الفهرس 
Anatomy of the LungOnly 14 pages are availabe for public view
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Abstract
The pulmonary nodule is a common finding at computed tomography (CT) that may be due to primary or secondary malignancy but also to benign conditions, including granulomatous diseases and other infectious processes. The morphologic imaging diagnosis of a pulmonary nodule can be performed, with special attention paid to the nodule’s margin or internal structure and to its relationships to surrounding structures. In addition, the degree of enhancement or the pattern of enhancement seen with administration of contrast medium at CT is useful for differentiating malignant from benign nodules.
With single–detector row computed tomography (CT), spiral CT images of the thorax are typically obtained with 6–10-mm section thickness. The acquisition of thin-section (i.e. 1–2-mm section thickness) images of the whole thorax is impractical, because it requires multiple breath-hold sets of contiguous spiral scans to cover the thorax completely. Spatial limitations due to thick sections may be compensated for partially by means of using small reconstruction intervals that would improve nodule detection and diagnostic confidence.
Multi–detector row CT, with its fast scanning speed and superb spatial resolution, allows us to routinely acquire thin-section images of the entire thorax in less than 10 seconds. This improvement in spatial and temporal resolution increases the sensitivity for detection of small pulmonary nodules. Furthermore, in multi–detector row CT, multiple spiral data are acquired during a single CT gantry rotation that allows us to generate CT images of different section thicknesses.
With MDCT systems, different section widths are achieved by collimating and adding together the signals of neighboring detector rows.
Thin section reconstructions are recommended for volumetric assessment and characterization of pulmonary nodules.
The advantages of MDCT include both improved nodule detection and nodule characterization on lung cancer screening programs, because the entire lung can be scanned with thin slice in a single breath-hold without an intersection gap. In the evaluation of lung cancer, MDCT will allow improved detection of pleural dissemination and hilar lymph node adenopathy because of the continuous and narrow scan collimation.
Recent advances in MDCT technology and post processing software have brought excellent post processing of axial images into superior quality non axial images. Commonly performed post processing techniques produce two dimensional images using multiplanar reformation (MPR) and maximum intensity projection (MIP), or three dimensional images using various types of volume rendering (VR).
Reading should be performed on a workstation. To avoid reading of an excessive number of individual axial slices (500–600) image by image.