Accuracy of imaging findings compared with that of histopathological findings of the ovarian lesions

Authors

  • Ponnam Bharath Kumar Department of Radio diagnosis, Malla Reddy Medical College for Women, Quthbullapur Municipality, Hyderabad, Telangana, India
  • Prem Sai Reddy Consultant Radiologist, Manipal Hospital, Bangalore, Karnataka, India

DOI:

https://doi.org/10.18203/2349-3933.ijam20191152

Keywords:

Accuracy, Endometriosis, MRI, Sonography, Teratoma

Abstract

Background: Newer imaging techniques have emerged, and it is necessary to study their accuracy in comparison to the gold standard of histopathology for increasing accuracy of diagnosis. Ovarian tumors are difficult to diagnose when they are of small size. But their diagnosis should be done at an earlier stage for effective outcome of the management of these tumors. The objective was to study accuracy of imaging findings compared with that of histopathological findings of the ovarian lesions.

Methods: This study was done for a period of two years from December 2010 to May 2012. A total of 30 patients who were clinically suspected to have ovarian pathology were referred to us for ultrasonography. In 30 patients, who were referred for sonography a total of 36 ovarian masses was found? Each patient was examined by Trans abdominal sonography / Trans vaginal sonography, MRI (Pre and Post contrast) and CT when required.

Results: Sonography could detect the origin of mass accurately in 29 (80.5 %) masses and MRI could detect the origin accurately in 34 (94.4%) masses. Sonography characterized 33/36 (91.6%) masses correctly. MRI correctly characterized 34/36 (94.5%) cases and tissue content was identified correctly. The sensitivity of imaging findings for correctly identifying malignant lesions was 100% and sensitivity for correctly making a benign diagnosis was 92.5%. The specificity of imaging findings for correctly identifying malignant lesion was 92% and specificity for correctly making a benign diagnosis was 84.6 %.

Conclusions: MRI is significantly superior to US in all respects due to the excellent soft tissue contrast and organ-specific information generated in the pelvis.

References

Rashid S, Sarwas G, Ali A. A Clinico-pathological study of ovarian cancer. Mother Child. 1998;36:117-25.

DePriest PD, Gallien HH, Pavlik EJ, Krysolo RJ, Van Nagell Jr. Trans vaginal sonography as a screening method for the detection of early ovarian cancer. Gynecol Oncol. 1997;65(3):408-14.

Fleischer AC, McKee MS, Gordon AN, Page DL, Kepple DM, Worrell JA, et al. Trans vaginal sonography of postmenopausal ovaries with pathologic correlation. J Ultrasound Med. 1990;9:637-44.

Iyer VR, Lee SI. MRI, CT, and PET/CT for Ovarian Cancer Detection and Adnexal Lesion Characterization. AJR. 2010;194:311-21.

Morikawa K, Hatabu H, Togashi K, Kataoka ML, Mori T, Konishi J. Granulosa cell tumor of the ovary: MR findings. J Comput Assist Tomogr. 1997;21:1001-4.

Shai S. Diagnostic ultrasound, Carol M. Rumack, 2nd ed, Published by Mosby; 1998:565.

Sittig KM. Sabiston's textbook of surgery, 16th Ed. Published by Harcourt Publishers; 2001:808.

Sarti DA. Textbook of Diagnostic Ultrasound, Dennis A Sarti, 2nd ed., published by Year Book Medical Publishers; 1987:800,814.

Jeremy PR. Jenkins, textbook of Radiology and Imaging, David Sutton, 7th ed, published by Churchill Livingstone; 2003:1007.

Valentin L. Imaging in Gynecology. Best Pract Res Clin Obstet Gynaecol. 2006 Dec;20(6):881-906.

Hricak H, Chen M, Coakley FV, Kinkel K, Yu KK, Sica G, et al. Yu, Gregory Sica, Peter Bacchetti, and C. Bethan Powell. Complex adnexal masses: Detection and characterization with MR Imaging- Multivariate Analysis Radiology. 2000;214:39-46.

Komatsu T, Konishi I, Mandai M, Togashi K, Kawakami S, Konishi J, et al. Adnexal masses: transvaginal US and gadolinium-enhanced MR imaging assessment of intratumoral structure. Radiol. 1996 Jan; 198(1):109-15.

Scoutt L, McCarthy S, Lange R, Bourque A, Schwartz P. MR evaluation of clinically suspected adnexal masses. J Comput Assist Tomogr. 1994;18:609-18.

Downloads

Published

2019-03-25

Issue

Section

Original Research Articles