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To evaluate clinical and cardiac magnetic resonance (CMR) short-term follow-up (FU) in patients with vaccine-associated myocarditis, pericarditis or myo-pericarditis (VAMP) following COVID-19 vaccination. We retrospectively analyzed 44 patients (2 women, mean age: 31.7 ± 15.1 years) with clinical and CMR manifestations of VAMP, recruited from 13 large tertiary national centers. Inclusion criteria were troponin raise, interval between the last vaccination dose and onset of symptoms

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 χ2 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

Background We investigated the radiodensity of epicardial (EAT), subcutaneous (SAT), and visceral adipose tissue (VAT) before and after treatment with anthracyclines in a population of breast cancer (BC) patients, and in controls not treated with anthracyclines, to detect a potential role of EAT density as a biomarker of changes related to chemotherapy cardiotoxicity. Methods We reviewed BC patients treated with anthracyclines who underwent CT before (CT-t0) and after (CT-t1) chemotherapy, and age- and sex-matched controls who underwent two CT examinations at comparable intervals. On non-contrast scans, EAT was segmented contouring the pericardium and thresholding between -190 and -30 Hounsfield units (HU), and SAT and VAT were segmented with two 15-mm diameter regions of interest thresholded between -195 and -45 HU. Results Thirty-two female patients and 32 controls were included. There were no differences in age (p = 0.439) and follow-up duration (p = 0.162) between patients and controls. Between CT-t0 and CT-t1, EAT density decreased in BC patients (-66 HU, interquartile range [IQR] -71 to -63 HU, to -71 HU, IQR -75 to -66 HU, p = 0.003), while it did not vary in controls (p = 0.955). SAT density increased from CT-t0 to CT-t1 in BC patients (-107 HU, IQR -111 to -105 HU, to -105 HU, IQR -110 to -100 HU, p = 0.014), whereas it did not change in controls (p = 0.477). VAT density did not vary in either BC patients (p = 0.911) or controls (p = 0.627). Conclusions EAT density appears to be influenced by anthracycline treatment for BC, well known for its cardiotoxicity, shifting towards lower values indicative of a less active metabolism.

The purpose of this study was to evaluate the level of agreement between flow/velocity data obtained from 2D-phase-contrast (PC) and 4D-flow in patients scheduled for treatment of carotid artery stenosis. Image acquisition was performed using a 1.5 T scanner. We compared mean flow rates, vessel areas, and peak velocities obtained during the acquisition with both techniques in 20 consecutive patients, 15 males and 5 females aged 69 ± 5 years (mean ± standard deviation). There was a good correlation between both techniques for the CCA flow (r = 0.65, p &lt, 0.001), whereas for the ICA flow and ECA flow the correlation was only moderate (r = 0.4, p = 0.011 and r = 0.45, p = 0.003, respectively). Correlations of peak velocities between methods were good for CCA (r = 0.56, p &lt, 0.001) and moderate for ECA (r = 0.41, p = 0.008). There was no correlation for ICA (r = 0.04, p = 0.805). Cross-sectional area values between methods showed no significant correlations for CCA (r = 0.18, p = 0.269), ICA (r = 0.1, p = 0.543), and ECA (r = 0.05, p = 0.767). Conclusion: the 4D-flow imaging provided a good correlation of CCA and a moderate correlation of ICA flow rates against 2D-PC, underestimating peak velocities and overestimating cross-sectional areas in all carotid segments.

Introduction Our aim was to investigate the means radiographers and radiographers in training (RTrs) use to seek information on magnetic resonance imaging (MRI) physics and technical issues. Methods An estimated 3000 radiographers and RTrs were reached by e-mail. We proposed an online survey with eight English-language multiple choice questions investigating how often radiographers have doubts about MRI physics or technical issues, where and what kind of information they search for, and on which websites. The statistical χ2 test was used. Results We obtained 300 answers from European professionals (228 radiographers, 72 RTrs) from 9 European countries, with 288 of 300 (96%) responses coming from Italy. Within the Italian respondents, 41% of RTrs have doubts about MRI physics versus 56% of radiographers (p = 0.028). Basic MRI sequences details are more searched by RTrs (36%) than radiographers (22%) (p = 0.088), as well as clinical protocols (64% versus 44%, p = 0.054). Radiographers and RTrs mostly search on the Internet (74% versus 81%, p = 0.404); “older colleagues” are more frequently asked for information by RTrs (27% versus 61%, p = 0.001), they consult the “MRI manufacturer” less frequently (11% versus 34%, p = 0.001); and 66% of radiographers and 72% of RTrs search “in mother-language and English” (p = 0.590). For clinical protocols RTrs prefer the website mriquestions.com (17% versus 44%, p = 0.001). Websites most used were: mriquestions.com (41%), radiopaedia.org (31%), and mrimaster.com (13%). In addition, 30 respondents mentioned using the Italian site fermononrespiri.com. Conclusion Italian radiographers and RTrs frequently search for information about MRI physics and technical issues, with slight differences between groups regarding sources and clinical protocols. Protocol setting, and MRI physics and sequences seem to be the main limitations of RTr knowledge. To remedy this gap, more time on training/university lectures and a rethinking of the practical training activities is required.

