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Intraoperative Detection of Subtle Endometriosis: A Novel Paradigm for Detection and Treatment of Pelvic Pain Associated with the Loss of Peritoneal Integrity

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Published on: December 21, 2012

Artificial intelligence applications in endometriosis imaging.

Sneha Mittal¹, Angela Tong², Scott Young³

¹University of Tennessee Health Science Center, Memphis, USA.

Abdominal Radiology (New York)

|April 1, 2025

Summary

This summary is machine-generated.

Artificial intelligence (AI) shows promise for improving endometriosis diagnosis through imaging. Current AI applications in ultrasound and MRI are emerging but require further research for standardization and broader use.

Keywords:

Adenomyosis Artificial intelligence Deep learning Endometriosis Imaging Machine learning

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Area of Science:

Medical Imaging
Artificial Intelligence
Gynecology

Background:

Endometriosis diagnosis presents challenges in medical imaging.
Artificial intelligence (AI) offers potential solutions for improving diagnostic accuracy.

Purpose of the Study:

To review the current landscape of AI applications in endometriosis imaging.
To guide future research directions in this field.

Main Methods:

A descriptive review of articles from PubMed.
Focus on AI applications in ultrasound (US) and magnetic resonance imaging (MRI) for endometriosis.

Main Results:

Most studies utilize transvaginal ultrasound (TVUS) data for detecting deep endometriosis, adenomyosis, endometriomas, and secondary signs.
Magnetic resonance imaging (MRI) studies are limited, focusing on diagnosis and segmentation.
Multi-modal approaches combining imaging and clinical data are emerging.
Current literature lacks generalizability, standardization, and utilizes small, retrospective, single-center datasets.
AI models are narrowly focused and lack standardized ground truth.

Conclusions:

AI applications in endometriosis imaging are in early development.
Further research is crucial for developing and enhancing AI models for standardized and generalizable endometriosis diagnosis.