Advances in imaging for lung emphysema

被引:18
|
作者
Martini, Katharina [1 ]
Frauenfelder, Thomas [1 ]
机构
[1] Univ Hosp Zurich, Inst Diagnost & Intervent Radiol, Zurich, Switzerland
关键词
Emphysema; imaging; chronic obstructive pulmonary disease (COPD); VOLUME-REDUCTION SURGERY; OBSTRUCTIVE PULMONARY-DISEASE; ENERGY COMPUTED-TOMOGRAPHY; AIR-FLOW OBSTRUCTION; THIN-SECTION CT; RADIOGRAPHIC APPEARANCE; MACROSCOPIC MORPHOMETRY; PERFUSION SCINTIGRAPHY; ENDOBRONCHIAL VALVES; CHEST RADIOGRAPHY;
D O I
10.21037/atm.2020.04.44
中图分类号
R73 [肿瘤学];
学科分类号
100214 ;
摘要
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) alpha 1-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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页数:15
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