INTRODUCTION:The Pfirrmann grading system is widely used for assessing degenerative disc disease (DDD) on T2-weighted MRI but is criticised for its subjectivity. This study evaluates inter-rater reliability between radiologists and orthopaedic surgeons using this system. METHODS:A retrospective review of 60 lumbar spine MRI scans. Four radiologists and four orthopaedic surgeons (two consultants, two specialist registrars per group) independently graded five intervertebral discs per scan using both the 5-level and 8-level Pfirrmann grading systems. Grading was repeated after two months to assess intra-rater reliability. RESULTS:The highest inter-rater agreement was observed among orthopaedic consultants, with quadratic weighted kappa values of 0.89 (95 % CI: 0.86-0.92) and 0.97 (95 % CI: 0.96-0.98) for the 5- and 8-level grading systems, respectively. Overall agreement across all assessors using the 5-level system was good according to Krippendorff's alpha (ordinal) of 0.67 (95 % CI: 0.63-0.72) and Gwet's AC2 (quadratic) of 0.67 (95 % CI: 0.64-0.71).In contrast, Fleiss's kappa indicated only fair agreement overall, with a coefficient of 0.37 (95 % CI: 0.27-0.47). Radiology consultants achieved the highest intra-rater agreement (76 %) on reassessment when using the 5-level grading system, although they also demonstrated notable grading discrepancies. CONCLUSION:This study found that variability exists across assessor groups when comparing inter-rater reliability between radiologists and orthopaedic surgeons using the Pfirrmann grading system for lumbar DDD. This highlights the need for standardised grading and the potential role of quantitative MRI biomarkers to improve reliability.

BACKGROUND AND PURPOSE: Lumbar disc herniation, potentially leading to nerve root compression and cauda equina syndrome, is typically evaluated using MR imaging. However, the limited availability of MR imaging outside regular hours in certain health care systems poses considerable challenges. This purpose of this study was to prospectively evaluate the diagnostic accuracy of an optimized CT lumbar spine protocol as a potential alternative to MR imaging in assessing suspected neural compression. MATERIALS AND METHODS: Patients presenting to the emergency department with suspected cauda equina syndrome or acute radicular symptoms secondary to lumbar disc herniation referred for MR imaging were prospectively enrolled for an additional CT optimized to assess spinal stenosis. An expert radiologist, blinded to clinical data, graded canal stenosis at each lumbar level on CT. The same grading process was applied to MR imaging after a 4-week interval to maintain blinding. RESULTS: Fifty-nine individuals were included in the final analysis. In 22 (39%) cases, no significant stenosis was identified. In a further 22 (37%) cases, disc pathology was identified that was managed conservatively. Thirteen (22%) individuals proceeded to urgent surgical decompression. In 1 (2%) instance, an alternative diagnosis was identified. Compared with MR imaging, the sensitivity, specificity, and positive and negative predictive values for CT in detecting disc pathology in patients presenting with symptoms suggestive of acute neural compression were 97% (95% CI, 82%-99%), 97% (95% CI, 83%-99%), 97% (95% CI, 92%-99%), and 97% (95% CI, 83%-99%), respectively. CT accurately identified all cases requiring urgent decompression. CONCLUSIONS: CT accurately predicted MR imaging findings in patients with suspected cauda equina and nerve root compression, demonstrating its utility as an adjunct tool for patient triage in emergency settings with limited MR imaging access. This protocol could enhance the allocation of emergency resources by appropriately selecting patients for emergent MR imaging.

To evaluate the performance of state-of-the-art AI algorithms, in particular Generative Adversarial Networks (GANs), and their potential use in Irish Radiology in creating synthetic cross-sectional imaging.

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. To define and validate the safety, radiation dose and image quality of a low-dose CTPA protocol optimised for pregnancy. 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. 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

Epilepsy is a condition which affects more than 40,000 people in Ireland. Currently the gold standard for diagnosing epilepsy is an Electroencephalogram (EEG), complimented with an MRI of the brain. In the Mater hospital patients referred for query epilepsy are routinely scanned on a 3.0 T MRI scanner, however due to large waiting lists and lack of availability this is not always possible and patients are scanned on the 1.5 T scanner. Clinical staff noted longer scan times on the 3.0 T although image quality is adequate on both scanners.

