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Objectives: The environmental footprint of iodinated contrast agents (ICAs) and gadolinium-based contrast agents (GBCAs) is noteworthy. This study assesses: (1) patients' "green sensitivity" as measured by their acceptance in a sustainability study and (2) the resulting potential reduction of contrast residuals in wastewater., Materials and Methods: After ethical approval, participants scheduled for administration of ICAs or GBCAs for diagnostic purposes were enrolled in this prospective observational study from July 2022 to October 2023. They were asked to prolong their hospital stay by up to 60 min to collect their first urine in dedicated canisters, thereby measuring the recovery rates of ICAs and GBCAs as found/theoretical ratio of concentrations. Mann-Whitney U, χ 2 tests, and multivariable regression analysis were used., Results: Patients scheduled for contrast-enhanced CT or MRI (n = 455) were screened; 422 (92.7%) accepted to participate. We enrolled 212 patients administered with ICAs and 210 administered with GBCAs. The median recovery rate was 51.2% (interquartile range 29.2-77.9%) for ICAs and 12.9% (9.0-19.3%) for GBCAs. At multivariable analysis, a significant effect of patient age (ICAs, p = 0.001; GBCAs, p = 0.014), urine volume (p < 0.001 for both), and time interval from contrast administration to urine collection (p < 0.001 for both) on recovery rates was found for both contrast agents; injected contrast volume (p = 0.046) and saline flushing usage (p = 0.008) showed a significant effect only for ICAs., Conclusion: The high patient enrollment compliance (93%) and potential recovery rates of 51% (ICAs) and 13% (GBCAs) play in favor of sustainable practices in reducing the environmental footprint of contrast agents., Key Points: Question How many patients are willing to extend their stay in radiology by up to 60 min to help reduce the environmental impact of contrast agents? Findings Over 90% of screened patients agreed to extend their stay by up to 60 min and collect their urine in dedicated containers. Clinical relevance Patients demonstrated a high willingness to cooperate in reducing the environmental impact of contrast agents, allowing for a potential recovery of approximately 51% for iodinated and 13% for gadolinium-based contrast agents., (© 2024. The Author(s), under exclusive licence to European Society of Radiology.)

In order to assess the perceptions and expectations of the radiology staff about artificial intelligence (AI), we conducted an online survey among ESR members (January-March 2024). It was designed considering that conducted in 2018, updated according to recent advancements and emerging topics, consisting of seven questions regarding demographics and professional background and 28 AI questions. Of 28,000 members contacted, 572 (2%) completed the survey. AI impact was predominantly expected on breast and oncologic imaging, primarily involving CT, mammography, and MRI, and in the detection of abnormalities in asymptomatic subjects. About half of responders did not foresee an impact of AI on job opportunities. For 273/572 respondents (48%), AI-only reports would not be accepted by patients; and 242/572 respondents (42%) think that the use of AI systems will not change the relationship between the radiological team and the patient. According to 255/572 respondents (45%), radiologists will take responsibility for any AI output that may influence clinical decision-making. Of 572 respondents, 274 (48%) are currently using AI, 153 (27%) are not, and 145 (25%) are planning to do so. In conclusion, ESR members declare familiarity with AI technologies, as well as recognition of their potential benefits and challenges. Compared to the 2018 survey, the perception of AI's impact on job opportunities is in general slightly less optimistic (more positive from AI users/researchers), while the radiologist's responsibility for AI outputs is confirmed. The use of large language models is declared not only limited to research, highlighting the need for education in AI and its regulations. CRITICAL RELEVANCE STATEMENT: This study critically evaluates the current impact of AI on radiology, revealing significant usage patterns and clinical implications, thereby guiding future integration strategies to enhance efficiency and patient care in clinical radiology. KEY POINTS: The survey examines ESR member's views about the impact of AI on radiology practice. AI use is relevant in CT and MRI, with varying impacts on job roles. AI tools enhance clinical efficiency but require radiologist oversight for patient acceptance., (© 2024. The Author(s).)

