DEep LearnIng-based QuaNtification of epicardial adipose tissue predicts MACE in patients undergoing stress CMR.

BACKGROUND AND AIMS: This study investigated the additional prognostic value of epicardial adipose tissue (EAT) volume for major adverse cardiovascular events (MACE) in patients undergoing stress cardiac magnetic resonance (CMR) imaging. METHODS: 730 consecutive patients [mean age: 63 ± 10 years; 616 men] who underwent stress CMR for known or suspected coronary artery disease were randomly divided into derivation (n = 365) and validation (n = 365) cohorts. MACE was defined as non-fatal myocardial infarction and cardiac deaths. A deep learning algorithm was developed and trained to quantify EAT volume from CMR. EAT volume was adjusted for height (EAT volume index). A composite CMR-based risk score by Cox analysis of the risk of MACE was created. RESULTS: In the derivation cohort, 32 patients (8.7 %) developed MACE during a follow-up of 2103 days. Left ventricular ejection fraction (LVEF) < 35 % (HR 4.407 [95 % CI 1.903-10.202]; p<0.001), stress perfusion defect (HR 3.550 [95 % CI 1.765-7.138]; p<0.001), late gadolinium enhancement (LGE) (HR 4.428 [95%CI 1.822-10.759]; p = 0.001) and EAT volume index (HR 1.082 [95 % CI 1.045-1.120]; p<0.001) were independent predictors of MACE. In a multivariate Cox regression analysis, adding EAT volume index to a composite risk score including LVEF, stress perfusion defect and LGE provided additional value in MACE prediction, with a net reclassification improvement of 0.683 (95%CI, 0.336-1.03; p<0.001). The combined evaluation of risk score and EAT volume index showed a higher Harrel C statistic as compared to risk score (0.85 vs. 0.76; p<0.001) and EAT volume index alone (0.85 vs.0.74; p<0.001). These findings were confirmed in the validation cohort. CONCLUSIONS: In patients with clinically indicated stress CMR, fully automated EAT volume measured by deep learning can provide additional prognostic information on top of standard clinical and imaging parameters.

Predictors of adverse cardiac events of coronary myocardial bridging diagnosed with computed tomography angiography.

AIMS: Myocardial bridging (MB) is a frequent congenital anomaly of the epicardial coronary arteries commonly considered a benign condition. However, in some cases a complex interplay between anatomical, clinical and physiology factors may lead to adverse events, including sudden cardiac death. Coronary CT angiography (CCTA) emerged as the gold standard noninvasive imaging technique for the evaluation of MB. Aim of the study was to evaluate MB prevalence and anatomical features in a large population of patients who underwent CCTA for suspected CAD and to identify potential anatomical and clinical predictors of adverse cardiac events at long-term follow-up. METHODS AND RESULTS: Two-hundred and six patients (mean age 60.3 ± 11.8 years, 128 male) with MB diagnosed at CCTA were considered. A long MB was defined as ≥25 mm of overlying myocardium, whereas a deep MB as ≥2 mm of overlying myocardium. The study endpoint was the sum of the following adverse events: cardiac death, bridge-related acute coronary syndrome, hospitalization for angina or bridge-related ventricular arrhythmias and MB surgical treatment. Of the 206 patients enrolled in the study, 9 were lost to follow-up, whereas 197 (95.6%) had complete follow-up (mean 7.01 ± 3.0 years) and formed the analytic population. Nineteen bridge-related events occurred in 18 patients (acute coronary syndrome in 7, MB surgical treatment in 2 and hospitalization for bridge-related events in 10). Typical angina at the time of diagnosis and long MB resulted as significant independent predictors of adverse outcome. CONCLUSIONS: Typical angina and MB length ≥ 25 mm were independent predictors of cardiac events.

Circulating Small Extracellular Vesicles Reflect the Severity of Myocardial Damage in STEMI Patients.