Sarcopenia has been associated with an increased incidence of adverse outcomes, including higher mortality, after endovascular aortic repair (EVAR). We aim to use computed tomography (CT) to quantify changes in total psoas muscles area (PMA) and psoas muscle density (PMD) after EVAR, and to evaluate the reproducibility of both measurements. PMA and PMD were assessed via manual segmentation of the psoas muscle on pre- and post-operative CT scans belonging to consecutive patients who underwent EVAR. Wilcoxon test was used to compare PMA and PMD before and after EVAR, and inter- and intra-reader agreements of both methods were evaluated through Bland–Altman analysis. A total of 50 patients, 42 of them males (84%), were included in the study. PMA changes from 1243 mm2 (1006–1445 mm2) to 1102 mm2 (IQR 937–1331 mm2), after EVAR (p < 0.001). PMD did not vary between pre-EVAR (33 HU, IQR 26.5–38.7 HU) and post-EVAR (32 HU, IQR 26–37 HU, p = 0.630). At inter-reader Bland–Altman analysis, PMA showed a bias of 64.0 mm2 and a coefficient of repeatability (CoR) of 359.2 mm2, whereas PMD showed a bias of −2.43 HU and a CoR of 6.19 HU. At intra-reader Bland–Altman analysis, PMA showed a bias of −81.1 mm2 and a CoR of 394.6 mm2, whereas PMD showed a bias of 1.41 HU and a CoR of 6.36 HU. In conclusion, PMA decreases after EVAR. A good intra and inter-reader reproducibility was observed for both PMA and PMD. We thus propose to use PMA during the follow-up of patients who underwent EVAR to monitor muscle depletion after surgery.

Objectives The current reference standard for diagnosing LAA thrombi is transesophageal echocardiography (TEE), a semi-invasive technique. We aimed to devise an optimal protocol for cardiac computed tomography (CCT) in diagnosing left atrial appendage (LAA) thrombus in patients with atrial fibrillation (AF), using TEE as reference standard. Methods Two hundred sixty consecutive patients referred for radiofrequency ablation for AF were prospectively enrolled. All patients underwent CCT and TEE within 2 hours. The CCT protocol included one standard angiographic phase and three delayed acquisitions at 1-, 3-, and 6-min after contrast injection. Thrombi were defined as persisting defects at 6-min delayed acquisition. Results TEE demonstrated spontaneous contrast in 52 (20%) patients and thrombus in 10 (4%). In 63 patients (24%), CCT demonstrated LAA early filling defects at angiographic phase. Among them, 15 (6%) had a persistent defect at 1-min, 12 (5%) at 3-min, and 10 (4%) at 6-min. All 10 thrombi diagnosed on TEE were correctly identified by delayed CCT, without any false positives. For all phases, sensitivity and negative predictive were 100%. Specificity increased from 79% for the angiographic phase to 100% at 6-min. Positive predictive value increased from 16% to 100%. Estimated radiation exposure was 2.08 ± 0.76 mSv (mean ± standard deviation) for the angiographic phase and 0.45 ± 0.23 mSv for each delayed phase. Conclusion A CCT protocol adding a 6-min delayed phase to the angiographic phase can be considered optimized for the diagnosis of LAA thrombi, with a low radiation dose. Key Points • In patients with persistent atrial fibrillation referred for ablation procedures, a cardiac CT examination comprising an angiographic-phase acquisition and, in case of filling defects, a 6-min delayed phase may help reduce the need for transesophageal echocardiography. • Cardiac CT would provide morphological and volumetric data, along with the potential to exclude the presence of thrombi in the left atrial appendage.

Objectives From December 2019, a novel coronavirus disease named COVID-19 was reported in China. Within 3 months, the World Health Organization defined COVID-19 as a pandemic, with more than 370,000 cases and 16,000 deaths worldwide. In consideration of the crucial role of diagnostic testing during COVID-19, the aim of this technical note was to provide a complete synthesis of approaches implemented for the management of suspected or confirmed COVID-19 patients. Key findings The planning of a robust plan to prevent the transmission of the virus to patients and department staff members should be fundamental in each radiology service. Moreover, the speed of spread and the incidence of the pandemic make it necessary to optimize the use of personal protective devices and dedicated COVID-19 equipment, given the limited availability of supplies. Conclusion In the management of radiographic and CT imaging, staff should take special precautions to limit contamination between patients and other patients or professionals. Implications for practice An isolated imaging room should be dedicated to suspected or confirmed COVID-19 cases, including radiography and CT scanners. This paper will provide guidance concerning disposable protective gear to be utilized, as well as on the cleaning and sanitation of radiology room and equipment.

Because of a recent increase in survival rates and life expectancy of patients with congenital heart disease (CHD), radiologists are facing new challenges when imaging the peculiar anatomy of individuals with repaired CHD. Cardiac computed tomography and magnetic resonance are paramount noninvasive imaging tools that are useful in assessing patients with repaired CHD, and both techniques are increasingly performed in centers where CHD is not the main specialization. This review provides general radiologists with insight into the main issues of imaging patients with repaired CHD, and the most common findings and complications of each individual pathology and its repair.

During the latest years, artificial intelligence, and especially machine learning (ML), have experienced a growth in popularity due to their versatility and potential in solving complex problems. In fact, ML allows the efficient handling of big volumes of data, allowing to tackle issues that were unfeasible before, especially with deep learning, which utilizes multilayered neural networks. Cardiac computed tomography (CT) is also experiencing a rise in examination numbers, and ML might help handle the increasing derived information. Moreover, cardiac CT presents some fields wherein ML may be pivotal, such as coronary calcium scoring, CT angiography, and perfusion. In particular, the main applications of ML involve image preprocessing and postprocessing, and the development of risk assessment models based on imaging findings. Concerning image preprocessing, ML can help improve image quality by optimizing acquisition protocols or removing artifacts that may hinder image analysis and interpretation. ML in image postprocessing might help perform automatic segmentations and shorten examination processing times, also providing tools for tissue characterization, especially concerning plaques. The development of risk assessment models from ML using data from cardiac CT could aid in the stratification of patients who undergo cardiac CT in different risk classes and better tailor their treatment to individual conditions. While ML is a powerful tool with great potential, applications in the field of cardiac CT are still expanding, and not yet routinely available in clinical practice due to the need for extensive validation. Nevertheless, ML is expected to have a big impact on cardiac CT in the near future.