Purpose: This study aimed to determine the accuracy of detecting ischemic core volume using computed tomography perfusion (CTP) in patients with suspected acute ischemic stroke compared to diffusion-weighted magnetic resonance imaging (DW-MRI) as the reference standard., Methods: This retrospective monocentric study included patients who underwent CTP and DW-MRI for suspected acute ischemic stroke. The ischemic core size was measured at DW-MRI. The detectability threshold volume was defined as the lowest volume detected by each method. Clinical data on revascularization therapy, along with the clinical decision that influenced the choice, were collected. Volumes of the ischemic cores were compared using the Mann-Whitney U test., Results: Of 83 patients who underwent CTP, 52 patients (median age 73 years, IQR 63-80, 36 men) also had DW-MRI and were included, with a total of 70 ischemic cores. Regarding ischemic cores, only 18/70 (26%) were detected by both CTP and DW-MRI, while 52/70 (74%) were detected only by DW-MRI. The median volume of the 52 ischemic cores undetected on CTP (0.6 mL, IQR 0.2-1.3 mL) was significantly lower (p < 0.001) than that of the 18 ischemic cores detected on CTP (14.2 mL, IQR 7.0-18.4 mL). The smallest ischemic core detected on CTP had a volume of 5.0 mL. Among the 20 patients with undetected ischemic core on CTP, only 10% (2/20) received thrombolysis treatment., Conclusions: CTP maps failed in detecting ischemic cores smaller than 5 mL. DW-MRI remains essential for suspected small ischemic brain lesions to guide a correct treatment decision-making., (© 2024. Italian Society of Medical Radiology.)

Introduction: Breast arterial calcifications (BAC) are common incidental findings on routine mammograms, which have been suggested as a sex-specific biomarker of cardiovascular disease (CVD) risk. Previous work showed the efficacy of a pretrained convolutional network (CNN), VCG16, for automatic BAC detection. In this study, we further tested the method by a comparative analysis with other ten CNNs., Material and Methods: Four-view standard mammography exams from 1,493 women were included in this retrospective study and labeled as BAC or non-BAC by experts. The comparative study was conducted using eleven pretrained convolutional networks (CNNs) with varying depths from five architectures including Xception, VGG, ResNetV2, MobileNet, and DenseNet, fine-tuned for the binary BAC classification task. Performance evaluation involved area under the receiver operating characteristics curve (AUC-ROC) analysis, F 1 -score (harmonic mean of precision and recall), and generalized gradient-weighted class activation mapping (Grad-CAM++) for visual explanations., Results: The dataset exhibited a BAC prevalence of 194/1,493 women (13.0%) and 581/5,972 images (9.7%). Among the retrained models, VGG, MobileNet, and DenseNet demonstrated the most promising results, achieving AUC-ROCs > 0.70 in both training and independent testing subsets. In terms of testing F 1 -score, VGG16 ranked first, higher than MobileNet (0.51) and VGG19 (0.46). Qualitative analysis showed that the Grad-CAM++ heatmaps generated by VGG16 consistently outperformed those produced by others, offering a finer-grained and discriminative localization of calcified regions within images., Conclusion: Deep transfer learning showed promise in automated BAC detection on mammograms, where relatively shallow networks demonstrated superior performances requiring shorter training times and reduced resources., Relevance Statement: Deep transfer learning is a promising approach to enhance reporting BAC on mammograms and facilitate developing efficient tools for cardiovascular risk stratification in women, leveraging large-scale mammographic screening programs., Key Points: • We tested different pretrained convolutional networks (CNNs) for BAC detection on mammograms. • VGG and MobileNet demonstrated promising performances, outperforming their deeper, more complex counterparts. • Visual explanations using Grad-CAM++ highlighted VGG16's superior performance in localizing BAC., (© 2024. The Author(s).)