Circulating small extracellular vesicles (sEVs) contribute to inflammation, coagulation and vascular injury, and have great potential as diagnostic markers of disease. The ability of sEVs to reflect myocardial damage assessed by Cardiac Magnetic Resonance (CMR) in ST-segment elevation myocardial infarction (STEMI) is unknown. To fill this gap, plasma sEVs were isolated from 42 STEMI patients treated by primary percutaneous coronary intervention (pPCI) and evaluated by CMR between days 3 and 6. Nanoparticle tracking analysis showed that sEVs were greater in patients with anterior STEMI (p = 0.0001), with the culprit lesion located in LAD (p = 0.045), and in those who underwent late revascularization (p = 0.038). A smaller sEV size was observed in patients with a low myocardial salvage index (MSI, p = 0.014). Patients with microvascular obstruction (MVO) had smaller sEVs (p < 0.002) and lower expression of the platelet marker CD41-CD61 (p = 0.039). sEV size and CD41-CD61 expression were independent predictors of MVO/MSI (OR [95% CI]: 0.93 [0.87-0.98] and 0.04 [0-0.61], respectively). In conclusion, we provide evidence that the CD41-CD61 expression in sEVs reflects the CMR-assessed ischemic damage after STEMI. This finding paves the way for the development of a new strategy for the timely identification of high-risk patients and their treatment optimization.

Early Biological Valve Failure: Structural Valve Degeneration, Thrombosis, or Endocarditis?

Biological valve failure (BVF) is an inevitable condition that compromises the durability of biological heart valves (BHVs). It stems from various causes, including rejection, thrombosis, and endocarditis, leading to a critical state of valve dysfunction. Echocardiography, cardiac computed tomography, cardiac magnetic resonance, and nuclear imaging play pivotal roles in the diagnostic multimodality workup of BVF. By providing a comprehensive overview of the pathophysiology of BVF and the diagnostic approaches in different clinical scenarios, this review aims to aid clinicians in their decision-making process. The significance of early detection and appropriate management of BVF cannot be overstated, as these directly impact patients' prognosis and their overall quality of life. Ensuring timely intervention and tailored treatments will not only improve outcomes but also alleviate the burden of this condition on patients' life. By prioritizing comprehensive assessments and adopting the latest advancements in diagnostic technology, medical professionals can significantly enhance their ability to manage BVF effectively.

Pre-TAVI aortic annulus sizing: comparison between manual and semi-automated new generation software measurements in operators with different experience.

OBJECTIVES: Aim of the study is to compare manual and semi-automatic measurements for aortic annulus assessment among different operators. METHODS: Eighty patients who underwent TAVI were retrospectively enrolled. The measurements manually performed by an experienced reader for aortic annulus (minimum and maximum diameters, perimeter, area), annulus-to-coronary ostia distance and time needed for the whole evaluation, were collected. The same operator (observer 1) and two less experienced readers (observer 2 and 3, with >5 years and 1 year of experience, respectively) assessed the same measurements using a semi-automatic software. Differences between manual and semi-automatic measurements, reading time and suggested valves size derived by CT were compared. RESULTS: Very good correlations were found between manual and software-aided measurements for aortic annulus area and perimeter in comparison with standard measurements for the three readers (ICC range 0.81-0.98). Good correlations were found for the distance with coronary ostia(0.75-0.79). The same area-derived prosthesis size for manual and semi-automatic measurements was selected in 96% of cases for observer 1; very good correlations were also found for observer 2 and 3 (ICC = 0.89 and 0.88, respectively). Using semi-automatic measurements, the mean time needed for CT images was significantly lower for observers 1 and 2 (1.50 and 1.72versus 3.14 min), respectively. CONCLUSIONS: Pre-TAVI CT using semi-automatic software allows accurate and reproducible measurements, reducing reconstruction time up to 50% and is reliable even for operators with different experience. ADVANCES IN KNOWLEDGE: The use of semi-automatic dedicated software for CT in TAVI planning is reliable even for operators without long time experience and allows accurate and reproducible measurements improving pre-TAVI workflow.

Quantification of extracellular volume with cardiac computed tomography in patients with dilated cardiomyopathy.