PURPOSE: To compare real-time compressed sensing (CS) and standard balanced steady-state free precession (bSSFP) cardiac cine imaging in children. MATERIALS AND METHODS: Twenty children (mean age, 15 years ± 5 [SD], range, 7–21 years; 10 male participants) with biventricular congenital heart disease (n = 11) or cardiomyopathy (n = 9) were prospectively included. Examinations were performed with 1.5-T imagers by using both bSSFP and CS sequences in all participants. Quantification of ventricular volumes and function was performed for all images by two readers blinded to patient diagnosis and type of sequence. Values were correlated with phase-contrast flow measurements by one reader. Intra- and interreader agreement were analyzed. RESULTS: There were no significant differences between ventricular parameters measured on CS compared with those of bSSFP (P > .05) for reader 1. Only ejection fraction showed a significant difference (P = .02) for reader 2. Intrareader agreement was considerable for both sequences (bSSFP: mean difference range, +1 to −2.6; maximum CI, +7.9, −13; bias range, 0.1%–4.1%; intraclass correlation coefficient [ICC] range, 0.931–0.997. CS: mean difference range, +7.4 to −5.6; maximum CI, +37.2, −48.8; bias range, 0.5%–7.5%; ICC range, 0.717–0.997). Interreader agreement was acceptable but less robust, especially for CS (bSSFP: mean difference range, +2.6 to −5.6; maximum CI, +60.7, −65.3; bias range, 1.6%–6.2%; ICC range, 0.726–0.951. CS: mean difference range, +10.7 to −9.1; maximum CI, +87.5, −84.6; bias range, 1.1%–17.3%; ICC range, 0.509–0.849). The mean acquisition time was shorter for CS (20 seconds; range, 17–25 seconds) compared with that for bSSFP (160 seconds; range, 130–190 seconds) (P < .001). CONCLUSION: CS cardiac cine imaging provided equivalent ventricular volume and function measurements with shorter acquisition times compared with those of bSSFP and may prove suitable for the pediatric population. Keywords: Compressed Sensing, Balanced Steady-State Free Precession, Cine Imaging, Cardiovascular MRI, Pediatrics, Cardiac, Heart, Cardiomyopathies, Congenital, Segmentation © RSNA, 2022

Objective: The objective of this study was to compare the use of pulmonary regurgitation volume (PRV) or indexed PRV (PRVi) with that of pulmonary regurgitation fraction (PRF) in the assessment of patients with pulmonary regurgitation (PR) undergoing cardiac magnetic resonance (CMR) imaging. Materials and Methods: CMR of 176 patients with PR were retrospectively evaluated. Their right ventricular diastolic (end-diastolic volume index [EDVi]) and systolic (end-systolic volume index) volume indexes, stroke volume, and ejection fraction were obtained from cine CMR sequences, whereas phase-contrast flow sequences were analyzed to obtain PRV, PRVi, and PRF. Patients were divided into subgroups, according to underlying pathology and according to PR severity. Correlations between PRV or PRF and RV parameters were studied through Spearman ρ, both in the main group and subgroups. Follow-up examinations were analyzed, and correlations between PRV or PRF from the first CMR examination and volume data from the second were calculated. Results: Tetralogy of Fallot was the main setting of PR (98/179). Overall, EDVi strongly correlates with PRV (ρ=0.592, P

PURPOSE The aim of this pilot study was to prospectively evaluate the first integrated positron emission tomography (PET)/dual-energy computed tomography (DECT) system performance in patients with non-small cell lung cancer (NSCLC). MATERIALS AND METHODS In this single-center, prospective trial, consecutive patients with NSCLC referred for a PET study between May 2017 and June 2018 were enrolled. All patients received contrast-enhanced imaging on a clinical PET/DECT system. Data analysis included PET-based standard uptake values (SUVmax) and DECT-based iodine densities of tumor masses, lymph nodes, and distant metastases. Results were analyzed using correlation tests and receiver operating characteristics curves. RESULTS The study population was composed of 21 patients (median age 62 y, 14 male patients). A moderate positive correlation was found between iodine density values (2.2 mg/mL) and SUVmax (10.5) in tumor masses (ρ=0.53, P

We assessed the role of artificial intelligence applied to chest X-rays (CXRs) in supporting the diagnosis of COVID-19. We trained and cross-validated a model with an ensemble of 10 convolutional neural networks with CXRs of 98 COVID-19 patients, 88 community-acquired pneumonia (CAP) patients, and 98 subjects without either COVID-19 or CAP, collected in two Italian hospitals. The system was tested on two independent cohorts, namely, 148 patients (COVID-19, CAP, or negative) collected by one of the two hospitals (independent testing I) and 820 COVID-19 patients collected by a multicenter study (independent testing II). On the training and cross-validation dataset, sensitivity, specificity, and area under the curve (AUC) were 0.91, 0.87, and 0.93 for COVID-19 versus negative subjects, 0.85, 0.82, and 0.94 for COVID-19 versus CAP. On the independent testing I, sensitivity, specificity, and AUC were 0.98, 0.88, and 0.98 for COVID-19 versus negative subjects, 0.97, 0.96, and 0.98 for COVID-19 versus CAP. On the independent testing II, the system correctly diagnosed 652 COVID-19 patients versus negative subjects (0.80 sensitivity) and correctly differentiated 674 COVID-19 versus CAP patients (0.82 sensitivity). This system appears promising for the diagnosis and differential diagnosis of COVID-19, showing its potential as a second opinion tool in conditions of the variable prevalence of different types of infectious pneumonia.