Objectives: MRI-derived extracellular volume (ECV) allows characterization of myocardial changes before the onset of overt pathology, which may be caused by cancer therapy cardiotoxicity. Our purpose was to review studies exploring the role of MRI-derived ECV as an early cardiotoxicity biomarker to guide timely intervention., Materials and Methods: In April 2022, we performed a systematic search on EMBASE and PubMed for articles on MRI-derived ECV as a biomarker of cancer therapy cardiotoxicity. Two blinded researchers screened the retrieved articles, including those reporting ECV values at least 3 months from cardiotoxic treatment. Data extraction was performed for each article, including clinical and technical data, and ECV values. Pooled ECV was calculated using the random effects model and compared among different treatment regimens and among those who did or did not experience overt cardiac dysfunction. Meta-regression analyses were conducted to appraise which clinical or technical variables yielded a significant impact on ECV., Results: Overall, 19 studies were included. Study populations ranged from 9 to 236 patients, for a total of 1123 individuals, with an average age ranging from 12.5 to 74 years. Most studies included patients with breast or esophageal cancer, treated with anthracyclines and chest radiotherapy. Pooled ECV was 28.44% (95% confidence interval, CI, 26.85-30.03%) among subjects who had undergone cardiotoxic cancer therapy, versus 25.23% (95%CI 23.31-27.14%) among those who had not (p = .003)., Conclusion: A higher ECV in patients who underwent cardiotoxic treatment could imply subclinical changes in the myocardium, present even before overt cardiac pathology is detectable., Clinical Relevance Statement: The ability to detect subclinical changes in the myocardium displayed by ECV suggests its use as an early biomarker of cancer therapy-related cardiotoxicity., Key Points: • Cardiotoxicity is a common adverse effect of cancer therapy; therefore, its prompt detection could improve patient outcomes. • Pooled MRI-derived myocardial extracellular volume was higher in patients who underwent cardiotoxic cancer therapy than in those who did not (28.44% versus 25.23%, p = .003). • MRI-derived myocardial extracellular volume represents a potential early biomarker of cancer therapy cardiotoxicity., (© 2023. The Author(s).)

Objectives: Energy consumption and carbon emissions from medical equipment like CT/MRI scanners and workstations contribute to the environmental impact of healthcare facilities. The aim of this systematic review was to identify all strategies to reduce energy use and carbon emissions in radiology., Methods: In June 2023, a systematic review (Medline/Embase/Web of Science) was performed to search original articles on environmental sustainability in radiology. The extracted data include environmental sustainability topics (e.g., energy consumption, carbon footprint) and radiological devices involved. Sustainable actions and environmental impact in radiology settings were analyzed. Study quality was assessed using the QualSyst tool., Results: From 918 retrieved articles, 16 met the inclusion criteria. Among them, main topics were energy consumption (10/16, 62.5%), life-cycle assessment (4/16, 25.0%), and carbon footprint (2/16, 12.5%). Eleven studies reported that 40-91% of the energy consumed by radiological devices can be defined as "nonproductive" (devices "on" but not working). Turning-off devices during idle periods 9/16 (56.2%) and implementing workflow informatic tools (2/16, 12.5%) were the sustainable actions identified. Energy-saving strategies were reported in 8/16 articles (50%), estimating annual savings of thousand kilowatt-hours (14,180-171,000 kWh). Cost-savings were identified in 7/16 (43.7%) articles, ranging from US $9,225 to 14,328 per device. Study quality was over or equal the 80% of high-quality level in 14/16 (87.5%) articles., Conclusion: Energy consumption and environmental sustainability in radiology received attention in literature. Sustainable actions include turning-off radiological devices during idle periods, favoring the most energy-efficient imaging devices, and educating radiological staff on energy-saving practices, without compromising service quality., Relevance Statement: A non-negligible number of articles - mainly coming from North America and Europe - highlighted the need for energy-saving strategies, attention to equipment life-cycle assessment, and carbon footprint reduction in radiology, with a potential for cost-saving outcome., Key Points: • Energy consumption and environmental sustainability in radiology received attention in the literature (16 articles published from 2010 to 2023). • A substantial portion (40-91%) of the energy consumed by radiological devices was classified as "non-productive" (devices "on" but not working). • Sustainable action such as shutting down devices during idle periods was identified, with potential annual energy savings ranging from 14,180 to 171,000 kWh., (© 2024. The Author(s).)