BACKGROUND: Cardiac computed tomography (CCT) was recently validated to measure extracellular volume (ECV) in the setting of cardiac amyloidosis, showing good agreement with cardiovascular magnetic resonance (CMR). However, no evidence is available with a whole-heart single source, single energy CT scanner in the clinical context of newly diagnosed left ventricular dysfunction. Therefore, the aim of this study was to test the diagnostic accuracy of ECVCCT in patients with a recent diagnosis of dilated cardiomyopathy, having ECVCMR as the reference technique. METHODS: 39 consecutive patients with newly diagnosed dilated cardiomyopathy (LVEF <50%) scheduled for clinically indicated CMR were prospectively enrolled. Myocardial segment evaluability assessment with each technique, agreement between ECVCMR and ECVCCT, regression analysis, Bland-Altman analysis and interclass correlation coefficient (ICC) were performed. RESULTS: Mean age of enrolled patients was 62 â€‹± â€‹11 years, and mean LVEF at CMR was 35.4 â€‹± â€‹10.7%. Overall radiation exposure for ECV estimation was 2.1 â€‹± â€‹1.1 â€‹mSv. Out of 624 myocardial segments available for analysis, 624 (100%) segments were assessable by CCT while 608 (97.4%) were evaluable at CMR. ECVCCT demonstrated slightly lower values compared to ECVCMR (all segments, 31.8 â€‹± â€‹6.5% vs 33.9 â€‹± â€‹8.0%, p â€‹< â€‹0.001). At regression analysis, strong correlations were described (all segments, r â€‹= â€‹0.819, 95% CI: 0.791 to 0.844). On Bland-Altman analysis, bias between ECVCMR and ECVCCT for global analysis was 2.1 (95% CI: -6.8 to 11.1). ICC analysis showed both high intra-observer and inter-observer agreement for ECVCCT calculation (0.986, 95%CI: 0.983 to 0.988 and 0.966, 95%CI: 0.960 to 0.971, respectively). CONCLUSIONS: ECV estimation with a whole-heart single source, single energy CT scanner is feasible and accurate. Integration of ECV measurement in a comprehensive CCT evaluation of patients with newly diagnosed dilated cardiomyopathy can be performed with a small increase in overall radiation exposure.

Comprehensive Evaluation of Left Ventricle Dysfunction by a New Computed Tomography Scanner: The E-PLURIBUS Study.

BACKGROUND: Although cardiac magnetic resonance (CMR) is considered the gold standard for myocardial fibrosis detection, cardiac computed tomography (CCT) is emerging as a promising alternative. OBJECTIVES: The purpose of this study was to assess feasibility and diagnostic accuracy of a comprehensive functional and anatomical evaluation with CCT as compared with CMR in patients with newly diagnosed left ventricular dysfunction (LVD). METHODS: A total of 128 consecutive patients with newly diagnosed LVD were screened. Based on the exclusion criteria, 28 cases were excluded. CCT was performed within 10 days from CMR. Biventricular volumes and ejection fraction, and presence and pattern of delayed enhancement (DE), were determined, along with evaluation of coronary arteries among patients undergoing invasive angiography in the 6 months after CCT. RESULTS: Six cases were excluded because of claustrophobia at CMR. Among the 94 patients who formed the study population, the concordance between CCT and CMR in suggesting the cause of the LVD was high (94.7%, 89/94 patients) in the overall population and was 100% for identifying ischemic cardiomyopathy. The CCT diagnostic rate for DE assessment was also high (96.7%, 1,544/1,598 territories) and similar to that of CMR (97.4%; P = 0.345, CCT vs CMR). Moreover, CCT showed high diagnostic accuracy in the detection of DE (94.8%, 95% CI: 93.6%-95.8%) in a territory-based analysis. Biventricular volumes and function parameters as measured by CCT and CMR were similar, without significant differences with the exception of a modest difference in RV volume. CCT was confirmed to be accurate for assessing arterial coronary circulation. The mean radiation exposure of the whole CCT was 7.78 ± 2.53 mSv (0.84 ± 0.24 mSv for DE). CONCLUSIONS: CCT performed with low-dose whole-heart coverage scanner and high-concentration contrast agent appears an effective noninvasive tool for a comprehensive assessment of patients with newly diagnosed LVD.

Approach to the Patient with Acute Aortic Syndromes in Light of the New Consensus Statement on Multimodality Imaging in Thoracic Aortic Diseases.

