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

Photon-counting detector computed tomography in cardiac imaging

Photon-counting detector computed tomography (PCD-CT) has emerged as a revolutionary technology in CT imaging. PCD-CT offers significant advancements over conventional energy-integrating detector CT, including increased spatial resolution, artefact reduction and inherent spectral imaging capabilities. In cardiac imaging, PCD-CT can offer a more accurate assessment of coronary artery disease, plaque characterisation and the in-stent lumen. Additionally, it might improve the visualisation of myocardial fibrosis through qualitative late enhancement imaging and quantitative extracellular volume measurements. The use of PCD-CT in cardiac imaging holds significant potential, positioning itself as a valuable modality that could serve as a one-stop-shop by integrating both angiography and tissue characterisation into a single examination. Despite its potential, large-scale clinical trials, standardisation of protocols and cost-effectiveness considerations are required for its broader integration into clinical practice. This narrative review provides an overview of the current literature on PCD-CT regarding the possibilities and limitations of cardiac imaging.

Strong Diagnostic Performance of Single Energy 256-row Multidetector Computed Tomography with Deep Learning Image Reconstruction in the Assessment of Myocardial Fibrosis

Objective Although magnetic resonance imaging (MRI) is the gold standard for evaluating abnormal myocardial fibrosis and extracellular volume (ECV) of the left ventricular myocardium (LVM), a similar evaluation has recently become possible using computed tomography (CT). In this study, we investigated the diagnostic accuracy of a new 256-row multidetector CT with a low tube-voltage single energy scan and deep-learning-image reconstruction (DLIR) in detecting abnormal late enhancement (LE) in LVM. Methods We evaluated the diagnostic performance of CT for detecting LE in LVM and compared the results with those of MRI as a reference. We also measured the ECV of the LVM on CT and compared the results with those on MRI. Materials We analyzed 50 consecutive patients who underwent cardiac CT, including a late-phase scan and MRI, within three months of suspected cardiomyopathy. All patients underwent 256-slice CT (Revolution APEX; GE Healthcare, Waukesha, USA) with a low tube-voltage (70 kV) single energy scan and DLIR for a late-phase scan. Results In patient- and segment-based analyses, the sensitivity, specificity, and accuracy of detection of LE on CT were 94% and 85%, 100% and 95%, and 96% and 93%, respectively. The ECV of LVM per patient on CT and MRI was 33.0±6.2% and 35.9±6.1%, respectively. These findings were extremely strongly correlated, with a correlation coefficient of 0.87 (p<0.0001). The effective radiation dose on late-phase scanning was 2.4±0.9 mSv. Conclusion The diagnostic performance of 256-row multislice CT with a low tube voltage and DLIR for detecting LE and measuring ECV in LVM is credible.

Advanced myocardial characterization and function with cardiac CT

Non-invasive imaging with characterization and quantification of the myocardium with computed tomography (CT) became feasible owing to recent technical developments in CT technology. Cardiac CT can serve as an alternative modality when cardiac magnetic resonance imaging and/or echocardiography are contraindicated, not feasible, inconclusive, or non-diagnostic. This review summarizes the current and potential future role of cardiac CT for myocardial characterization including a summary of late enhancement techniques, extracellular volume quantification, and strain analysis. In addition, this review highlights potential fields for research about myocardial characterization with CT to possibly include it in clinical routine in the future.

Comparison of left ventricular mass and wall thickness between cardiac computed tomography angiography and cardiac magnetic resonance imaging using machine learning algorithms

Aims

Cardiac magnetic resonance imaging (MRI) is the gold standard in the assessment of left ventricle (LV) mass and wall thickness. In recent years, cardiac computed tomography angiography (CCTA) has gained widespread usage as an imaging modality. Despite this, limited previous investigations have specifically addressed the potential of CCTA as an alternative modality for quantitative LV assessment. The aim of this study was to compare CCTA derived LV mass and wall thickness with cardiac MRI utilizing machine learning algorithms.