Background: The FRAX® algorithm is a tool used to calculate the 10-year probability of fracture in patients with osteoporosis and is based the assessment of several risk factors. We assessed the performance and accuracy of the completion of the FRAX® anamnestic questionnaire by the radiographer without impact on the clinical workflow., Methodology: We evaluated the accuracy of fracture risk calculation by the radiographer using the FRAX® algorithm before and after specific training. A total of 100 women were enrolled in the study. The radiographer preliminarily administered the FRAX® questionnaire to all subjects before the execution of the DXA examination. After the end of the examination, a radiologist administered the questionnaire to the patient. Women were divided into two groups: group A (pre-training) and group B (post-training). The radiographer in group A completed the FRAX® questionnaire for the patients before training. For group B, the same radiographer completed the FRAX® questionnaire after training. The results of the FRAX® questionnaire completed by radiographer were compared with that completed by the referring physician., Results: Before training, radiographer's accuracy ranged from 92% (question 7, alcohol consumption) to 36% (question 6, secondary osteoporosis). After training, accuracy values improved substantially, ranging from 100% to 92%. Analysis of the absolute values of FRAX® showed that in the pre-training group data tended to be overestimated by the radiographer, with both major and fractures probabilities being significantly higher when assessed by the radiographer (12% and 5.8%, respectively). After the training, there was a marked decrease in the variation between the FRAX® data calculated by the radiographer and the radiologist., Conclusions: The accuracy of fracture risk calculation by the radiographer using the FRAX® algorithm is significantly improved after a specific training period. This study demonstrates the importance of dedicated training radiographers on the FRAX® algorithm., Competing Interests: Declaration of Competing Interest None., (Copyright © 2023 The Author(s). Published by Elsevier Inc. All rights reserved.)

Purpose: To evaluate myocardial status through the assessment of extracellular volume (ECV) calculated at computed tomography (CT) in patients hospitalized for novel coronavirus disease (COVID-19), with regards to the presence of pulmonary embolism (PE) as a risk factor for cardiac dysfunction., Method: Hospitalized patients with COVID-19 who underwent contrast-enhanced CT at our institution were retrospectively included in this study and grouped with regards to the presence of PE. Unenhanced and portal venous phase scans were used to calculate ECV by placing regions of interest in the myocardial septum and left ventricular blood pool. ECV values were compared between patients with and without PE, and correlations between ECV values and clinical or technical variables were subsequently appraised., Results: Ninety-four patients were included, 63/94 of whom males (67%), with a median age of 70 (IQR 56-76 years); 28/94 (30%) patients presented with PE. Patients with PE had a higher myocardial ECV than those without (33.5%, IQR 29.4-37.5% versus 29.8%, IQR 25.1-34.0%; p = 0.010). There were no correlations between ECV and patients' age (p = 0.870) or sex (p = 0.122), unenhanced scan voltage (p = 0.822), portal phase scan voltage (p = 0.631), overall radiation dose (p = 0.569), portal phase scan timing (p = 0.460), and contrast agent dose (p = 0.563)., Conclusions: CT-derived ECV could help identify COVID-19 patients at higher risk of cardiac dysfunction, especially when related to PE, to potentially plan a dedicated, patient-tailored clinical approach., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier B.V. All rights reserved.)

The potential enviromental impact of iodinated (ICAs) and gadolinium-based contrast agents (GBCAs) have recently come under scrutiny, considering the current nonselective wastewater treatment. However, their rapid excretion after intravenous administration could allow their potential recovery by targeting hospital sewage. The GREENWATER study aims to appraise the effective quantities of ICAs and GBCAs retrievable from patients' urine collected after computed tomography (CT) and magnetic resonance imaging (MRI) exams, selecting ICA/GBCA per-patient urinary excretion and patients' acceptance rate as study endpoints. Within a prospective, observational, single-centre, 1-year framework, we will enrol outpatients aged ≥ 18 years, scheduled to perform contrast-enhanced CT or MRI, willing to collect post-examination urine in dedicated canisters by prolonging their hospital stay to 1 h after injection. Collected urine will be processed and partially stored in the institutional biobank. Patient-based analysis will be performed for the first 100 CT and 100 MRI patients, and then, all analyses will be conducted on the pooled urinary sample. Quantification of urinary iodine and gadolinium will be performed with spectroscopy after oxidative digestion. The evaluation of the acceptance rate will assess the "environmental awareness" of patients and will aid to model how procedures to reduce ICA/GBCA enviromental impact could be adapted in different settings. Key points • Enviromental impact of iodinated and gadolinium-based contrast agents represents a growing point of attention.• Current wastewater treatment is unable to retrieve and recycle contrast agents.• Prolonging hospital stay may allow contrast agents retrieval from patients' urine.• The GREENWATER study will assess the effectively retrievable contrast agents' quantities.• The enrolment acceptance rate will allow to evaluate patients' "green sensitivity"., (© 2023. The Author(s).)

