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Preoperative Tumor Size at MRI Predicts Deep Myometrial Invasion, Lymph Node Metastases, and Patient Outcome in Endometrial Carcinomas
  1. Sigmund Ytre-Hauge, MD*,,
  2. Jenny A. Husby, MD*,,
  3. Inger J. Magnussen, MD*,
  4. Henrica M.J. Werner, MD, PhD,§,
  5. Øyvind O. Salvesen, MSc, PhD,
  6. Line Bjørge, MD, PhD,§,
  7. Jone Trovik, MD, PhD,§,
  8. Ingunn M. Stefansson, MD, PhD,#,
  9. Helga B. Salvesen, MD, PhD,§ and
  10. Ingfrid S. Haldorsen, MD, PhD*,
  1. *Department of Radiology, Haukeland University Hospital;
  2. Section for Radiology, Department of Clinical Medicine, University of Bergen;
  3. Department of Obstetrics and Gynecology, Haukeland University Hospital;
  4. §Center for Cancer Biomarkers, Department of Clinical Science, University of Bergen, Bergen;
  5. Unit for Applied Clinical Research, Department of Cancer Research and Molecular Medicine, Norwegian University of Science and Technology, Trondheim;
  6. Center for Cancer Biomarkers, the Gade Institute, Department of Clinical Medicine, University of Bergen; and
  7. #Department of Pathology, Haukeland University Hospital, Bergen, Norway.
  1. Address correspondence and reprint requests to Ingfrid S. Haldorsen, MD, PhD, Department of Radiology, Haukeland University Hospital, Jonas Liesvei 65, 5021 Bergen, Norway. E-mail:


Objective The aim of this study was to explore the relation between preoperative tumor size based on magnetic resonance imaging (MRI) and the surgical pathologic staging parameters (deep myometrial invasion, cervical stroma invasion, and metastatic lymph nodes) and to assess the prognostic impact of tumor size in endometrial carcinomas. Interobserver variability for the different tumor size measurements was also assessed.

Methods/Materials Preoperative pelvic MRI of 212 patients with histologically confirmed endometrial carcinomas was read independently by 3 radiologists. Maximum tumor diameters were measured in 3 orthogonal planes (anteroposterior, transverse, and craniocaudal planes [CC]), and tumor volumes were estimated. Tumor size was analyzed in relation to surgical staging results and patient survival. The multivariate analyses were adjusted for preoperative risk status based on endometrial biopsy. Intraclass correlation coefficients and receiver operating characteristics curves for the different tumor measurements were also calculated.

Results Anteroposterior tumor diameter independently predicted deep myometrial invasion (P < 0.001), whereas CC tumor diameter tended to independently predict lymph node metastases (P = 0.06). Based on receiver operating characteristic curves, the following tumor size cutoff values were identified: anteroposterior diameter greater than 2 cm predicted deep myometrial invasion (unadjusted odds ratio [OR], 12.4; P < 0.001; adjusted OR, 6.7; P < 0.001) and CC diameter greater than 4 cm predicted lymph node metastases (unadjusted OR, 6.2; P < 0.001; adjusted OR, 4.9; P = 0.009). Large tumor size was associated with reduced progression/recurrence-free survival (P ⩽ 0.005 for all size parameters), and CC diameter had an independent impact on survival (adjusted hazards ratio, 1.04; P = 0.009). The interobserver variability for the different size measurements was very low (intraclass correlation coefficient, 0.78–0.85).

Conclusions Anteroposterior tumor diameter greater than 2 cm predicts deep myometrial invasion, and CC tumor diameter greater than 4 cm predicts lymph node metastases. Tumor size is a strong prognostic factor in endometrial carcinomas. Preoperative tumor measurements based on MRI may potentially improve preoperative risk stratification models and thus enable better tailored surgical treatment in endometrial cancer.

  • Endometrial carcinoma
  • Tumor size
  • Magnetic resonance imaging
  • Prognosis

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  • Supported by the Western Norway Regional Health Authority; Research Funds at the Department of Radiology; Haukeland University Hospital; Norwegian Research Council; the University of Bergen; the Meltzer Foundation; the Norwegian Cancer Society (the Harald Andersen’s legacy); MedViz (; a medical imaging and visualization research and development cluster in Western Norway founded by Haukeland University Hospital, University of Bergen, and Christian Michelsen Research; and Bergen Research Foundation.

  • Supplemental digital content is available for this article. Direct URL citation appears in the printed text and is provided in the HTML and PDF versions of this article on the journal’s Web site (

  • The authors declare no conflicts of interest.

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