Methods and results

Fifty-seven participants who underwent both CCTA and cardiac MRI were identified. LV mass and wall thickness was calculated using LV contours which were automatically placed using in-house developed machine learning models. Pearson's correlation coefficients were calculated along with Bland-Altman plots to assess the agreement between the LV mass and wall thickness per region on CCTA and cardiac MRI. Inter-observer correlations were tested using Pearson's correlation coefficient. Average LV mass and wall thickness for CCTA and cardiac MRI were 127 g, 128 g, 7, and 8 mm, respectively. Bland-Altman plots demonstrated mean differences and corresponding 95% limits of agreement of -1.26 (25.06; -27.58) and -0.57 (1.78; -2.92), for LV mass and average LV wall thickness, respectively. Mean differences and corresponding 95% limits of agreement for wall thickness per region were -0.75 (1.34; -2.83), -0.58 (2.14; -3.30), and -0.29 (3.21; -3.79) for the basal, mid, and apical regions, respectively. Inter-observer correlations were excellent.

Conclusion

Quantitative assessment of LV mass and wall thickness on CCTA using machine learning algorithms seems feasible and shows good agreement with cardiac MRI.

The future of CMR: All-in-one vs. real-time CMR (Part 2)

Cardiac Magnetic Resonance (CMR) protocols can be lengthy and complex, which has driven the research community to develop new technologies to make these protocols more efficient and patient-friendly. Two different approaches to improving CMR have been proposed, specifically "all-in-one" CMR, where several contrasts and/or motion states are acquired simultaneously, and "real-time" CMR, in which the examination is accelerated to avoid the need for breathholding and/or cardiac gating. The goal of this two-part manuscript is to describe these two different types of emerging rapid CMR protocols. To this end, the vision of all-in-one and real-time imaging are described, along with techniques which have been devised and tested along the pathway of clinical implementation. The pros and cons of the different methods are presented, and the remaining open needs of each are detailed. Part 1 tackles the "All-in-One" approaches, and Part 2 focuses on the "Real-Time" approaches along with an overall summary of these emerging methods.

Imaging in patients with cardiovascular implantable electronic devices: part 1-imaging before and during device implantation. A clinical consensus statement of the European Association of Cardiovascular Imaging (EACVI) and the European Heart Rhythm Association (EHRA) of the ESC

More than 500 000 cardiovascular implantable electronic devices (CIEDs) are implanted in the European Society of Cardiology countries each year. The role of cardiovascular imaging in patients being considered for CIED is distinctly different from imaging in CIED recipients. In the former group, imaging can help identify specific or potentially reversible causes of heart block, the underlying tissue characteristics associated with malignant arrhythmias, and the mechanical consequences of conduction delays and can also aid challenging lead placements. On the other hand, cardiovascular imaging is required in CIED recipients for standard indications and to assess the response to device implantation, to diagnose immediate and delayed complications after implantation, and to guide device optimization. The present clinical consensus statement (Part 1) from the European Association of Cardiovascular Imaging, in collaboration with the European Heart Rhythm Association, provides comprehensive, up-to-date, and evidence-based guidance to cardiologists, cardiac imagers, and pacing specialists regarding the use of imaging in patients undergoing implantation of conventional pacemakers, cardioverter defibrillators, and resynchronization therapy devices. The document summarizes the existing evidence regarding the use of imaging in patient selection and during the implantation procedure and also underlines gaps in evidence in the field. The role of imaging after CIED implantation is discussed in the second document (Part 2).

