title: Quantitative computerized two-point correlation analysis of lung CT scans correlates with pulmonary function in pulmonary sarcoidosis.
abstract: BACKGROUND
  Chest CT scans are commonly used to clinically assess disease severity in patients presenting with pulmonary sarcoidosis. Despite their ability to reliably detect subtle changes in lung disease, the utility of chest CT scans for guiding therapy is limited by the fact that image interpretation by radiologists is qualitative and highly variable. We sought to create a computerized CT image analysis tool that would provide quantitative and clinically relevant information.
  
  
  METHODS
  We established that a two-point correlation analysis approach reduced the background signal attendant to normal lung structures, such as blood vessels, airways, and lymphatics while highlighting diseased tissue. This approach was applied to multiple lung fields to generate an overall lung texture score (LTS) representing the quantity of diseased lung parenchyma. Using deidentified lung CT scan and pulmonary function test (PFT) data from The Ohio State University Medical Center's Information Warehouse, we analyzed 71 consecutive CT scans from patients with sarcoidosis for whom simultaneous matching PFTs were available to determine whether the LTS correlated with standard PFT results.
  
  
  RESULTS
  We found a high correlation between LTS and FVC, total lung capacity, and diffusing capacity of the lung for carbon monoxide (P &lt; .0001 for all comparisons). Moreover, LTS was equivalent to PFTs for the detection of active lung disease. The image analysis protocol was conducted quickly (&lt; 1 min per study) on a standard laptop computer connected to a publicly available National Institutes of Health ImageJ toolkit.
  
  
  CONCLUSIONS
  The two-point image analysis tool is highly practical and appears to reliably assess lung disease severity. We predict that this tool will be useful for clinical and research applications.
authors.affiliation: Department of Electrical and Computer Engineering, The Ohio State University College of Engineering, Columbus, OH; Department of Radiology, The Ohio State University College of Medicine, Columbus, OH.
authors.forename: Barbaros Selnur
authors.initials: BS
authors.lastname: Erdal
authors.affiliation: Division of Pulmonary, Allergy, Critical Care and Sleep Medicine, The Ohio State University College of Medicine, Columbus, OH. Electronic address: elliott.crouser@osumc.edu.
authors.forename: Elliott D
authors.initials: ED
authors.lastname: Crouser
authors.affiliation: Center for Biostatistics, The Ohio State University Office of Health Sciences, Columbus, OH.
authors.forename: Vedat
authors.initials: V
authors.lastname: Yildiz
authors.affiliation: Department of Radiology, The Ohio State University College of Medicine, Columbus, OH.
authors.forename: Mark A
authors.initials: MA
authors.lastname: King
authors.affiliation: Department of Radiology, The Ohio State University College of Medicine, Columbus, OH.
authors.forename: Andrew T
authors.initials: AT
authors.lastname: Patterson
authors.affiliation: Department of Radiology, The Ohio State University College of Medicine, Columbus, OH.
authors.forename: Michael V
authors.initials: MV
authors.lastname: Knopp
authors.affiliation: Department of Electrical and Computer Engineering, The Ohio State University College of Engineering, Columbus, OH.
authors.forename: Bradley D
authors.initials: BD
authors.lastname: Clymer
mesh_terms: D002248:Carbon Monoxide / Q000378:metabolism; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008168:Lung / Q000000981:diagnostic imaging* / Q000378:metabolism / Q000503:physiopathology*; D012129:Respiratory Function Tests; D017565:Sarcoidosis, Pulmonary / Q000000981:diagnostic imaging* / Q000378:metabolism / Q000503:physiopathology*; D012720:Severity of Illness Index; D014057:Tomography, X-Ray Computed; D014109:Total Lung Capacity / Q000502:physiology; D014797:Vital Capacity / Q000502:physiology
chemical_list: D002248:Carbon Monoxide