Impact and effect of imaging referral guidelines on patients and radiology services: a systematic review.

OBJECTIVES: The objective of this systematic review was to offer a comprehensive overview and explore the associated outcomes from imaging referral guidelines on various key stakeholders, such as patients and radiologists. MATERIALS AND METHODS: An electronic database search was conducted in Medline, Embase and Web of Science to retrieve citations published between 2013 and 2023. The search was constructed using medical subject headings and keywords. Only full-text articles and reviews written in English were included. The quality of the included papers was assessed using the mixed methods appraisal tool. A narrative synthesis was undertaken for the selected articles. RESULTS: The search yielded 4384 records. Following the abstract, full-text screening, and removal of duplication, 31 studies of varying levels of quality were included in the final analysis. Imaging referral guidelines from the American College of Radiology were most commonly used. Clinical decision support systems were the most evaluated mode of intervention, either integrated or standalone. Interventions showed reduced patient radiation doses and waiting times for imaging. There was a general reduction in radiology workload and utilisation of diagnostic imaging. Low-value imaging utilisation decreased with an increase in the appropriateness of imaging referrals and ratings and cost savings. Clinical effectiveness was maintained during the intervention period without notable adverse consequences. CONCLUSION: Using evidence-based imaging referral guidelines improves the quality of healthcare and outcomes while reducing healthcare costs. Imaging referral guidelines are one essential component of improving the value of radiology in the healthcare system. CLINICAL RELEVANCE STATEMENT: There is a need for broader dissemination of imaging referral guidelines to healthcare providers globally in tandem with the harmonisation of the application of these guidelines to improve the overall value of radiology within the healthcare system. KEY POINTS: The application of imaging referral guidelines has an impact and effect on patients, radiologists, and health policymakers. The adoption of imaging referral guidelines in clinical practice can impact healthcare costs and improve healthcare quality and outcomes. Implementing imaging referral guidelines contributes to the attainment of value-based radiology.

Minimal dose CT for left ventricular ejection fraction and combination with chest-abdomen-pelvis CT.

Objectives: This prospective study tested the diagnostic accuracy, and absolute agreement with MRI of a low-dose CT protocol for left ventricular ejection fraction (LVEF) measurement. Furthermore we assessed its potential for combining it with Chest-Abdomen-Pelvis CT (CAP-CT) for a one-stop examination. Materials & methods: Eighty-two patients underwent helical low-dose CT. Cardiac magnetic resonance imaging (MRI) was the reference standard. In fifty patients, CAP-CT was performed concurrently, using a modified injection protocol. In these, LVEF was measured with radioisotope cardiography (MUGA). Patients >18 years, without contrast media or MRI contraindications, were included. Bias was measured with Bland-Altman analysis, classification accuracy with Receiver Operating Characteristics, and inter-reader agreement with Intra-Class Correlation Coefficient (ICC). Correlation was examined using Pearson's correlation coefficients. CAP image quality was compared to previous scans with visual grading characteristics. Results: The mean CT dose-length-product (DLP) was 51.8 mGycm, for an estimated effective dose of 1.4 mSv, compared to 5.7 mSv for MUGA. CT LVEF bias was between 2 % and 10 %, overestimating end-diastolic volume. When corrected for bias, sensitivity and specificity of 100 and 98.5 % for classifying reduced LVEF (50 % MRI value) was achieved. ICC for MUGA was significantly lower than MRI and CT. Distinction of renal medulla and cortex was reduced in the CAP scan, but proportion of diagnostic scans was not significantly different from standard protocol. Conclusion: When corrected for inter-modality bias, CT classifies patients with reduced LVEF with high accuracy at a quarter of MUGA dose and can be combined with CAP-CT without loss of diagnostic quality.

Machine learning and deep learning for classifying the justification of brain CT referrals.

