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Insights into Imaging is a copyright of Springer, 2017.

Abstract

Objectives

To describe the imaging features of the central airway pathology, correlating the findings with those in pathology and virtual endoscopy. To propose a schematic and practical approach to reach diagnoses, placing strong emphasis on multidetector computed tomography (MDCT) findings.

Methods

We reviewed our thoracic pathology database and the central airway pathology-related literature. Best cases were selected to illustrate the main features of each disease. MDCT was performed in all cases. Multiplanar and volume-rendering reconstructions were obtained when necessary. Virtual endoscopy was obtained from the CT with dedicated software.

Results

Pathological conditions affecting the central airways are a heterogeneous group of diseases. Focal alterations include benign neoplasms, malignant neoplasms, and non-neoplastic conditions. Diffuse abnormalities are divided into those that produce dilation and those that produce stenosis and tracheobronchomalacia. Direct bronchoscopy (DB) visualises the mucosal layer and is an important diagnostic and therapeutic weapon. However, assessing the deep layers or the adjacent tissue is not possible. MDCT and post-processing techniques such as virtual bronchoscopy (VB) provide an excellent evaluation of the airway wall.

Conclusion

This review presents the complete spectrum of the central airway pathology with its clinical, pathological and radiological features.

Teaching points

* Dividing diseases into diffuse and focal lesions helps narrow the differential diagnosis.

* Focal lesions with nodularity are more likely to correspond to tumours.

* Focal lesions with stenosis are more likely to correspond to inflammatory disease.

* Posterior wall involvement is the main feature in diffuse lesions with stenosis.

Details

Title
Central airway pathology: clinic features, CT findings with pathologic and virtual endoscopy correlation
Author
Barnes, Daniel; Gutiérrez Chacoff, José; Benegas, Mariana; Perea, Rosario J; de Caralt, Teresa M; Ramirez, José; Vollmer, Ivan; Sanchez, Marcelo
Pages
255-270
Publication year
2017
Publication date
Feb 2017
Publisher
Springer Nature B.V.
e-ISSN
18694101
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
1879394578
Copyright
Insights into Imaging is a copyright of Springer, 2017.