Adipose tissue, in particular epicardial adipose tissue, has been identified as a potential biomarker of cardiovascular pathologies such as coronary artery disease (CAD) in the light of its metabolic activity and close anatomic and pathophysiologic relationship to the heart. Our purpose was to evaluate epicardial adipose tissue density at both unenhanced and contrast-enhanced computed tomography (CT), along with CT densities of paracardiac and subcutaneous adipose tissue, as well as the relations of such densities with CAD. We retrospectively reviewed patients who underwent cardiac CT at our institution for CAD assessment. We segmented regions of interest on epicardial, paracardiac, and subcutaneous adipose tissue on unenhanced and contrast-enhanced scans. A total of 480 patients were included, 164 of them presenting with CAD. Median epicardial adipose tissue density measured on contrast-enhanced scans (−81.5 HU, interquartile range −84.9 to −78.0) was higher than that measured on unenhanced scans (−73.4 HU, −76.9 to −69.4) (p &lt, 0.001), whereas paracardiac and subcutaneous adipose tissue densities were not (p ≥ 0.055). Patients with or without CAD, did not show significant differences in density of epicardial, paracardiac, and subcutaneous adipose tissue either on unenhanced or contrast-enhanced scans (p ≥ 0.092). CAD patients may experience different phenomena (inflammation, fibrosis, increase in adipose depots) leading to rises or drops in epicardial adipose tissue density, resulting in variations that are difficult to detect.

Background: We aimed to train and test a deep learning classifier to support the diagnosis of coronavirus disease 2019 (COVID-19) using chest x-ray (CXR) on a cohort of subjects from two hospitals in Lombardy, Italy. Methods: We used for training and validation an ensemble of ten convolutional neural networks (CNNs) with mainly bedside CXRs of 250 COVID-19 and 250 non-COVID-19 subjects from two hospitals (Centres 1 and 2). We then tested such system on bedside CXRs of an independent group of 110 patients (74 COVID-19, 36 non-COVID-19) from one of the two hospitals. A retrospective reading was performed by two radiologists in the absence of any clinical information, with the aim to differentiate COVID-19 from non-COVID-19 patients. Real-time polymerase chain reaction served as the reference standard. Results: At 10-fold cross-validation, our deep learning model classified COVID-19 and non-COVID-19 patients with 0.78 sensitivity (95% confidence interval [CI] 0.74-0.81), 0.82 specificity (95% CI 0.78-0.85), and 0.89 area under the curve (AUC) (95% CI 0.86-0.91). For the independent dataset, deep learning showed 0.80 sensitivity (95% CI 0.72-0.86) (59/74), 0.81 specificity (29/36) (95% CI 0.73-0.87), and 0.81 AUC (95% CI 0.73-0.87). Radiologists' reading obtained 0.63 sensitivity (95% CI 0.52-0.74) and 0.78 specificity (95% CI 0.61-0.90) in Centre 1 and 0.64 sensitivity (95% CI 0.52-0.74) and 0.86 specificity (95% CI 0.71-0.95) in Centre 2. Conclusions: This preliminary experience based on ten CNNs trained on a limited training dataset shows an interesting potential of deep learning for COVID-19 diagnosis. Such tool is in training with new CXRs to further increase its performance.

Anatomical substrate and mechanical trigger co-act in arrhythmia’s onset in patients with bileaflet mitral valve prolapse (bMVP). Feature tracking (FT) may improve risk stratification provided by cardiac magnetic resonance (CMR). The aim was to investigate differences in CMR and FT parameters in bMVP patients with and without complex arrhythmias (cVA and no-cVA). In this retrospective study, 52 patients with bMVP underwent 1.5 T CMR and were classified either as no-cVA (n = 32; 12 males; 49.6 ± 17.4 years) or cVA (n = 20; 3 males; 44.7 ± 11.2 years), the latter group including 6 patients (1 male; 45.7 ± 12.7 years) with sustained ventricular tachycardia or ventricular fibrillation (SVT-FV). Twenty-four healthy volunteers (11 males, 36.2 ± 12.5 years) served as control. Curling, prolapse distance, mitral annulus disjunction (MAD), and late gadolinium enhancement (LGE) were recorded and CMR-FT analysis performed. Statistical analysis included non-parametric tests and binary logistic regression. LGE and MAD distance were associated with cVA with an odds ratio (OR) of 8.51 for LGE (95% CI 1.76, 41.28; p = 0.008) and of 1.25 for MAD (95% CI 1.02, 1.54; p = 0.03). GLS 2D (− 11.65 ± 6.58 vs − 16.55 ± 5.09 1/s; p = 0.04), PSSR longitudinal 2D (0.04 ± 1.62 1/s vs − 1.06 ± 0.35 1/s; p = 0.0001), and PSSR radial 3D (3.95 ± 1.97 1/s vs 2.64 ± 1.03 1/s; p = 0.0001) were different for SVT-VF versus the others. PDSR circumferential 2D (1.10 ± 0.54 vs. 0.84 ± 0.34 1/s; p = 0.04) and 3D (0.94 ± 0.42 vs. 0.69 ± 0.17 1/s; p = 0.04) differed between patients with and without papillary muscle LGE. CMR-FT allowed identifying subtle myocardial deformation abnormalities in bMVP patients at risk of SVT-VF. LGE and MAD distance were associated with cVA. • CMR-FT allows identifying several subtle myocardial deformation abnormalities in bMVP patients, especially those involving the papillary muscle. • CMR-FT allows identifying subtle myocardial deformation abnormalities in bMVP patients at risk of SVT and VF. • In patients with bMVP, the stronger predictor of cVA is LGE (OR = 8.51; 95% CI 1.76, 41.28; p = 0.008), followed by MAD distance (OR = 1.25; 95% CI 1.02, 1.54; p = 0.03).

