Deep Learning to Detect Pulmonary Hypertension from the Chest X-Ray Images of Patients with Systemic Sclerosis.

IF 1.2 4区 医学 Q3 CARDIAC & CARDIOVASCULAR SYSTEMS
International heart journal Pub Date : 2024-11-30 Epub Date: 2024-11-14 DOI:10.1536/ihj.24-111
Mai Shimbo, Masaru Hatano, Susumu Katsushika, Satoshi Kodera, Yoshitaka Isotani, Shinnosuke Sawano, Ryo Matsuoka, Shun Minatsuki, Toshiro Inaba, Hisataka Maki, Hayakazu Sumida, Norifumi Takeda, Hiroshi Akazawa, Issei Komuro
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引用次数: 0

Abstract

Pulmonary hypertension (PH) is a serious prognostic complication in patients with systemic sclerosis (SSc). Deep learning models can be applied to detect PH in the chest X-ray images of these patients. The aim of the study was to investigate the performance and prognostic implications of a deep learning algorithm for the diagnosis of PH in SSc patients using chest X-ray images.Chest X-ray images were acquired from 230 SSc patients with suspected PH who underwent chest X-ray and right heart catheterization (RHC). A convolutional neural network was trained to identify the data of patients with PH (mean pulmonary arterial pressure > 20 mmHg). Kaplan-Meier analysis was used to evaluate survival. The area under the receiver operating characteristic curve (AUC) obtained with the deep learning algorithm was 0.826 while the AUC obtained with cardiologist assessments of the same images was 0.804. The 5-year prognosis was 83.4% in patients with PH detected by RHC, and 85% in those with PH detected by the model.The deep learning model developed in this study can detect PH from the chest X-ray data of SSc patients. The prognostic accuracy of the model was demonstrated as well.

通过深度学习从系统性硬化症患者的胸部 X 光图像中检测肺动脉高压。
肺动脉高压(PH)是系统性硬化症(SSc)患者的一种严重预后并发症。深度学习模型可用于检测这些患者胸部X光图像中的肺动脉高压。这项研究旨在研究深度学习算法的性能和对预后的影响,该算法利用胸部X光图像诊断SSc患者的PH。对卷积神经网络进行了训练,以识别 PH 患者的数据(平均肺动脉压 > 20 mmHg)。Kaplan-Meier 分析用于评估存活率。采用深度学习算法得出的接收器工作特征曲线下面积(AUC)为 0.826,而采用心脏病专家对相同图像进行评估得出的接收器工作特征曲线下面积(AUC)为 0.804。RHC检测出的PH患者的5年预后为83.4%,而模型检测出的PH患者的5年预后为85%。该研究开发的深度学习模型可以从 SSc 患者的胸部 X 光数据中检测出 PH,并证明了该模型在预后方面的准确性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
International heart journal
International heart journal 医学-心血管系统
CiteScore
2.50
自引率
6.70%
发文量
148
审稿时长
6-12 weeks
期刊介绍: Authors of research articles should disclose at the time of submission any financial arrangement they may have with a company whose product figures prominently in the submitted manuscript or with a company making a competing product. Such information will be held in confidence while the paper is under review and will not influence the editorial decision, but if the article is accepted for publication, the editors will usually discuss with the authors the manner in which such information is to be communicated to the reader.
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