Intra-Operative Frozen Sections for Ovarian Tumors – A Tertiary Center Experience

Document Type : Research Articles


1 Department of Obstetrics and Gynaecology, Universiti Kebangsaan Malaysia Medical Centre, Jalan Yaacob Latif, Cheras, 56000 Kuala Lumpur, Malaysia.

2 Department of Pathology, Hospital Sultanah Bahiyah, Km 6, Jln Langgar, Bandar Alor Setar, 05460 Alor Setar, Kedah, Malaysia.

3 Department of Obstetrics and Gynaecology, Hospital Sultanah Bahiyah, Km 6, Jln Langgar, Bandar Alor Setar, 05460 Alor Setar, Kedah, Malaysia.


Background: Accuracy of diagnosis with intra-operative frozen sections is extremely important in the evaluation of ovarian tumors so that appropriate surgical procedures can be selected. Study design: All patients who with intra-operative frozen sections for ovarian masses in a tertiary center over nine years from June 2008 until April 2017 were reviewed. Frozen section diagnosis and final histopathological reports were compared. Main outcome measures: Sensitivity, specificity, positive and negative predictive values of intra-operative frozen section as compared to final histopathological results for ovarian tumors. Results: A total of 92 cases were recruited for final evaluation. The frozen section diagnoses were comparable with the final histopathological reports in 83.7% of cases. The sensitivity, specificity, positive predictive value and negative predictive value for benign and malignant ovarian tumors were 95.6%, 85.1%, 86.0% and 95.2% and 69.2%, 100%, 100% and 89.2% respectively. For borderline ovarian tumors, the sensitivity and specificity were 76.2% and 88.7%, respectively; the positive predictive value was 66.7% and the negative predictive value was 92.7%. Conclusion: The accuracy of intra-operative frozen section diagnoses for ovarian tumors is high and this approach remains a reliable option in assessing ovarian masses intra-operatively.


Main Subjects

Volume 19, Issue 1
January 2018
Pages 213-218
  • Receive Date: 07 October 2017
  • Revise Date: 31 October 2017
  • Accept Date: 13 December 2017
  • First Publish Date: 01 January 2018