BACKGROUND: Breast arterial calcifications (BAC), representing Mönckeberg’s sclerosis of the tunica media of breast arteries, are an imaging biomarker for cardiovascular risk stratification in the female population. Our aim was to estimate the intra- and inter-reader reproducibility of a semiquantitative score for BAC assessment (BAC-SS). METHODS: Consecutive women who underwent screening mammography at our center from January 1(st) to January 31(st), 2018 were retrieved and included according to BAC presence. Two readers (R1 and R2) independently applied the BAC-SS to medio-lateral oblique views, obtaining a BAC score by summing: (I) number of calcified vessels (from 0 to n); (II) vessel opacification, i.e., the degree of artery coverage by calcium bright pixels (0 or 1); and (III) length class of calcified vessels (from 0 to 4). R1 repeated the assessment 2 weeks later. Scoring time was recorded. Cohen’s κ statistics and Bland-Altman analysis were used. RESULTS: Among 408 women, 57 (14%) had BAC; 114 medio-lateral oblique views were assessed. Median BAC score was 4 [interquartile range (IQR): 3–6] for R1 and 4 (IQR: 2–6) for R2 (P=0.417) while median scoring time was 156 s (IQR: 99–314 s) for R1 and 191 s (IQR: 137–292 s) for R2 (P=0.743). Bland-Altman analysis showed a 77% intra-reader reproducibility [bias: 0.193, coefficient of repeatability (CoR): 0.955] and a 64% inter-reader reproducibility (bias: 0.211, CoR: 1.516). Cohen’s κ for BAC presence was 0.968 for intra-reader agreement and 0.937 for inter-reader agreement. CONCLUSIONS: Our BAC-SS has a good intra- and inter-reader reproducibility, within acceptable scoring times. A large-scale study is warranted to test its ability to stratify cardiovascular risk in women.

Objectives We aimed to assess extracellular volume (ECV) through non-gated, contrast-enhanced computed tomography (CT) before and after radiation therapy (RT) in patients with esophageal cancer (EC). Materials and methods EC patients who had undergone CT before and after RT were retrospectively assessed. Patients with preexisting cardiovascular disease or with heavily artifacted CT were excluded. ECV was calculated using density values for the myocardial septum and blood pool. Data were reported as mean and standard deviation or median and interquartile range according to their distribution; t test or Wilcoxon and Pearson r or Spearman ρ were subsequently used. Results Twenty-one patients with stage ≥ IB EC, aged 64 ± 18 years, were included. Mean and maximum RT doses were 21.2 Gy (16.9–24.1) and 42.5 Gy (41.8–49.2), respectively. At baseline (n = 21), hematocrit was 39% ± 4%, ECV 27.9% ± 3.5%; 35 days (30–38) after RT (n = 20), hematocrit was 36% ± 4%, lower than at baseline (p = 0.002), ECV 30.3% ± 8.3%, higher than at baseline (p = 0.081); at follow-up 420 days (244–624) after RT (n = 13), hematocrit was 36% ± 5%, lower than at baseline (p = 0.030), ECV 31.4% ± 4.5%, higher than at baseline (p = 0.011). No patients showed signs of overt cardiotoxicity. ECV early after RT was moderately positively correlated with maximum RT dose (ρ = 0.50, p = 0.036). Conclusions In EC patients, CT-derived myocardial ECV was increased after RT and may thus appear as a potential early biomarker of cardiotoxicity.

To evaluate the diagnostic performance of dual-energy computed tomography (DECT) with regard to its post-processing techniques, namely linear blending (LB), iodine maps (IM), and virtual monoenergetic (VM) reconstructions, in diagnosing acute pulmonary embolism (PE). This meta-analysis was conducted according to PRISMA. A systematic search on MEDLINE and EMBASE was performed in December 2019, looking for articles reporting the diagnostic performance of DECT on a per-patient level. Diagnostic performance meta-analyses were conducted grouping study parts according to DECT post-processing methods. Correlations between radiation or contrast dose and publication year were appraised. Seventeen studies entered the analysis. Only lobar and segmental acute PE were considered, subsegmental acute PE being excluded from analysis due to data heterogeneity or lack of data. LB alone was assessed in 6 study parts accounting for 348 patients, showing a pooled sensitivity of 0.87 and pooled specificity of 0.93. LB and IM together were assessed in 14 study parts accounting for 1007 patients, with a pooled sensitivity of 0.89 and pooled specificity of 0.90. LB, IM, and VM together were assessed in 2 studies (for a total 144 patients) and showed a pooled sensitivity of 0.90 and pooled specificity of 0.90. The area under the curve for LB alone, and LB together with IM was 0.93 (not available for studies using LB, IM and VM because of paucity of data). Radiation and contrast dose did not decrease with increasing year of publication. Considering the published performance of single-energy CT in diagnosing acute PE, either dual-energy or single-energy computed tomography can be comparably used for the detection of acute PE. • Dual-energy CT displayed pooled sensitivity and specificity of 0.87 and 0.93 for linear blending alone, 0.89 and 0.90 for linear blending and iodine maps, and 0.90 and 0.90 for linear blending iodine maps, and virtual monoenergetic reconstructions. • The performance of dual-energy CT for patient management is not superior to that reported in literature for single-energy CT (0.83 sensitivity and 0.96 specificity). • Dual-energy CT did not yield substantial advantages in the identification of patients with acute pulmonary embolism compared to single-energy techniques.

