Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Imaging Studies for Cardiovascular System III: X-Ray

Imaging Studies for Cardiovascular System III: X-Ray

The most common cardiovascular diagnostic test is an X-ray. It produces images of the heart, blood vessels, and adjacent structures.
Definition and Purpose
An X-ray, or radiograph, is a non-invasive method that uses ionizing radiation to take images of internal structures. It is mainly used in cardiac imaging to examine the heart, lungs, and major blood vessels, aiming to identify abnormalities in the heart's size, shape, and position, such as heart failure, congenital defects, and vascular...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

Fully automated artificial intelligence-based echocardiographic analysis for global longitudinal strain monitoring and cancer therapy-related cardiac dysfunction detection in breast cancer patients.

European heart journal. Digital health·2026

Same author

JCS/JPCPHS 2025 Guideline on Pulmonary Hypertension and Pulmonary Embolism/Deep Vein Thrombosis.

Circulation journal : official journal of the Japanese Circulation Society·2026

Same author

Left Atrial Stiffness Index and Outcomes After Discharge in Heart Failure With Preserved Ejection Fraction.

JACC. Asia·2026

Same author

Observational multicentre registry to update key interventions and new approaches with artificial intelligence for heart failure (OKINAWA-HF): a retrospective medical record-derived registry study protocol.

BMJ open·2026

Same author

Validation of a fully automated workflow for longitudinal strain using artificial intelligence.

Journal of echocardiography·2026

Same author

One-Year Trajectory of Step Counts and Weight Loss in Adults With Overweight/Obesity: Retrospective Cohort Study.

JMIR mHealth and uHealth·2026

Search research articles

Related Experiment Video

Updated: Sep 5, 2025

Author Spotlight: Advancing 3D Modeling for Enhanced Diagnosis and Treatment of Pulmonary Nodules in Early-Stage Lung Cancer

Author Spotlight: Advancing 3D Modeling for Enhanced Diagnosis and Treatment of Pulmonary Nodules in Early-Stage Lung Cancer

Published on: October 13, 2023

Deep Learning for Detection of Exercise-Induced Pulmonary Hypertension Using Chest X-Ray Images.

Kenya Kusunose¹, Yukina Hirata², Natsumi Yamaguchi²

¹Department of Cardiovascular Medicine, Tokushima University Hospital, Tokushima, Japan.

Frontiers in Cardiovascular Medicine

|July 5, 2022

Summary

A deep learning model using chest X-rays can help detect exercise-induced pulmonary hypertension (EIPH). This AI approach shows potential for clinical use, improving upon traditional methods for identifying EIPH in patients.

Keywords:

artificial intelligence connective tissue disease echocardiography exercise pulmonary hypertension scleroderma (SSc)

More Related Videos

Author Spotlight: Standardization and Best Practices for Advancing Lung Imaging Using 129Xe MRI

Author Spotlight: Standardization and Best Practices for Advancing Lung Imaging Using ¹²⁹Xe MRI

Published on: November 21, 2023

Three-Dimensional Phase Resolved Functional Lung Magnetic Resonance Imaging

Three-Dimensional Phase Resolved Functional Lung Magnetic Resonance Imaging

Published on: June 21, 2024

Related Experiment Videos

Last Updated: Sep 5, 2025

Author Spotlight: Advancing 3D Modeling for Enhanced Diagnosis and Treatment of Pulmonary Nodules in Early-Stage Lung Cancer

Author Spotlight: Advancing 3D Modeling for Enhanced Diagnosis and Treatment of Pulmonary Nodules in Early-Stage Lung Cancer

Published on: October 13, 2023

Author Spotlight: Standardization and Best Practices for Advancing Lung Imaging Using 129Xe MRI

Author Spotlight: Standardization and Best Practices for Advancing Lung Imaging Using ¹²⁹Xe MRI

Published on: November 21, 2023

Three-Dimensional Phase Resolved Functional Lung Magnetic Resonance Imaging

Three-Dimensional Phase Resolved Functional Lung Magnetic Resonance Imaging

Published on: June 21, 2024

Area of Science:

Cardiology
Pulmonary Medicine
Artificial Intelligence in Medicine

Background:

Stress echocardiography is a key tool for detecting exercise-induced pulmonary hypertension (EIPH).
Availability of stress echocardiography is limited by cost and equipment constraints.
Developing alternative, accessible methods for EIPH detection is crucial.

Purpose of the Study:

To evaluate a deep learning (DL) model utilizing chest X-rays (CXRs) for predicting EIPH during 6-minute walk stress echocardiography.
To assess the efficacy of an AI-driven approach in identifying EIPH in patients with connective tissue diseases.

Main Methods:

142 patients with scleroderma or related conditions underwent 6-minute walk stress echocardiography.
EIPH was defined by abnormal cardiac output responses and elevated mean pulmonary artery pressure (mPAP).
A pre-existing AI model was used to predict pulmonary hypertension (PH) probability.

Main Results:

EIPH was identified in 52 patients, with higher resting mPAP compared to non-EIPH patients (n=90).
The DL model demonstrated a significantly higher PH probability in patients with EIPH.
The DL model improved prediction accuracy (AUC from 0.65 to 0.74) when added to baseline parameters.

Conclusions:

A DL model based on CXRs shows promise for detecting EIPH in clinical settings.
This AI approach offers a potential non-invasive method for EIPH screening.
Further validation could integrate CXR-based AI into routine patient assessment for EIPH.