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Objective: To investigate the association between sarcopenia, as appraised with CT-derived muscle metrics, and cardiovascular status, as assessed via coronary CT angiography (CCTA) using the Coronary Artery Disease-Reporting and Data System (CAD-RADS) and with pericoronary adipose tissue (pCAT) metrics. Methods: A retrospective observational study conducted on patients who underwent CCTA. The cross-sectional area (CSA) and attenuation values of the paravertebral muscles at the T8 level and the pectoralis major muscles at the T6 level were measured. The patient height was employed for the normalization of the skeletal muscle CSA. The pCAT attenuation around the coronary arteries was assessed, and the CAD severity was graded using the CAD-RADS reporting system. Regression analyses were performed to assess the impact of demographics, clinical factors, and CT variables on the CAD-RADS and pCAT. Results: A total of 220 patients were included (132 males, median age 65 years). Regression analyses showed the associations of CAD with age and sex (p < 0.001). Familiarity with CAD was related to the left anterior descending artery pCAT (p = 0.002) and circumflex artery pCAT (p = 0.018), whereas age was related to the left anterior descending artery pCAT (p = 0.032). Weak positive correlations were found between the lower muscle density and lower pCAT attenuation (ρ = 0.144–0.240, p < 0.039). Conclusions: This study demonstrated weak associations between the sarcopenia indicators and the cardiovascular risk, as assessed by the CAD severity and pCAT inflammation. However, these correlations were not strong predictors of CAD severity, as age and traditional cardiovascular risk factors overshadowed the impact of sarcopenia in the cardiovascular risk assessment.

Abstract Sample size, namely the number of subjects that should be included in a study to reach the desired endpoint and statistical power, is a fundamental concept of scientific research. Indeed, sample size must be planned a priori, and tailored to the main endpoint of the study, to avoid including too many subjects, thus possibly exposing them to additional risks while also wasting time and resources, or too few subjects, failing to reach the desired purpose. We offer a simple, go-to review of methods for sample size calculation for studies concerning data reliability (repeatability/reproducibility) and diagnostic performance. For studies concerning data reliability, we considered Cohen’s κ or intraclass correlation coefficient (ICC) for hypothesis testing, estimation of Cohen’s κ or ICC, and Bland-Altman analyses. With regards to diagnostic performance, we considered accuracy or sensitivity/specificity versus reference standards, the comparison of diagnostic performances, and the comparisons of areas under the receiver operating characteristics curve. Finally, we considered the special cases of dropouts or retrospective case exclusions, multiple endpoints, lack of prior data estimates, and the selection of unusual thresholds for α and β errors. For the most frequent cases, we provide example of software freely available on the Internet. Relevance statement Sample size calculation is a fundamental factor influencing the quality of studies on repeatability/reproducibility and diagnostic performance in radiology. Key points • Sample size is a concept related to precision and statistical power. • It has ethical implications, especially when patients are exposed to risks. • Sample size should always be calculated before starting a study. • This review offers simple, go-to methods for sample size calculations. Graphical Abstract

Abstract 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.

In this study, we aimed to quantify LGE and edema at short-tau inversion recovery sequences on cardiac magnetic resonance (CMR) in patients with myocarditis. We retrospectively evaluated CMR examinations performed during the acute phase and at follow-up. Forty-seven patients were eligible for retrospective LGE assessment, and, among them, twenty-five patients were eligible for edema evaluation. Both groups were paired with age- and sex-matched controls. The median left ventricle LGE was 6.4% (interquartile range 5.0–9.2%) at the acute phase, 4.4% (3.3–7.2%) at follow-up, and 4.3% (3.0–5.3%) in controls, the acute phase being higher than both follow-up and controls (p < 0.001 for both), while follow-up and controls did not differ (p = 0.139). An optimal threshold of 5.0% was obtained for LGE with 87% sensitivity and 48% specificity; the positive likelihood ratio (LR) was 1.67, and the negative LR was 0.27. Edema was 12.8% (9.4–18.1%) at the acute phase, 7.3% (5.5–8.8%) at follow-up, and 6.7% (5.6–8.6%) in controls, the acute phase being higher than both follow-up and controls (both p < 0.001), while follow-up and controls did not differ (p = 0.900). An optimal threshold of 9.5% was obtained for edema with a sensitivity of 76% and a specificity of 88%; the positive LR was 6.33, and the negative LR was 0.27. LGE and edema thresholds are useful in cases of suspected mild myocarditis.

Abstract 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 < 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 < 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.

Abstract 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.

