reaching clinical practice in many forms and its presence will continue to increase over the short and long-term future. Radiographers must learn to work with AI, embracing it and maximising the positive outcomes from this new technology.

Evaluating the use of gradient echo imaging for the detection of cerebral microbleeds in acute stroke cases: A retrospective data analysis in a UK stroke unit.

INTRODUCTION: Imaging in stroke, allows its classification into ischaemic stroke (IS) or intracranial haemorrhagic stroke (ICH), ensuring time-sensitive treatment to be administered. Imaging can also allow detection of cerebral microbleeds (CMBs), which may further determine pharmacological intervention in acute stroke. True gradient echo (T2∗GRE) or susceptibility weighted imaging (SWI) have high sensitivity for the detection of CMBs. These two sequences are included in the national guidelines; however, the implementation of these guidelines can vary depending on local interpretation and scanner capabilities. AIM: To explore the use and application of blood sensitive MRI sequences in a specialist UK stroke unit for the detection of CMBs, to improve local practice. METHODS: A retrospective data analysis of the native database, spanning a 6-month period, was used. The data of 281 acute stroke patients with an MRI were reviewed and analysed. The MRI sequences applied, and the final diagnosis were noted for each case. RESULTS: Of the 281 acute stroke patients with MRI, 259 (92.1%) had an IS, 16 (5.68%) an ICH and 6 (2.14%) had both. Overall, 13 (4.63%) had a CMB diagnosis. All of these 13 patients had a true T2∗GRE sequence. CMBs were not detected in the absence of a T2∗GRE sequence. CONCLUSION: T2∗GRE imaging is essential for detecting CMBs. When omitted, CMB incidence can be considerably lower than that suggested in the literature. Missing CMB diagnoses in stroke patients may result in suboptimal treatment pathways, compromising the patients' standard of care. IMPLICATIONS FOR PRACTICE: When SWI is not available, it is imperative to always include a true T2∗GRE sequence to detect microbleeds in suspected acute stroke cases.

COVID-19 in the radiology department: What radiographers need to know.

OBJECTIVES: The aim is to review current literature related to the diagnosis, management, and follow-up of suspected and confirmed Covid-19 cases. KEY FINDINGS: Medical Imaging plays an important auxiliary role in the diagnosis of Covid-19 patients, mainly those most seriously affected. Practice differs widely among different countries, mainly due to the variability of access to resources (viral testing and imaging equipment, specialised staff, protective equipment). It has been now well-documented that chest radiographs should be the first-line imaging tool and chest CT should only be reserved for critically ill patients, or when chest radiograph and clinical presentation may be inconclusive. CONCLUSION: As radiographers work on the frontline, they should be aware of the potential risks associated with Covid-19 and engage in optimal strategies to reduce these. Their role in vetting, conducting and often reporting the imaging examinations is vital, as well as their contribution in patient safety and care. Medical Imaging should be limited to critically ill patients, and where it may have an impact on the patient management plan. IMPLICATIONS FOR PRACTICE: At the time of publication, this review offers the most up-to-date recommendations for clinical practitioners in radiology departments, including radiographers. Radiography practice has to significantly adjust to these new requirements to support optimal and safe imaging practices for the diagnosis of Covid-19. The adoption of low dose CT, rigorous infection control protocols and optimal use of personal protective equipment may reduce the potential risks of radiation exposure and infection, respectively, within Radiology departments.

Automated fetal brain segmentation from 2D MRI slices for motion correction.