BACKGROUND:Prostate cancer ranks among the most prevalent cancers affecting men globally. While conventional MRI serves as a diagnostic tool, its extended acquisition time, associated costs, and strain on healthcare systems, underscore the necessity for more efficient methods. The emergence of AI-acceleration in prostate MRI offers promise to mitigate these challenges.METHODS:A systematic review of studies looking at AI-accelerated prostate MRI was conducted, with a focus on acquisition time along with various qualitative and quantitative measurements.RESULTS:Two primary findings were observed. Firstly, all studies indicated that AI-acceleration in MRI achieved notable reductions in acquisition times without compromising image quality. This efficiency offers potential clinical advantages, including reduced scan durations, improved scheduling, diminished patient discomfort, and economic benefits. Secondly, AI demonstrated a beneficial effect in reducing or maintaining artefact levels in T2-weighted images despite this accelerated acquisition time. Inconsistent results were found in all other domains, which were likely influenced by factors such as heterogeneity in methodologies, variability in AI models, and diverse radiologist profiles. These variances underscore the need for larger, more robust studies, standardization, and diverse training datasets for AI models.CONCLUSION:The integration of AI-acceleration in prostate MRI thus far shows some promising results for efficient and enhanced scanning. These advancements may fill current gaps in early detection and prognosis. However, careful navigation and collaborative efforts are essential to overcome challenges and maximize the potential of this innovative and evolving field.ADVANCES IN KNOWLEDGE:This article reveals overall significant reductions in acquisition time without compromised image quality in AI-accelerated prostate MRI, highlighting potential clinical and diagnostic advantages.

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.

Objective: The purpose of this study was to evaluate the technical success and complication rates of image-guided lumbar puncture (IGLP) and to evaluate for differences in approach employed to help establish the optimum technique. Methods: A retrospective search of the hospital picture archiving and communications system was performed to identify all IGLPs that had taken place over a 5-year period. Radiology reports and the electronic medical record were examined to identify technical parameters and complications associated with each procedure. Results: The technical success rate was 96% (219/228). 69.4% (n = 161) had a previously failed bedside attempt. The rate of complications was 0.01% (n = 2). No major complications were observed. There was no difference in the rates of failure (2.4% vs 3.6%, p = 0.68) or complications (0.008% vs 0.012%, p = 1) between interlaminar and interspinous approaches. Conclusion: IGLP is a safe procedure with a high rate of technical success. Where a difficult bedside attempt is anticipated, it is reasonable to forego this and proceed directly to IGLP. Advances in knowledge: : This paper helps to confirm what is already assumed about a common radiological procedure. This is important as there has been a shift from bedside technique to most lumbar punctures being performed via image guidance.

Identification and re-identification are two major security and privacy threats to medical imaging data. De-identification in DICOM medical data is essential to preserve the privacy of patients’ Personally Identifiable Information (PII) and requires a systematic approach. However, there is a lack of sufficient detail regarding the de-identification process of DICOM attributes, for example, what needs to be considered before removing a DICOM attribute. In this paper, we first highlight and review the key challenges in the medical image data de-identification process. In this paper, we develop a two-stage de-identification process for CT scan images available in DICOM file format. In the first stage of the de-identification process, the patient’s PII—including name, date of birth, etc., are removed at the hospital facility using the export process available in their Picture Archiving and Communication System (PACS). The second stage employs the proposed DICOM de-identification tool for an exhaustive attribute-level investigation to further de-identify and ensure that all PII has been removed. Finally, we provide a roadmap for future considerations to build a semi-automated or automated tool for the DICOM datasets de-identification.

