ReviewDiagnostics (Basel, Switzerland)2021
Pulmonary Hypertension in Association with Lung Disease: Quantitative CT and Artificial Intelligence to the Rescue? State-of-the-Art Review.
Review in Diagnostics (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 2 of them syntheses that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
21 citing papers in PubMed, 2 syntheses or guidelines pooled it, 30 citations in OpenAlex.
- A Comprehensive Review of Artificial Intelligence (AI) Applications in Pulmonary Hypertension (PH).Medicina (Kaunas, Lithuania) · 2025Pooled it
- Meta-Analysis of Interobserver Agreement in Assessment of Interstitial Lung Disease Using High-Resolution CT.Radiology · 2024Pooled it
- Artificial Intelligence and Multi-Omics Approaches in the Precision Management of Pulmonary Hypertension: From Early Diagnosis to Therapeutic Stratification.International journal of molecular sciences · 2026Review
- Artificial Intelligence in Pulmonary Hypertension: Current State and Future Prospects.Reviews in cardiovascular medicine · 2026Review
- AI-based pulmonary artery to ascending aorta ratio on non-contrast CT for pulmonary hypertension: diameter vs. volume assessment.European heart journal. Imaging methods and practice · 2026Article
- The vascular fingerprint of the lungs: why pulmonary vessel count matters in COPD.The European respiratory journal · 2026Article
- AI-based prediction of pulmonary hypertension in COPD patients with cor pulmonale using clinical and CT features.Frontiers in medicine · 2026Article
- A fully automated explainable predictive model for diagnosing pre-capillary and post-capillary pulmonary hypertension on routine unenhanced CT: results from the ASPIRE registry.European heart journal. Digital health · 2026Article
- Chest Computed Tomography-Based Radiomics for the Diagnosis and Prognosis of Pulmonary Hypertension.Journal of the American Heart Association · 2025Article
- Development and Evaluation of a Deep Learning-Based Pulmonary Hypertension Screening Algorithm Using a Digital Stethoscope.Journal of the American Heart Association · 2025Article
- Automated 3D Quantitative Analysis of Intrapulmonary Vessel Volume on Noncontrast CT in Healthy Individuals.Current medical imaging · 2025Article
- Significance of Normal Lung Volume on Quantitative CT Imaging Analysis in Group 1 and Group 3 Pulmonary Hypertension.CHEST pulmonary · 2024Article
- Emerging multimodality imaging techniques for the pulmonary circulation.The European respiratory journal · 2024Review
- Machine learning assisted feature identification and prediction of hemodynamic endpoints using computed tomography in patients with CTEPH.The international journal of cardiovascular imaging · 2024Article
- Bridging the Gap: Exploring Bronchopulmonary Dysplasia through the Lens of Biomedical Informatics.Journal of clinical medicine · 2024Review
- Improving Prognostication in Pulmonary Hypertension Using AI-quantified Fibrosis and Radiologic Severity Scoring at Baseline CT.Radiology · 2024Article
- Review
- A transparent artificial intelligence framework to assess lung disease in pulmonary hypertension.Scientific reports · 2023Article
- Severe pulmonary hypertension associated with lung disease is characterised by a loss of small pulmonary vessels on quantitative computed tomography.ERJ open research · 2022Article
- Article
Corrections and comments
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Authors and funding
11 authors at 5 institutions in 2 countries.
Funding
Abstract
Accurate phenotyping of patients with pulmonary hypertension (PH) is an integral part of informing disease classification, treatment, and prognosis. The impact of lung disease on PH outcomes and response to treatment remains a challenging area with limited progress. Imaging with computed tomography (CT) plays an important role in patients with suspected PH when assessing for parenchymal lung disease, however, current assessments are limited by their semi-qualitative nature. Quantitative chest-CT (QCT) allows numerical quantification of lung parenchymal disease beyond subjective visual assessment. This has facilitated advances in radiological assessment and clinical correlation of a range of lung diseases including emphysema, interstitial lung disease, and coronavirus disease 2019 (COVID-19). Artificial Intelligence approaches have the potential to facilitate rapid quantitative assessments. Benefits of cross-sectional imaging include ease and speed of scan acquisition, repeatability and the potential for novel insights beyond visual assessment alone. Potential clinical benefits include improved phenotyping and prediction of treatment response and survival. Artificial intelligence approaches also have the potential to aid more focused study of pulmonary arterial hypertension (PAH) therapies by identifying more homogeneous subgroups of patients with lung disease. This state-of-the-art review summarizes recent QCT developments and potential applications in patients with PH with a focus on lung disease.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.