Background We investigated mitral valve annular geometry changes during the cardiac cycle in patients with severe mitral regurgitation (MR) who underwent cardiac computed tomography angiography (CCTA) prior to percutaneous mitral valve replacement or annuloplasty. Methods Fifty-one patients with severe MR and high surgical risk (Carpentier classification: 3 type I, 16 type II, 16 type IIIa, 16 type IIIb) underwent multiphase electrocardiographically gated (0–90%) CCTA, using a second generation dual-source CT scanner, as pre-procedural planning. Twenty-one patients without MR served as controls. The mitral valve annulus was segmented every 10% step of the R-R interval, according to the D-shaped segmentation model, and differences among groups were analysed by t-test or ANOVA. Results Mitral annular area and diameters were larger in MR patients compared to controls, particularly in type II. Mitral annular area varied in MR patients throughout the cardiac cycle (mean ± standard deviation of maximum and minimum area 15.6 ± 3.9 cm2 versus 13.0 ± 3.5 cm2, respectively; p = 0.001), with greater difference between annular areas versus controls (2.59 ± 1.61 cm2 and 1.98 ± 0.6 cm2, p < 0.001). The largest dimension was found in systolic phases (20–40%) in most of MR patients (n = 27, 53%), independent of Carpentier type (I: n = 1, 33%; II: n = 10, 63%; IIIa: n = 8, 50%; IIIb: n = 8, 50%), and in protodiastolic phases (n = 14, 67%) for the control group. Conclusions In severe MR, mitral annular area varied significantly throughout the cardiac cycle, with a tendency towards larger dimensions in systole.

BACKGROUND Cardiac strain represents an imaging biomarker of contractile dysfunction. PURPOSE The purpose of this study was to investigate the diagnostic value of cardiac strain obtained by feature-tracking cardiac magnetic resonance (MR) in acute myocarditis. MATERIALS AND METHODS Cardiac MR examinations of 46 patients with myocarditis and preserved ejection fraction at acute phase and follow-up were analyzed along with cardiac MR of 46 healthy age- and sex-matched controls. Global circumferential strain and global radial strain were calculated for each examination, along with myocardial edema and late gadolinium enhancement, and left ventricle functional parameters, through manual contouring of the myocardium. Correlations were assessed using Spearman ρ. Wilcoxon and Mann-Whitney U test were used to assess differences between data. Receiver operating characteristics curves and reproducibility were obtained to assess the diagnostic role of strain parameters. RESULTS Global circumferential strain was significantly lower in controls (median, -20.4%; interquartile range [IQR], -23.4% to -18.7%) than patients in acute phase (-18.4%; IQR, -21.0% to -16.1%; P = 0.001) or at follow-up (-19.2%; IQR, -21.5% to -16.1%; P = 0.020). Global radial strain was significantly higher in controls (82.4%; IQR, 62.8%-104.9%) than in patients during the acute phase (65.8%; IQR, 52.9%-79.5%; P = 0.001). Correlations were found between global circumferential strain and global radial strain in all groups (acute, ρ = -0.580, P < 0.001; follow-up, ρ = -0.399, P = 0.006; controls, ρ = -0.609, P < 0.001), and between global circumferential strain and late gadolinium enhancement only in myocarditis patients (acute, ρ = 0.035, P = 0.024; follow-up, ρ = 0.307, P = 0.038). CONCLUSIONS Cardiac strain could potentially have a role in detecting acute myocarditis in low-risk acute myocarditis patients where cardiac MR is the main diagnosing technique.

BACKGROUND: Cancer treatment with anthracyclines may lead to an increased incidence of cardiac disease due to cardiotoxicity, as they may cause irreversible myocardial fibrosis. So far, the proposed methods for screening patients for cardiotoxicity have led to only limited success, while the analysis of myocardial extracellular volume (mECV) at cardiac magnetic resonance (CMR) has shown promising results, albeit requiring a dedicated exam. Recent studies have found strong correlations between mECV values obtained through computed tomography (CT), and those derived from CMR. Thus, our purpose was to evaluate the feasibility of estimating mECV on thoracic contrast-enhanced CT performed for staging or follow-up in breast cancer patients treated with anthracyclines, and, if feasible, to assess if a rise in mECV is associated with chemotherapy, and persistent over time. METHODS: After ethics committee approval, female patients with breast cancer who had undergone at least 2 staging or follow-up CT examinations at our institution, one before and one shortly after the end of chemotherapy including anthracyclines were retrospectively evaluated. Patients without available haematocrit, with artefacts in CT images, or who had undergone radiation therapy of the left breast were excluded. Follow-up CT examinations at longer time intervals were also analysed, when available. mECV was calculated on scans obtained at 1, and 7 min after contrast injection. RESULTS: Thirty-two female patients (aged 57±13 years) with pre-treatment haematocrit 38%±4%, and ejection fraction 64%±6% were analysed. Pre-treatment mECV was 27.0%±2.9% at 1 min, and 26.4%±3.8% at 7 min, similar to values reported for normal subjects in the literature. Post-treatment mECV (median interval: 89 days after treatment) was 31.1%±4.9%, and 30.0%±5.1%, respectively, values significantly higher than pre-treatment values at all times (P0.548) when compared to post-treatment values. CONCLUSIONS: mECV values from contrast-enhanced CT scans could play a role in the assessment of myocardial condition in breast cancer patients undergoing anthracycline-based chemotherapy. CT-derived ECV could be an imaging biomarker for the monitoring of therapy-related cardiotoxicity, allowing for potential secondary prevention of cardiac damage, using data derived from an examination that could be already part of patients’ clinical workflow.

Background T1 mapping is emerging as a powerful tool in cardiac magnetic resonance (CMR) to evaluate diffuse fibrosis. However, right ventricular (RV) T1 mapping proves difficult due to the limited wall thickness in diastolic phase. Several studies focused on systolic T1 mapping, albeit only on the left ventricle (LV). Purpose To estimate intra- and inter-observer variability of native T1 (nT1) mapping of the RV, and its correlations with biventricular and pulmonary function in patients with congenital heart disease (CHD). Material and Methods In this retrospective, observational, cross-sectional study we evaluated 36 patients with CHD, having undergone CMR on a 1.5-T scanner. LV and RV functional evaluations were performed. A native modified look-locker inversion recovery short-axis sequence was acquired in the systolic phase. Intra- and inter-reader reproducibility were reported as complement to 100% of the ratio between coefficient of reproducibility and mean. Spearman ρ and Mann–Whitney U-test were used to compare distributions. Results Intra- and inter-reader reproducibility was 84% and 82%, respectively. Median nT1 was 1022 ms (interquartile range [IQR] 1108–972) for the RV and 947 ms (IQR 986–914) for the LV. Median RV–nT1 was 1016 ms (IQR 1090–1016) in patients with EDVI ≤100 mL/m2 and 1100 ms (IQR 1113–1100) in patients with EDVI >100 mL/m2 ( P = 0.049). A significant negative correlation was found between RV ejection fraction and RV–nT1 (ρ = −0.284, P = 0.046). Conclusion Systolic RV-nT1 showed a high reproducibility and a negative correlation with RV ejection fraction, potentially reflecting an adaptation of the RV myocardium to pulmonary valve/conduit (dys)-function.