Multi-detector computed tomography (MDCT) is superior in fracture detection than conventional radiography; however, dose is increased. Cone-beam computed tomography (CBCT) offers higher spatial resolution and lower dose than MDCT. Manufacturers offer an ultra-low-dose algorithm. This study compares the diagnostic accuracy of the ultra-low-dose CBCT (ULDCBCT) with that of the standard-dose CBCT (SDCBCT). In total, 64 patients were scanned with both the SDCBCT and the ULDCBCT protocols. Both studies were reported by two consultant radiologists with fellowship training in emergency radiology separated in time. The reporter recorded a diagnosis of fracture or normal and diagnostic confidence using a 5-point Likert scale. The gold standard was taken as the SDCBCT. Reporters were blinded to the indication and the SDCBCT report. Cases of discrepancy were resolved by consensus. There were 34 fractures and 30 cases had no fracture. Several fractures were missed using the UDCBCT, and there were also several cases of overdiagnosis. ULD was inferior to SD for fracture diagnosis (p < 0.00001). The diagnostic accuracy of ULDCBCT was 82.8% (75.1–88.9 CI). The diagnostic accuracy of plain radiograph was 64% (55.1–75.7% CI). Diagnostic confidence was reduced; the mean confidence for SDCBCT was 4.68 vs 4.12 for ULDCBCT (p < 0.001). The Kappa for interobserver agreement was 0.6. ULDCBCT is inferior to SDCBCT in fracture detection and confidence is reduced. For diagnostic studies, the standard dose should be used.

PURPOSE:In excess of 100 million procedures using iodinated radio-contrast media are conducted each year. There is a common misunderstanding regarding the links between allergy to iodinated substances and the risk of allergic reaction to intravenous iodinated contrast agents. These perceived risks are managed via administration of corticosteroids or avoidance of iodinated contrast altogether.METHODS:An extensive review of published literature on scientific databases and international guidelines was conducted in order to inform the research question. A questionnaire was formulated and distributed to hospital doctors in four tertiary centres. Within this questionnaire, hospital doctors were presented with six different scenarios of bona fide allergy to iodinated substances (e.g. shellfish) and asked to select the treatment response option which they deemed to be the most suitable from a choice of three (standard contrast scan/delay scan with pre-medication/change to non-contrast scan).RESULTS:Eighty-seven questionnaire responses were received. Contrast (standard protocol) was the most appropriate regimen in the setting of all the listed allergies. This was identified correctly by 76%, 69%, 44%, 32%, 18% and 14% for kiwi, fish, poly-food, shellfish, betadine and tincture of iodine allergies, respectively.CONCLUSIONS:There is a lack of understanding amongst local junior medical staff regarding administration of iodinated contrast media to patients with a history of allergy to iodinated substances. These misconceptions may potentiate the unnecessary usage of pre-medication and ordering of non-contrast scans in the setting of a gold-standard enhanced scan. Findings from this study suggest that there is a need for future education efforts targeted during the basic specialty training stage.

Background:Limited magnetic resonance (MR) pulse sequences facilitate lumbosacral nerve imaging with acceptable image quality. This study aimed to evaluate the impact of parameter modification for Diffusion Weighted Image (DWI) using Readout Segmentation of Long Variable Echo-trains (RESOLVE) sequence with opportunities for improving the visibility of lumbosacral nerves and image quality.Methods:Following ethical approval and acquisition of informed consent, imaging of an MR phantom and twenty healthy volunteers (n=20) was prospectively performed with 3T MRI scanner. Acquired sequences included standard two-dimensional (2D) turbo spin echo sequences and readout-segmented echo-planar imaging (EPI) DWI-RESOLVE using three different b-values b-50, b-500 and b-800 s/mm2. Signal-to-noise ratio (SNR), apparent diffusion coefficient (ADC) and nerve size were measured. Two musculoskeletal radiologists evaluated anatomical structure visualisation and image quality. Quantitative and qualitative findings for healthy volunteers were investigated for differences using Wilcoxon signed-rank and Friedman tests, respectively. Inter and intra-observer agreement was determined with κ statistics.Results:Phantom images revealed higher SNR for images with low b-values with 206.1 (±10.9), 125.1 (±45.2) and 59.2 (±17.8) for DWI-RESOLVE images acquired at b50, b500 and b800, respectively. Comparable results were found for SNR, ADC and nerve size across normal right and left sided for healthy volunteer images. The SNR findings for b-50 images were higher than b-500 and b-800 images for healthy volunteer images. The qualitative findings ranked images acquired using b-50 and b-500 images significantly higher than corresponding b-800 images (P<0.05). Inter and intra-observer agreements for evaluation across all b-values ranged from 0.59 to 0.81 and 0.83 to 0.92, respectively.Conclusions:The modified DWI-RESOLVE images facilitated visualization of the normal lumbosacral nerves with acceptable image quality, which support the clinical applicability of this sequence.

