title: Fractal analysis of small peripheral pulmonary nodules in thin-section CT: evaluation of the lung-nodule interfaces.
abstract: OBJECTIVE
  To analyze the lung-nodule interfaces on small peripheral pulmonary nodules (<2 cm) in thin-section CT (HRCT) images with fractal analysis.
  
  
  METHODS
  Thin-section CT images from 70 patients with bronchogenic carcinomas (61 adenocarcinomas and 9 squamous cell carcinomas) and 47 patients with benign pulmonary nodules (23 hamartomas, 13 organizing pneumonias, and 11 tuberculomas) were used. For calculation of fractal dimensions (FDs), the authors used a box-counting method for binary- and gray-scale images of nodules. FD(two-dimensional [2D]) was an FD obtained from the binary image, and FD(three-dimensional [3D]) was an FD obtained from the gray-scale image.
  
  
  RESULTS
  The FD(2D)s of hamartomas were smaller than those of other nodules ( < 0.05). The FD(3D)s obtained from the gray-scale images of organizing pneumonias and tuberculomas were greater than those of bronchogenic carcinomas ( < 0.0001) and hamartomas ( < 0.0001). In bronchogenic carcinomas, FD(3D)s of adenocarcinomas were greater than those of squamous cell carcinomas ( < 0.05).
  
  
  CONCLUSIONS
  Fractal dimensions reflect the characteristics of the lung-nodule interfaces of small peripheral pulmonary nodules. The FD(2D)s revealed the irregularities of the contours. On the other hand, FD(3D)s revealed the complexities of the heterogeneous textures. With use of FD(2D) and FD(3D), it may be possible to distinguish bronchogenic carcinomas from benign pulmonary nodules. Moreover, FD(3D) may make it possible to distinguish between adenocarcinomas and squamous cell carcinomas.
authors.affiliation: Department of Computer Science and System Engineering, Faculty of Wngineering, Yamaguchi University, Japan. kido@ai.csse.yamaguchi-u.ac.jp
authors.forename: Shoji
authors.initials: S
authors.lastname: Kido
authors.forename: Keiko
authors.initials: K
authors.lastname: Kuriyama
authors.forename: Masahiko
authors.initials: M
authors.lastname: Higashiyama
authors.forename: Tsutomu
authors.initials: T
authors.lastname: Kasugai
authors.forename: Chikazumi
authors.initials: C
authors.lastname: Kuroda
mesh_terms: D000230:Adenocarcinoma / Q000000981:diagnostic imaging*; D000368:Aged; D002283:Carcinoma, Bronchogenic / Q000000981:diagnostic imaging*; D002294:Carcinoma, Squamous Cell / Q000000981:diagnostic imaging*; D003937:Diagnosis, Differential; D005260:Female; D017709:Fractals; D006801:Humans; D007091:Image Processing, Computer-Assisted; D021621:Imaging, Three-Dimensional; D008171:Lung Diseases / Q000000981:diagnostic imaging; D008175:Lung Neoplasms / Q000000981:diagnostic imaging*; D008297:Male; D008875:Middle Aged; D012680:Sensitivity and Specificity; D003074:Solitary Pulmonary Nodule / Q000000981:diagnostic imaging*; D014057:Tomography, X-Ray Computed