Diagnostic Accuracy of Intraoperative Tools for Detecting Endometriosis: A Systematic Review and Meta-analysis
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This systematic review and meta-analysis evaluated the diagnostic accuracy of various intraoperative tools used for detecting endometriosis during surgery.
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Abstract
ObjectiveTo evaluate the diagnostic accuracy of intraoperative laparoscopic imaging tools in reference to that of histopathology for detecting endometriotic lesions and to compare them with conventional white-light inspection by performing a systematic review with meta-analysis.Data sourcesWe searched the MEDLINE, EMBASE, and CENTRAL databases in addition to citations and reference lists until the end of February 2019.Methods of study selectionTwo authors screened 1038 citations for eligibility. We included randomized controlled trials or prospective cohort studies published in English, assessing the accuracy of intraoperative imaging tools for diagnosing endometriosis during laparoscopy. We considered studies using histopathologic evaluation as a standard criterion.Tabulation, integration, and resultsSeven studies were eligible, including 472 women and 1717 histopathologic specimens, and they involved study of the use of narrow-band imaging (2 studies), 5-aminolevulinic acid-induced fluorescence (2 studies), autofluorescence imaging (1 study), indocyanine green (1 study), and a 3-dimensional robotic laparoscopy (1 study). Two authors extracted data and assessed the validity of the included studies. Bivariate random-effects models and McNemar's test were used to compare the tests and evaluate sources of heterogeneity. Four studies were attributed a high risk of bias, and biopsies of normal-looking peritoneum were not performed to verify the results in 3 studies; both factors were identified as significant sources of heterogeneity, leading to the overestimation of the sensitivity and underestimation of the specificity of imaging tools. In all studies, additional endometriotic lesions were diagnosed with the enhanced imaging tool compared with white-light inspection alone. In the 4 studies that appropriately performed control biopsies (171 women, 448 specimens), enhanced imaging techniques were associated with a higher sensitivity and specificity compared with white-light inspection (0.84 and 0.89 compared with 0.75 and 0.76, respectively, p ≤.001). Adverse events were uncommon (n = 5) and reported only with the use of exogeneous photosensitizers. There were no reports of long-term changes in patient-reported outcomes arising from better detection of endometriosis lesions.ConclusionStudies report that enhanced imaging allows for the detection of additional endometriotic lesions missed by conventional white-light laparoscopy. The benefits of finding these additional lesions using enhanced imaging compared with white-light inspection alone on long-term postoperative outcomes have not been determined, and these tools should be considered only in a research context at this time.
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Cited by (21)
- Near-Infrared Indocyanine Green (NIR-ICG) Fluorescence Imaging for Intraoperative Detection of Endometriosis: A Systematic Review and Meta-Analysis 2026
- Guideline No. 468: Clinical Management of Endometriosis 2026
- A systematic approach to standardizing the visual appearance of endometriotic lesions for artificial intelligence recognition 2026
- Quality of Life and Psychological Comorbidities in Endometriosis and Adenomyosis: A Prospective Observational Study Using Advanced Ultrasound 2026
- Lignes directrices de pratique clinique n° 468 : Prise en charge clinique de l'endométriose 2026
- SWOT Analysis of Vision Transformers (ViTs) for Automated Diagnosis of Endometriosis from Laparoscopic Videos: Feasibility and Ethical Challenges 2025
- Interobserver Reproducibility of Two Endometriosis Scoring Systems: A Multicentre Observational Prospective Study 2025
- Initial Results in the Automatic Visual Recognition of Endometriosis Lesions by Artificial Intelligence During Laparoscopy: A Proof-of-Concept Study 2025
- Additional file 4 of PARP-1, EpCAM, and FRα as potential targets for intraoperative detection and delineation of endometriosis: a quantitative tissue expression analysis 2024
- Additional file 1 of PARP-1, EpCAM, and FRα as potential targets for intraoperative detection and delineation of endometriosis: a quantitative tissue expression analysis 2024
- Additional file 2 of PARP-1, EpCAM, and FRα as potential targets for intraoperative detection and delineation of endometriosis: a quantitative tissue expression analysis 2024
- Additional file 4 of PARP-1, EpCAM, and FRα as potential targets for intraoperative detection and delineation of endometriosis: a quantitative tissue expression analysis 2024
- Additional file 1 of PARP-1, EpCAM, and FRα as potential targets for intraoperative detection and delineation of endometriosis: a quantitative tissue expression analysis 2024
- Additional file 3 of PARP-1, EpCAM, and FRα as potential targets for intraoperative detection and delineation of endometriosis: a quantitative tissue expression analysis 2024
- Additional file 3 of PARP-1, EpCAM, and FRα as potential targets for intraoperative detection and delineation of endometriosis: a quantitative tissue expression analysis 2024
- Additional file 2 of PARP-1, EpCAM, and FRα as potential targets for intraoperative detection and delineation of endometriosis: a quantitative tissue expression analysis 2024
- PARP-1, EpCAM, and FRα as potential targets for intraoperative detection and delineation of endometriosis: a quantitative tissue expression analysis 2023
- Effect of Postoperative Hormonal Suppression on Fertility in Patients With Endometriosis After Conservative Surgery: A Systematic Review and Meta-analysis 2022
- Near-Infrared Imaging With Indocyanine Green for the Treatment of Endometriosis: Results From the Gre-Endo Trial 2021
- Novel diagnostic strategies for endometriosis 2021
- Indocyanine green in the surgical management of endometriosis: A systematic review 2020
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