Acute aortic syndromes comprise a range of interrelated conditions including aortic dissection, intramural hematoma, penetrating atherosclerotic ulcer, and contained or not contained aortic aneurysm rupture. These syndromes are potentially life threatening; therefore, a rapid and accurate diagnosis is crucial. A new Clinical Consensus Statement on Aortic and Peripheral Vascular Disease has recently been published, and we will try to highlight the main innovations in the document.

Position-based dynamics simulator of vessel deformations for path planning in robotic endovascular catheterization.

A major challenge during autonomous navigation in endovascular interventions is the complexity of operating in a deformable but constrained workspace with an instrument. Simulation of deformations for it can provide a cost-effective training platform for path planning. Aim of this study is to develop a realistic, auto-adaptive, and visually plausible simulator to predict vessels' global deformation induced by the robotic catheter's contact and cyclic heartbeat motion. Based on a Position-based Dynamics (PBD) approach for vessel modeling, Particle Swarm Optimization (PSO) algorithm is employed for an auto-adaptive calibration of PBD deformation parameters and of the vessels movement due to a heartbeat. In-vitro experiments were conducted and compared with in-silico results. The end-user evaluation results were reported through quantitative performance metrics and a 5-Point Likert Scale questionnaire. Compared with literature, this simulator has an error of 0.23±0.13% for deformation and 0.30±0.85mm for the aortic root displacement. In-vitro experiments show an error of 1.35±1.38mm for deformation prediction. The end-user evaluation results show that novices are more accustomed to using joystick controllers, and cardiologists are more satisfied with the visual authenticity. The real-time and accurate performance of the simulator make this framework suitable for creating a dynamic environment for autonomous navigation of robotic catheters.

The Applications of Artificial Intelligence in Cardiovascular Magnetic Resonance-A Comprehensive Review.

Cardiovascular disease remains an integral field on which new research in both the biomedical and technological fields is based, as it remains the leading cause of mortality and morbidity worldwide. However, despite the progress of cardiac imaging techniques, the heart remains a challenging organ to study. Artificial intelligence (AI) has emerged as one of the major innovations in the field of diagnostic imaging, with a dramatic impact on cardiovascular magnetic resonance imaging (CMR). AI will be increasingly present in the medical world, with strong potential for greater diagnostic efficiency and accuracy. Regarding the use of AI in image acquisition and reconstruction, the main role was to reduce the time of image acquisition and analysis, one of the biggest challenges concerning magnetic resonance; moreover, it has been seen to play a role in the automatic correction of artifacts. The use of these techniques in image segmentation has allowed automatic and accurate quantification of the volumes and masses of the left and right ventricles, with occasional need for manual correction. Furthermore, AI can be a useful tool to directly help the clinician in the diagnosis and derivation of prognostic information of cardiovascular diseases. This review addresses the applications and future prospects of AI in CMR imaging, from image acquisition and reconstruction to image segmentation, tissue characterization, diagnostic evaluation, and prognostication.

Changing Paradigms in the Diagnosis of Ischemic Heart Disease by Multimodality Imaging.

Coronary artery disease (CAD) represents the most common cardiovascular disease, with high morbidity and mortality. Historically patients with chest pain of suspected coronary origin have been assessed with functional tests, capable to detect haemodynamic consequences of coronary obstructions through depiction of electrocardiographic changes, myocardial perfusion defects or regional wall motion abnormalities under stress condition. Stress echocardiography (SE), single-photon emission computed tomography (SPECT), positron emission tomography (PET) and cardiovascular magnetic resonance (CMR) represent the functional techniques currently available, and technical developments contributed to increased diagnostic performance of these techniques. More recently, cardiac computed tomography angiography (cCTA) has been developed as a non-invasive anatomical test for a direct visualisation of coronary vessels and detailed description of atherosclerotic burden. Cardiovascular imaging techniques have dramatically enhanced our knowledge regarding physiological aspects and myocardial implications of CAD. Recently, after the publication of important trials, international guidelines recognised these changes, updating indications and level of recommendations. This review aims to summarise current standards with main novelties and specific limitations, and a diagnostic algorithm for up-to-date clinical management is also proposed.

Diagnostic performance of deep learning algorithm for analysis of computed tomography myocardial perfusion.

