Estimating pulmonary arterial pressure from 4D flow images
The non-invasive method for estimating the pulmonary arterial pressure (PAP) plays an important role in the screening and diagnosis of pulmonary arterial hypertension (PAH). We aimed to establish a phase-contrast magnetic resonance imaging (PC-MRI) based method to estimate PAP. Through analyzing a p...
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| Format: | Article |
| Language: | English |
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Elsevier
2025-06-01
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| Series: | Medicine in Novel Technology and Devices |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2590093525000050 |
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| author | Chi Zhang Yaowen Dong Tongxi Liu Jin She Jian Yang Deyu Li Sheng Xie |
| author_facet | Chi Zhang Yaowen Dong Tongxi Liu Jin She Jian Yang Deyu Li Sheng Xie |
| author_sort | Chi Zhang |
| collection | DOAJ |
| description | The non-invasive method for estimating the pulmonary arterial pressure (PAP) plays an important role in the screening and diagnosis of pulmonary arterial hypertension (PAH). We aimed to establish a phase-contrast magnetic resonance imaging (PC-MRI) based method to estimate PAP. Through analyzing a patient's morphologic and hemodynamic features, this method could be used to identify PAH, and provide diagnostic and grading information for PAH. We selected 39 study participants, comprising 18 healthy volunteers and 21 patients with PAH. Morphologic and hemodynamic parameters of each participant's pulmonary arteries were obtained from 4D Flow images. Hemodynamic features were performed selected by principal component analysis (PCA). PAH identification model was built with binary logistic regression. Furthermore, A multiple linear regression (MLR) model was developed to estimate PAP, the accuracy of which was evaluated by comparing it with the value measured by right heart catheterization (RHC). PAH identification was achieved with high accuracy, using the features of pulmonary arterial morphology or blood flow velocity (BFV). Compared with RHC, MLR results showed that using pulmonary arterial morphology and BFV features in combination can greatly improve the accuracy of PAP estimation. Our results showed that the mean relative error of PAP estimation in PAH patients could reach <10 %. A highly accurate PC-MRI based method for PAH identification and PAP estimation was successfully established. Using hemodynamic features of the pulmonary artery could improve PAP estimation accuracy, which highlights the importance of hemodynamic evaluation of pulmonary arteries in the screening and diagnosis of PAH. |
| format | Article |
| id | doaj-art-506defceb50f444db4fcfeaecb10a3ff |
| institution | DOAJ |
| issn | 2590-0935 |
| language | English |
| publishDate | 2025-06-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Medicine in Novel Technology and Devices |
| spelling | doaj-art-506defceb50f444db4fcfeaecb10a3ff2025-08-20T03:10:27ZengElsevierMedicine in Novel Technology and Devices2590-09352025-06-012610035410.1016/j.medntd.2025.100354Estimating pulmonary arterial pressure from 4D flow imagesChi Zhang0Yaowen Dong1Tongxi Liu2Jin She3Jian Yang4Deyu Li5Sheng Xie6Key Laboratory of Biomechanics and Mechanobiology, School of Biological Science and Medical Engineering, Beihang University, Beijing, China; State Key Laboratory of Virtual Reality Technology and Systems, Beihang University, Beijing, ChinaKey Laboratory of Biomechanics and Mechanobiology, School of Biological Science and Medical Engineering, Beihang University, Beijing, ChinaDepartment of Radiology, China-Japan Friendship Hospital, Beijing, ChinaThe First College of Clinical Medical Science, China Three Gorges University & Yichang Central People's Hospital, Yichang, ChinaThe First College of Clinical Medical Science, China Three Gorges University & Yichang Central People's Hospital, Yichang, China; Hubei Key Laboratory of Ischemic Cardiovascular Disease, Yichang, China; Hubei Provincial Clinical Research Center for Ischemic Cardiovascular Disease, Yichang, ChinaKey Laboratory of Biomechanics and Mechanobiology, School of Biological Science and Medical Engineering, Beihang University, Beijing, China; State Key Laboratory of Virtual Reality Technology and Systems, Beihang University, Beijing, ChinaDepartment of Radiology, China-Japan Friendship Hospital, Beijing, China; Corresponding author. No. 2 Yinghuayuan East Street, Chaoyang District, Beijing, 100029, China.The non-invasive method for estimating the pulmonary arterial pressure (PAP) plays an important role in the screening and diagnosis of pulmonary arterial hypertension (PAH). We aimed to establish a phase-contrast magnetic resonance imaging (PC-MRI) based method to estimate PAP. Through analyzing a patient's morphologic and hemodynamic features, this method could be used to identify PAH, and provide diagnostic and grading information for PAH. We selected 39 study participants, comprising 18 healthy volunteers and 21 patients with PAH. Morphologic and hemodynamic parameters of each participant's pulmonary arteries were obtained from 4D Flow images. Hemodynamic features were performed selected by principal component analysis (PCA). PAH identification model was built with binary logistic regression. Furthermore, A multiple linear regression (MLR) model was developed to estimate PAP, the accuracy of which was evaluated by comparing it with the value measured by right heart catheterization (RHC). PAH identification was achieved with high accuracy, using the features of pulmonary arterial morphology or blood flow velocity (BFV). Compared with RHC, MLR results showed that using pulmonary arterial morphology and BFV features in combination can greatly improve the accuracy of PAP estimation. Our results showed that the mean relative error of PAP estimation in PAH patients could reach <10 %. A highly accurate PC-MRI based method for PAH identification and PAP estimation was successfully established. Using hemodynamic features of the pulmonary artery could improve PAP estimation accuracy, which highlights the importance of hemodynamic evaluation of pulmonary arteries in the screening and diagnosis of PAH.http://www.sciencedirect.com/science/article/pii/S25900935250000504D flow imageBinary logistic regressionMultiple linear regressionPhase-contrast magnetic resonance imagingPulmonary arterial hypertension |
| spellingShingle | Chi Zhang Yaowen Dong Tongxi Liu Jin She Jian Yang Deyu Li Sheng Xie Estimating pulmonary arterial pressure from 4D flow images Medicine in Novel Technology and Devices 4D flow image Binary logistic regression Multiple linear regression Phase-contrast magnetic resonance imaging Pulmonary arterial hypertension |
| title | Estimating pulmonary arterial pressure from 4D flow images |
| title_full | Estimating pulmonary arterial pressure from 4D flow images |
| title_fullStr | Estimating pulmonary arterial pressure from 4D flow images |
| title_full_unstemmed | Estimating pulmonary arterial pressure from 4D flow images |
| title_short | Estimating pulmonary arterial pressure from 4D flow images |
| title_sort | estimating pulmonary arterial pressure from 4d flow images |
| topic | 4D flow image Binary logistic regression Multiple linear regression Phase-contrast magnetic resonance imaging Pulmonary arterial hypertension |
| url | http://www.sciencedirect.com/science/article/pii/S2590093525000050 |
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