How is emphysema diagnosed with CT imaging?

Updated: Mar 13, 2019
  • Author: Ali Nawaz Khan, MBBS, FRCS, FRCP, FRCR; Chief Editor: Eugene C Lin, MD  more...
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For the visual detection of emphysema, use of a high-definition algorithm (bone or lung settings) is helpful. However, for the automatic detection of emphysema by computer, the standard algorithm is probably best. High-definition filters affect the attenuation measured by the computer, deviating from the values from the real Hounsfield scale and generally increasing the attenuation to variable degrees depending on the air-lung-tissue proportion. This effect is even more important when the attenuation of the lungs is compared for high-definition processing with scanners from different suppliers.

To enhance the margins of adjacent structures with different attenuations, processing artificially changes the original attenuation of the interface planes between the adjacent high- and low-attenuating structures, as in the case of the lung parenchyma and the air content of the lungs. This phenomenon is more obvious in the lung and skin than in solid viscera. This is probably why thresholds for discriminating emphysema differ in the current literature. The authors' personal experience suggests that the threshold -950 HU, as Gevenois suggested, with the standard algorithm without edge enhancement is the most appropriate method. This method may be most consistent and reliable for measuring the lung attenuation by using different machines.

Volumetric quantification of emphysema is based on the Hounsfield scale by using CT pulmonary densitovolumetry (shown in the images below). Some studeis suggest that precocious detection with quantification and 3-dimensional (3D) demonstration of the extension and distribution of emphysema can be helpful in smoking cessation programs or in risk assessments for occupational exposures.

CT densitovolumetry of a nonsmoker, healthy young CT densitovolumetry of a nonsmoker, healthy young patient shows normal lungs. Less than 0.35% of lungs have attenuations below -950 HU (Corrêa da Silva, 2001).
CT densitovolumetry in a patient with lung cancer. CT densitovolumetry in a patient with lung cancer. Three-dimensional (3D) image shows that the cancer is in the portion of the right lung that was less affected by emphysema in a patient with poor pulmonary function (Corrêa da Silva, 2001).
CT densitovolumetry shows the attenuation mask. Gr CT densitovolumetry shows the attenuation mask. Green areas are those with attenuation below the selected threshold (here, -950 HU to evaluate emphysema), and pink areas are those with attenuations above the threshold. Area outside the patient is highlighted in green because of air (Corrêa da Silva, 2001).

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