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Related Experiment Video

Updated: Feb 3, 2026

Surgical Techniques to Optimize Ovarian Reserve during Laparoscopic Cystectomy for Ovarian Endometrioma

Surgical Techniques to Optimize Ovarian Reserve during Laparoscopic Cystectomy for Ovarian Endometrioma

Published on: January 22, 2022

Preoperative Prediction of Prolonged Operative Time in Laparoscopic Ovarian Cystectomy Using Convolutional Neural

Jisoo Kim¹, Hyemi Bak¹, Myung Eun Jang²

¹Department of Artificial Intelligence, Jeju National University (Drs. Kim and Kim), Jeju-si, Jeju, Republic of Korea.

Journal of Minimally Invasive Gynecology

|February 1, 2026

Summary

This study identified clinical factors and Convolutional Neural Network (CNN)-derived ultrasound features that predict prolonged operative time in laparoscopic ovarian cystectomy. Integrating these factors improves prediction accuracy for surgical planning.

Keywords:

CNN-extracted image feature Laparoscopy Operative time Ovarian cystectomy

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Area of Science:

Gynecologic Surgery
Medical Imaging Analysis
Machine Learning in Healthcare

Background:

Prolonged operative time in laparoscopic ovarian cystectomy can impact patient outcomes and resource allocation.
Predictive factors for extended surgical duration are crucial for preoperative planning.

Purpose of the Study:

To identify clinical and imaging predictors of prolonged operative time during laparoscopic ovarian cystectomy.
To evaluate the incremental value of Convolutional Neural Network (CNN)-derived ultrasound features in predicting operative duration.

Main Methods:

Retrospective cohort study of 247 patients undergoing laparoscopic ovarian cystectomy.
Development of logistic regression models using clinical variables and CNN-derived ultrasound features.
Comparison of predictive accuracy between models with and without imaging features.

Main Results:

Robotic surgery, bilateral ovarian cysts, and elevated CA-125 levels were associated with prolonged operative time.
CNN-derived ultrasound features also independently predicted longer operative durations.
The combined model showed a non-significant increase in predictive accuracy (AUC 0.889 to 0.920).

Conclusions:

A combined model incorporating clinical and CNN-derived imaging features can predict prolonged operative time in laparoscopic ovarian cystectomy.
This approach shows potential for preoperative risk stratification and surgical scheduling.
Further external validation is needed to confirm its utility in surgical planning and resource management.