OBJECTIVES: To train the machine and deep learning models to automate the justification analysis of radiology referrals in accordance with iGuide categorisation, and to determine if prediction models can generalise across multiple clinical sites and outperform human experts. METHODS: Adult brain computed tomography (CT) referrals from scans performed in three CT centres in Ireland in 2020 and 2021 were retrospectively collected. Two radiographers analysed the justification of 3000 randomly selected referrals using iGuide, with two consultant radiologists analysing the referrals with disagreement. Insufficient or duplicate referrals were discarded. The inter-rater agreement among radiographers and consultants was computed. A random split (4:1) was performed to apply machine learning (ML) and deep learning (DL) techniques to unstructured clinical indications to automate retrospective justification auditing with multi-class classification. The accuracy and macro-averaged F1 score of the best-performing classifier of each type on the training set were computed on the test set. RESULTS: 42 referrals were ignored. 1909 (64.5%) referrals were justified, 811 (27.4%) were potentially justified, and 238 (8.1%) were unjustified. The agreement between radiographers (κ = 0.268) was lower than radiologists (κ = 0.460). The best-performing ML model was the bag-of-words-based gradient-boosting classifier achieving a 94.4% accuracy and a macro F1 of 0.94. DL models were inferior, with bi-directional long short-term memory achieving 92.3% accuracy, a macro F1 of 0.92, and outperforming multilayer perceptrons. CONCLUSION: Interpreting unstructured clinical indications is challenging necessitating clinical decision support. ML and DL can generalise across multiple clinical sites, outperform human experts, and be used as an artificial intelligence-based iGuide interpreter when retrospectively vetting radiology referrals. CLINICAL RELEVANCE STATEMENT: Healthcare vendors and clinical sites should consider developing and utilising artificial intelligence-enabled systems for justifying medical exposures. This would enable better implementation of imaging referral guidelines in clinical practices and reduce population dose burden, CT waiting lists, and wasteful use of resources. KEY POINTS: Significant variations exist among human experts in interpreting unstructured clinical indications/patient presentations. Machine and deep learning can automate the justification analysis of radiology referrals according to iGuide categorisation. Machine and deep learning can improve retrospective and prospective justification auditing for better implementation of imaging referral guidelines.

Validating the safety of low-dose CTPA in pregnancy: results from the OPTICA (Optimised CT Pulmonary Angiography in Pregnancy) Study.

BACKGROUND: Pulmonary embolism (PE) is a leading cause of pregnancy-related mortality. CT pulmonary angiogram (CTPA) is the first-line advanced imaging modality for suspected PE in pregnancy at institutes offering low-dose techniques; however, a protocol balancing safety with low dose remains undefined. The wide range of CTPA doses reported in pregnancy suggests a lack of confidence in implementing low-dose techniques in this group. PURPOSE: To define and validate the safety, radiation dose and image quality of a low-dose CTPA protocol optimised for pregnancy. MATERIALS AND METHODS: The OPTICA study is a prospective observational study. Pregnant study participants with suspected PE underwent the same CTPA protocol between May 2018 and February 2022. The primary outcome, CTPA safety, was judged by the reference standard; the 3-month incidence of venous thromboembolism (VTE) in study participants with a negative index CTPA. Secondary outcomes defined radiation dose and image quality. Absorbed breast, maternal effective and fetal doses were estimated by Monte-Carlo simulation on gestation-matched phantoms. Image quality was assessed by signal-to-noise and contrast-to-noise ratios and a Likert score for pulmonary arterial enhancement. RESULTS: A total of 116 CTPAs were performed in 113 pregnant women of which 16 CTPAs were excluded. PE was diagnosed on 1 CTPA and out-ruled in 99. The incidence of recurrent symptomatic VTE was 0.0% (one-sided 95% CI, 2.66%) at follow-up. The mean absorbed breast dose was 2.9 ± 2.1mGy, uterine/fetal dose was 0.1 ± 0.2mGy and maternal effective dose was 1.4 ± 0.9mSv. Signal-to-noise ratio (SNR) was 11.9 ± 3.7. Contrast-to-noise ratio (CNR) was 10.4 ± 3.5. CONCLUSION: The OPTICA CTPA protocol safely excluded PE in pregnant women across all trimesters, with low fetal and maternal radiation. CLINICAL RELEVANCE: OPTICA (Optimised CT Pulmonary Angiography in Pregnancy) is the first prospective study to define the achievable radiation dose, image-quality and safety of a low-dose CT pulmonary angiogram protocol optimised for pregnancy (NCT04179487). It provides the current benchmark for safe and achievable CT pulmonary angiogram doses in the pregnant population. KEY POINTS: • Despite the increased use of CT pulmonary angiogram in pregnancy, an optimised low-dose protocol has not been defined and reported doses in pregnancy continue to vary widely. • The OPTICA (Optimised CT Pulmonary Angiography in Pregnancy) study prospectively defines the achievable dose, image quality and safety of a low-dose CT pulmonary angiogram protocol using widely available technology. • OPTICA provides a benchmark for safe and achievable CT pulmonary angiogram doses in the pregnant population.

Development of the EVIBEC Learning Outcomes Framework to support the delivery of evidence-based practice curricula in health care professional programmes: a codesign approach.