Epidural steroid injections (ESIs) play an important role in the multifaceted management of neck and back pain. Corticosteroid preparations used in ESIs may be considered “particulate” or “non-particulate” based on whether they form a crystalline suspension or a soluble clear solution, respectively. In the past two decades, there have been reports of rare but severe and permanent neurological complications as a result of ESI. These complications have principally occurred with particulate corticosteroid preparations when using a transforaminal injection technique at cervical or thoracic levels, and only rarely in the lumbosacral spine. As a result, some published clinical guidelines and recommendations have advised against the use of particulate corticosteroids for transforaminal ESI, and the FDA introduced a warning label for injectable corticosteroids regarding the risk of serious neurological adverse events. There is growing evidence that the efficacy of non-particulate corticosteroids for pain relief and functional improvement after ESI is non-inferior to particulate agents, and that non-particulate injections almost never result in permanent neurological injury. Despite this, particulate corticosteroids continue to be routinely used for transforaminal epidural injections. More consistent clinical guidelines and societal recommendations are required alongside increased awareness of the comparative efficacy of non-particulate agents among specialists who perform ESIs. The current role for particulate corticosteroids in ESIs should be limited to caudal and interlaminar approaches, or transforaminal injections in the lumbar spine only if initial non-particulate ESI resulted in a significant but short-lived improvement.

Neuroradiologists at MMUH have been concerned with inconsistencies in brain CT image quality received from the various scanners and hospitals. Our study aimed to develop an objective method of measuring low contrast detectability (LCD) in CT, identify which combination of CT acquisition parameters maximises LCD and to investigate the variation in imaging protocols for suspected acute stroke at different institutions in the regional hospital network.

Purpose: To date, the majority of chest imaging studies in COVID-19 pneumonia have focused on CT. Evidence for the utility of chest radiographs (CXRs) in this population is less robust. Our objectives were to develop a systematic approach for reporting likelihood of COVID-19 pneumonia on CXRs, to measure the interobserver variability of this approach and to evaluate the diagnostic performance of CXRs compared to real-time reverse transcription polymerase chain reaction (RT-PCR). Method: Retrospective review of patients suspected of having COVID-19 pneumonia who attended our emergency department and underwent both CXR and a RT-PCR were included. Two radiologists reviewed the CXRs, blind to the RT-PCR, and classified them according to a structured reporting template with five categories (Characteristic, High Suspicion, Indeterminate, Unlikely and Normal) which we devised. For analysis of diagnostic accuracy, Characteristic and High Suspicion CXRs were considered positive and the remaining categories negative. Concordance between the two assessors was also measured. Results: Of 582 patients (51 +/- 20 years), 143/582 (24.6 %) had a positive RT-PCR. The absolute concordance between the two assessors was 71.1 % (414/582) with a Fleiss-Cohen-weighted Cohen's kappa of 0.81 (95 % confidence interval, 0.78-0.85). A patient with a positive CXR had an 88 % (95 % CI 80-96 %) probability of having a positive RT-PCR during a period of high incidence, early in the COVID-19 pandemic. Conclusion: Using a structured approach, a positive CXR had a high likelihood of predicting a positive RT-PCR, with good interrater reliability. CXRs can be useful in identifying new cases of COVID-19.

