Korean J Radiol.  2011 Jun;12(3):297-307. 10.3348/kjr.2011.12.3.297.

Comparison of Usual Interstitial Pneumonia and Nonspecific Interstitial Pneumonia: Quantification of Disease Severity and Discrimination between Two Diseases on HRCT Using a Texture-Based Automated System

• Park SO
• Seo JB
• Kim N
• Lee YK
• Lee J
• Kim DS

• KMID: 1122327
• DOI: http://doi.org/10.3348/kjr.2011.12.3.297

Abstract

OBJECTIVE
To evaluate the usefulness of an automated system for quantification and discrimination of usual interstitial pneumonia (UIP) and nonspecific interstitial pneumonia (NSIP).
MATERIALS AND METHODS
An automated system to quantify six regional high-resolution CT (HRCT) patterns: normal, NL; ground-glass opacity, GGO; reticular opacity, RO; honeycombing, HC; emphysema, EMPH; and consolidation, CONS, was developed using texture and shape features. Fifty-four patients with pathologically proven UIP (n = 26) and pathologically proven NSIP (n = 28) were included as part of this study. Inter-observer agreement in measuring the extent of each HRCT pattern between the system and two thoracic radiologists were assessed in 26 randomly selected subsets using an interclass correlation coefficient (ICC). A linear regression analysis was used to assess the contribution of each disease pattern to the pulmonary function test parameters. The discriminating capacity of the system between UIP and NSIP was evaluated using a binomial logistic regression.
RESULTS
The overall ICC showed acceptable agreement among the system and the two radiologists (r = 0.895 for the abnormal lung volume fraction, 0.706 for the fibrosis fraction, 0.895 for NL, 0.625 for GGO, 0.626 for RO, 0.893 for HC, 0.800 for EMPH, and 0.430 for CONS). The volumes of NL, GGO, RO, and EMPH contribute to forced expiratory volume during one second (FEV1) (r = 0.72, beta values, 0.84, 0.34, 0.34 and 0.24, respectively) and forced vital capacity (FVC) (r = 0.76, beta values, 0.82, 0.28, 0.21 and 0.34, respectively). For diffusing capacity (DLco), the volumes of NL and HC were independent contributors in opposite directions (r = 0.65, beta values, 0.64, -0.21, respectively). The automated system can help discriminate between UIP and NSIP with an accuracy of 82%.
CONCLUSION
The automated quantification system of regional HRCT patterns can be useful in the assessment of disease severity and may provide reliable agreement with the radiologists' results. In addition, this system may be useful in differentiating between UIP and NSIP.

Keyword

UIP; NSIP; HRCT; automated, quantification, texture, shape

MeSH Terms

Female
Humans
Idiopathic Pulmonary Fibrosis/pathology/radiography
Logistic Models
Lung Diseases, Interstitial/pathology/*radiography
Male
Middle Aged
Pattern Recognition, Automated/*methods
Respiratory Function Tests
Severity of Illness Index
*Tomography, X-Ray Computed

Figure

• 

  Fig. 1 50-year-old man who had pathologically proven usual interstitial pneumonia. A. CT images predominantly showed basal and peripheral honeycombing and reticular opacities. Reader 1 gave five-point rating scale as 4, thereby suggesting probable usual interstitial pneumonia. And reader 2 gave five-point rating scale as 3, thereby suggesting possible usual interstitial pneumonia. B. Automated system interpreted approximately one-half of lung volume as honeycombing and reticular opacities. Value of prob (event)* was 0.61, thus classifying CT images as usual interstitial pneumonia. Pathology also indicated usual interstitial pneumonia. C. System determined 66% of whole lung as abnormal, whereas radiologist regarded 70% as abnormal lung. Extent of fibrosis was 52% according to system, and 50% according to radiologist. Fractional volumes of six patterns were also very similar. *Logistic prediction equation was: ln(prob(event)/[1-prob(event)]) = 0.404 HC + 0.178 GGO + 0.181 RO - 0.010 HC × RO - 0.006 GGO × RO - 0.064 CONS × GGO - 4.347 where, prob(event) < 0.50 was nonspecific interstitial pneumonia and prob(event) ≥ 0.50 was usual interstitial pneumonia.

• 

  Fig. 2 55-year-old woman who had pathologically proven nonspecific interstitial pneumonia. A. CT images showed basal ground glass and reticular opacities with no areas of honeycombing. Reader 1 gave five-point rating scale as 2, thus suggesting probable nonspecific interstitial pneumonia. Reader 2 gave five-point rating scale as 1, thereby suggesting definite nonspecific interstitial pneumonia. B. System interpreted approximately one-half of lung volume as ground glass and reticular opacities. System also detected some areas of consolidation and honeycombing. Value of prob (event)* was < 0.01, thus classifying CT images as nonspecific interstitial pneumonia. Pathology also indicated nonspecific interstitial pneumonia. C. System determined 58% of whole lung as abnormal, whereas radiologist regarded 50% as abnormal lung. Extent of fibrosis was 26% according to system, and 20% according to radiologist. *Logistic prediction equation was: ln(prob(event)/[1-prob(event)]) = 0.404 HC + 0.178 GGO + 0.181 RO - 0.010 HC × RO - 0.006 GGO × RO - 0.064 CONS × GGO - 4.347 where, prob(event) < 0.50 was nonspecific interstitial pneumonia and prob(event) ≥ 0.50 was usual interstitial pneumonia.

• 

  Fig. 3 47-year-old man who had pathologically proven nonspecific interstitial pneumonia. A. CT images predominantly showed basal and peripheral reticular opacities. There were also some areas of honeycombing and subpleural emphysema. Two readers gave five-point rating scale as 3, thus suggesting possible usual interstitial pneumonia. B. System interpreted more lung volume as ground glass and reticular opacities than did human reader. Honeycombing was less prominent in system's quantification. Value of prob (event)* was 0.35, thus classifying CT images as nonspecific interstitial pneumonia. Pathology also indicated nonspecific interstitial pneumonia. C. System determined that 25% of whole lung as abnormal, whereas radiologist regarded 35% as abnormal lung. Extent of fibrosis was 15% according to system, and 20% according to radiologist. *Logistic prediction equation was: ln(prob(event)/[1-prob(event)]) = 0.404 HC + 0.178 GGO + 0.181 RO - 0.010 HC × RO - 0.006 GGO × RO - 0.064 CONS × GGO - 4.347 where, prob(event) < 0.50 was nonspecific interstitial pneumonia and prob(event) ≥ 0.50 was usual interstitial pneumonia.

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