PURPOSE: To evaluate the diagnostic accuracy of a deep learning (DL) algorithm predicting hemodynamically significant coronary artery disease (CAD) by using a rest dataset of myocardial computed tomography perfusion (CTP) as compared to invasive evaluation. METHODS: One hundred and twelve consecutive symptomatic patients scheduled for clinically indicated invasive coronary angiography (ICA) underwent CCTA plus static stress CTP and ICA with invasive fractional flow reserve (FFR) for stenoses ranging between 30 and 80%. Subsequently, a DL algorithm for the prediction of significant CAD by using the rest dataset (CTP-DLrest) and stress dataset (CTP-DLstress) was developed. The diagnostic accuracy for identification of significant CAD using CCTA, CCTA + CTP stress, CCTA + CTP-DLrest, and CCTA + CTP-DLstress was measured and compared. The time of analysis for CTP stress, CTP-DLrest, and CTP-DLStress was recorded. RESULTS: Patient-specific sensitivity, specificity, NPV, PPV, accuracy, and area under the curve (AUC) of CCTA alone and CCTA + CTPStress were 100%, 33%, 100%, 54%, 63%, 67% and 86%, 89%, 89%, 86%, 88%, 87%, respectively. Patient-specific sensitivity, specificity, NPV, PPV, accuracy, and AUC of CCTA + DLrest and CCTA + DLstress were 100%, 72%, 100%, 74%, 84%, 96% and 93%, 83%, 94%, 81%, 88%, 98%, respectively. All CCTA + CTP stress, CCTA + CTP-DLRest, and CCTA + CTP-DLStress significantly improved detection of hemodynamically significant CAD compared to CCTA alone (p < 0.01). Time of CTP-DL was significantly lower as compared to human analysis (39.2 ± 3.2 vs. 379.6 ± 68.0 s, p < 0.001). CONCLUSION: Evaluation of myocardial ischemia using a DL approach on rest CTP datasets is feasible and accurate. This approach may be a useful gatekeeper prior to CTP stress..

The Role of Multimodality Imaging in Left-Sided Prosthetic Valve Dysfunction.

Prosthetic valve (PV) dysfunction (PVD) is a complication of mechanical or biological PV. Etiologic mechanisms associated with PVD include fibrotic pannus ingrowth, thrombosis, structural valve degeneration, and endocarditis resulting in different grades of obstruction and/or regurgitation. PVD can be life threatening and often challenging to diagnose due to the similarities between the clinical presentations of different causes. Nevertheless, identifying the cause of PVD is critical to treatment administration (thrombolysis, surgery, or percutaneous procedure). In this report, we review the role of multimodality imaging in the diagnosis of PVD. Specifically, this review discusses the characteristics of advanced imaging modalities underlying the importance of an integrated approach including 2D/3D transthoracic and transesophageal echocardiography, fluoroscopy, and computed tomography. In this scenario, it is critical to understand the strengths and weaknesses of each modality according to the suspected cause of PVD. In conclusion, for patients with suspected or known PVD, this stepwise imaging approach may lead to a simplified, more rapid, accurate and specific workflow and management.

Cardiac Care of Non-COVID-19 Patients During the SARS-CoV-2 Pandemic: The Pivotal Role of CCTA.

Aim: The aim of this study is to evaluate the potential use of coronary CT angiography (CCTA) as the sole available non-invasive diagnostic technique for suspected coronary artery disease (CAD) during the coronavirus disease 2019 (COVID-19) pandemic causing limited access to the hospital facilities. Methods and Results: A consecutive cohort of patients with suspected stable CAD and clinical indication to non-invasive test was enrolled in a hub hospital in Milan, Italy, from March 9 to April 30, 2020. Outcome measures were obtained as follows: cardiac death, ST-elevation myocardial infarction (STEMI), non-ST-elevation myocardial infarction (NSTEMI), and unstable angina. All the changes in medical therapy following the result of CCTA were annotated. A total of 58 patients with a mean age of 64 ± 11 years (36 men and 22 women) were enrolled. CCTA showed no CAD in 14 patients (24.1%), non-obstructive CAD in 30 (51.7%) patients, and obstructive CAD in 14 (24.1%) patients. Invasive coronary angiography (ICA) was considered deferrable in 48 (82.8%) patients. No clinical events were recorded after a mean follow-up of 376.4 ± 32.1 days. Changes in the medical therapy were significantly more prevalent in patients with vs. those without CAD at CCTA. Conclusion: The results of the study confirm the capability of CCTA to safely defer ICA in the majority of symptomatic patients and to correctly identify those with critical coronary stenoses necessitating coronary revascularization. This characteristic could be really helpful especially when the hospital resources are limited.