BACKGROUND: All healthcare professional education programmes must adopt a systematic approach towards ensuring graduates achieve the competencies required to be an evidence-based practitioner. While a list of competencies for evidence-based practice exist, health care educators continue to struggle with effectively integrating the necessary competencies into existing curricula. The purpose of this project was to develop an open access cross-discipline, learning outcomes framework to support educators in integrating the teaching, learning and assessment required to ensure all graduates of health care professional programmes can achieve the necessary evidence-based practice competencies. METHODS: An interdisciplinary team of health care professional educators and a librarian completed a review of the health professions literature on the teaching and assessment of evidence-based practice. The literature, coupled with the teams' collective experiences in evidence-based education and research, were used to identify relevant teaching, learning and evidence-based competency frameworks to inform the project design. The guide and toolkit for experience-based co-design developed by the National Health Service Institute for Innovation and Improvement was adopted for this study ( Institute for Innovation and Improvement: Experience Based Design: Guide & Tools In. Leeds: NHS; 2009.). A four-step approach involving three online participatory co-design workshops and a national validation workshop was designed. Students (n = 33), faculty (n = 12), and clinical educators (n = 15) participated in formulating and mapping learning outcomes to evidence-based competencies. RESULTS: Through a rigorous, systematic co-design process the Evidenced-based Education Collaborative (EVIBEC) Learning Outcomes Framework was developed. This framework consists of a series of student-centred learning outcomes, aligned to evidence-based practice competencies, classified according to the 5 As of EBP and mapped to the cognitive levels of Bloom's taxonomy. Associated learning activities for each step of EBP are suggested. CONCLUSIONS: A consensus-based, student-centred learning outcomes framework aligned to a contemporary set of EBP core competencies has been developed. The freely accessible EVIBEC framework may support entry level health care professional EBP education, by informing EBP curriculum development and offering the potential for interdisciplinary approaches to and sharing of valuable teaching and learning resources. Co-design proved an effective method in creating and refining this framework.

Potential for Dose Reduction in CT-Derived Left Ventricular Ejection Fraction: A Simulation Study.

BACKGROUND: Measuring left ventricular ejection fraction (LVEF) is important for detecting heart failure, e.g., in treatment with potentially cardiotoxic chemotherapy. MRI is considered the reference standard for LVEF, but availability may be limited and claustrophobia or metal implants still present challenges. CT has been shown to be accurate and would be advantageous, as LVEF could be measured in conjunction with routine chest-abdomen-pelvis oncology CT. However, the use of CT is not recommended due to the excessive radiation dose. This study aimed to explore the potential for dose reduction using simulation. Using an anthropomorphic heart phantom scanned at 13 dose levels, a noise simulation algorithm was developed to introduce controlled Poisson noise. Filtered backprojection parameters were iteratively tested to minimise differences in myocardium-to-ventricle contrast/noise ratio, as well as structural similarity index (SSIM) differences between real and simulated images at all dose levels. Fifty-one clinical CT coronary angiographies, scanned with full dose through end-systolic and -diastolic phases, were located retrospectively. Using the developed algorithm, noise was introduced corresponding to 25, 10, 5 and 2% of the original dose level. LVEF was measured using clinical software (Syngo.via VB50) with papillary muscles in and excluded from the LV volume. At each dose level, LVEF was compared to the 100% dose level, using Bland-Altman analysis. The effective dose was calculated from DLP using a conversion factor of 0.026 mSv/mGycm. RESULTS: In the clinical images, mean CTDIvol and DLP were 47.1 mGy and 771.9 mGycm, respectively (effective dose 20.0 mSv). Measurements with papillary muscles excluded did not exhibit statistically significant LVEF bias to full-dose images at 25, 10 and 5% simulated dose. At 2% dose, a significant bias of 4.4% was found. With papillary muscles included, small but significant biases were found at all simulated dose levels. CONCLUSION: Provided that measurements are performed with papillary muscles excluded from the LV volume, the dose can be reduced by a factor of 20 without significantly affecting LVEF measurements. This corresponds to an effective dose of 1 mSv. CT can potentially be used for LVEF measurement with minimal excessive radiation.

Symptomatic Carotid Atheroma Inflammation Lumen-stenosis score compared with Oxford and Essen risk scores to predict recurrent stroke in symptomatic carotid stenosis.

