Cardiac imaging to detect coronary artery disease in athletes aged 35 years and older. A scoping review

Evaluation of the electrocardiogram RV5 /V6 criteria in the diagnosis of left ventricular hypertrophy in marathon runners

To assess the value of electrocardiogram (ECG) RV5/V6 criteria for diagnosing left ventricular hypertrophy (LVH) in marathons. A total of 112 marathon runners who met the requirements for "Class A1" events certified by the Chinese Athletics Association in Changzhou City were selected, and their general clinical information was collected. ECG examinations were performed using a Fukuda FX7402 Cardimax Comprehensive Electrocardiograph Automatic Analyser, whereas routine cardiac ultrasound examinations were performed using a Philips EPIQ 7C echocardiography system. Real-time 3-dimensional echocardiography (RT-3DE) was performed to acquire 3-dimensional images of the left ventricle and to calculate the left ventricular mass index (LVMI). According to the LVMI criteria of the American Society of Echocardiography for the diagnosis of LVH, the participants were divided into an LVMI normal group (n = 96) and an LVH group (n = 16). The correlation between the ECG RV5/V6 criteria and LVH in marathon runners was analysed using multiple linear regression stratified by sex and compared with the Cornell (SV3 + RaVL), modified Cornell (SD + RaVL), Sokolow-Lyon (SV1 + RV5/V6), Peguero-Lo Presti (SD + SV4), SV1, SV3, SV4, and SD criteria. In marathon runners, the ECG parameters SV3 + RaVL, SD + RaVL, SV1 + RV5/V6, SD + SV4, SV3, SD, and RV5/V6 were able to identify LVH (all p < .05). When stratified by sex, linear regression analysis revealed that a significantly higher number of ECG RV5/V6 criteria were evident in the LVH group than in the LVMI normal group (p < .05), both with no adjustment and after initial adjustment (including age and body mass index), as well as after full adjustment (including age, body mass index, interventricular septal thickness, left ventricular end-diastolic diameter, left ventricular posterior wall thickness, and history of hypertension). Additionally, curve fitting showed that the ECG RV5/V6 values increased with increasing LVMI in marathon runners, exhibiting a nearly linear positive correlation. In conclusions, the ECG RV5/V6 criteria were correlated with LVH in marathon runners.

An accurate and time-efficient deep learning-based system for automated segmentation and reporting of cardiac magnetic resonance-detected ischemic scar

BACKGROUND AND OBJECTIVES

Myocardial infarction scar (MIS) assessment by cardiac magnetic resonance provides prognostic information and guides patients' clinical management. However, MIS segmentation is time-consuming and not performed routinely. This study presents a deep-learning-based computational workflow for the segmentation of left ventricular (LV) MIS, for the first time performed on state-of-the-art dark-blood late gadolinium enhancement (DB-LGE) images, and the computation of MIS transmurality and extent.

METHODS

DB-LGE short-axis images of consecutive patients with myocardial infarction were acquired at 1.5T in two centres between Jan 1, 2019, and June 1, 2021. Two convolutional neural network (CNN) models based on the U-Net architecture were trained to sequentially segment the LV and MIS, by processing an incoming series of DB-LGE images. A 5-fold cross-validation was performed to assess the performance of the models. Model outputs were compared respectively with manual (LV endo- and epicardial border) and semi-automated (MIS, 4-Standard Deviation technique) ground truth to assess the accuracy of the segmentation. An automated post-processing and reporting tool was developed, computing MIS extent (expressed as relative infarcted mass) and transmurality.

RESULTS

The dataset included 1355 DB-LGE short-axis images from 144 patients (MIS in 942 images). High performance (> 0.85) as measured by the Intersection over Union metric was obtained for both the LV and MIS segmentations on the training sets. The performance for both LV and MIS segmentations was 0.83 on the test sets. Compared to the 4-Standard Deviation segmentation technique, our system was five times quicker (<1 min versus 7 ± 3 min), and required minimal user interaction.

CONCLUSIONS

Our solution successfully addresses different issues related to automatic MIS segmentation, including accuracy, time-effectiveness, and the automatic generation of a clinical report.

Potential Application of Cardiac Computed Tomography for Early Detection of Coronary Atherosclerosis: From Calcium Score to Advanced Atherosclerosis Analysis

In the present article, an overview of advanced analysis of coronary atherosclerosis by coronary computed tomography angiography (CCTA) is provided, focusing on the potential application of this technique in a primary prevention setting. Coronary artery calcium score (CACS) has a well-demonstrated prognostic value even in a primary prevention setting; however, fibro-fatty, high-risk coronary plaque may be missed by this tool. On the contrary, even if not recommended for primary prevention in the general population, CCTA may enable early high-risk atherosclerosis detection, and specific subgroups of patients may benefit from its application. However, further studies are needed to determine the possible use of CCTA in a primary prevention setting.

Prevalence of Myocardial Fibrosis in Intensive Endurance Training Athletes: A Systematic Review and Meta-Analysis

Objective: To review the published literature reporting on the incidence of myocardial fibrosis (MF) in high-intensity endurance athletes measured by late gadolinium enhancement (LGE) with cardiac magnetic resonance imaging (CMR). Methods: Five databases (PubMed, Cochrane Controlled Trials Register, EMBASE, Web of Science, and SPORTDiscus) were searched to obtain case cohort studies published before November 10, 2019. From 96 abstracts or reports extracted, 18 full-text articles were reviewed. The incidence of LGE was reported as outcome measures. Subgroup analysis was performed by age (under or above 50 years). Pooled estimates were obtained using a fixed-effects model. Results: After a full-text assessment, 12 studies involving 1,359 participants were included for analysis. Among them, 163/772 participants in the endurance athletes group showed LGE positive, compared with 19/587 participants in the comparison group. The results of the meta-analysis suggested that the prevalence of LGE was higher in the athletes group with long-term endurance exercise (OR 7.20;95%CI: 4.51-11.49). In addition, the same conclusion was drawn after the stratification of age. Conclusions: The available evidence demonstrates that high-intensity endurance athletes is associated with an increased incidence of LGE positive.