ReviewAnnals of translational medicine2020
Advances in imaging for lung emphysema.
Review in Annals of translational medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed, 28 citations in OpenAlex.
- Artificial Intelligence in Asthma and COPD: Current Status and Future Potential.Journal of clinical medicine · 2026Review
- Respiratory symptoms associated with a new lobe-based bronchial scoring system in an urban Chinese low-dose CT screening population.European radiology · 2025Article
- Pulmonary Biomechanics in COPD: Imaging Techniques and Clinical Applications.Journal of biomechanical engineering · 2025Review
- Co-occurrence of bronchiectasis, airway wall thickening, and emphysema in Chinese low-dose CT screening.European radiology · 2025Article
- Automatic recognition and differentiation of pulmonary contusion and bacterial pneumonia based on deep learning and radiomics.BMC medical imaging · 2025Article
- Article
- Pulmonary emphysema: the assessment of lung perfusion with Dual-Energy CT and pulmonary scintigraphy.La Radiologia medica · 2024Article
- Artificial intelligence in COPD CT images: identification, staging, and quantitation.Respiratory research · 2024Review
- [Using Artificial Intelligence Software for Diagnosing Emphysema and Interstitial Lung Disease].Journal of the Korean Society of Radiology · 2024Review
- Development of machine learning model to predict pulmonary function with low-dose CT-derived parameter response mapping in a community-based chest screening cohort.Journal of applied clinical medical physics · 2023Article
- Association between visual emphysema and lung nodules on low-dose CT scan in a Chinese Lung Cancer Screening Program (Nelcin-B3).European radiology · 2022Article
- The role of routine pulmonary imaging before hyperbaric oxygen treatment.Diving and hyperbaric medicine · 2022Review
- Performance of virtual non-contrast images generated on clinical photon-counting detector CT for emphysema quantification: proof of concept.The British journal of radiology · 2022Article
- Radiomics in Lung Diseases Imaging: State-of-the-Art for Clinicians.Journal of personalized medicine · 2021Review
- Pulmonary Emphysema Regional Distribution and Extent Assessed by Chest Computed Tomography Is Associated With Pulmonary Function Impairment in Patients With COPD.Frontiers in medicine · 2021Article
Corrections and comments
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Lung emphysema represents a major public health burden and still accounts for five percent of all deaths worldwide. Hence, it is essential to further understand this disease in order to develop effective diagnostic and therapeutic strategies. Lung emphysema is an irreversible enlargement of the airways distal to the terminal bronchi (i.e., the alveoli) due to the destruction of the alveolar walls. The two most important causes of emphysema are (I) smoking and (II) α1-antitrypsin-deficiency. In the former lung emphysema is predominant in the upper lung parts, the latter is characterized by a predominance in the basal areas of the lungs. Since quantification and evaluation of the distribution of lung emphysema is crucial in treatment planning, imaging plays a central role. Imaging modalities in lung emphysema are manifold: computed tomography (CT) imaging is nowadays the gold standard. However, emerging imaging techniques like dynamic or functional magnetic resonance imaging (MRI), scintigraphy and lately also the implementation of radiomics and artificial intelligence are more and more diffused in the evaluation, diagnosis and quantification of lung emphysema. The aim of this review is to shortly present the different subtypes of lung emphysema, to give an overview on prediction and risk assessment in emphysematous disease and to discuss not only the traditional, but also the new imaging techniques for diagnosis, quantification and evaluation of lung emphysema.
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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.