Coronary sinus (CS) Reducer implantation improves myocardial perfusion and symptoms in patients with debilitating refractory angina. Its impact on myocardial remodeling remain uncertain. Aim of the present study was to assess possible impact of CS Reducer on myocardial systolic-diastolic deformation and microstructural remodeling, as assessed through cardiac magnetic resonance (CMR) feature tracking and mapping analysis. Twenty-eight consecutive patients with refractory angina underwent multiparametric stress CMR before and 4months after CS Reducer implantation. Eight patients were excluded (6 for absence of inducible ischemia, 2 for artifacts). Modifications in 3D systo-diastolic myocardial deformation were evaluated using feature tracking analysis on rest cine images. Myocardial microstructural remodeling was assessed by native T1 mapping, cellular and matrix volume and extracellular volume fraction (ECV). Collaterally, the percentage of ischemic myocardium (ischemic burden %) and the myocardial perfusion reserve index (MPRI) were measured. After CS Reducer implantation, myocardial contractility improved (ejection fraction rose from 61 to 67%; p = 0.0079), along with longitudinal (from − 16 to − 19%; p = 0.0192) and circumferential strain (from − 18 to − 21%; p = 0.0017). Peak diastolic radial, circumferential and longitudinal strain rate did not change (p > 0.05), and no changes in native T1, ECV, cellular and matrix volume were observed. Myocardial perfusion improved, with a reduction of ischemic burden (13–11%; p = 0.0135), and recovery of intramural perfusion balance in segments with baseline ischemia (MPRi endocardial/epicardial ratio from 0.67 to 0.96; p = 0.0107). CS Reducer improves myocardial longitudinal and circumferential strain, without microstructural remodeling and no impact on diastolic proprieties.

ObjectivesWe tested artificial intelligence (AI) to support the diagnosis of COVID-19 using chest X-ray (CXR). Diagnostic performance was computed for a system trained on CXRs of Italian subjects from two hospitals in Lombardy, Italy.MethodsWe used for training and internal testing an ensemble of ten convolutional neural networks (CNNs) with mainly bedside CXRs of 250 COVID-19 and 250 non-COVID-19 subjects from two hospitals. We then tested such system on bedside CXRs of an independent group of 110 patients (74 COVID-19, 36 non-COVID-19) from one of the two hospitals. A retrospective reading was performed by two radiologists in the absence of any clinical information, with the aim to differentiate COVID-19 from non-COVID-19 patients. Real-time polymerase chain reaction served as reference standard.ResultsAt 10-fold cross-validation, our AI model classified COVID-19 and non COVID-19 patients with 0.78 sensitivity (95% confidence interval [CI] 0.74–0.81), 0.82 specificity (95% CI 0.78–0.85) and 0.89 area under the curve (AUC) (95% CI 0.86–0.91). For the independent dataset, AI showed 0.80 sensitivity (95% CI 0.72–0.86) (59/74), 0.81 specificity (29/36) (95% CI 0.73–0.87), and 0.81 AUC (95% CI 0.73– 0.87). Radiologists’ reading obtained 0.63 sensitivity (95% CI 0.52–0.74) and 0.78 specificity (95% CI 0.61–0.90) in one centre and 0.64 sensitivity (95% CI 0.52–0.74) and 0.86 specificity (95% CI 0.71–0.95) in the other.ConclusionsThis preliminary experience based on ten CNNs trained on a limited training dataset shows an interesting potential of AI for COVID-19 diagnosis. Such tool is in training with new CXRs to further increase its performance.Key pointsArtificial intelligence based on convolutional neural networks was preliminary applied to chest-X-rays of patients suspected to be infected by COVID-19.Convolutional neural networks trained on a limited dataset of 250 COVID-19 and 250 non-COVID-19 were tested on an independent dataset of 110 patients suspected for COVID-19 infection and provided a balanced performance with 0.80 sensitivity and 0.81 specificity.Training on larger multi-institutional datasets may allow this tool to increase its performance.

The aim of this paper was to compare the open 1-T (O-1T) versus the closed 1.5-T (C-1.5T) cardiac magnetic resonance (MR).The MR examinations of two concurrent cohorts (each including 100 subjects) of patients with suspected or known cardiac disease were reviewed. Such examinations were obtained using O-1T or C-1.5T MRI. The bright-blood cine, T1-weighted (T1), T2-weighed short-tau inversion recovery (T2-STIR), late gadolinium enhancement (LGE) sequences were performed. Signal-to-noise ratio of blood (SNRb) or myocardium (SNRm), and contrast-to-noise ratio of myocardium (CNRm) were calculated. Subjective image quality (SIQ) of each sequence was graded as 0 = poor, 1 = intermediate, or 2 = optimal. Each examination was considered as diagnostic when the report answered the clinical question.C-1.5T was better than O-1T on cine for SNRb(median 172 versus 452), SNRm(71 versus 160) and CNRm (107 versus 265) and on T2-STIR for SNRb(10 versus 29), SNRm(74 versus 261) and CNRm(-67 versus -233)(P 0.001). On LGE, SNRm was higher with O-1T than for C-1.5T (312 versus 79, P 0.001) while CNR was lower (158 versus 389; P 0.001). No significant differences were found for SNRb on LGE and both SNRm and CNRm on T1 (P ≥ 0.215). SIQ of O-1T was not significantly different from that of C-1.5T for both R1 and R2 for cine, T1, and LGE (P ≥ 0.157); for T2-STIR, SIQ of O-1T was significantly lower (P = 0.003). R1-R2 concordance was almost perfect (κ = 0.816-0.894), and all examinations were diagnostic.Even though quantitative measurements mostly favored C-1.5T, the SIQ of O-1T was not significantly different for any sequence, with the only exception of T2-STIR.