We aimed to explore the feasibility of 4D flow magnetic resonance imaging (MRI) for patients undergoing thoracic aorta endovascular repair (TEVAR). We retrospectively evaluated ten patients (two female), with a mean (±standard deviation) age of 61 ± 20 years, undergoing MRI for a follow-up after TEVAR. All 4D flow examinations were performed using a 1.5-T system (MAGNETOM Aera, Siemens Healthcare, Erlangen, Germany). In addition to the standard examination protocol, a 4D flow-sensitive 3D spatial-encoding, time-resolved, phase-contrast prototype sequence was acquired. Among our cases, flow evaluation was feasible in all patients, although we observed some artifacts in 3 out of 10 patients. Three individuals displayed a reduced signal within the vessel lumen where the endograft was placed, while others presented with turbulent or increased flow. An aortic endograft did not necessarily hinder the visualization of blood flow through 4D flow sequences, although the graft could generate flow artifacts in some cases. A 4D Flow MRI may represent the ideal tool to follow up on both healthy subjects deemed to be at an increased risk based on their anatomical characteristics or patients submitted to TEVAR for whom a surveillance protocol with computed tomography angiography would be cumbersome and unjustified.

Abstract 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.

Abstract Objectives Iodinated contrast media (ICM) could be more appropriately dosed on patient lean body weight (LBW) than on total body weight (TBW). Methods After Ethics Committee approval, trial registration NCT03384979, patients aged ≥ 18 years scheduled for multiphasic abdominal CT were randomised for ICM dose to LBW group (0.63 gI/kg of LBW) or TBW group (0.44 gI/kg of TBW). Abdominal 64-row CT was performed using 120 kVp, 100–200 mAs, rotation time 0.5 s, pitch 1, Iopamidol (370 mgI/mL), and flow rate 3 mL/s. Levene, Mann–Whitney U, and χ 2 tests were used. The primary endpoint was liver contrast enhancement (LCE). Results Of 335 enrolled patients, 17 were screening failures; 44 dropped out after randomisation; 274 patients were analysed (133 LBW group, 141 TBW group). The median age of LBW group (66 years) was slightly lower than that of TBW group (70 years). Although the median ICM-injected volume was comparable between groups, its variability was larger in the former (interquartile range 27 mL versus 21 mL, p = 0.01). The same was for unenhanced liver density (IQR 10 versus 7 HU) (p = 0.02). Median LCE was 40 (35–46) HU in the LBW group and 40 (35–44) HU in the TBW group, without significant difference for median (p = 0.41) and variability (p = 0.23). Suboptimal LCE (

Abstract Background Contrast-enhanced cardiac magnetic resonance (CMR) is pivotal for evaluating chronic myocardial infarction (CMI). Concerns about safety of gadolinium-based contrast agents favour dose reduction. We assessed image quality of scar tissue in CMRs performed with different doses of gadobutrol in CMI patients. Methods Informed consent was waived for this Ethics Committee-approved single-centre retrospective study. Consecutive contrast-enhanced CMRs from CMI patients were retrospectively analysed according to the administered gadobutrol dose (group A, 0.10 mmol/kg; group B, 0.15 mmol/kg; group C, 0.20 mmol/kg). We calculated the signal-to-noise ratio for scar tissue (SNRscar) and contrast-to-noise ratio between scar and either remote myocardium (CNRscar-rem) or blood (CNRscar-blood). Results Of 79 CMRs from 79 patients, 22 belonged to group A, 26 to group B, and 31 to group C. The groups were homogeneous for age, sex, left ventricular morpho-functional parameters, and percentage of scar tissue over whole myocardium (p ≥ 0.300). SNRscar was lower in group A (46.4; 40.3–65.1) than in group B (70.1; 52.2–111.5) (p = 0.013) and group C (72.1; 59.4–100.0) (p = 0.002), CNRscar-rem was lower in group A (62.9; 52.2–87.4) than in group B (96.5; 73.1–152.8) (p = 0.008) and in group C (103.9; 83.9–132.0) (p = 0.001). No other significant differences were found (p ≥ 0.335). Conclusions Gadobutrol at 0.10 mmol/kg provides inferior scar image quality of CMI than 0.15 and 0.20 mmol/kg; the last two dosages seem to provide similar LGE. Thus, for CMR of CMI, 0.15 mmol/kg of gadobutrol can be suggested instead of 0.20 mmol/kg, with no hindrance to scar visualisation. Dose reduction would not impact on diagnostic utility of CMR examinations.