Feasibility of late gadolinium enhancement (LGE) in ischemic cardiomyopathy using 2D-multisegment LGE combined with artificial intelligence reconstruction deep learning noise reduction algorithm.

BACKGROUND: Despite the low spatial resolution of 2D-multisegment late gadolinium enhancement (2D-MSLGE) sequences, it may be useful in uncooperative patients instead of standard 2D single segmented inversion recovery gradient echo late gadolinium enhancement sequences (2D-SSLGE). The aim of the study is to assess the feasibility and comparison of 2D-MSLGE reconstructed with artificial intelligence reconstruction deep learning noise reduction (NR) algorithm compared to standard 2D-SSLGE in consecutive patients with ischemic cardiomyopathy (ICM). METHODS: Fifty-seven patients with known ICM referred for a clinically indicated CMR were enrolled in this study. 2D-MSLGE were reconstructed using a growing level of NR (0%,25%,50%,75%and 100%). Subjective image quality, signal to noise ratio (SNR) and contrast to noise ratio (CNR) were evaluated in each dataset and compared to standard 2D-SSLGE. Moreover, diagnostic accuracy, LGE mass and scan time were compared between 2D-MSLGE with NR and 2D-SSLGE. RESULTS: The application of NR reconstruction ≥50% to 2D-MSLGE provided better subjective image quality, CNR and SNR compared to 2D-SSLGE (p < 0.01). The best compromise in terms of subjective and objective image quality was observed for values of 2D-MSLGE 75%, while no differences were found in terms of LGE quantification between 2D-MSLGE versus 2D-SSLGE, regardless the NR applied. The sensitivity, specificity, negative predictive value, positive predictive value and accuracy of 2D-MSLGE NR 75% were 87.77%,96.27%,96.13%,88.16% and 94.22%, respectively. Time of acquisition of 2D-MSLGE was significantly shorter compared to 2D-SSLGE (p < 0.01). CONCLUSION: When compared to standard 2D-SSLGE, the application of NR reconstruction to 2D-MSLGE provides superior image quality with similar diagnostic accuracy.

Additional diagnostic value of cardiac magnetic resonance feature tracking in patients with biopsy-proven arrhythmogenic cardiomyopathy.

BACKGROUND: We aim to evaluate the value of Cardiac magnetic resonance (CMR) feature tracking (CMR-FT) in addition to Task Force Criteria(TFC) in patients with (arrhythmogenic cardiomyopathy) AC biopsy-proved. METHODS: Thirty-five patients with AC histologically proven who performed CMR with late gadolinium enhancement (LGE) acquisition were enrolled. The study population was divided in Group1 (negative CMR TFC and LV ejection fraction≥55%) and Group2 (positive CMR TFC and/or LVEF<55%) and compared to an age and gender-matched control group. CMR datasets of all patients were analyzed to calculate LV indexed end-diastolic (LVEDi) and end-systolic (LVESi) volumes and RV indexed end-diastolic (RVEDi) and end-systolic (RVESi) volumes, both LV ejection fraction (LVEF) and RV ejection fraction (RVEF). Moreover, LV and RV global longitudinal (GLS), circumferential (GCS) and radial (GRS) strain were measured. RESULTS: The AC patients showed both higher LVEDi (p:0.002) and RVEDi (p:0.017) and lower LVEF (p: 0.016) as compared to control patients. Moreover, AC patients showed impaired LV-GLS (p < 0.001), LV-GRS (p < 0.001), LV-GCS (p < 0.001) and RV-GRS (p:0.026) as compared to control subjects. Group1 patients showed a significant reduction of LV-GRS (p < 0.05) and LV-GCS p < 0.01) as compared to control subjects. At univariate analysis LV-GCS was the most discriminatory parameter between Group1 vs heathy subjects with an optimal cut-off of -15.8 (Sensitivity: 74%; Specificity: 10%). CONCLUSIONS: In patients with AC biopsy-proven, CMR-FT could improve the diagnostic yield in the subset of patients who results negative for imaging TFC criteria resulting as useful gatekeeper for indication of myocardial biopsy in case of equivocal clinical and imaging presentation.

