title: The method and efficacy of support vector machine classifiers based on texture features and multi-resolution histogram from (18)F-FDG PET-CT images for the evaluation of mediastinal lymph nodes in patients with lung cancer.
abstract: OBJECTIVE
  In clinical practice, image analysis is dependent on simply visual perception and the diagnostic efficacy of this analysis pattern is limited for mediastinal lymph nodes in patients with lung cancer. In order to improve diagnostic efficacy, we developed a new computer-based algorithm and tested its diagnostic efficacy.
  
  
  METHODS
  132 consecutive patients with lung cancer underwent (18)F-FDG PET/CT examination before treatment. After all data were imported into the database of an on-line medical image analysis platform, the diagnostic efficacy of visual analysis was first evaluated without knowing pathological results, and the maximum short diameter and maximum standardized uptake value (SUVmax) were measured. Then lymph nodes were segmented manually. Three classifiers based on support vector machine (SVM) were constructed from CT, PET, and combined PET-CT images, respectively. The diagnostic efficacy of SVM classifiers was obtained and evaluated.
  
  
  RESULTS
  According to ROC curves, the areas under curves for maximum short diameter and SUVmax were 0.684 and 0.652, respectively. The areas under the ROC curve for SVM1, SVM2, and SVM3 were 0.689, 0.579, and 0.685, respectively.
  
  
  CONCLUSIONS
  The algorithm based on SVM was potential in the diagnosis of mediastinal lymph nodes.
authors.affiliation: Center of PET/CT, The Third Affiliated Hospital of Harbin Medical University, The Affiliated Tumor Hospital of Harbin Medical University, Harbin, China.
authors.forename: Xuan
authors.initials: X
authors.lastname: Gao
authors.affiliation: HIT-INSA Sino French Research Centre for Biomedical Imaging, Harbin Institute of Technology, Harbin, China.
authors.forename: Chunyu
authors.initials: C
authors.lastname: Chu
authors.affiliation: Center of PET/CT, The Third Affiliated Hospital of Harbin Medical University, The Affiliated Tumor Hospital of Harbin Medical University, Harbin, China.
authors.forename: Yingci
authors.initials: Y
authors.lastname: Li
authors.affiliation: Center of PET/CT, The Third Affiliated Hospital of Harbin Medical University, The Affiliated Tumor Hospital of Harbin Medical University, Harbin, China.
authors.forename: Peiou
authors.initials: P
authors.lastname: Lu
authors.affiliation: Center of PET/CT, The Third Affiliated Hospital of Harbin Medical University, The Affiliated Tumor Hospital of Harbin Medical University, Harbin, China.
authors.forename: Wenzhi
authors.initials: W
authors.lastname: Wang
authors.affiliation: HIT-INSA Sino French Research Centre for Biomedical Imaging, Harbin Institute of Technology, Harbin, China.
authors.forename: Wanyu
authors.initials: W
authors.lastname: Liu
authors.affiliation: Center of PET/CT, The Third Affiliated Hospital of Harbin Medical University, The Affiliated Tumor Hospital of Harbin Medical University, Harbin, China. Electronic address: yulijuan2003@126.com.
authors.forename: Lijuan
authors.initials: L
authors.lastname: Yu
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D000465:Algorithms; D005260:Female; D019788:Fluorodeoxyglucose F18; D006801:Humans; D008175:Lung Neoplasms / Q000000981:diagnostic imaging / Q000473:pathology*; D008198:Lymph Nodes / Q000000981:diagnostic imaging* / Q000473:pathology*; D008207:Lymphatic Metastasis / Q000000981:diagnostic imaging; D008297:Male; D008875:Middle Aged; D049268:Positron-Emission Tomography / Q000379:methods; D012372:ROC Curve; D019275:Radiopharmaceuticals; D012189:Retrospective Studies; D060388:Support Vector Machine; D014057:Tomography, X-Ray Computed
chemical_list: D019275:Radiopharmaceuticals; D019788:Fluorodeoxyglucose F18
keywords: (18)F-FDG; Lung carcinoma; PET-CT; Support vector machine