The efficacy of ultrasonographic morphological index using Depriest score in ovarian cancer prediction

Authors

  • Hossam Hassan Aly Hassan El Sokkary Department of Obstetrics and Gynecology, El Shatby Maternity Hospital, Alexandria University, Alexandria, Egypt

DOI:

https://doi.org/10.18203/2320-1770.ijrcog20164315

Keywords:

Depriest et al score, Ovarian ultrasongraphic morphological index, Ovarian cancer prediction

Abstract

Background: Ovarian cancer is the second most common cancer after cancer breast and the most lethal gynecologic malignancy in developed countries.The objective of this study was to evaluate the efficacy of ultrasonographic morphological index using Depriest score et al in identifying ovarian cancer and to calculate its specificity, sensitivity, positive predictive value and negative predictive value in ovarian cancer prediction.

Methods: Preoperative estimation of morphological index by Depriest score using vaginal ultrasound examination for 130 cases with ovarian masses, followed by laparotomy, and histopathological examination of the masses. Correlation of the cases morphological index score was done for histopathological nature of masses whether it is benign or malignant. Calculation of the Depriest index score was done using 3 parameters which are tumor volume, cyst wall structure and thickness and Septal structure.

Results: A significant difference were found between mean Depriest score (p=0.001) of malignant cases (mean score 8.27±1.77) and benign cases (mean score 4.38±1.61) while the mean volume showed no significant difference (p=0.101) between malignant (mean volume 3.24±0.69) and benign cases (mean volume 3.00±0.91). In relation to CA125 there was a significant difference (p=0.001) between malignant (mean CA125 86.34±73.87) and benign cases (mean CA125 31.48±12.83).

Conclusions: Depriest et al morphological index is an effective and cost efficient method for malignant ovarian masses prediction and differentiation from benign masses.

Downloads

Published

2016-12-07

Issue

Section

Original Research Articles