A comparison of visual and quantitative methods to identify interstitial lung abnormalities

BMC Pulm Med. 2015 Oct 29;15:134. doi: 10.1186/s12890-015-0124-x.

Abstract

Background: Evidence suggests that individuals with interstitial lung abnormalities (ILA) on a chest computed tomogram (CT) may have an increased risk to develop a clinically significant interstitial lung disease (ILD). Although methods used to identify individuals with ILA on chest CT have included both automated quantitative and qualitative visual inspection methods, there has been not direct comparison between these two methods. To investigate this relationship, we created lung density metrics and compared these to visual assessments of ILA.

Methods: To provide a comparison between ILA detection methods based on visual assessment we generated measures of high attenuation areas (HAAs, defined by attenuation values between -600 and -250 Hounsfield Units) in >4500 participants from both the COPDGene and Framingham Heart studies (FHS). Linear and logistic regressions were used for analyses.

Results: Increased measures of HAAs (in ≥ 10 % of the lung) were significantly associated with ILA defined by visual inspection in both cohorts (P < 0.0001); however, the positive predictive values were not very high (19 % in COPDGene and 13 % in the FHS). In COPDGene, the association between HAAs and ILA defined by visual assessment were modified by the percentage of emphysema and body mass index. Although increased HAAs were associated with reductions in total lung capacity in both cohorts, there was no evidence for an association between measurement of HAAs and MUC5B promoter genotype in the FHS.

Conclusion: Our findings demonstrate that increased measures of lung density may be helpful in determining the severity of lung volume reduction, but alone, are not strongly predictive of ILA defined by visual assessment. Moreover, HAAs were not associated with MUC5B promoter genotype.

Publication types

  • Comparative Study
  • Research Support, N.I.H., Extramural
  • Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

  • Aged
  • Aged, 80 and over
  • Body Mass Index
  • Cohort Studies
  • Female
  • Forced Expiratory Volume
  • Humans
  • Image Processing, Computer-Assisted / methods*
  • Linear Models
  • Logistic Models
  • Lung / diagnostic imaging*
  • Lung / physiopathology
  • Lung Diseases, Interstitial / diagnostic imaging*
  • Lung Diseases, Interstitial / genetics
  • Lung Diseases, Interstitial / physiopathology
  • Male
  • Middle Aged
  • Mucin-5B / genetics
  • Promoter Regions, Genetic
  • Pulmonary Disease, Chronic Obstructive / diagnostic imaging
  • Pulmonary Disease, Chronic Obstructive / genetics
  • Pulmonary Disease, Chronic Obstructive / physiopathology
  • Pulmonary Emphysema / diagnostic imaging*
  • Pulmonary Emphysema / genetics
  • Pulmonary Emphysema / physiopathology
  • Spirometry
  • Tomography, X-Ray Computed
  • Total Lung Capacity
  • Vital Capacity

Substances

  • MUC5B protein, human
  • Mucin-5B