Purpose The aim of our work was to systematically review and meta-analyze epicardial adipose tissue (EAT) density values reported in literature, assessing potential correlations of EAT density with segmentation thresholds and other technical and clinical variables. Method A systematic search was performed, aiming for papers reporting global EAT density values in Hounsfield Units (HU) in patients undergoing chest CT for any clinical indication. After screening titles, abstract and full text of each retrieved work, studies reporting mean and standard deviation for EAT density were ultimately included. Technical, clinical and EAT data were extracted, and divided into subgroups according to clinical conditions of reported subjects. Pooled density analyses were performed both overall and for subgroups according to clinical conditions. Metaregression analyses were done to appraise the impact of clinical and technical variables on EAT volume. Results Out of 152 initially retrieved works, 13 were ultimately included, totaling for 7683 subjects. EAT density showed an overall pooled value of −85.86 HU (95% confidence interval [95% CI] −91.84, −79.89 HU), being −86.40 HU (95% CI −112.69, −60.12 HU) in healthy subjects and −80.71 HU (95% CI −87.43, −73.99 HU) in patients with coronary artery disease. EAT volume and lower and higher segmentation thresholds were found to be significantly correlated with EAT density (p = 0.044, p Conclusions Patients with coronary artery disease appear to present with higher EAT density values, while the correlations observed at metaregression highlight the need for well-established, shared thresholds for EAT segmentation.

Preclinical cardiac MR is challenging and time-consuming. A fast and comprehensive acquisition protocol and standardized image post-processing may improve preclinical research, reducing acquisition time, costs and variability of results. In the present study, we evaluated the feasibility of a contrast-enhanced 3D IntraGate steady-state cine sequence (ce-3D-IG-cine) with short acquisition time (11 min) for a single-shot combined characterization of left ventricle (LV) remodeling and infarct size (IS) in a mouse model of acute ischemia-reperfusion injury. Sixteen male C57BL/6N mice underwent 7T cardiac MR (Bruker, BioSpec 70/30) including optimized ce-3D-IG-cine (total scan time 11 min) at day 1, 5 and 28 after surgery. LV end-diastolic volume (EDVMR) and ejection fraction (EFMR) extracted from MR were compared to ones from short-axis (SA-EDVecho, SA-EFecho) and parasternal long-axis (LA-EDVecho, LA-EFecho) echocardiography. IS was manually and semiautomatically segmented from ce-3D-IG-cine using different standard deviation (SD +2, +3, +4, +5, +6 in respect to a reference tissue). Mice were sacrificed at day 28, immediately after imaging. IS at day 28 was compared to injury burden at histology. MR and echocardiographic morpho-functional parameters were compared, as IS from MR and histology. Bland-Altman plots were used to assess the agreement in ischemic burden segmentation. Volumetric and functional parameters measured on ce-3D-IG-cine correlated to the correspondent echocardiographic parameter (EDVMR vs SA-EDVecho: ρ = 0.813; EDVMR vs LA-EDVecho: ρ = 0.845; EFMR vs SA-EFecho ρ = 0.612; EFMR vs LA-EFecho ρ = 0.791; p < 0.001 in all cases). Manually segmented IS strongly correlated with the scar at histology (ρ = 0.904, p < 0.001). A threshold of +3SD showed the highest performance for semiautomatic assessment of IS compared to manual segmentation (ρ = 0.965, p < 0.001), with an overall reproducibility of 73%, and a peak reproducibility of 80% at day 1. The ce-3D-IG-cine sequence, manually or semiautomatically segmented using 3SD threshold, allows fast and comprehensive LV morpho-functional and structural characterization in myocardial ischemia-reperfusion injury model.

Epicardial adipose tissue (EAT) is a metabolically activated beige adipose tissue, non-homogeneously surrounding the myocardium. Physiologically, EAT regulates toxic fatty acids, protects the coronary arteries against mechanical strain, regulates proinflammatory cytokines, stimulates the production of nitric oxide, reduces oxidative stress, and works as a thermogenic source against hypothermia. Conversely, EAT has pathologic paracrine interactions with the surrounded vessels, and might favour the onset of atrial fibrillation. In addition, initial atherosclerotic lesions can promote inflammation and trigger the EAT production of cytokines increasing vascular inflammation, which, in turn, may help the development of collateral vessels but also of self-stimulating, dysregulated inflammatory process, increasing coronary artery disease severity. Variations in EAT were also linked to metabolic syndrome. Echocardiography first estimated EAT measuring its thickness on the free wall of the right ventricle but does not allow accurate volumetric EAT estimates. Cardiac CT (CCT) and cardiac MR (CMR) allow for three-dimensional EAT estimates, the former showing higher spatial resolution and reproducibility but being limited by radiation exposure and long segmentation times, the latter being radiation-free but limited by lower spatial resolution and reproducibility, higher cost, and difficulties for obese patients. EAT radiodensity at CCT could to be related to underlying metabolic processes. The correlation between EAT and response to certain pharmacological therapies has also been investigated, showing promising results. In the future, semi-automatic or fully automatic techniques, machine/deep-learning methods, if validated, will facilitate research for various EAT measures and may find a place in CCT/CMR reporting.