Digital PCR for high sensitivity viral detection in false-negative SARS-CoV-2 patients.

Patients requiring diagnostic testing for coronavirus disease 2019 (COVID-19) are routinely assessed by reverse-transcription quantitative polymerase chain reaction (RT-qPCR) amplification of Sars-CoV-2 virus RNA extracted from oro/nasopharyngeal swabs. Despite the good specificity of the assays certified for SARS-CoV-2 molecular detection, and a theoretical sensitivity of few viral gene copies per reaction, a relatively high rate of false negatives continues to be reported. This is an important challenge in the management of patients on hospital admission and for correct monitoring of the infectivity after the acute phase. In the present report, we show that the use of digital PCR, a high sensitivity method to detect low amplicon numbers, allowed us to correctly detecting infection in swab material in a significant number of false negatives. We show that the implementation of digital PCR methods in the diagnostic assessment of COVID-19 could resolve, at least in part, this timely issue.

State of the art paper: Cardiovascular CT for planning ventricular tachycardia ablation procedures.

In the last 20 years coronary computed tomography angiography (CCTA) gained a pivotal role in the evaluation of patients with suspected coronary artery disease (CAD) as finally recognized by the ESC guidelines on stable CAD. Technological advances have progressively improved the temporal resolution of CT scanners, contemporary reducing acquisition time, radiation dose and contrast volume needed for the whole heart volume acquisition, further expanding the role of cardiac CT beyond coronary anatomy evaluation. Aim of the present review is to discuss use and benefit of cardiac CT for the planning and preparation of VT ablation.

Quantitative Evaluation of COVID-19 Pneumonia Lung Extension by Specific Software and Correlation with Patient Clinical Outcome.

Lung infection named as COVID-19 is an infectious disease caused by the most recently discovered coronavirus 2 (SARS-CoV-2). CT (computed tomography) has been shown to have good sensitivity in comparison with RT-PCR, particularly in early stages. However, CT findings appear to not always be related to a certain clinical severity. The aim of this study is to evaluate a correlation between the percentage of lung parenchyma volume involved with COVID-19 infection (compared to the total lung volume) at baseline diagnosis and correlated to the patient's clinical course (need for ventilator assistance and or death). All patients with suspected COVID-19 lung disease referred to our imaging department for Chest CT from 24 February to 6 April 2020were included in the study. Specific CT features were assessed including the amount of high attenuation areas (HAA) related to lung infection. HAA, defined as the percentage of lung parenchyma above a predefined threshold of -650 (HAA%, HAA/total lung volume), was automatically calculated using a dedicated segmentation software. Lung volumes and CT findings were correlated with patient's clinical course. Logistic regressions were performed to assess the predictive value of clinical, inflammatory and CT parameters for the defined outcome. In the overall population we found an average infected lung volume of 31.4 ± 26.3% while in the subgroup of patients who needed ventilator assistance and who died as well as the patients who died without receiving ventilator assistance the volume of infected lung was significantly higher 41.4 ± 28.5 and 72.7 ± 36.2 (p < 0.001). In logistic regression analysis best predictors for ventilation and death were the presence of air bronchogram (p = 0.006), crazy paving (p = 0.007), peripheral distribution (p < 0.001), age (p = 0.002), fever at admission (p = 0.007), dyspnea (p = 0.002) and cardiovascular comorbidities (p < 0.001). In multivariable analysis, quantitative CT parameters and features added incremental predictive value beyond a model with only clinical parameters (area under the curve, 0.78 vs. 0.74, p = 0.02). Our study demonstrates that quantitative evaluation of lung volume involved by COVID-19 pneumonia helps to predict patient's clinical course.