European Radiology

, Volume 23, Issue 4, pp 975–984 | Cite as

Optimal threshold in CT quantification of emphysema

  • Zhimin Wang
  • Suicheng Gu
  • Joseph K. Leader
  • Shinjini Kundu
  • John R. Tedrow
  • Frank C. Sciurba
  • David Gur
  • Jill M. Siegfried
  • Jiantao Pu
Computed Tomography



To determine the optimal threshold by quantitatively assessing the extent of emphysema at the level of the entire lung and at the level of individual lobes using a large, diverse dataset of computed tomography (CT) examinations.


This study comprises 573 chest CT examinations acquired from subjects with different levels of airway obstruction (222 none, 83 mild, 141 moderate, 63 severe and 64 very severe). The extent of emphysema was quantified using the percentage of the low attenuation area (LAA%) divided by the total lung or lobe volume(s). The correlations between the extent of emphysema, and pulmonary functions and the five-category classification were assessed using Pearson and Spearman’s correlation coefficients, respectively. When quantifying emphysema using a density mask, a wide range of thresholds from −850 to −1,000 HU were used.


The highest correlations of LAA% with the five-category classification and PFT measures ranged from −925 to −965 HU for each individual lobe and the entire lung. However, the differences between the highest correlations and those obtained at −950 HU are relatively small.


Although there are variations in the optimal cut-off thresholds for individual lobes, the single threshold of −950 HU is still an acceptable threshold for density-based emphysema quantification.

Key Points

CT is widely used to assess the severity of emphysema

Density mask technique helps clinicians assess the extent of emphysema with CT

A standardised cut-off for density mask analysis at lobe level is desirable

−950 HU is acceptable for density-based emphysema quantification at the lobar level


Chronic obstructive pulmonary disease Computed tomography Pulmonary emphysema Density mask Lobe segmentation 



This work was supported in part by grants HL096613, CA090440, HL084948, HL095397, 2012KTCL03-07 to the University of Pittsburgh from the National Institute of Health, the Bonnie J. Addario Lung Cancer Foundation, and the SPORE in Lung Cancer Career Development Program.


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Copyright information

© European Society of Radiology 2012

Authors and Affiliations

  • Zhimin Wang
    • 1
  • Suicheng Gu
    • 1
  • Joseph K. Leader
    • 1
  • Shinjini Kundu
    • 2
  • John R. Tedrow
    • 3
  • Frank C. Sciurba
    • 4
  • David Gur
    • 1
  • Jill M. Siegfried
    • 5
  • Jiantao Pu
    • 1
  1. 1.Department of RadiologyUniversity of PittsburghPittsburghUSA
  2. 2.School of MedicineUniversity of PittsburghPittsburghUSA
  3. 3.Department of Internal MedicineUniversity of PittsburghPittsburghUSA
  4. 4.Division of Pulmonary and Critical Care MedicineUniversity of PittsburghPittsburghUSA
  5. 5.Department of Pharmacology & Chemical BiologyUniversity of PittsburghPittsburghUSA

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