HomeRadiologyVol. 300, No. 3 PreviousNext Reviews and CommentaryFree AccessPerspectivesRadiology and the Climate Crisis: Opportunities and Challenges—Radiology In TrainingBryan W. Buckley , Peter J. MacMahonBryan W. Buckley , Peter J. MacMahonAuthor AffiliationsFrom the Department of Radiology, Mater Misericordiae University Hospital, Eccles Street, Dublin 7, Ireland.Address correspondence to B.W.B. (e-mail: [email protected]).Bryan W. Buckley Peter J. MacMahonPublished Online:Jul 13 2021https://doi.org/10.1148/radiol.2021210851MoreSectionsPDF ToolsImage ViewerAdd to favoritesCiteTrack CitationsPermissionsReprints ShareShare onFacebookTwitterLinked In Dr Bryan Buckley is a third-year resident at the Mater Misericordiae University Hospital in Dublin, Ireland. He is a recipient of the 2019 Royal College of Surgeons Ireland Faculty of Radiologists Publication Award. His research interests include environmental sustainability, artificial intelligence, and medical education.Download as PowerPointOpen in Image Viewer SummaryRadiology trainees have an important role to play in advancing more sustainable and environmentally conscious radiology practices through research, education, and local advocacy.IntroductionThe COVID-19 pandemic continues to challenge our perspective of “normal” within every health care system around the world. The willingness to adapt and rapidly change normal practices has been a crucial component of our response to the pandemic. Within radiology specifically this has been no different, with drastic changes to some areas of practice, including remote reporting, new services aimed specifically at the needs of patients with COVID-19, and even the redeployment of radiology staff. With vaccination programs progressing worldwide, there is now hope that an end is in sight. The ability of health care and radiology to adapt, as it has over the past year, must be harnessed for the next challenge to world health—the climate crisis. As radiology trainees, we must lead in pressing the issue.Energy-intensive Health CareThe contribution of health care activity to global greenhouse gas emission is substantial. If the health care sectors of the United States, Canada, Australia, and England were combined and ranked as an independent nation, they would be estimated to be the seventh largest emitter of greenhouse gases in the world (1). Specifically within the United States, estimation of health care contribution to the overall greenhouse gas emissions was estimated at 10% in 2013 (2).With the increasing awareness of the impact of human activity on the environment, there has been a noticeable societal shift toward a demand for environmentally sustainable business practices. Research carried out in 2015 in the United Kingdom revealed that 92% of the public believed it is important for the health system to work in a more sustainable way, with one in four believing it should be a top priority (up from 19% 2 years prior) (3). Anesthesiology and surgery have led in the field of sustainability within medicine. Within radiology specifically, there has been a surprising lack of research on sustainability, as technology is energy-intensive and plays a substantial role in our specialty.The largest contributors to the energy usage within the radiology department are large advanced diagnostic imaging equipment (ie, those used with MRI, CT, US, and nuclear medicine). MRI has the largest energy consumption when production and in-use phases are considered; the energy used for each individual study performed with an MRI scanner is comparable to that used when cooling a three-bedroom house with central air conditioning for 1 day or the desalination of 7000 gallons of fresh water (4). US was demonstrated to use one-twentieth of the overall energy used with either CT or MRI. Even when imaging equipment is not in active use or is in a nonproductive idle state, it continues to require energy. For example, approximately two-thirds of energy usage for CT occurs during this nonproductive idle state, indicating a substantial energy inefficiency (5). Elsewhere within the radiology department, an analysis of 32 radiology reporting stations demonstrated overall power consumption of 53 170 kWh per annum, or the equivalent of the annual energy consumption of 12 family households in Switzerland (6). Other devices that are regularly used within a radiology department, from desktop computers to air conditioning systems, also contribute to the overall environmental impact of a service.Although every imaging study performed must be clinically justified, it must also be performed as an efficient allocation of a limited resource. Models such as “utilization management” have been proposed as a systemic approach to evaluating the appropriateness of clinical care and achieving best possible patient outcomes by using the most appropriate health resources. However, these only examine economic impacts. In choosing any one modality over another, consideration of the ecologic impact should also factor into decision making around the allocation of these resources.The Ecologic Cost of Big DataOne overlooked aspect in assessing the environmental impact of the radiology services has been the rapid growth in the need for storage in radiologic data centers. As of 2020, there were 28.5 million individual imaging studies in the Irish national radiologic data storage system (the National Integrated Medical Imaging System, or NIMIS). This amounts to over 1 petabyte of radiologic data, with an approximate growth in data storage of 23% every year over the past 5 years. Fifty-three percent of that data is dominated by CT studies. This is reflected in the increase of the average size of a CT study stored in the National Integrated Medical Imaging System as measured in megabytes. In 2011, the average size was 66 megabytes but has grown year-on-year by approximately 20%, with the current average size of a CT study now standing at 160 megabytes. This reflects the increasing complexity of the average CT study now performed, with more thin-section reconstructions, multiple reformats, and other postprocessing to create additional imaging series. The storage and transmission of large volumes of medical imaging requires energy.Data storage servers and cooling systems account for the greatest shares of direct electricity use within a data center, approximately 86% of the energy usage (7). Total water consumption in United States data centers was estimated in 2014 at 626 billion liters of water per year (over 75% directly related to electricity generation), with this estimated at the time to grow to 660 billion liters of water per year in 2020 (7). Data centers across the world may emit as much carbon dioxide as the global aviation industry (8). Furthermore, with the increasing interest and expectations around artificial intelligence, particularly within radiology as a specialty, the need for higher computing power is only going to grow. The computational effort required to solve problems increases exponentially with the size of data sets, so with an ultimate goal of continuous-learning artificial intelligence models, this will not be solved with the addition of more hardware (9). Further research and promotion of more computationally efficient algorithms, as well as hardware requiring less energy, is needed (10).Aside from the initial environmental costs associated with putting such infrastructure in place, every chest radiograph or brain CT scan that is stored in a data center (including the inherent need for duplicate copies and redundancy) places an energy demand on that system. While any one individual study likely has miniscule energy requirements, even for very long-term storage, any study or part of a study that may serve no future purpose to the health care system creates a needless carbon footprint. For most health care systems, such as ours in Ireland, these data are often retained indefinitely. If the volumes and size of data that is required to be maintained continues to grow at current rates, this may need to be addressed with clear guidelines for the minimization of excess or redundant data that is of no perceived future benefit. One such example would be the multiple scans performed during CT perfusion imaging and CT-guided procedures or the multiplanar reconstructions that are created for ease of reviewing by the radiologist. These data or some part of them could be dispensed with at some defined point in time and the carbon footprint of a service reduced with no impact on future patient care while providing cost savings to the health care system.Greening RadiologyWhile medicine as a whole may be slow to adopt sustainable business practices and respond to societal shifts and patients’ expectations in this regard, radiology is uniquely placed to contribute due to its inherent technology base. These changes must be driven at a local level and, as trainees, we can play our part in this regard through advocacy and education. All of the factors contributing to the specialty’s environmental impact have not yet been considered, and more research is needed, specifically on the environmental impacts of data storage and processing. The COVID-19 pandemic has demonstrated that health care systems and radiology departments are adaptable and can reconfigure to deal with crises. This same ingenuity will be needed to overcome the climate crisis.Within radiology, we are well accustomed to the “as low as reasonably achievable” principle, or ALARA, which dictates that the radiation exposure to a patient undergoing a particular study or procedure should be as low as reasonably possible. A similar approach should be taken to environmental impact where appropriate. For example, when it is agreed that an ovarian cyst can be followed with US rather than MRI (the former of which uses one-twentieth of the energy required compared with that needed for a single MRI examination), this optimizes the ecologic as well as the economic impact without affecting patient outcomes.Similarly, a debate around data creation and storage is warranted. Not all data are created equal. As a specialty, radiology is arguably in its infancy when it comes to data creation. Limiting the excess data that is routinely created and often stored indefinitely makes sense from both an economic and ecologic perspective. The recent interest in abbreviated MRI protocols that limit “excess” sequences in answering a clinical question are very welcomed in this regard. On the storage end, the multiple reconstructions and iterations of the raw data that are routinely created in CT imaging are unlikely to serve a clinical use in the future and do not need to be sent for data storage.Being comfortable with and aware of sustainable business practices will