European heart journal. Imaging methods and practice最新文献

Aims: Myocardial calcification is an unusual condition in which excess calcium is deposited in the myocardium. Herein, we report two cases of myocardial calcification from our clinical experience. Furthermore, we conduct a systematic review to examine the clinical course and associated pathologies of myocardial calcification.

Methods and results: This systematic review was registered in PROSPERO (CRD42023463285). PubMed and Scopus were searched according to the following inclusion criteria: (i) case reports or case series describing patients with myocardial calcification; (ii) diagnosis of myocardial calcification by computed tomography (CT); (iii) adequate description of patients, including their chief complaint, medical history, evaluations, and treatments; and (iv) publication in English. Among the 75 patients, 24 had sepsis, 14 had myocarditis, and 37 had other pathologies. The mortality rate was 33% for patients with sepsis, 14% for patients with myocarditis, and 11% for patients with other pathologies. Follow-up CT findings beyond 2 years were reported in six patients, showing that the CT findings of myocardial calcification persisted but subsided over time. Autopsy was performed in seven patients, and extensive interstitial fibrosis and collection of inflammatory cells were observed in patients with myocarditis, sepsis, and ischaemic heart disease.

Conclusion: While various medical conditions can cause myocardial calcification, accompanying conditions commonly reported with myocardial calcification were sepsis and myocarditis. The CT findings of myocardial calcification tend to regress over time if the underlying disease can be treated.

[This corrects the article DOI: 10.1093/ehjimp/qyae017.].

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.

Aims: This study assessed an artificial intelligence (AI) model's performance in predicting elevated brain natriuretic peptide (BNP) levels from chest radiograms and its effect on diagnostic performance among healthcare professionals.

Methods and results: Patients who underwent chest radiography and BNP testing on the same day were included. Data were sourced from two hospitals: one for model development, and the other for external testing. Two final ensemble models were developed to predict elevated BNP levels of ≥ 200 pg/mL and ≥ 100 pg/mL, respectively. Humans were evaluated to predict elevated BNP levels, followed by the same test, referring to the AI model's predictions. A total of 8390 images were collected for model creation, and 1713 images, for tests. The AI model achieved an accuracy of 0.855, precision of 0.873, sensitivity of 0.827, specificity of 0.882, f1 score of 0.850, and receiver-operating-characteristics area-under-curve of 0.929. The accuracy of the testing by 35 participants significantly improved from 0.708 ± 0.049 to 0.829 ± 0.069 (P < 0.001) with the AI assistance (an accuracy of 0.920). Without the AI assistance, the accuracy of the veterans in the medical career was higher than that of early-career professionals (0.728 ± 0.051 vs. 0.692 ± 0.042, P = 0.030); however, with the AI assistance, the accuracy of the early-career professionals was rather higher than that of the veterans (0.851 ± 0.074 vs. 0.803 ± 0.054, P = 0.033).

Conclusion: The AI model can predict elevated BNP levels from chest radiograms and has the potential to improve human performance. The gap in utilizing new tools represents one of the emerging issues.

Aims: Atrial fibrillation (AF) is a common comorbidity in non-ischaemic dilated cardiomyopathy (NIDCM) affecting conventional measures of left atrial (LA) function. We aimed to determine whether LA function analysis could identify patients at higher risk of major cardiovascular events (MACEs).

Methods and results: A retrospective study of patients with NIDCM in AF referred to a single centre for transthoracic echocardiography (TTE) between 2015 and 2019. Peak atrial longitudinal strain (PALS) was measured along with LA emptying fraction and LA filling index (LAFI = E wave/PALS). Cox regression analysis was conducted. A total of 153 patients were included [median age 74 years, left ventricular ejection fraction (LVEF) 35%], and 57 (37.3%) had MACE after a median follow-up of 3.2 years. LAFI was the only independent TTE parameter associated with MACE after adjustment for age, diabetes, LVEF, left ventricular global longitudinal strain (LV-GLS), and LA volume index [adjusted hazard ratio (HR) = 1.02 per point increase, P = 0.024], with the best cut-off at ≥15. LAFI ≥15 predicted each of MACE components when separately analysed: MACE HR = 1.95, 95% confidence interval (CI) 1.16-3.30; cardiovascular death HR = 3.68, 95% CI 1.41-9.56, heart failure admission HR = 2.13, 95% CI 1.19-3.80, and ventricular arrhythmia HR = 4.72, 95% CI 1.52-14.67. Higher LAFI was associated with worsening LV-GLS, E/e', systolic pulmonary artery (PA) pressure, tricuspid annular plane systolic excursion, and right ventricular to PA coupling.

