title: Computer-aided Diagnosis for Lung Cancer: Usefulness of Nodule Heterogeneity.
abstract: To develop a computer-aided diagnosis system to differentiate between malignant and benign nodules.
  
  
  
  Seventy-three lung nodules revealed on 60 sets of computed tomography (CT) images were analyzed. Contrast-enhanced CT was performed in 46 CT examinations. The images were provided by the LUNGx Challenge, and the ground truth of the lung nodules was unavailable; a surrogate ground truth was, therefore, constructed by radiological evaluation. Our proposed method involved novel patch-based feature extraction using principal component analysis, image convolution, and pooling operations. This method was compared to three other systems for the extraction of nodule features: histogram of CT density, local binary pattern on three orthogonal planes, and three-dimensional random local binary pattern. The probabilistic outputs of the systems and surrogate ground truth were analyzed using receiver operating characteristic analysis and area under the curve. The LUNGx Challenge team also calculated the area under the curve of our proposed method based on the actual ground truth of their dataset.
  
  
  
  Based on the surrogate ground truth, the areas under the curve were as follows: histogram of CT density, 0.640; local binary pattern on three orthogonal planes, 0.688; three-dimensional random local binary pattern, 0.725; and the proposed method, 0.837. Based on the actual ground truth, the area under the curve of the proposed method was 0.81.
  
  
  
  The proposed method could capture discriminative characteristics of lung nodules and was useful for the differentiation between malignant and benign nodules.
authors.affiliation: Clinical PET Center, Institute of Biomedical Research and Innovation, 2-2 Minatojimaminamimachi, Chuo-ku, Kobe, Hyogo 650-0047, Japan. Electronic address: jurader@yahoo.co.jp.
authors.forename: Mizuho
authors.initials: M
authors.lastname: Nishio
authors.affiliation: Clinical PET Center, Institute of Biomedical Research and Innovation, 2-2 Minatojimaminamimachi, Chuo-ku, Kobe, Hyogo 650-0047, Japan.
authors.forename: Chihiro
authors.initials: C
authors.lastname: Nagashima
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D003287:Contrast Media; D003937:Diagnosis, Differential; D005260:Female; D006801:Humans; D008168:Lung / Q000000981:diagnostic imaging; D008175:Lung Neoplasms / Q000000981:diagnostic imaging*; D008297:Male; D008875:Middle Aged; D025341:Principal Component Analysis; D012372:ROC Curve; D011856:Radiographic Image Enhancement / Q000379:methods; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods*; D003074:Solitary Pulmonary Nodule / Q000000981:diagnostic imaging*; D014057:Tomography, X-Ray Computed / Q000379:methods*; D055815:Young Adult
chemical_list: D003287:Contrast Media
keywords: CAD; CT; Computer-aided diagnosis; Lung cancer