BACKGROUND: The Oxford Carotid Stenosis tool (OCST) and Essen Stroke Risk Score (ESRS) are validated to predict recurrent stroke in patients with and without carotid stenosis. The Symptomatic Carotid Atheroma Inflammation Lumen stenosis (SCAIL) score combines stenosis and plaque inflammation on fluorodeoxyglucose positron-emission tomography (18FDG-PET). We compared SCAIL with OCST and ESRS to predict ipsilateral stroke recurrence in symptomatic carotid stenosis. PATIENTS AND METHODS: We pooled three prospective cohort studies of patients with recent (<30 days) non-severe ischaemic stroke/TIA and internal carotid artery stenosis (>50%). All patients had carotid 18FDG-PET/CT angiography and late follow-up, with censoring at carotid revascularisation. RESULTS: Of 212 included patients, 16 post-PET ipsilateral recurrent strokes occurred in 343 patient-years follow-up (median 42 days (IQR 13-815)).Baseline SCAIL predicted recurrent stroke (unadjusted hazard ratio [HR] 1.96, CI 1.20-3.22, p = 0.007, adjusted HR 2.37, CI 1.31-4.29, p = 0.004). The HR for OCST was 0.996 (CI 0.987-1.006, p = 0.49) and for ESRS was 1.26 (CI 0.87-1.82, p = 0.23) (all per 1-point score increase). C-statistics were: SCAIL 0.66 (CI 0.51-0.80), OCST 0.52 (CI 0.40-0.64), ESRS 0.61 (CI 0.48-0.74). Compared with ESRS, addition of plaque inflammation (SUVmax) to ESRS improved risk prediction when analysed continuously (HR 1.51, CI 1.05-2.16, p = 0.03) and categorically (ptrend = 0.005 for risk increase across groups; HR 3.31, CI 1.42-7.72, p = 0.006; net reclassification improvement 10%). Findings were unchanged by further addition of carotid stenosis. CONCLUSIONS: SCAIL predicted recurrent stroke, had discrimination better than chance, and improved the prognostic utility of ESRS, suggesting that measuring plaque inflammation may improve risk stratification in carotid stenosis.

European survey on the use of patient contact shielding during radiological examinations.

OBJECTIVES: Contact shielding (CS) of patients during X-ray studies has been used for decades to protect radiosensitive organs. This practice has not changed much despite increasing evidence that CS is not useful in many cases. The Gonad And Patient Shielding (GAPS) group-founded by representatives of the main European bodies involved in radiology-promoted this survey to assess the current practice of CS among European radiology departments and the attitude towards a non-shielding policy. METHODS: Over a four-month period (15 May-15th September 2021) European Society of Radiology and European Society of Paediatric Radiology radiologist members were invited to respond to a web-based questionnaire consisting of 59 questions. RESULTS: 225 centres from 35 countries responded to this survey. CS was routinely applied in at least one radiological modality in 49.2% of centres performing studies in adults, 57.5% of centres performing studies in children, and 47.8% of centres performing studies on pregnant women. CS was most frequently used in conventional radiography, where the most frequently shielded organs were the gonads, followed by thyroid, female breasts, and eye lens. 83.6% respondents would follow European recommendations on the use of CS when provided by the main European bodies involved in radiology. CONCLUSIONS: This review shows that CS is still largely used across Europe. However, a non-shielding policy could be adopted in most departments if European professional societies provided recommendations. In this regard, a strong commitment by European and national professional societies to educate and inform practitioners, patients and carers is paramount. CLINICAL RELEVANCE STATEMENT: According to this survey expectations of patients and carers, and skepticism among professionals about the limited benefits of CS are the most important obstacles to the application of a no-shielding policy. A strong commitment from European and national professional societies to inform practitioners, patients and carers is fundamental.

Current and potential applications of artificial intelligence in medical imaging practice: A narrative review.

BACKGROUND AND PURPOSE: Artificial intelligence (AI) is present in many areas of our lives. Much of the digital data generated in health care can be used for building automated systems to bring improvements to existing workflows and create a more personalised healthcare experience for patients. This review outlines select current and potential AI applications in medical imaging practice and provides a view of how diagnostic imaging suites will operate in the future. Challenges associated with potential applications will be discussed and healthcare staff considerations necessary to benefit from AI-enabled solutions will be outlined. METHODS: Several electronic databases, including PubMed, ScienceDirect, Google Scholar, and University College Dublin Library Database, were used to identify relevant articles with a Boolean search strategy. Textbooks, government sources and vendor websites were also considered. RESULTS/DISCUSSION: Many AI-enabled solutions in radiographic practice are available with more automation on the horizon. Traditional workflow will become faster, more effective, and more user friendly. AI can handle administrative or technical types of work, meaning it is applicable across all aspects of medical imaging practice. CONCLUSION: AI offers significant potential to automate most of the manual tasks, ensure service consistency, and improve patient care. Radiographers, radiation therapists, and clinicians should ensure they have adequate understanding of the technology to enable ethical oversight of its implementation.

Education and training in radiation protection in Europe: results from the EURAMED Rocc-n-Roll project survey.