Interpretation and management of premature ventricular beats in athletes: An expert opinion document of the Italian Society of Sports Cardiology (SICSPORT)

Premature ventricular beats (PVBs) are recorded in a sizeable proportion of athletes during pre-participation screening, especially if the evaluation includes both resting and exercise ECG. While in the majority of cases no underlying heart disease is present, in others PVBs may be the sign of a condition at risk of sudden cardiac death, including cardiomyopathies, congenital, coronary artery, heart valves and ion channels diseases. In this expert opinion document of the Italian Society of Sports Cardiology, we propose a multiparametric interpretation approach to PVBs in athletes and a stepwise diagnostic algorithm. The clinical work-up should include the assessment of the probable site of origin based on the ECG pattern of the ectopic QRS and of the arrhythmia behavior (including the number of different PVB morphologies, complexity, response to exercise and reproducibility), as well as first-line tests such as echocardiography. Based on this initial evaluation, most athletes can be reassured of the benign nature of PVBs and cleared for competition under periodical follow-up. However, when the clinical suspicion is high, further investigations with non-invasive (e.g. cardiac magnetic resonance, cardiac computed tomography, genetic testing) and, in very selected cases, invasive (e.g. endocardial voltage mapping and endomyocardial biopsy) tests should be carried out to rule out a high-risk condition. Importantly, such advanced tests should be performed in centers with a consolidated experience not only in the technique, but also in evaluation of athletes.

The Contemporary Role of Cardiac Computed Tomography and Cardiac Magnetic Resonance Imaging in the Diagnosis and Management of Pericardial Diseases

Pericardial syndromes encompass different clinical conditions from acute pericarditis to idiopathic chronic pericardial effusion. Transthoracic echocardiography is the first and most important initial diagnostic imaging modality in most patients affected by pericardial disease. However, cardiac computed tomography (CCT) and cardiac magnetic resonance imaging (CMR) have recently gained a pivotal role in cardiology, and recent reports have supported the role of both of these advanced techniques in the evaluation and guiding therapy of pericardial disease. Most promising is the capability of CMR to identify the presence of pericardial inflammation, carrying both diagnostic and prognostic value in the setting of recurrent and chronic pericarditis. In addition, CCT permits accurate evaluation of the presence and extension of pericardial calcification, providing important information in confirming the diagnosis of constrictive pericarditis and during the preprocedural planning for patients undergoing pericardiectomy. Both CCT and CMR require specific expertise, especially for the evaluation of pericardial disease. The aim of the present review is to provide physicians an updated overview of CCT and CMR in pericardial disease, focusing on technical issues, recent research findings, and potential clinical applications.

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 ​± ​11 years, and mean LVEF at CMR was 35.4 ​± ​10.7%. Overall radiation exposure for ECV estimation was 2.1 ​± ​1.1 ​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 ​± ​6.5% vs 33.9 ​± ​8.0%, p ​< ​0.001). At regression analysis, strong correlations were described (all segments, r ​= ​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.

A deep-learning approach for myocardial fibrosis detection in early contrast-enhanced cardiac CT images

Aims

Diagnosis of myocardial fibrosis is commonly performed with late gadolinium contrast-enhanced (CE) cardiac magnetic resonance (CMR), which might be contraindicated or unavailable. Coronary computed tomography (CCT) is emerging as an alternative to CMR. We sought to evaluate whether a deep learning (DL) model could allow identification of myocardial fibrosis from routine early CE-CCT images.

Methods and results

Fifty consecutive patients with known left ventricular (LV) dysfunction (LVD) underwent both CE-CMR and (early and late) CE-CCT. According to the CE-CMR patterns, patients were classified as ischemic (n = 15, 30%) or non-ischemic (n = 35, 70%) LVD. Delayed enhancement regions were manually traced on late CE-CCT using CE-CMR as reference. On early CE-CCT images, the myocardial sectors were extracted according to AHA 16-segment model and labeled as with scar or not, based on the late CE-CCT manual tracing. A DL model was developed to classify each segment. A total of 44,187 LV segments were analyzed, resulting in accuracy of 71% and area under the ROC curve of 76% (95% CI: 72%-81%), while, with the bull's eye segmental comparison of CE-CMR and respective early CE-CCT findings, an 89% agreement was achieved.

Conclusions

DL on early CE-CCT acquisition may allow detection of LV sectors affected with myocardial fibrosis, thus without additional contrast-agent administration or radiational dose. Such tool might reduce the user interaction and visual inspection with benefit in both efforts and time.