Assessment of prognosis of patients with idiopathic pulmonary fibrosis by computer-aided analysis of CT images

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  • A. A
  • F. S
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Abstract

PURPOSE: To present the Gaussian Histogram Normalized Correlation (GHNC) system, to quantify the extent of disease on computed tomography (CT) images of idiopathic pulmonary fibrosis (IPF), and to assess its utility by comparing the radiologist' scoring and prognosis. MATERIALS AND METHODS: GHNC was used to analyze baseline thin-section CT images (30-60images per patients) of 40 patients with IPF. It classified the CT lung field into normal (N), ground-glass opacities (G), consolidation (C), emphysema (E) and fibrosis (F) patterns [the latter was also subdivided into reticular (F1) and honeycomb (F2) patterns], then the relative lung volume and relative each pattern volume (area multiplied by slice thickness and interval and divided by predicted total lung capacity) were estimated. The radiologists estimated the area of these patterns on 4 slices per patient; the average was regarded as total extent of each pattern. We compared the estimates determined by radiologists and GHNC with pulmonary function tests, and used Cox regression analysis to examine the relationships between the volumes and patient survival. RESULTS: The area of each pattern measured by GHNC correlated significantly with that estimated by the radiologist on 160 images (P

Author-supplied keywords

  • Aquiron-16
  • X-Vigor
  • adult
  • aged
  • article
  • carbon monoxide
  • clinical article
  • computed tomography scanner
  • computer analysis
  • computer assisted tomography
  • controlled study
  • corticosteroid therapy
  • cyclosporin
  • diffusion
  • disease severity
  • feasibility study
  • female
  • fibrosing alveolitis
  • follow up
  • human
  • imaging system
  • lung emphysema
  • lung fibrosis
  • lung function test
  • lung slice
  • lung volume
  • male
  • mortality
  • multidetector computed tomography
  • multivariate analysis
  • prednisolone
  • prognosis
  • radiologist
  • retrospective study
  • survival
  • total lung capacity
  • univariate analysis

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Authors

  • Iwasawa T.

  • Asakura A.

  • Sakai F.

  • Kanauchi T.

  • Gotoh T.

  • Ogura T.

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