title: Diagnosis of lymph node metastasis in uterine cervical cancer: usefulness of computer-aided diagnosis with comprehensive evaluation of MR images and clinical findings.
abstract: BACKGROUND
  Lymph node (LN) status is an important parameter for determining the treatment strategy and for predicting the prognosis for patients with uterine cervical cancer. Computer-aided diagnosis (CAD) can be feasible for differentiating metastatic from non-metastatic lymph nodes in patients with uterine cervical cancer.
  
  
  OBJECTIVE
  To determine the usefulness of CAD that comprehensively evaluates MR images and clinical findings for detecting LN metastasis in uterine cervical cancer.
  
  
  METHODS
  In 680 LNs from 143 patients who underwent radical hysterectomy for uterine cervical cancer, the CAD system using the Bayesian classifier estimated the probability of metastasis based on MR findings and clinical findings. We compared the diagnostic accuracy for detecting metastatic LNs in the CAD and MR findings.
  
  
  RESULTS
  Metastasis was diagnosed in 70 (12%) LNs from 34 (24%) patients. The area under ROC curves of CAD (0.924) was greater than those of the mean ADC (0.854), minimum ADC (0.849), maximum ADC (0.827), short-axis diameter (0.856) and long-axis diameter (0.753) (P < 0.05). The specificity and accuracy of the CAD (86%, 86%) were greater than those of the mean ADC (77%, 77%), maximum ADC (77%, 77%), minimum ADC (68%, 70%), and short-axis diameter (65%, 67%) (P < 0.05).
  
  
  CONCLUSIONS
  CAD system can improve the diagnostic performance of MR for detecting metastatic LNs in uterine cervical cancer.
authors.affiliation: Department of Radiology, Research Institute of Radiology, Medical Imaging Laboratory, Asan Medical Center, University of Ulsan College of Medicine, Seoul.
authors.forename: Mi-hyun
authors.initials: MH
authors.lastname: Kim
authors.forename: Jeong Kon
authors.initials: JK
authors.lastname: Kim
authors.forename: Youngjoo
authors.initials: Y
authors.lastname: Lee
authors.forename: Bum-Woo
authors.initials: BW
authors.lastname: Park
authors.forename: Chang Kyung
authors.initials: CK
authors.lastname: Lee
authors.forename: Namkug
authors.initials: N
authors.lastname: Kim
authors.forename: Gyunggoo
authors.initials: G
authors.lastname: Cho
authors.forename: Hyuck Jae
authors.initials: HJ
authors.lastname: Choi
authors.forename: Kyoung-Sik
authors.initials: KS
authors.lastname: Cho
mesh_terms: D000328:Adult; D001499:Bayes Theorem; D001706:Biopsy; D003937:Diagnosis, Differential; D038524:Diffusion Magnetic Resonance Imaging / Q000379:methods*; D017352:Echo-Planar Imaging / Q000379:methods; D005260:Female; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008198:Lymph Nodes / Q000473:pathology*; D008207:Lymphatic Metastasis; D008875:Middle Aged; D015588:Observer Variation; D012372:ROC Curve; D015203:Reproducibility of Results; D012189:Retrospective Studies; D012680:Sensitivity and Specificity; D021701:Sentinel Lymph Node Biopsy / Q000379:methods*; D002583:Uterine Cervical Neoplasms / Q000473:pathology*