ArticleEuropean radiology2019
Combined automated 3D volumetry by pulmonary CT angiography and echocardiography for detection of pulmonary hypertension.
Article in European radiology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 1 of them a synthesis that pooled it.
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Who cites it
19 citing papers in PubMed, 1 synthesis or guideline pooled it, 28 citations in OpenAlex.
- A Comprehensive Review of Artificial Intelligence (AI) Applications in Pulmonary Hypertension (PH).Medicina (Kaunas, Lithuania) · 2025Pooled it
- Development of a predictive model and nomogram using CTPA parameters for the identification of group 1 pulmonary arterial hypertension.iScience · 2026Article
- Diagnostic performance of the main pulmonary artery-to-ascending aorta diameter ratio for pulmonary hypertension defined by mean pulmonary arterial pressure in children with left-to-right shunt congenital heart disease.Quantitative imaging in medicine and surgery · 2026Article
- Artificial Intelligence in Pulmonary Hypertension: Current State and Future Prospects.Reviews in cardiovascular medicine · 2026Review
- Multi-Omics Identification of Biomarkers for High-Altitude Pulmonary Hypertension.Journal of cardiovascular development and disease · 2026Article
- Anthropometry, sex, and age at diagnosis affect pulmonary blood volume quantification from computed tomography pulmonary angiography in pulmonary hypertension assessment.Frontiers in cardiovascular medicine · 2026Article
- AI-based prediction of pulmonary hypertension in COPD patients with cor pulmonale using clinical and CT features.Frontiers in medicine · 2026Article
- Pediatric three-dimensional quantitative cardiovascular computed tomography.Pediatric radiology · 2025Review
- Automated 3D Quantitative Analysis of Intrapulmonary Vessel Volume on Noncontrast CT in Healthy Individuals.Current medical imaging · 2025Article
- Automated volumetry of core and peel intrapulmonary vasculature on computed tomography angiography for non-invasive estimation of hemodynamics in patients with pulmonary hypertension (2022 updated hemodynamic definition).Cardiovascular diagnosis and therapy · 2024Article
- Diagnostic value of 3D volume measurement of central pulmonary artery based on CTPA images in the pulmonary hypertension.BMC medical imaging · 2023Article
- Application of CT pulmonary angiography and echocardiography in acute pulmonary embolism: A cross-sectional study.Health science reports · 2023Article
- Machine Learning Based on Computed Tomography Pulmonary Angiography in Evaluating Pulmonary Artery Pressure in Patients with Pulmonary Hypertension.Journal of clinical medicine · 2023Article
- Clinical and Predictive Value of Computed Tomography Angiography in High-Altitude Pulmonary Hypertension.JACC. Asia · 2022Article
- Multi-Imaging Modality Facilitates Screening of Pulmonary Hypertension at High Altitude.JACC. Asia · 2022Article
- [Increased pulmonary arterial and venous pressure].Der Radiologe · 2022Review
- From Early Morphometrics to Machine Learning-What Future for Cardiovascular Imaging of the Pulmonary Circulation?Diagnostics (Basel, Switzerland) · 2020Review
- Pulmonary hypertension due to left heart disease: diagnostic value of pulmonary artery distensibility.European radiology · 2020Article
- Echocardiographic evaluation of the size of the main pulmonary artery and right pulmonary artery in dogs with pulmonary hypertension.Journal of veterinary internal medicineArticle
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Authors and funding
9 authors at 3 institutions in 2 countries.
Funding
Abstract
objectivesTo assess the diagnostic accuracy of automated 3D volumetry of central pulmonary arteries using computed tomography pulmonary angiography (CTPA) for suspected pulmonary hypertension alone and in combination with echocardiography.
methodsThis retrospective diagnostic accuracy study included 70 patients (mean age 66.7, 48 female) assessed for pulmonary hypertension by CTPA and transthoracic echocardiography with estimation of the pulmonary arterial systolic pressure (PASP). Gold standard right heart catheterisation with measurement of the invasive mean pulmonary arterial pressure (invasive mPAP) served as the reference. Volumes of the main, right and left pulmonary arteries (MPA, RPA and LPA) were computed using automated 3D segmentation. For comparison, axial dimensions were manually measured. A linear regression model was established for prediction of mPAP (predicted mPAP).
resultsMPA, RPA and LPA volumes were significantly increased in patients with vs. without pulmonary hypertension (all p < 0.001). Of all measures, MPA volume demonstrated the strongest correlation with invasive mPAP (r = 0.76, p < 0.001). Predicted mPAP using MPA volume and echocardiographic PASP as covariates showed excellent correlation with invasive mPAP (r = 0.89, p < 0.001). Area under the curves for predicting pulmonary hypertension were 0.94 for predicted mPAP, compared to 0.90 for MPA volume and 0.92 for echocardiographic PASP alone. A predicted mPAP > 25.8 mmHg identified pulmonary hypertension with sensitivity, specificity, positive and negative predictive values of 86%, 93%, 95% and 81%, respectively.
conclusionsAutomated 3D volumetry of central pulmonary arteries based on CTPA may be used in conjunction with echocardiographic pressure estimates to noninvasively predict mPAP and pulmonary hypertension as confirmed by gold standard right heart catheterisation with higher diagnostic accuracy than either test alone. KEY POINTS: • This diagnostic accuracy study derived a regression model for noninvasive prediction of invasively measured mean pulmonary arterial pressure as assessed by gold standard right heart catheterisation. • This regression model using automated 3D volumetry of the central pulmonary arteries based on CT pulmonary angiography in conjunction with the echocardiographic pressure estimate predicted pulmonary arterial pressure and the presence of pulmonary hypertension with good diagnostic accuracy. • The combination of automated 3D volumetry and echocardiographic pressure estimate in the regression model provided superior diagnostic accuracy compared to each parameter alone.
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