likely become an increasingly important factor in patient decision making and expectations. Considering the environmental impact of our decisions, making recommendations that limit carbon emissions, and advocating for business practices that can reduce them will improve our specialty and better serve our patients of the future.Disclosures of Conflicts of Interest: B.W.B. disclosed no relevant relationships. P.J.M. disclosed no relevant relationships.AcknowledgmentsThe authors express their gratitude to the staff at the National Integrated Medical Imaging System, or NIMIS, for their help in researching this article.References1. Sherman JD, MacNeill A, Thiel C. Reducing pollution from the health care industry. JAMA 2019;322(11):1043–1044. Crossref, Medline, Google Scholar2. Eckelman MJ, Sherman J. Environmental impacts of the U.S. health care system and effects on public health. PLoS One 2016;11(6):e0157014. Crossref, Medline, Google Scholar3. Public opinion survey 2015: Sustainability and the NHS, Public Health and Social Care system – Ipsos Mori survey. Public Health England. https://www.england.nhs.uk/greenernhs/wp-content/uploads/sites/51/2021/02/Sustainability-and-the-NHS-Public-opinion-survey-2015.pdf. Published March 2016.Accessed November 16, 2020. Google Scholar4. Martin M, Mohnke A, Lewis GM, Dunnick NR, Keoleian G, Maturen KE. Environmental Impacts of Abdominal Imaging: A Pilot Investigation. J Am Coll Radiol 2018;15(10):1385–1393. Crossref, Medline, Google Scholar5. Heye T, Knoerl R, Wehrle T, et al. The Energy Consumption of Radiology: Energy- and Cost-saving Opportunities for CT and MRI Operation. Radiology 2020;295(3):593–605. Link, Google Scholar6. Hainc N, Brantner P, Zaehringer C, Hohmann J. “Green Fingerprint” Project: evaluation of the power consumption of reporting stations in a radiology department. Acad Radiol 2020;27(11):1594–1600. Crossref, Medline, Google Scholar7. Shehabi A, Smith S, Sartor D, et al. United States Data Center Energy Usage Report. LBNL-1005775. Lawrence Berkeley National Laboratory,Berkeley, California. https://www.osti.gov/biblio/1372902/. Published 2016. Accessed November 16, 2020. Google Scholar8. Pearce F. Energy Hogs: Can World’s Huge Data Centers Be Made More Efficient? Yale Environment 360. https://e360.yale.edu/Features/Energy-Hogs-Can-Huge-Data-Centers-Be-Made-More-Efficient. Published April 3, 2018. Accessed January 10, 2021. Google Scholar9. Pianykh OS, Langs G, Dewey M, et al. Continuous learning AI in radiology: implementation principles and early applications. Radiology 2020;297(1):6–14. Link, Google Scholar10. Strubell E, Ganesh A, McCallum A. Energy and Policy Considerations for Deep Learning in NLP. Association for Computational Linguistics. https://www.aclweb.org/anthology/P19-1355/. Published 2019. Accessed November 16, 2020. Google ScholarArticle HistoryReceived: Apr 9 2021Revision requested: Apr 27 2021Revision received: May 6 2021Accepted: May 12 2021Published online: July 13 2021Published in print: Sept 2021 FiguresReferencesRelatedDetailsCited ByClimate Change and Radiology: Impetus for Change and a Toolkit for ActionMaura Brown, Julia Hyde Schoen, Jonathan Gross, Reed A. Omary, Kate Hanneman, 18 April 2023 | Radiology, Vol. 307, No. 4The evolving call to action for including climate change and environmental sustainability themes in health professional education: A scoping reviewMeagan E.Brennan, Diana L.Madden2023 | The Journal of Climate Change and Health, Vol. 9All Specialties in Radiology Must Address the Climate CrisisJonathan S. Gross, Cassandra L. Thiel, 8 February 2022 | Radiology, Vol. 303, No. 2Sustainability in interventional radiology: are we doing enough to save the environment?Pey LingShum, Hong KuanKok, JulianMaingard, KevinZhou, VivienneVan Damme, Christen D.Barras, Lee-AnneSlater, WinstonChong, Ronil V.Chandra, AshuJhamb, MarkBrooks, HamedAsadi2022 | CVIR Endovascular, Vol. 5, No. 1Accompanying This ArticleAuthor Interview: Radiology and the Climate Crisis: Opportunities and Challenges—Radiology In TrainingApr 11 2023Default Digital Object SeriesRecommended Articles Increasing Opportunities for Trainees to Engage in Global Health Radiology: Radiology In TrainingRadiology2021Volume: 300Issue: 2pp. E320-E322Cardiac Imaging Trends from 2010 to 2019 in the Medicare PopulationRadiology: Cardiothoracic Imaging2021Volume: 3Issue: 5Small Steps toward a More Sustainable and Energy-efficient Operation of MRIRadiology2023Volume: 307Issue: 4The Impact of the COVID-19 Pandemic on the Radiology Research Enterprise: Radiology Scientific Expert PanelRadiology2020Volume: 296Issue: 3pp. E134-E140External Factors That Influence the Practice of Radiology: Proceedings of the International Society for Strategic Studies in Radiology MeetingRadiology2017Volume: 283Issue: 3pp. 845-853See More RSNA Education Exhibits Climate Change and Radiology: What Radiologists Need to KnowDigital Posters2022Pandemic Preparedness: Streamlining the Breast Imaging Patient Care and Teaching Experience During COVID-19Digital Posters2020Misplaced Gas — Sinister Finding in Septic Diabetics: A Pictorial Review of Emphysematous InfectionsDigital Posters2019 RSNA Case Collection Hydrogen peroxide ingestionRSNA Case Collection2020High Pressure Injection InjuryRSNA Case Collection2021Amoebic abscess RSNA Case Collection2020 Vol. 300, No. 3 Video SummaryMetrics Altmetric Score PDF download