PURPOSE: To analyse the existing radiation protection (RP) education and training (E&T) capabilities in the European Union and identify associated needs, problems and challenges. METHOD: An online survey was disseminated via the EURAMED Rocc-n-Roll consortium network and prominent medical societies in the field of radiological research. The survey sections analyse the RP E&T during undergraduate, residency/internship and continuous professional development; RP E&T problems and legal implementation. Differences were analysed by European geographic regions, profession, years of professional experience and main area of practice/research. RESULTS: The majority of the 550 respondents indicated that RP topics are part of undergraduate curricula in all courses for their profession and country (55%); however, hands-on practical training is not included according to 30% of the respondents. The lack of E&T, practical aspects in current E&T, and mandatory continuing E&T were considered the major problems. The legal requirement that obtained higher implementation score was the inclusion of the practical aspects of medical radiological procedures on education (86%), and lower score was obtained for the inclusion of RP E&T on medical and dental school curriculums (61%). CONCLUSIONS: A heterogeneity in RP E&T during undergraduate, residency/internship and continuous professional development is evident across Europe. Differences were noted per area of practice/research, profession, and European geographic region. A large variation in RP E&T problem rating was also obtained.

The architectural characteristics of the hamstring muscles do not differ between male and female elite-level rugby union players.

Purpose: To determine whether differences exist in the architectural characteristics of the hamstring muscles of elite-level male and female rugby union players. Methods: Forty elite-level rugby union players (male n = 20, female n = 20) participated in this cross-sectional study. A sonographer acquired static ultrasound images using a 92 mm linear transducer to quantify (via a semi-automated tracing software tool) the architectural characteristics (muscle length, fascicle length, pennation angle, and muscle thickness) of the biceps femoris long head and semimembranosus muscles of participants' left limb. Muscle length and muscle thickness of the biceps femoris short head and semitendinosus muscles of participants' left limb were also quantified. Bonferroni adjusted independent samples t-tests were performed to evaluate whether differences exist in the architectural characteristics of the hamstring muscles of elite-level male and female rugby union players. Results: There were no significant differences in fascicle length or pennation angle of the hamstring muscles of elite-level male and female rugby union players. Some significant differences in muscle thickness (biceps femoris short head, and semimembranosus) and muscle length (biceps femoris short head, biceps femoris long head, semitendinosus, and semimembranosus) were observed; in all cases the male players had thicker and longer muscles. Conclusion: At a group level, hamstring muscle fascicle length and pennation angle are unlikely to be a sex-specific intrinsic risk factor for Hamstring strain injuries.

Breast Shielding Combined With an Optimized Computed Tomography Pulmonary Angiography Pregnancy Protocol: A Special Use-Case for Shielding?

OBJECTIVES: To determine the impact of breast shields on breast dose and image quality when combined with a low-dose computed tomography pulmonary angiography (CTPA) protocol for pregnancy. METHODS: A low-dose CTPA protocol, with and without breast shields, was evaluated by anthropomorphic phantom and 20 prospectively recruited pregnant participants from January to October 2019. Thermoluminescent dosimeters measured surface and absorbed breast dose in the phantom and surface breast dose in participants. The Monte-Carlo method estimated the absorbed breast dose in participants. Image quality was assessed quantitatively by regions of interest analysis and subjectively by the Likert scale. Doses and image quality for CTPA alone were compared with CTPA with breast shields. RESULTS: Mean surface and absorbed breast dose for CTPA alone were 1.3±0.4 and 2.8±1.5 mGy in participants, and 1.5±0.7 and 1.6±0.6 mGy in the phantom. Shielding reduced surface breast dose to 0.5±0.3 and 0.7±0.2 mGy in the phantom (66%) and study participants (48%), respectively. Absorbed breast dose reduced to 0.9±0.5 mGy (46%) in the phantom.Noise increased with breast shields at lower kV settings (80 to 100 kV) in the phantom; however, in study participants there was no significant difference between shield and no-shield groups for main pulmonary artery noise (no-shield: 34±9.8, shield: 36.3±7.2, P =0.56), SNR (no-shield: 11.2±3.7, shield: 10.8±2.6, P =0.74) or contrast-to-noise ratio (no-shield: 10.0±3.3, shield: 9.3±2.4, P =0.6). Median subjective image quality scores were comparable (no-shield: 4.0, interquartile range: 3.5 to 4.4, shield: 4.3, interquartile range: 4.0 to 4.5). CONCLUSION: Combining low-dose CTPA with breast shields confers additional breast-dose savings without impacting image quality and yields breast doses approaching those of low-dose scintigraphy, suggesting breast shields play a role in protocol optimization for select groups.

COMBINING HI-RESOLUTION SCAN MODE WITH DEEP LEARNING RECONSTRUCTION ALGORITHMS IN CARDIAC CT.

