title: Clinical Application of Diffusion-Weighted Magnetic Resonance Imaging in Uterine Cervical Cancer.
abstract: OBJECTIVE
  This study aimed to investigate the application value of apparent diffusion coefficient (ADC) values in evaluating histological type as well as pathologic grade of uterine cervical cancer; and to investigate whether ADC values could reflect tumor cellular density.
  
  
  METHODS
  Ninety-eight patients with histopathologically proven uterine cervical cancer were included in this study. Mean ADC value and minimum ADC value of the tumor were measured. Tumor cellular density was counted using colored multifunction imaging analyzing system.
  
  
  RESULTS
  Both mean ADC value and minimum ADC value of squamous cell carcinoma were significantly lower than that of adenocarcinoma (P = 0.001; P = 0.000). Using mean ADC criteria (≤0.965 × 10⁻³ mm/s²) and minimum ADC criteria (≤0.844 × 10⁻³ mm/s²), the sensitivity and specificity for differentiating squamous cell carcinoma from adenocarcinoma were 83.5% and 76.9%, and 77.6% and 92.3%, respectively. Receiver operating characteristic analysis revealed that there was no statistically significant difference in the Az values between them (P = 0.990). Tumor cellular density, mean ADC value, and minimum ADC value of different pathological grade varied significantly (P = 0.000, P = 0.000, P = 0.000). There was a significant positive linear correlation between tumor cellular density and pathological grade of tumor (P = 0.000). Both mean ADC value and minimum ADC value correlated negatively with cellular density (P = 0.000, P = 0.000) and the pathological grade of tumor (P = 0.000, P = 0.000). Comparisons of correlation coefficients showed no significant differences (P = 0.656, P = 0.631).
  
  
  CONCLUSIONS
  Diffusion-weighted magnetic resonance imaging has a potential ability to indicate the histologic type of uterine cervical cancer. Apparent diffusion coefficient measurements of uterine cervical cancer can represent tumor cellular density, thus providing a new method for evaluating the pathological grade of tumor.
authors.affiliation: *Department of Radiology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center of Cancer, Key Laboratory of Cancer Prevention and Therapy; and †Department of Radiology, General Hospital of Tianjin Medical University, Tianjin, China.
authors.forename: Ying
authors.initials: Y
authors.lastname: Liu
authors.forename: Zhaoxiang
authors.initials: Z
authors.lastname: Ye
authors.forename: Haoran
authors.initials: H
authors.lastname: Sun
authors.forename: Renju
authors.initials: R
authors.lastname: Bai
mesh_terms: D000230:Adenocarcinoma / Q000473:pathology*; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D002294:Carcinoma, Squamous Cell / Q000473:pathology*; D038524:Diffusion Magnetic Resonance Imaging / Q000379:methods*; D005260:Female; D005500:Follow-Up Studies; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008875:Middle Aged; D060787:Neoplasm Grading; D009367:Neoplasm Staging; D015588:Observer Variation; D011379:Prognosis; D012372:ROC Curve; D002583:Uterine Cervical Neoplasms / Q000473:pathology*