Currently, there is much variation in the terminology used to describe groin pain in athletes. Several groups have attempted to reach consensus on nomenclature in this area. This article outlines the current status of groin pain nomenclature for the radiologist, highlighting inherent heterogeneity, recent attempts to reach a consensus, the need for a radiological consensus and why imprecise terminology should be avoided when reporting.

Non-contrast computed tomography (NCCT) of the brain is a critical tool in the investigation of suspected acute ischaemic stroke. The recognition of subtle differences in attenuation values between normal brain parenchyma and regions of ischaemic tissue may be crucial to accurate and timely diagnosis. Radiologists at MMUH have been concerned with inconsistencies in image quality received from the various scanners and hospitals. Our study aimed to investigate the variation in imaging protocols for suspected acute stroke at different institutions in the regional hospital network using an objective measure of low contrast detectability (LCD).

Mass casualty incidents (MCIs) create a large number of casualties in a short period of time. Diagnostic radiology plays an important role in major incident responses but is often underrepresented during major incident planning (MIP) and simulation. Surveys suggest radiologists are unfamiliar with their role during an MCI. We aimed to identify key topics for radiology MIP, familiarize radiologists with their role during an MCI and identify areas for future research. The terms “radiology” and “mass casualty incident” were entered into the advanced search builder on PubMed. Abstracts from this primary search were reviewed and papers selected for inclusion. Additional studies of interest were identified upon review of reference sections of relevant articles and from the related article tab on PubMed. MCI and trauma guidelines were reviewed. Key factors that caused issues during prior MCIs were identified including staff alert mechanisms, patient identification strategies, patient tracking, scan ordering and result communication. Limitations of local imaging resources and capacity should be identified and inform plans for the utilization of diagnostic radiology in the MCI setting. Simulation can help identify areas for improvement and familiarize staff with their roles. Further development of reliable MCI alert technology and patient identification strategies are needed as well as prospective validation of trauma CT selection criteria to identify patients who will benefit most from CT. Radiology should take part in MIP to address key issues encountered during prior MCIs and in MCI simulation to optimize major incident response.

Purpose To qualitatively assess the legibility of radiopaque patient identification stickers and their effect on image quality. These stickers are intended for use as a part of a patient registration and identification pack utilized in a mass casualty incident (MCI), to prevent errors in correlating patients with their diagnostic imaging and reports. Methods Four different prototype designs of stickers with radiopaque identification numbers which are legible on radiographs and CT were created. These were affixed to head and thorax phantoms and scanned using standard imaging protocols. Images were reviewed qualitatively for legibility and the presence of image degradation due to the radiopaque sticker materials using Likert scales by four radiologists and four emergency physicians. Results All four prototypes were confidently legible on forehead, shoulder and sternum on CT on topogram and reconstructed images. Sticker positioning over the temple resulted in unreliable legibility on topogram. All prototypes were confidently legible on shoulder and sternum on CT and radiographs. Significant image degradation was reported on radiographs with sticker position over the sternum. The preferred anatomic position was the forehead. Conclusion In a mass casualty incident, radiopaque patient identification stickers affixed to injured patients may help to ensure confidence in the correlation between patients and their imaging. Tested prototypes were found to be easily legible without substantial degradation of image quality. Preferred anatomical position and construction material was established. Consideration should be given to addition of such radiographic identity aides to MCI patient registration packs.