To investigate the impact of combining the high-resolution (Hi-res) scan mode with deep learning image reconstruction (DLIR) algorithm in CT. Two phantoms (Catphan600® and Lungman, small, medium, large size) were CT scanned using combinations of Hi-res/standard mode and high-definition (HD)/standard kernels. Images were reconstructed with ASiR-V and three levels of DLIR. Spatial resolution, noise and contrast-to-noise ratio (CNR) were assessed. The radiation dose was recorded. The spatial resolution increased using Hi-res & HD. Image noise in the Catphan600® (69%) and the Lungman (10-70%) significantly increased when Hi-res & HD was applied. DLIR reduced the mean noise (54%). The CNR was reduced (64%) for Hi-res & HD. The radiation dose increased for both small (+70%) and medium (+43%) Lungman phantoms but decreased slightly for the large ones (-3%) when Hi-res was applied. In conclusion, the Hi-res scan mode improved the spatial resolution. The HD kernel significantly increased the image noise. DLIR improved the image noise and CNR and did not affect the spatial resolution.

Hamstring muscle architecture assessed sonographically using wide field of view: A reliability study.

PURPOSE: To assess the intra-rater reliability of static wide field of view ultrasound to quantify the architectural characteristics of the hamstring muscles. METHODS: Twenty amateur male athletes were recruited. Their left hamstring muscles were assessed using static wide field of view ultrasound on two separate occasions. Static ultrasound images were acquired by a single sonographer using a 92mm linear transducer. The architectural characteristics (muscle length, fascicle length, pennation angle and muscle thickness) from two distinct locations of the bicep femoris long head and semimembranosus were evaluated. Muscle length and thickness of the bicep femoris short head and semitendinosus muscle were also evaluated. Intraclass correlation coefficient analyses were performed to determine the intra-rater reliability of the performed measurements. RESULTS: Both muscle (intraclass correlation coefficient = 0.99; standard error of measurement = 4.3 to 6.6mm) and fascicle (intraclass correlation coefficient = 0.92 to 0.98; standard error measurement = 1.1 to 2.4mm) length were measured with excellent intra-rater reliability. Muscle thickness was measured with excellent reliability (intraclass correlation coefficient = 0.9 to 0.96; standard error of measurement = 0.91mm to 1.4mm) for all hamstring muscles except for the proximal segments of the bicep femoris short head (intraclass correlation coefficient = 0.85; standard error of measurement = 0.84mm) and semitendinosus (intraclass correlation coefficient = 0.88; standard error of measurement = 0.82mm), which were measured with good reliability. Pennation angle was measured with good reliability (intraclass correlation coefficient = 0.77 to 0.87; standard error of measurement = 1 to 1.6°). CONCLUSION: The architectural characteristics of the hamstring muscles of male amateur athletes can be reliably quantified using static wide field of view ultrasound.

Justification of CT practices across Europe: results of a survey of national competent authorities and radiology societies.

OBJECTIVES: Published literature on justification of computed tomography (CT) examinations in Europe is sparse but demonstrates consistent sub-optimal application. As part of the EU initiated CT justification project, this work set out to capture CT justification practices across Europe. METHODS: An electronic questionnaire consisting of mostly closed multiple-choice questions was distributed to national competent authorities and to presidents of European radiology societies in EU member states as well as Iceland, Norway, Switzerland, and the UK (n = 31). RESULTS: Fifty-one results were received from 30 European countries. Just 47% (n = 24) stated that advance justification of individual CT examinations is performed by a medical practitioner. Radiologists alone mostly (n = 27, 53%) perform daily justification of CT referrals although this is a shared responsibility in many countries. Imaging referral guidelines are widely available although just 13% (n = 6) consider them in daily use. Four countries (Cyprus, Ireland, Sweden, UK) reported having them embedded within clinical decision support systems. Justification of new practices with CT is mostly regulated (77%) although three countries (Belgium, Iceland and Portugal) reported not having any national system in place for generic justification. Health screening with CT was reported by seven countries as part of approved screening programmes and by eight countries outside. When performed, CT justification audits were reported to improve CT justification rates. CONCLUSIONS: CT justification practices vary across Europe with less than 50% using advance justification and a minority having clinical decision support systems in place. CT for health screening purposes is not currently widely used in Europe.

Education and training in radiation protection in Europe: an analysis from the EURAMED rocc-n-roll project.