Conclusion: LA deformation analysis is feasible in patients with NIDCM presenting with AF. LAFI may identify patients at higher risk of MACE and correlates with higher pulmonary pressures and worse right ventricular function, suggesting an elevation of left-sided ventricular pressures in patients with higher LAFI.

Aims: Recovery of cardiovascular diagnostic testing in Italy after the coronavirus disease-2019 (COVID-19) pandemic has not been quantified. The study aims to describe cardiac diagnostic procedure volumes, centres practice and protocols, and staff members' well-being 1 year after COVID-19 outbreak in Italy.

Methods and results: A global survey was conducted by the International Atomic Energy Agency to evaluate changes in cardiac diagnostic procedure volumes in April 2021. Evaluated procedures were transoesophageal echocardiogram, coronary computed tomography angiography, coronary artery calcium scanning, nuclear medicine infection studies, invasive coronary angiography, rest and stress transthoracic echocardiogram, cardiac magnetic resonance, single-photon emission computed tomography and positron emission tomography, and stress electrocardiogram. Data were compared with April 2020 and March 2019. Forty-two Italian centres took part in the survey. In April 2020, there was a 72% decrease of median volumes of cardiac diagnostic procedures compared with March 2019. In April 2021, volumes of cardiac diagnostic procedures remained decreased by 3% when compared with March 2019. Stress electrocardiogram, coronary computed tomography angiography, and stress cardiac magnetic resonance volumes increased in April 2021 compared with baseline (29%, 6%, and 16%, respectively). The majority of centres had adopted physical distancing measures (93%), COVID-19 screening through questionnaires (76%), or temperature checks (93%). Twenty-five per cent of physicians at Italian responding sites reported excessive levels of psychological stress.

Conclusion: In April 2021, volumes of cardiac diagnostic procedures at Italian responding sites were still recovering. Centres had implemented several adaptations to ensure the provision of care to their patients. Even 1 year after the pandemic, a substantial minority of Italian healthcare providers were still experiencing excessive psychological stress.

Aims: Speckle tracking echocardiography increasingly supports left atrial (LA) strain (LAS) analysis for diagnosis and prognosis of various clinical conditions. Prior limitations, such as the absence of dedicated software, have been overcome by validated ventricular-based software. A newly automated real-time and offline LA-specific software have now become available on echocardiographs and dedicated workstations. This study aimed at comparing LA strain measures obtained from new fully automated software vs. traditional semi-automated ventricular-based methods in different groups of patients.

Methods and results: Two operators acquired LA images in a mixed population of healthy individuals and patients with pressure overload (hypertension and aortic stenosis) or pressure-volume overload (mitral regurgitation and heart failure). Subjects with prosthetic valves, heart transplant, or atrial fibrillation were excluded. Strain analysis was performed twice by old semi-automated software and new LA dedicated. LAS was then measured online on the scanning echocardiograph. Overall, 100 patients were analysed (41 healthy subjects, 28 pressure overload, 31 volume overload). LAS proved to be highly reproducible with both software. The dedicated method exhibited slightly superior inter- and intra-operator reproducibility. The online software results showed a nearly perfect reproducibility with offline software [intraclass correlation coefficient = 0.99 [0.99; 1.00]] in addition to being able to save an average of ∼30 s.

Conclusion: The recently developed fully automated software for dedicated LAS analysis demonstrates excellent inter- and intra-operator reproducibility, making it a reliable and efficient strain calculation method in routine clinical practice. Another advantage of online LAS calculation is time efficiency.

Aims: Recent studies have shown that extracellular volume (ECV) can also be obtained without blood sampling by the linear relationship between haematocrit (HCT) and blood pool R1 (1/T1). However, whether this relationship holds for patients with myocardial infarction is still unclear. This study established and validated an ECV model without blood sampling in ST-segment elevation myocardial infarction (STEMI) patients.

Methods and results: A total of 398 STEMI patients who underwent cardiac magnetic resonance (CMR) examination with T1 mapping and venous HCT within 24 h were retrospectively analysed. All patients were randomly divided into a derivation group and a validation group. The mean CMR scan time was 3 days after primary percutaneous coronary intervention. In the derivation group, a synthetic HCT formula was obtained by the linear regression between HCT and blood pool R1 (R ² = 0.45, P < 0.001). The formula was used in the validation group; the results showed high concordance and correlation between synthetic ECV and conventional ECV in integral (bias = -0.12; R ² = 0.92, P < 0.001), myocardial infarction site (bias = -0.23; R ² = 0.93, P < 0.001), and non-myocardial infarction sites (bias = -0.09; R ² = 0.94, P < 0.001).

Conclusion: In STEMI patients, synthetic ECV without blood sampling had good consistency and correlation with conventional ECV. This study might provide a convenient and accurate method to obtain the ECV from CMR to identify myocardial fibrosis.