The value of real-time myocardial contrast echocardiography for detecting coronary microcirculation function in coronary artery disease patients

An Automatic Coronary Microvascular Dysfunction Classification Method Based on Hybrid ECG Features and Expert Features

OBJECTIVE

In recent years, the early diagnosis and treatment of coronary microvascular dysfunction (CMD) have become crucial for preventing coronary heart disease. This paper aims to develop a computer-assisted autonomous diagnosis method for CMD by using ECG features and expert features.

APPROACH

Clinical electrocardiogram (ECG), myocardial contrast echocardiography (MCE), and coronary angiography (CAG) are used in our method. Firstly, morphological features, temporal features, and T-wave features of ECG are extracted by multi-channel residual network with BiLSTM (MCResnet-BiLSTM) model and the multi-source T-wave features (MTF) extraction model, respectively. And these features are fused to form ECG features. In addition, the CFR[Formula: see text] is calculated based on the parameters related to the MCE at rest and stress state, and the Angio-IMR is calculated based on CAG. The combination of CFR[Formula: see text] and Angio-IMR is termed as expert features. Furthermore, the hybrid features, fused from the ECG features and the expert features, are input into the multilayer perceptron to implement the identification of CMD. And the weighted sum of the softmax loss and center loss is used as the total loss function for training the classification model, which optimizes the classification ability of the model.

RESULT

The proposed method achieved 93.36% accuracy, 94.46% specificity, 92.10% sensitivity, 95.89% precision, and 93.95% F1 score on the clinical dataset of the Second Affiliated Hospital of Zhejiang University.

CONCLUSION

The proposed method accurately extracts global ECG features, combines them with expert features to obtain hybrid features, and uses weighted loss to significantly improve diagnostic accuracy. It provides a novel and practical method for the clinical diagnosis of CMD.

Prognostic value of myocardial contrast echocardiography in acute anterior wall ST-segment elevation myocardial infarction with successful epicardial recanalization

Although myocardial contrast echocardiography (MCE) can evaluate microvascular perfusion abnormalities, its prognostic value is uncertain in acute anterior wall ST-Segment elevation myocardial infarction (STEMI) with successful epicardial recanalization. Therefore, the study aims to investigate the prognostic role of qualitative and quantitative MCE in acute anterior wall STEMI with successful epicardial recanalization. 153 STEMI patients were assessed by MCE within 7 days after successful epicardial recanalization. Qualitative perfusion parameters (microvascular perfusion score index, MPSI) and quantitative perfusion parameters (A, β, and Aβ) were acquired using a 17-segment model. And corrected A and Aβ were calculated. Patients were all followed for major adverse cardiovascular events (MACEs). During median follow-up of 27 (4) months, 39 (25.49%) patients experienced MACEs, while 114 (74.51%) were free from MACEs. Patients with MACEs had higher MPSI (1.65 ± 0.13 vs. No-MACEs 1.35 ± 0.20, P < 0.001), lower β (1.09 ± 0.19 s-1 vs. No-MACEs 1.34 ± 0.30 s-1, P < 0.001), corrected A (0.17 ± 0.03 dB vs. No-MACEs 0.19 ± 0.04 dB, P = 0.039) and lower corrected Aβ (0.19 ± 0.06 dB/s vs. No-MACEs 0.25 ± 0.08 dB/s, P < 0.001). MPSI of 1.44 provided an area under the curve (AUC) of 0.872, while β of 1.18 s-1 and corrected Aβ of 0.22 dB/s provided AUCs of 0.759 and 0.724, respectively. The combination of MPSI, β and corrected Aβ provided an increased AUC of 0.964 (all P < 0.05). Time-dependent ROC analysis showed that the AUCs of the MPSI, β, corrected Aβ and the combination at 1, 1.5 and 2 years indicated a strong predictive power for MACEs (AUC = 0.900/0.894/0.881 for MPSI, 0.648/0.704/0.732 for β, 0.674/0.686/0.722 for corrected Aβ, and 0.947/0.962/0.967 for the combination, respectively). Patients with MPSI < 1.44, β > 1.18 s-1, or corrected Aβ > 0.22 dB/s had lower event rate (all Log Rank P ≤ 0.001). MPSI, β, corrected Aβ, GLS and WBC were independent predictors of MACEs with adjusted hazard ratio of 34.41 (8.18-144.87), P < 0.001 for MPSI; 39.29 (27.46-65.44), P < 0.001 for β; 8.93 (1.46-54.55), P = 0.018 for corrected Aβ; 10.88 (2.83-41.86), P = 0.001 for GLS; and 1.43 (1.16-1.75), P = 0.001 for WBC. Qualitative and quantitative MCE can accurately predict MACEs in acute anterior wall STEMI with successful epicardial recanalization, and their combined predictive value is higher.