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. 2021 Aug 23:8:697396.
doi: 10.3389/fmed.2021.697396. eCollection 2021.

Right Ventricular Function Predicts Adverse Clinical Outcomes in Patients With Chronic Thromboembolic Pulmonary Hypertension: A Three-Dimensional Echocardiographic Study

Yidan Li  1 , Lirong Liang  2 , Dichen Guo  1 , Yuanhua Yang  3 , Juanni Gong  3 , Xinyuan Zhang  1 , Di Zhang  2 , Zhe Jiang  1 , Xiuzhang Lu  1
Affiliations

Right Ventricular Function Predicts Adverse Clinical Outcomes in Patients With Chronic Thromboembolic Pulmonary Hypertension: A Three-Dimensional Echocardiographic Study

Yidan Li et al. Front Med (Lausanne). .

Abstract

Background: Right ventricular (RV) function plays a vital role in the prognosis of patients with chronic thromboembolic pulmonary hypertension (CTEPH). We used new machine learning (ML)-based fully automated software to quantify RV function using three-dimensional echocardiography (3DE) to predict adverse clinical outcomes in CTEPH patients. Methods: A total of 151 consecutive CTEPH patients were registered in this prospective study between April 2015 and July 2019. New ML-based methods were used for data management, and quantitative analysis of RV volume and ejection fraction (RVEF) was performed offline. RV structural and functional parameters were recorded using 3DE. CTEPH was diagnosed using right heart catheterization, and 62 patients underwent cardiac magnetic resonance to assess right heart function. Adverse clinical outcomes were defined as PH-related hospitalization with hemoptysis or increased RV failure, including conditions requiring balloon pulmonary angioplasty or pulmonary endarterectomy, as well as death. Results: The median follow-up time was 19.7 months (interquartile range, 0.5-54 months). Among the 151 CTEPH patients, 72 experienced adverse clinical outcomes. Multivariate Cox proportional-hazard analysis showed that ML-based 3DE analysis of RVEF was a predictor of adverse clinical outcomes (hazard ratio, 1.576; 95% confidence interval (CI), 1.046~2.372; P = 0.030). Conclusions: The new ML-based 3DE algorithm is a promising technique for rapid 3D quantification of RV function in CTEPH patients.

Keywords: clinical failure; machine learning; prognosis; pulmonary hypertension; right ventricular function; three-dimensional echocardiography.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
Flow chart showing patient selection process.
Figure 2
Figure 2
Example of ML-based 3D RVEF analysis using QLAB 13.0 software. RVEF calculation in a 48-year-old female CTEPH patient who was treated with riociguat. End-diastolic and systolic verification and editing of endocardial RV borders, from which RVEDV, RVESV, and RVEF were obtained.
Figure 3
Figure 3
Correlation between ML-based 3D RVEF and physiological parameters. (A) RV longitudinal strain (Free wall). (B) Cardiac index. (C) 6MWD. (D) NT-proBNP.
Figure 4
Figure 4
Correlation and Bland-Altman analysis of parameters measured by ML-based 3DE and CMR. (A) Correlation between RVEDV measured by ML-based 3DE and CMR. (B) Correlation between RVESV measured by ML-based 3DE and CMR. (C) Correlation between RVEF measured by ML-based 3DE and CMR. (D) Bland-Altman analyses of RVEDV measured by ML-based 3DE and CMR. (E) Bland-Altman analysis of RVESV measured by ML-based 3DE and CMR. (F) Bland-Altman analysis of RVEF measured by ML-based 3DE and CMR.
Figure 5
Figure 5
ROC analysis of RAFi. AUC, area under the curve. Receiver operating characteristic curve analysis demonstrating the ability of RVEF, RVLS, cardiac index, and 6MWD to predictive adverse clinical outcomes of CTEPH patients.
Figure 6
Figure 6
Kaplan-Meier survival analysis for CTEPH patients with a RVEF < 31.4 and ≥ 31.4%.
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