Background: Our purpose was to evaluate the correlations between right ventricular (RV) late gadolinium enhancement (LGE) at cardiac magnetic resonance (CMR) in patients with tetralogy of Fallot (ToF) scheduled for pulmonary valve replacement (PVR) and post-PVR functional data., Methods: We retrospectively reviewed ToF patients scheduled for PVR who underwent two CMR examinations at our institution, one before the procedure (CMR-0), including contrast-enhanced sequences, and one after the procedure (CMR-1). Functional left and RV data were obtained by segmenting short-axis stacks on both CMR examinations, and normalised variations were calculated by dividing differences between CMR-1 and CMR-0 by the intercurring time interval, whereas the RV scar burden was assessed on CMR-0 LGE sequences both semiquantitatively and quantitatively. Data were reported as median and interquartile range, differences were appraised with the Mann-Whitney U test, while correlations were assessed with Spearman's ρ., Results: Fifteen patients with a median age of 25 years (16-29), including 9 (60%) males, with a median time interval between CMR-0 and CMR-1 of 17 months (12-23), were retrospectively reviewed. The semiquantitative LGE score at CMR-0 was 7 (6-9), and LGE volume was 4.49 mL (3.70-5.78), covering 5.63% (4.92-7.00) of the RV. RV LGE score showed a moderate positive correlation with the normalised variation of RV stroke volume (ρ = 0.662, p = 0.007) and a borderline moderate positive correlation with the normalised variation of RV end-diastolic indexed volume (ρ = 0.513, p = 0.050)., Conclusions: The assessment of RV LGE before PVR may provide insights on post-PVR functional data, potentially facilitating a patient-tailored treatment pathway., (© 2023. The Author(s).)

Objectives: The aim of this review is to assess the methodological quality of guidelines for the management of vertigo and dizziness and to compare their recommendations, with specific focus on neuroimaging., Databases Reviewed: MEDLINE, EMBASE, National Guideline Clearinghouse, and National Institute for Health and Clinical Excellence database., Methods: In March 2022, a systematic search was performed to find practice guidelines of management of vertigo and dizziness. The evaluation of guidelines quality was performed independently by four authors using the AGREE II tool. We excluded from the results those guidelines that were not primarily focused on vertigo and dizziness, such as national/international guidelines in which vertigo and dizziness were only briefly mentioned., Results: Our strategy of literature search identified 161 studies, and 18 guidelines were selected for the appraisal. Only five guidelines reached the acceptance level in the overall result (at least 60%), with three of them reaching the highest scores (at least 80%). The highest scores were found in Domain 6 "Editorial Independence," Domain 1 "Scope and purpose," and Domain 4 "Clarity of presentation" (median value = 66%, 62%, and 61%, respectively). The remaining domains showed a low level of quality: Domain 2 "Stakeholder Involvement," Domain 3 "Rigor of development," and Domain 5 "Applicability" had median values of 27%, 27%, and 22%, respectively. The quality of these guidelines was very low, because of low involvement of multidisciplinary teams in writing guidelines recommendations., Conclusion: Considering all guidelines, only three had a "high" overall score, whereas 13 of 18 (72%) of them were rated as of "low" quality. Future guidelines might take this into account to improve clinical applicability., Competing Interests: The authors disclose no conflicts of interest., (Copyright © 2022, Otology & Neurotology, Inc.)

Colorectal medullary carcinoma (CMC) is a rare subset of minimally differentiated carcinomas. CMC tend to be right-sided and present at an advanced stage. Despite this, distant metastases are rare at presentation. The liver and the regional lymph nodes represent the most common sites of metastases. Most of the time, CMCs exhibit mismatch repair deficiency and a strong association with high-level microsatellite instability. There is no conspicuous data regarding treatment strategies and short-term outcomes. CMC is supposed to be related to better prognosis compared to poorly-differentiated and undifferentiated colonic adenocarcinomas, but reports are controversial.This lesion, with heterogeneous presentations and unclear prognostic significance, may be unfamiliar to histopathologists and can lead to diagnostic uncertainty and overtreatments.Our aim is to renew the attention to this rare histological subtype through the report of two cases.