BACKGROUND: A Strengths, weaknesses, opportunities and threats analysis was performed to understand the status quo of education and training in radiation protection (RP) and to develop a coordinated European approach to RP training needs based on stakeholder consensus and existing activities in the field. Fourteen team members represented six European professional societies, one European voluntary organisation, two international healthcare organisations and five professions, namely: Medical Physicists; Nuclear Medicine Physicians; Radiologists; Radiation Oncologists and Radiographers. Four subgroups analysed the "Strengths", "Weaknesses", "Opportunities" and "Threats" related to E&T in RP developed under previous European Union (EU) programmes and on the Guidelines on Radiation Protection Education and Training of Medical Professionals in the EU. RESULTS: Consensus agreement identified four themes for strengths and opportunities, namely: (1) existing structures and training recommendations; (2) RP training needs assessment and education & training (E&T) model(s) development; (3) E&T dissemination, harmonisation, and accreditation; (4) financial supports. Weaknesses and Threats analysis identified two themes: (1) awareness and prioritisation at a national/global level and (2) awareness and prioritisation by healthcare professional groups and researchers. CONCLUSIONS: A lack of effective implementation of RP principles in daily practice was identified. EuRnR strategic planning needs to consider processes at European, national and local levels. Success is dependent upon efficient governance structures and expert leadership. Financial support is required to allow the stakeholder professional agencies to have sufficient resources to achieve a pan European radiation protection training network which is sustainable and accredited across multiple national domains.

Automated vetting of radiology referrals: exploring natural language processing and traditional machine learning approaches.

BACKGROUND: With a significant increase in utilisation of computed tomography (CT), inappropriate imaging is a significant concern. Manual justification audits of radiology referrals are time-consuming and require financial resources. We aimed to retrospectively audit justification of brain CT referrals by applying natural language processing and traditional machine learning (ML) techniques to predict their justification based on the audit outcomes. METHODS: Two human experts retrospectively analysed justification of 375 adult brain CT referrals performed in a tertiary referral hospital during the 2019 calendar year, using a cloud-based platform for structured referring. Cohen's kappa was computed to measure inter-rater reliability. Referrals were represented as bag-of-words (BOW) and term frequency-inverse document frequency models. Text preprocessing techniques, including custom stop words (CSW) and spell correction (SC), were applied to the referral text. Logistic regression, random forest, and support vector machines (SVM) were used to predict the justification of referrals. A test set (300/75) was used to compute weighted accuracy, sensitivity, specificity, and the area under the curve (AUC). RESULTS: In total, 253 (67.5%) examinations were deemed justified, 75 (20.0%) as unjustified, and 47 (12.5%) as maybe justified. The agreement between the annotators was strong (κ = 0.835). The BOW + CSW + SC + SVM outperformed other binary models with a weighted accuracy of 92%, a sensitivity of 91%, a specificity of 93%, and an AUC of 0.948. CONCLUSIONS: Traditional ML models can accurately predict justification of unstructured brain CT referrals. This offers potential for automated justification analysis of CT referrals in clinical departments.

The impact of ASiR-V on abdominal CT radiation dose and image quality - A phantom study.

INTRODUCTION: To investigate how ASiR-V and kVp changes in Computed tomography (CT) affect radiation dose and image quality, when using automatic tube current modulation (ATCM) for different sized phantoms. METHODS: A liver-phantom with two different liver inserts (QRM, Moehrendorf, Germany), with extension rings, representing fat, were additionally applied to the phantom to simulate patients of different sizes (small: 30cm diameter, medium: 35cm and large: 40cm). Abdominal scans were performed on a 256 slice CT scanner (GE Healthcare, Milwaukee, WI, USA), with consistent pitch (0.992), rotation time (0.5s), slice thickness (0.625mm) and collimation (80mm), while other parameters were varied (kVp: 80/100/120/140; Noise Index: 13/22; mA interval 80-720, ASiR-V: 30/60/100%). CTDI and DLP was recorded for each scan and image quality was assessed using objective metrics in predefined anatomic areas (HU and noise). Radiation dose and image quality metrics were compared between protocols. RESULTS: CTDI decreased by 80% from ASIR-V 30% to ASiR-V 100% for prescribed NI 13, and by 79% for the prescribed NI of 22. For 100% ASiR-V and a prescribed NI of 22 the CTDI remained the same regardless of phantom size for the different kVp settings. Pairwise comparison revealed significant differences in CTDI (p < 0.0001) for all combinations of prescribed NI and ASIR-V levels, except the difference between ASIR-V levels of 30 and 60%, with a prescribed NI of 13 (p = 0.124). When data from the three phantom sizes were combined, increasing ASIR-V from 30-100%, resulted in noise decreases of 22% for NI of 13 and by 8% for NI of 22. Notably, image quality in the low contrast area of the liver insert was impaired when the large phantom was scanned with 100% ASiR-V and either 80/100kVp (NI 22), because of the large reduction in tube current applied (down to 80 mA). CONCLUSION: Substantial radiation dose reductions (up to 80%) resulted from increasing ASiR-V levels. However, image quality deteriorates when 100% ASiR-V is applied due to low applied tube current by the ATCM.

