title: Magnetic Resonance Imaging as a Valuable Tool for Predicting Parametrial Invasion in Stage IB1 to IIA2 Cervical Cancer.
abstract: The aims of study were to determine the predictive value of preoperative magnetic resonance imaging (MRI) for parametrial invasion (PMI) and to develop a predictive model for PMI in patients with stage IB1 to IIA2 cervical cancer.
  
  
  
  We retrospectively analyzed patients with stage IB1 to IIA2 cervical cancer (n = 215) who underwent radical hysterectomy between 2003 and 2014. The presence of PMI from postoperative pathological reports and its association with preoperative MRI findings were evaluated. We developed a predictive model for PMI using independent predictive factors identified by logistic regression and estimated its predictive performance.
  
  
  
  Thirty patients (14.0%) had PMI from postoperative pathological reports. Among the preoperative MRI findings, a greater tumor diameter (4.2 vs 2.0 cm; P < 0.001), a larger tumor volume (92.6 vs 12.7 cm; P < 0.001), the presence of PMI (53.3% vs 8.6%; P < 0.001), and upper vaginal involvement (73.3% vs 22.7%; P < 0.001) were significantly associated with PMI. Multivariate analysis identified tumor volume (odds ratio, 7.0; 95% confidence interval, 2.63-18.53; P < 0.001) and PMI (odds ratio, 6.1; 95% confidence interval, 2.31-15.97; P < 0.001) from preoperative MRI findings as independent predictive factors for PMI. Our predictive model demonstrates that the presence of PMI or a tumor volume of greater than 18.0 cm has a higher sensitivity (86.7% vs 53.3%) and lower specificity (74.6% vs 91.4%) than the presence of PMI alone. Specifically, the model's negative predictive value was superior to that of PMI only (97.2% vs 92.3%). In the low-risk group, defined as preoperative MRI findings suggesting no PMI and a tumor volume of 18.0 cm or less, the proportion of false negative cases was just 2.8%.
  
  
  
  When tumor volume with findings suggesting that PMI is considered, preoperative MRI is useful in excluding PMI. A predictive model based on preoperative MRI findings seems to be valuable in identifying potential candidates for less radical surgery in stage IB1 to IIA2 cervical cancer.
authors.affiliation: Departments of *Obstetrics and Gynecology and †Radiology, Seoul National University Bundang Hospital, Seongnam, Republic of Korea.
authors.forename: Miseon
authors.initials: M
authors.lastname: Kim
authors.forename: Dong Hoon
authors.initials: DH
authors.lastname: Suh
authors.forename: Kidong
authors.initials: K
authors.lastname: Kim
authors.forename: Hak Jong
authors.initials: HJ
authors.lastname: Lee
authors.forename: Yong Beom
authors.initials: YB
authors.lastname: Kim
authors.forename: Jae Hong
authors.initials: JH
authors.lastname: No
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D005260:Female; D006801:Humans; D016015:Logistic Models; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008875:Middle Aged; D009361:Neoplasm Invasiveness; D009367:Neoplasm Staging; D011237:Predictive Value of Tests; D012189:Retrospective Studies; D002583:Uterine Cervical Neoplasms / Q000000981:diagnostic imaging* / Q000473:pathology* / Q000601:surgery