title: Clinical and pathological correlates of severity classifications in trigger fingers based on computer-aided image analysis.
abstract: BACKGROUND
  The treatment of trigger finger so far has heavily relied on clinicians' evaluations for the severity of patients' symptoms and the functionality of affected fingers. However, there is still a lack of pathological evidence supporting the criteria of clinical evaluations. This study's aim was to correlate clinical classification and pathological changes for trigger finger based on the tissue abnormality observed from microscopic images.
  
  
  METHODS
  Tissue samples were acquired, and microscopic images were randomly selected and then graded by three pathologists and two physicians, respectively. Moreover, the acquired images were automatically analyzed to derive two quantitative parameters, the size ratio of the abnormal tissue region and the number ratio of the abnormal nuclei, which can reflect tissue abnormality caused by trigger finger. A self-developed image analysis system was used to avoid human subjectivity during the quantification process. Finally, correlations between the quantitative image parameters, pathological grading, and clinical severity classification were assessed.
  
  
  RESULTS
  One-way ANOVA tests revealed significant correlations between the image quantification and pathological grading as well as between the image quantification and clinical severity classification. The Cohen's kappa coefficient test also depicted good consistency between pathological grading and clinical severity classification.
  
  
  CONCLUSIONS
  The criteria of clinical classification were found to be highly associated with the pathological changes of affected tissues. The correlations serve as explicit evidence supporting clinicians in making a treatment strategy of trigger finger. In addition, our proposed computer-aided image analysis system was considered to be a promising and objective approach to determining trigger finger severity at the microscopic level.
authors: Tai-Hua
authors: TH
authors: Yang
authors: Hsin-Chen
authors: HC
authors: Chen
authors: Yung-Chun
authors: YC
authors: Liu
authors: Hui-Hsuan
authors: HH
authors: Shih
authors: Li-Chieh
authors: LC
authors: Kuo
authors: Stephen
authors: S
authors: Cha
authors: Hsiao-Bai
authors: HB
authors: Yang
authors: Dee-Shan
authors: DS
authors: Yang
authors: I-Ming
authors: IM
authors: Jou
authors: Department of Biomedical Engineering, National Cheng Kung University, 1 University Road, Tainan 701, Taiwan. ynsun@mail.ncku.edu.tw.
authors: Yung-Nien
authors: YN
authors: Sun
authors: Fong-Chin
authors: FC
authors: Su
mesh_terms: D000328:Adult; D000368:Aged; D000704:Analysis of Variance; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008297:Male; D008853:Microscopy; D008875:Middle Aged; D052582:Trigger Finger Disorder / Q000175:diagnosis* / Q000473:pathology*