Association of Plaque Inflammation With Stroke Recurrence in Patients With Unproven Benefit From Carotid Revascularization.

BACKGROUND AND OBJECTIVES: In pooled analyses of endarterectomy trials for symptomatic carotid stenosis, several subgroups experienced no net benefit from revascularization. The validated symptomatic carotid atheroma inflammation lumen-stenosis (SCAIL) score includes stenosis severity and inflammation measured by PET and improves the identification of patients with recurrent stroke compared with lumen-stenosis alone. We investigated whether the SCAIL score improves the identification of recurrent stroke in subgroups with uncertain benefit from revascularization in endarterectomy trials. METHODS: We did an individual-participant data pooled analysis of 3 prospective cohort studies (Dublin Carotid Atherosclerosis Study [DUCASS], 2008-2011; Biomarkers and Imaging of Vulnerable Atherosclerosis in Symptomatic Carotid Artery Disease [BIOVASC], 2014-2018; Barcelona Plaque Study, 2015-2018). Eligible patients had a recent nonsevere (modified Rankin Scale score ≤3) anterior circulation ischemic stroke/TIA and ipsilateral mild carotid stenosis (<50%); ipsilateral moderate carotid stenosis (50%-69%) plus at least 1 of female sex, age <65 years, diabetes mellitus, TIA, or delay >14 days to revascularization; or monocular loss of vision. Patients underwent coregistered carotid 18F-fluorodeoxyglucosePET/CT angiography (≤7 days from inclusion). The primary outcome was 90-day ipsilateral ischemic stroke. Multivariable Cox regression modeling was performed. RESULTS: We included 135 patients. All patients started optimal modern-era medical treatment at admission, and 62 (45.9%) underwent carotid revascularization (36 within the first 14 days and 26 beyond). At 90 days, 18 (13.3%) patients had experienced at least 1 stroke recurrence. The risk of recurrence increased progressively according to the SCAIL score (0.0% in patients scoring 0-1, 15.1% scoring 2-3, and 26.7% scoring 4-5; p = 0.04). The adjusted (age, smoking, hypertension, diabetes, carotid revascularization, antiplatelets and statins) hazard ratio for ipsilateral recurrent stroke per 1-point SCAIL increase was 2.16 (95% CI 1.32-3.53; p = 0.002). A score ≥2 had a sensitivity of 100% for recurrence. DISCUSSION: The SCAIL score improved the identification of early recurrent stroke in subgroups who did not experience benefit in endarterectomy trials. Randomized trials are needed to test whether a combined stenosis-inflammation strategy will improve selection for carotid revascularization when benefit is currently uncertain. CLASSIFICATION OF EVIDENCE: This study provides Class II evidence that, in patients with recent anterior circulation ischemic stroke who do not benefit from carotid revascularization, the SCAIL score accurately distinguishes those at risk for recurrent ipsilateral ischemic stroke.

Exploring the translational challenge for medical applications of ionising radiation and corresponding radiation protection research.

BACKGROUND: Medical applications of ionising radiation and associated radiation protection research often encounter long delays and inconsistent implementation when translated into clinical practice. A coordinated effort is needed to analyse the research needs for innovation transfer in radiation-based high-quality healthcare across Europe which can inform the development of an innovation transfer framework tailored for equitable implementation of radiation research at scale. METHODS: Between March and September 2021 a Delphi methodology was employed to gain consensus on key translational challenges from a range of professional stakeholders. A total of three Delphi rounds were conducted using a series of electronic surveys comprised of open-ended and closed-type questions. The surveys were disseminated via the EURAMED Rocc-n-Roll consortium network and prominent medical societies in the field. Approximately 350 professionals were invited to participate. Participants' level of agreement with each generated statement was captured using a 6-point Likert scale. Consensus was defined as median ≥ 4 with ≥ 60% of responses in the upper tertile of the scale. Additionally, the stability of responses across rounds was assessed. RESULTS: In the first Delphi round a multidisciplinary panel of 20 generated 127 unique statements. The second and third Delphi rounds recruited a broader sample of 130 individuals to rate the extent to which they agreed with each statement as a key translational challenge. A total of 60 consensus statements resulted from the iterative Delphi process of which 55 demonstrated good stability. Ten statements were identified as high priority challenges with ≥ 80% of statement ratings either 'Agree' or 'Strongly Agree'. CONCLUSION: A lack of interoperability between systems, insufficient resources, unsatisfactory education and training, and the need for greater public awareness surrounding the benefits, risks, and applications of ionising radiation were identified as principal translational challenges. These findings will help to inform a tailored innovation transfer framework for medical radiation research.