title: High-resolution CT scanning: potential outcome measure.
abstract: OBJECTIVE
  High-resolution CT (HRCT) imaging of the chest can provide both structural and functional lung analysis useful to evaluate initial and progressive cystic fibrosis (CF) lung disease. Chest HRCT scoring systems have been used to evaluate the extent and severity of CF specific airway and lung parenchymal disease. The purpose of this review is to summarize recent developments in HRCT and volumetric chest CT imaging, CF chest CT scoring systems, and review how HRCT/volumetric CT can provide useful outcome measures for future CF clinical research.
  
  
  RESULTS
  Early manifestation of CF lung disease determined by chest CT/HRCT imaging in CF infants and children with mild disease include regional air trapping and bronchial wall thickness. The distribution of findings in more progressed CF lung disease are heterogeneous, and there appears to be a large amount of nonhomogeneity of progressive lung pathology. Recent CF studies have used new clinical CT parameters such as quantitative air trapping, quantitative airway measurements, and a composite CT/pulmonary function test (PFT) score, which appear to be promising new outcome measures that are more sensitive than global pulmonary function measurements or total chest CT scores in discriminating early or mild CF lung disease and treatment effects during clinical interventions.
  
  
  CONCLUSIONS
  Chest HRCT and volumetric CT imaging can detect regional CF lung changes before changes in global pulmonary function measurements. Chest HRCT scoring has been used in descriptive studies defining CF lung disease severity, in longitudinal studies to define progression of disease, and in clinical intervention studies to evaluate treatment effects. In the last 2 years, CF CT research has evolved from solely using chest HRCT scoring systems to utilization of composite CT/PFT scores, quantitative airway and air trapping measurements, and the utilization of volumetric CT imaging to evaluate three-dimensional data sets in patients with CF lung disease.
authors.affiliation: Pediatric Pulmonary Division, Stanford University Medical Center, Palo Alto, California 94305-5786, USA. ter@stanford.edu
authors.forename: Terry E
authors.initials: TE
authors.lastname: Robinson
mesh_terms: D003550:Cystic Fibrosis / Q000000981:diagnostic imaging*; D018450:Disease Progression; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008137:Longitudinal Studies; D008168:Lung / Q000000981:diagnostic imaging*; D011856:Radiographic Image Enhancement; D014057:Tomography, X-Ray Computed / Q000379:methods*; D016896:Treatment Outcome