Anogenital distance on MRI does not correlate to surgical diagnosis of endometriosis in patients without prior abdominal surgery

Anogenital distance (AGD) is regarded as a potential biomarker for endometriosis, and a measurement on MRI images has been found to be promising. This study aimed to evaluate the measurement of AGD on MRI to predict the surgical diagnosis of endometriosis. We included 127 patients who received an MRI for endometriosis between October 2018 and February 2023. AGD was measured on MRI by two readers (MRI-AGD-AC: clitoris to anus; MRI-AGD-AF: posterior fourchette to anus). The feasibility and interobserver reliability of AGD measurements were evaluated. Differences in AGD between patient groups were analyzed. The intraclass correlation coefficient estimates indicated a good to excellent reliability of MRI-AGD-AC (0.92; 95% CI: 0.83-0.95) and a poor to good reliability of MRI-AGD-AF (0.68; 95% CI: 0.27-0.83). No statistically significant differences in the mean MRI-AGD-AC and MRI-AGD-AF in patients with and without surgical diagnosis of DIE (p = 0.413; p = 0.110), peritoneal endometriosis with and without DIE (p = 0.641; p = 0.323), and ovarian endometriosis (p = 0.155; p = 0.150) were found. The AUC ranged from 0.475 (95% CI: 0.365-0.584) to 0.586 (95% CI: 0.454-0.718). Thus, AGD does not constitute a valuable biomarker for patients with clinically suspected endometriosis.

Authors

Institutions

Publication Details

Journal
Scientific Reports
Published
2024-12-16
DOI
https://doi.org/10.1038/s41598-024-82407-6
Primary Topic
Endometriosis Research and Treatment
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Anogenital distance on MRI does not correlate to surgical diagnosis of endometriosis in patients without prior abdominal surgery

Alexander Brose, Gabriele Anja Krombach, Felix Alexander Zeppernick, Sebastian Harth et al.
Scientific Reports
Endometriosis Research and Treatment
article

Anogenital distance on MRI does not correlate to surgical diagnosis of endometriosis in patients without prior abdominal surgery

Alexander Brose, Gabriele Anja Krombach, Felix Alexander Zeppernick, Sebastian Harth, Fritz Roller, Ivo M. Meinhold-Heerlein, Lena Metze, Daniel Leufkens
article en

Abstract

Anogenital distance (AGD) is regarded as a potential biomarker for endometriosis, and a measurement on MRI images has been found to be promising. This study aimed to evaluate the measurement of AGD on MRI to predict the surgical diagnosis of endometriosis. We included 127 patients who received an MRI for endometriosis between October 2018 and February 2023. AGD was measured on MRI by two readers (MRI-AGD-AC: clitoris to anus; MRI-AGD-AF: posterior fourchette to anus). The feasibility and interobserver reliability of AGD measurements were evaluated. Differences in AGD between patient groups were analyzed. The intraclass correlation coefficient estimates indicated a good to excellent reliability of MRI-AGD-AC (0.92; 95% CI: 0.83-0.95) and a poor to good reliability of MRI-AGD-AF (0.68; 95% CI: 0.27-0.83). No statistically significant differences in the mean MRI-AGD-AC and MRI-AGD-AF in patients with and without surgical diagnosis of DIE (p = 0.413; p = 0.110), peritoneal endometriosis with and without DIE (p = 0.641; p = 0.323), and ovarian endometriosis (p = 0.155; p = 0.150) were found. The AUC ranged from 0.475 (95% CI: 0.365-0.584) to 0.586 (95% CI: 0.454-0.718). Thus, AGD does not constitute a valuable biomarker for patients with clinically suspected endometriosis.

Scientific ReportsVol. 14(1)
Justus-Liebig-Universität Gießen (DE)
No poverty
Openalex Percentile: Top 66%
Endometriosis Research and Treatment
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.