title: Density features of screened lung tumors in low-dose computed tomography.
abstract: OBJECTIVE
  Using low-dose computed tomography (LDCT), small and heterogeneous lung tumors are detected in screening. The criteria for assessing detected tumors are crucial for determining follow-up or resection strategies. The purpose of this study was to investigate the capacity of density features in differentiating lung tumors.
  
  
  METHODS
  From July 2008 to December 2011, 48 surgically confirmed tumors (29 malignancies, comprising 17 cases of adenocarcinoma and 12 cases of adenocarcinoma in situ [AdIs], and 19 benignancies, comprising 11 cases of atypical adenomatous hyperplasia [AAH] and eight cases of benign non-AAH) in 38 patients were retrospectively evaluated, indicating that the positive predictive value (PPV) of physicians is 60.4% (29/48). Three types of density features, tumor disappearance rate (TDR), mean, and entropy, were obtained from the CT values of detected tumors.
  
  
  RESULTS
  Entropy is capable of differentiating malignancy from benignancy but is limited in differentiating AdIs from benign non-AAH. The combination of entropy and TDR is effective for predicting malignancy with an accuracy of 87.5% (42/48) and a PPV of 89.7% (26/29), improving the PPV of physicians by 29.3%. The combination of entropy and mean adequately clarifies the four pathology groups with an accuracy of 72.9% (35/48). For tumors with a mean below -400 Hounsfield units, the criterion of an entropy larger than 5.4 might be appropriate for diagnosing malignancy. For others, the pathology is either benign non-AAH or adenocarcinoma; adenocarcinoma has a higher entropy than benign non-AAH, with the exception of tuberculoma.
  
  
  CONCLUSIONS
  Combining density features enables differentiating heterogeneous lung tumors in LDCT.
authors: Department of Computer Science and Information Engineering, Asia University, Taichung, Taiwan.
authors: Wei-Chih
authors: WC
authors: Shen
authors: Department of Radiology, China Medical University Hospital, Taichung, Taiwan; Department of Biomedical Imaging and Radiological Science, China Medical University, Taichung, Taiwan.
authors: Juhn-Cherng
authors: JC
authors: Liu
authors: Department of Health Services Administration, China Medical University, Taichung, Taiwan.
authors: Shwn-Huey
authors: SH
authors: Shieh
authors: Department of Radiology, China Medical University Hospital, Taichung, Taiwan; School of Chinese Medicine, College of Chinese Medicine, China Medical University, Taichung, Taiwan.
authors: Su-Tso
authors: ST
authors: Yang
authors: Department of Pathology, China Medical University Hospital, Taichung, Taiwan.
authors: Guan-Chin
authors: GC
authors: Tseng
authors: Department of Internal Medicine, China Medical University Hospital, Taichung, Taiwan; School of Medicine, China Medical University, Taichung, Taiwan.
authors: Wu-Huei
authors: WH
authors: Hsu
authors: Division of Thoracic Surgery, China Medical University Hospital, Taichung, Taiwan; Cancer Center, China Medical University Hospital, Taichung, Taiwan.
authors: Chih-Yi
authors: CY
authors: Chen
authors: School of Medicine, China Medical University, Taichung, Taiwan; Graduate Institute of Clinical Medical Science, School of Medicine, China Medical University, Taichung, Taiwan; Divisions of Pulmonary and Critical Care Medicine, China Medical University Hospital, 2 Yeu-Der Road, Taichung 40447, Taiwan. Electronic address: yuchest71@gmail.com.
authors: Yang-Hao
authors: YH
authors: Yu
mesh_terms: D015502:Absorptiometry, Photon / Q000379:methods*; D000230:Adenocarcinoma / Q000000981:diagnostic imaging* / Q000503:physiopathology; D000465:Algorithms; D002278:Carcinoma in Situ / Q000000981:diagnostic imaging*; D055088:Early Detection of Cancer / Q000379:methods; D005260:Female; D006801:Humans; D008175:Lung Neoplasms / Q000000981:diagnostic imaging* / Q000503:physiopathology; D008297:Male; D008875:Middle Aged; D011829:Radiation Dosage; D011835:Radiation Protection; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D014057:Tomography, X-Ray Computed / Q000379:methods*
keywords: Density feature; computer-aided diagnosis; low-dose computed tomography; lung tumor