Magnetic resonance imaging (MRI) is an important part of breast cancer diagnosis and multimodal workup. It provides unsurpassed soft tissue contrast to analyse the underlying pathophysiology, and it is adopted for a variety of clinical indications. Predictive and prognostic breast MRI (P2-bMRI) is an emerging application next to these indications. The general objective of P2-bMRI is to provide predictive and/or prognostic biomarkers in order to support personalisation of breast cancer treatment. We believe P2-bMRI has a great clinical potential, thanks to the in vivo examination of the whole tumour and of the surrounding tissue, establishing a link between pathophysiology and response to therapy (prediction) as well as patient outcome (prognostication). The tools used for P2-bMRI cover a wide spectrum: standard and advanced multiparametric pulse sequences; structured reporting criteria (for instance BI-RADS descriptors); artificial intelligence methods, including machine learning (with emphasis on radiomics data analysis); and deep learning that have shown compelling potential for this purpose. P2-bMRI reuses the imaging data of examinations performed in the current practice. Accordingly, P2-bMRI could optimise clinical workflow, enabling cost savings and ultimately improving personalisation of treatment. This review introduces the concept of P2-bMRI, focusing on the clinical application of P2-bMRI by using semantic criteria., (© 2022. The Author(s) under exclusive licence to European Society of Radiology.)

Life expectancy in adults with congenital heart disease (ACHD) has increased. As these patients grow older, they experience aging-related diseases more than their healthy peers. To better characterize this field, we launched the multi-disciplinary BACH (Brain Aging in Congenital Heart disease) San Donato study, that aimed at investigating signs of brain injury in ACHD. Twenty-three adults with repaired tetralogy of Fallot and 23 age- and sex-matched healthy controls were prospectively recruited and underwent brain magnetic resonance imaging. White matter hyperintensities (WMHs) were segmented using a machine-learning approach and automatically split into periventricular and deep. Cerebral microbleeds were manually counted. A subset of 14 patients were also assessed with an extensive neuropsychological battery. Age was 41.78 ± 10.33 years (mean ± standard deviation) for patients and 41.48 ± 10.28 years for controls (p = 0.921). Albeit not significantly, total brain (p = 0.282) and brain tissue volumes (p = 0.539 for cerebrospinal fluid, p = 0.661 for grey matter, p = 0.793 for white matter) were lower in ACHD, while total volume (p = 0.283) and sub-classes of WMHs (p = 0.386 for periventricular WMHs and p = 0.138 for deep WMHs) were higher in ACHD than in controls. Deep WMHs were associated with poorer performance at the frontal assessment battery (r = -0.650, p = 0.012). Also, patients had a much larger number of microbleeds than controls (median and interquartile range 5 [3-11] and 0 [0-0] respectively; p < 0.001). In this study, adults with tetralogy of Fallot showed specific signs of brain injury, with some clinical implications. Eventually, accurate characterization of brain health using neuroimaging and neuropsychological data would aid in the identification of ACHD patients at risk of cognitive deterioration., (© 2022. The Author(s).)

Purpose: Imaging of brain involvement in infective endocarditis can drive the clinical management of this serious condition. MRI is very sensitive, but CT is more readily available. In this retrospective study, we compared the detection rates of CT and MRI., Methods: After Ethics Committee approval, we retrospectively reviewed a series of 20 patients (13 males, median age 64 years) who underwent both CT and MRI either before or after cardiac surgery for definite infective endocarditis. Plain CT and MRI were evaluated for acute ischemic lesions, both punctuate and large, intraparenchymal hemorrhages, cerebral microbleeds, subarachnoid hemorrhages, abscesses, microabscesses, and meningitis. Qualitative assessment and McNemar test were performed. The value of contrast-enhanced scans (MRI, n = 14; CT, n = 9) and cognitive status were also assessed., Results: A total of 166 lesions were identified on either technique: 137 (83%) on MRI only, 4 (2%) on CT only, and 25 (15%) on both techniques (p < 0.001). For these last 25 lesions, concordance on lesion type was only 16/25 (64%). MRI detected more microbleeds and ischemic lesions, while the 4 CT-only findings were false positives. Contrast-enhanced scans identified 68 enhancing lesions, mainly abscesses and microabscesses, and allowed a better characterization for 61/117 lesions (52%) with MRI, and for 11/81 (14%) with CT. Follow-up identified mild cognitive impairment in 6/13 and dementia in 3/13 patients., Conclusion: While CT rapidly excludes large hemorrhages in patients with infective endocarditis, MRI accurately distinguishes the whole spectrum of brain lesions, including small ischemic lesions, microbleeds, and microabscesses., (© 2021. The Author(s).)

