Page 139 - EJMO-9-2

Eurasian Journal of Medicine

and Oncology

ORIGINAL RESEARCH ARTICLE
A scoring method for differentiating incidental

ovarian endometriotic cysts from ovarian
cystadenomas based on CT and clinical features

Xue-Liu 1,2 , Jian-Xia Xu 3 , Qiao-Ling Ding 4 , Jin-Er Shu 2 , Jian-Bin He 2 ,
1
2
Xiao-Chen Xu 2 , Ting-Ting Xu 2 , Xiao-Ming Wu * , and Ri-Sheng Yu *
1 Department of Radiology, Second Affiliated Hospital, School of Medicine, Zhejiang University,
Hangzhou, Zhejiang, China
2 Department of Radiology, Affiliated Jinhua Hospital of Wenzhou Medical University, Jinhua,
Zhejiang, China
3 Department of Radiology, The Second Affiliated Hospital of Zhejiang Chinese Medical University,
Hangzhou, Zhejiang, China
4 Department of Radiology, Hangzhou Xixi Hospital Affiliated to Zhejiang Chinese Medical University,
Hangzhou, Zhejiang, China

Abstract

Detecting and distinguishing between ovarian endometriotic cysts and ovarian
*Corresponding authors:
Ri-Sheng Yu cystadenomas using computed tomography (CT) scans is a clinical challenge due to
(risheng-yu@zju.edu.cn) their similar CT characteristics. This study aims to identify key CT and clinical features
Xiao-Ming Wu that can effectively differentiate these two diseases and to develop a simple and
(wxm56@163.com)
practical scoring system. We conducted a retrospective analysis of 202 patients who
Citation: Xue-Liu, Xu J, Ding Q, underwent pre-operative contrast-enhanced CT at two medical centers. The subjects
et al. A scoring method for
differentiating incidental ovarian were divided into training cohort (n=151) and validation cohort (n=51). Utilizing
endometriotic cysts from ovarian univariate analyses and binary logistic regression, predictive factors for ovarian
cystadenomas based on CT and endometriotic cysts and ovarian cystadenomas were identified to construct an initial
clinical features. Eurasian J Med
Oncol. 2025;9(2):131-141. model. Subsequently, a scoring system was developed by assigning weights to each
doi: 10.36922/ejmo.8507 feature based on the initial model. The accuracy of both models (the initial model
Received: January 12, 2025 and the scoring system) was quantified by calculating the area under the receiver
operating characteristic curve (AUC). We further determined the optimal cutoff point
1st revised: February 08, 2025 for the scoring system (0 – 15 points) and established three predictive ranges based
2nd revised: February 21, 2025 on the probabilities of ovarian endometriotic cyst occurrence (<7 points; 7 – 8 points;
Accepted: March 10, 2025 >8 points). The initial model, which incorporated two clinical factors (age and CA125
level) and three CT characteristics (wall thickness, density heterogeneity, and edge
Published online: March 24, 2025 adhesion), demonstrated an AUC of 0.993. In the training cohort, the proportions
Copyright: © 2025 Author(s). of patients correctly diagnosed with ovarian endometriotic cysts within these three
This is an Open-Access article score ranges were 0%, 38.89%, and 96.83%, respectively, while in the validation
distributed under the terms of the
Creative Commons Attribution cohort, they were 0%, 33.33%, and 95.00%. Thus, having a refined scoring range can
License, permitting distribution, help improve diagnostic accuracy, with a higher score indicating a diagnosis with
and reproduction in any medium, ovarian endometriosis cysts, and assist with differentiating patients with different
provided the original work is
properly cited. risk levels.
Publisher’s Note: AccScience
Publishing remains neutral with Keywords: Contrast-enhanced CT; Differential diagnosis; Endometrioma; Ovarian
regard to jurisdictional claims in
published maps and institutional cystadenoma; Scoring system
affiliations.

Volume 9 Issue 2 (2025) 131 doi: 10.36922/ejmo.8507