Motion correction is a key element for imaging the fetal brain in-utero using Magnetic Resonance Imaging (MRI). Maternal breathing can introduce motion, but a larger effect is frequently due to fetal movement within the womb. Consequently, imaging is frequently performed slice-by-slice using single shot techniques, which are then combined into volumetric images using slice-to-volume reconstruction methods (SVR). For successful SVR, a key preprocessing step is to isolate fetal brain tissues from maternal anatomy before correcting for the motion of the fetal head. This has hitherto been a manual or semi-automatic procedure. We propose an automatic method to localize and segment the brain of the fetus when the image data is acquired as stacks of 2D slices with anatomy misaligned due to fetal motion. We combine this segmentation process with a robust motion correction method, enabling the segmentation to be refined as the reconstruction proceeds. The fetal brain localization process uses Maximally Stable Extremal Regions (MSER), which are classified using a Bag-of-Words model with Scale-Invariant Feature Transform (SIFT) features. The segmentation process is a patch-based propagation of the MSER regions selected during detection, combined with a Conditional Random Field (CRF). The gestational age (GA) is used to incorporate prior knowledge about the size and volume of the fetal brain into the detection and segmentation process. The method was tested in a ten-fold cross-validation experiment on 66 datasets of healthy fetuses whose GA ranged from 22 to 39 weeks. In 85% of the tested cases, our proposed method produced a motion corrected volume of a relevant quality for clinical diagnosis, thus removing the need for manually delineating the contours of the brain before motion correction. Our method automatically generated as a side-product a segmentation of the reconstructed fetal brain with a mean Dice score of 93%, which can be used for further processing.

Motion-compensation techniques in neonatal and fetal MR imaging.

SUMMARY: Fetal and neonatal MR imaging is increasingly used as a complementary diagnostic tool to sonography. MR imaging is an ideal technique for imaging fetuses and neonates because of the absence of ionizing radiation, the superior contrast of soft tissues compared with sonography, the availability of different contrast options, and the increased FOV. Motion in the normally mobile fetus and the unsettled, sleeping, or sedated neonate during a long acquisition will decrease image quality in the form of motion artifacts, hamper image interpretation, and often necessitate a repeat MR imaging to establish a diagnosis. This article reviews current techniques of motion compensation in fetal and neonatal MR imaging, including the following: 1) motion-prevention strategies (such as adequate patient preparation, patient coaching, and sedation, when required), 2) motion-artifacts minimization methods (such as fast imaging protocols, data undersampling, and motion-resistant sequences), and 3) motion-detection/correction schemes (such as navigators and self-navigated sequences, external motion-tracking devices, and postprocessing approaches) and their application in fetal and neonatal brain MR imaging. Additionally some background on the repertoire of motion of the fetal and neonatal patient and the resulting artifacts will be presented, as well as insights into future developments and emerging techniques of motion compensation.

The anatomic variations of the circle of Willis in preterm-at-term and term-born infants: an MR angiography study at 3T.

BACKGROUND AND PURPOSE: It has been shown that the brain of a preterm infant develops differently from that of a term infant, but little is known about the neonatal cerebrovascular anatomy. Our aims were to establish reference data for the prevalence of the anatomic variations of the neonatal circle of Willis (CoW) and to explore the effect of prematurity, MR imaging abnormality, vascular-related abnormality, laterality, and sex on these findings. MATERIALS AND METHODS: We scanned 103 infants with an optimized MR angiography (MRA) protocol. Images were analyzed for different variations of the CoW, and results were compared for the following: 1) preterm-at-term and term-born infants, 2) infants with normal and abnormal MR imaging, 3) infants with and without a vascular-related abnormality, 4) boys and girls, and 5) left- and right-sided occurrence. RESULTS: The most common anatomic variation was absence/hypoplasia of the posterior communicating artery. Preterm infants at term had a higher prevalence of a complete CoW and a lower prevalence of anatomic variations compared with term-born infants; this finding was significant for the anterior cerebral artery (P = .02). There was increased prevalence of variations of the major cerebral arteries in those infants with vascular-related abnormalities, statistically significant for the posterior cerebral artery (P = .004). There was no statistically significant difference between boys and girls and left/right variations. CONCLUSIONS: Prematurity is associated with more complete CoWs and fewer anatomic variations. In vascular-related abnormalities, more variations involved major arterial segments, but fewer variations occurred in the communicating arteries. Overall reference values of the variations match those of the general adult population.