title: Histogram-based quantitative evaluation of endobronchial ultrasonography images of peripheral pulmonary lesion.
abstract: BACKGROUND
  Endobronchial ultrasonography using a guide sheath (EBUS-GS) is an increasingly common bronchoscopic technique, but currently, no methods have been established to quantitatively evaluate EBUS images of peripheral pulmonary lesions.
  
  
  OBJECTIVE
  The purpose of this study was to evaluate whether histogram data collected from EBUS-GS images can contribute to the diagnosis of lung cancer.
  
  
  METHODS
  Histogram-based analyses focusing on the brightness of EBUS images were retrospectively conducted: 60 patients (38 lung cancer; 22 inflammatory diseases), with clear EBUS images were included. For each patient, a 400-pixel region of interest was selected, typically located at a 3- to 5-mm radius from the probe, from recorded EBUS images during bronchoscopy. Histogram height, width, height/width ratio, standard deviation, kurtosis and skewness were investigated as diagnostic indicators.
  
  
  RESULTS
  Median histogram height, width, height/width ratio and standard deviation were significantly different between lung cancer and benign lesions (all p < 0.01). With a cutoff value for standard deviation of 10.5, lung cancer could be diagnosed with an accuracy of 81.7%. Other characteristics investigated were inferior when compared to histogram standard deviation.
  
  
  CONCLUSIONS
  Histogram standard deviation appears to be the most useful characteristic for diagnosing lung cancer using EBUS images.
authors.affiliation: Division of Respiratory and Infectious Diseases, Department of Internal Medicine, Kawasaki, Japan.
authors.forename: Kei
authors.initials: K
authors.lastname: Morikawa
authors.forename: Noriaki
authors.initials: N
authors.lastname: Kurimoto
authors.forename: Takeo
authors.initials: T
authors.lastname: Inoue
authors.forename: Masamichi
authors.initials: M
authors.lastname: Mineshita
authors.forename: Teruomi
authors.initials: T
authors.lastname: Miyazawa
mesh_terms: D000230:Adenocarcinoma / Q000000981:diagnostic imaging* / Q000473:pathology; D001999:Bronchoscopy; D002294:Carcinoma, Squamous Cell / Q000000981:diagnostic imaging* / Q000473:pathology; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008175:Lung Neoplasms / Q000000981:diagnostic imaging* / Q000473:pathology; D012189:Retrospective Studies; D055752:Small Cell Lung Carcinoma / Q000000981:diagnostic imaging / Q000473:pathology; D018084:Ultrasonography, Interventional