We aimed to investigate whether unenhanced magnetic resonance imaging (MRI) could represent a safe and highly sensitive tool for endoleak screening in patients treated with endovascular aneurysm repair (EVAR) using computed tomography angiography (CTA) as a reference standard. Patients who underwent CTA for EVAR follow-up at our institution were prospectively enrolled. All MRI examinations were performed with a 1.5 T unit. The true-FISP and HASTE sequences of the MRI scans were assessed for the presence of hyperintensity within the aneurysm sac outside the graft, whereas phase-contrast through-plane sequences were used for blood flow quantification. We included 45 patients, 5 (11%) of whom were female. The median age was 73 years (IQR 68–78 years). Among our patients, 19 (42%) were positive for endoleaks at CTA, of whom 13 (68%) had type II endoleaks and 6 (32%) had type I endoleaks. There were no significant differences in age, sex, aneurysm type, prosthesis type, or contrast-to-noise ratio between hyperintensity and thrombus between patients with and without endoleaks (p > 0.300). The combined evaluation of true-FISP and HASTE yielded 100% sensitivity (95% CI: 79–100%) and 19% specificity (95% CI: 7–40%). Patients with a positive CTA had a median thrombus flow of 0.06 L/min (IQR 0.03–0.23 L/min), significantly greater than that of patients with a negative CTA (p = 0.007). Setting a threshold at 0.01 L/min, our MRI protocol yielded 100% sensitivity, 56% specificity, and an AUC of 0.76 (95% CI 0.60–0.91). In conclusion, unenhanced MRI has perfect sensitivity for endoleak detection, although with subpar specificity that could be improved with phase-contrast flow analysis.

Abstract We reviewed technical parameters, acquisition protocols and adverse reactions (ARs) for contrast-enhanced spectral mammography (CESM). A systematic search in databases, including MEDLINE/EMBASE, was performed to extract publication year, country of origin, study design; patients; mammography unit/vendor, radiation dose, low-/high-energy tube voltage; contrast molecule, concentration and dose; injection modality, ARs and acquisition delay; order of views; examination time. Of 120 retrieved articles, 84 were included from 22 countries (September 2003–January 2019), totalling 14012 patients. Design was prospective in 44/84 studies (52%); in 70/84 articles (83%), a General Electric unit with factory-set kVp was used. Per-view average glandular dose, reported in 12/84 studies (14%), ranged 0.43–2.65 mGy. Contrast type/concentration was reported in 79/84 studies (94%), with Iohexol 350 mgI/mL mostly used (25/79, 32%), dose and flow rate in 72/84 (86%), with 1.5 mL/kg dose at 3 mL/s in 62/72 studies (86%). Injection was described in 69/84 articles (82%), automated in 59/69 (85%), manual in 10/69 (15%) and flush in 35/84 (42%), with 10–30 mL dose in 19/35 (54%). An examination time

Introduction: To evaluate myocardial strain and extracellular volume in myotonic dystrophy type 1 (DM1) patients as potential imaging biomarkers of subclinical cardiac pathology.Materials and methods: We retrospectively analyzed 9 DM1 patients without apparent cardiac disease who had undergone cardiac magnetic resonance at our center. Patients were age- and sex-matched with healthy controls. The Mann-Whitney U test was used to compare cardiac strain between the two groups. The t-test was used to compare the extracellular volume obtained in DM1 patients with that in healthy subject. Spearman's ρ was used for studying the associations among imaging parameters.Results: Global cardiac strain (median −19.1%; IQR −20.5%, −16.5%) in DM1 patients was lower (p = 0.011) than that in controls (median−21.7%; IQR−22.7%,-21.3%). Global extracellular volume in DM1 patients (median 32.3%; IQR 29.3%,36.8%) was significantly (p = 0.008) higher than that reported in literature in healthy subjects (median 25.6%; IQR 19.9%,31.9%). Global cardiac strain showed a strong, positive correlation with septal strain (ρ = 0.767, p = 0.016) and with both global (ρ = 0.733 p = 0.025) and septal extracellular volume (ρ = 0.767, p = 0.016).Discussion: The increase in cardiac extracellular volume and decrease in strain are signs of early cardiac pathology in DM1. Physicians dealing with DM1 may take into consideration cardiac magnetic resonance as a screening tool to identify early cardiac involvement in this condition.

The “bovine” aortic arch is an anatomic variant consisting in a common origin of the innominate and left carotid artery (CILCA), associated with a greater risk of thoracic aortic diseases (aneurysms and dissections), stroke, and complications after endovascular procedures. CILCA can be detected by visual assessment of computed tomography (CT) chest scans, but it is rarely reported. We developed a deep learning (DL) segmentation-plus-classification system to automatically detect CILCA based on 302 CT studies acquired at 2 centers. One model (3D U-Net) was trained from scratch (supervised by manual segmentation), validated, and tested for the automatic segmentation of the aortic arch and supra-aortic vessels. Three DL architectures (ResNet50, DenseNet-201, and SqueezeNet), pre-trained over millions of common images, were trained, validated, and tested for the automatic classification of CILCA versus non-CILCA, supervised by radiologist’s classification. The 3D U-Net-plus-DenseNet-201 was found to be the best system (Dice index 0.912); its classification performance obtained from internal, independent testing on 126 patients gave a receiver operating characteristic area under the curve of 87.0%, sensitivity 66.7%, specificity 90.5%, positive predictive value 87.5%, negative predictive value 73.1%, positive likelihood ratio 7.0, and negative likelihood ratio 0.4. In conclusion, a combined DL system applied to chest CT scans was developed and proven to be an effective tool to detect individuals with “bovine” aortic arch with a low rate of false-positive findings.