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ID 117225
Title Alternative
AI for Exercise-Induced Pulmonary Hypertension
Hirata, Yukina Tokushima University
Yamaguchi, Natsumi Tokushima University
Kosaka, Yoshitaka Tokushima University
Tsuji, Takumasa Teikyo University
Kotoku, Jun’ichi Teikyo University
artificial intelligence
connective tissue disease
exercise pulmonary hypertension
scleroderma (SSc)
Content Type
Journal Article
Background: Stress echocardiography is an emerging tool used to detect exercise-induced pulmonary hypertension (EIPH). However, facilities that can perform stress echocardiography are limited by issues such as cost and equipment.
Objective: We evaluated the usefulness of a deep learning (DL) approach based on a chest X-ray (CXR) to predict EIPH in 6-min walk stress echocardiography.
Methods: The study enrolled 142 patients with scleroderma or mixed connective tissue disease with scleroderma features who performed a 6-min walk stress echocardiographic test. EIPH was defined by abnormal cardiac output (CO) responses that involved an increase in mean pulmonary artery pressure (mPAP). We used the previously developed AI model to predict PH and calculated PH probability in this cohort.
Results: EIPH defined as ΔmPAP/ΔCO >3.3 and exercise mPAP >25 mmHg was observed in 52 patients, while non-EIPH was observed in 90 patients. The patients with EIPH had a higher mPAP at rest than those without EIPH. The probability of PH based on the DL model was significantly higher in patients with EIPH than in those without EIPH. Multivariate analysis showed that gender, mean PAP at rest, and the probability of PH based on the DL model were independent predictors of EIPH. A model based on baseline parameters (age, gender, and mPAP at rest) was improved by adding the probability of PH predicted by the DL model (AUC: from 0.65 to 0.74; p = 0.046).
Conclusion: Applying the DL model based on a CXR may have a potential for detection of EIPH in the clinical setting.
Journal Title
Frontiers in Cardiovascular Medicine
Frontiers Media S.A.
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This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) ( The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
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University Hospital
Medical Sciences