Background Contrast-enhanced mammography (CEM) is a promising technique for breast cancer detection, but conflicting results have been reported in previous meta-analyses. Purpose To perform a systematic review and meta-analysis of CEM diagnostic performance considering different interpretation methods and clinical settings. Materials and Methods The MEDLINE, EMBASE, Web of Science, and Cochrane Library databases were systematically searched up to July 15, 2021. Prospective and retrospective studies evaluating CEM diagnostic performance with histopathology and/or follow-up as the reference standard were included. Study quality was assessed with the Quality Assessment of Diagnostic Accuracy Studies 2 tool. Summary diagnostic odds ratio and area under the receiver operating characteristic curve were estimated with the hierarchical summary receiver operating characteristic (HSROC) model. Summary estimates of sensitivity and specificity were obtained with the hierarchical bivariate model, pooling studies with the same image interpretation approach or focused on the same findings. Heterogeneity was investigated through meta-regression and subgroup analysis. Results Sixty studies (67 study parts, 11 049 CEM examinations in 10 605 patients) were included. The overall area under the HSROC curve was 0.94 (95% CI: 0.91, 0.96). Pooled diagnostic odds ratio was 55.7 (95% CI: 42.7, 72.7) with high heterogeneity (τ 2 = 0.3). At meta-regression, CEM interpretation with both low-energy and recombined images had higher sensitivity (95% vs 94%, P < .001) and specificity (81% vs 71%, P = .03) compared with recombined images alone. At subgroup analysis, CEM showed a 95% pooled sensitivity (95% CI: 92, 97) and a 78% pooled specificity (95% CI: 66, 87) from nine studies in patients with dense breasts, while in 10 studies on mammography-detected suspicious findings, CEM had a 92% pooled sensitivity (95% CI: 89, 94) and an 84% pooled specificity (95% CI: 73, 91). Conclusion Contrast-enhanced mammography demonstrated high performance in breast cancer detection, especially with joint interpretation of low-energy and recombined images. © RSNA, 2021 Online supplemental material is available for this article. See also the editorial by Bahl in this issue.

Introduction: Radiation therapy technologists (RTTs) are exposed to high stress levels which may lead to burnout, which could be further increased by the current pandemic. The aim of our study was to assess burnout and stress among Italian RTTs before and during the pandemic., Methods: The Italian Association of Radiation Therapy and Medical Physics Technologists (AITRO) and the Italian Federation of Scientific Radiographers Societies (FASTeR) proposed a national online survey, including the Maslach Burnout Inventory assessing emotional exhaustion (EE), depersonalisation (DP), and personal accomplishment (PA) to RTTs before and during the pandemic. Multivariate regression analyses and χ 2 tests were used for data analysis., Results: We obtained 367 answers, 246 before and 121 during the pandemic. RTTs before and during the pandemic showed high EE and DP, intermediate PA. Median EE was 37 (interquartile range [IQR] 31-46] before and 37 (IQR 30-43) during the pandemic, median DP was 16 (IQR 13-21) and 15 (IQR 12-20), respectively. PA was 31 (IQR 28-34) and 32 (IQR 28-34), respectively. Through multivariate analysis, being female and having children led to higher EE scores before and during the pandemic (p≤0.026). Only the presence of workplace stress management courses was related to lower DP before and being female was related to higher DP during the pandemic (p<0.001). Being female, having children, and working with paediatric patients were related to lower PA before and during the pandemic (p≤0.015)., Conclusion: Our study highlighted high burnout levels for RTTs regardless of the pandemic. Future interventions aimed at preventing burnout should be implemented in their work environment, independently of the impact of exceptional events., (Copyright © 2021. Published by Elsevier Inc.)