title: Non-invasive modalities for predicting lymph node spread in early stage endometrial cancer?
abstract: BACKGROUND
  Lymph node status in EC determines the staging and has important prognostic and therapeutic implications.
  
  
  OBJECTIVE
  We have examined the diagnostic value of preoperative and intraoperative non-invasive methods to determine the lymph node status in endometrial cancer, or, indirectly, for identification of patients at increased risk of lymph node involvement.
  
  
  METHODS
  We conducted a literature search to identify all relevant reports that evaluated lymph node spread in EC.
  
  
  METHODS
  Articles were only considered when data of investigational modalities were compared with histopathological findings of the surgical specimens, considered as the gold standard.
  
  
  METHODS
  When numerous relevant articles were identified for one investigational modality, only series including more than 50 patients were considered.
  
  
  RESULTS
  Sensitivity of CT and MRI for diagnosis metastatic lymph node is limited. TVS performs as well as MRI in predicting deep myometrial invasion. It is unclear whether intraoperative gross visual examination and frozen section perform better than preoperative methods to predict deep myometrial invasion. There is a limited sensitivity of intraoperative frozen section for predicting poorly differentiated EC.
  
  
  CONCLUSIONS
  Accurate non-invasive assessment of lymph node status in patients with EC remains challenging.
  
  
  CONCLUSIONS
  Despite imaging advances in the past 20 years, accurate non-invasive assessment of lymph node status in patients with EC remains challenging.
authors.affiliation: Department of Imaging. Geneva University Hospitals, Geneva, Switzerland. pierre.loubeyre@hcuge.ch
authors.forename: Pierre
authors.initials: P
authors.lastname: Loubeyre
authors.forename: Manuela
authors.initials: M
authors.lastname: Undurraga
authors.forename: Alexandre
authors.initials: A
authors.lastname: Bodmer
authors.forename: Patrick
authors.initials: P
authors.lastname: Petignat
mesh_terms: D003952:Diagnostic Imaging; D016889:Endometrial Neoplasms / Q000175:diagnosis*; D005260:Female; D006801:Humans; D008198:Lymph Nodes / Q000473:pathology*; D009367:Neoplasm Staging; D011379:Prognosis