Differentiation of Endometriomas from Ovarian Hemorrhagic Cysts at Magnetic Resonance: The Role of Texture Analysis
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Whole-lesion magnetic resonance texture analysis provides superior discrimination between endometriomas and hemorrhagic cysts compared to classic MRI signal evaluation.
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Abstract
Background and Objectives: To assess ovarian cysts with texture analysis (TA) in magnetic resonance (MRI) images for establishing a differentiation criterion for endometriomas and functional hemorrhagic cysts (HCs) that could potentially outperform their classic MRI diagnostic features. Materials and Methods: Forty-three patients with known ovarian cysts who underwent MRI were retrospectively included (endometriomas, n = 29; HCs, n = 14). TA was performed using dedicated software based on T2-weighted images, by incorporating the whole lesions in a three-dimensional region of interest. The most discriminative texture features were highlighted by three selection methods (Fisher, probability of classification error and average correlation coefficients, and mutual information). The absolute values of these parameters were compared through univariate, multivariate, and receiver operating characteristic analyses. The ability of the two classic diagnostic signs (“T2 shading” and “T2 dark spots”) to diagnose endometriomas was assessed by quantifying their sensitivity (Se) and specificity (Sp), following their conventional assessment on T1-and T2-weighted images by two radiologists. Results: The diagnostic power of the one texture parameter that was an independent predictor of endometriomas (entropy, 75% Se and 100% Sp) and of the predictive model composed of all parameters that showed statistically significant results at the univariate analysis (100% Se, 100% Sp) outperformed the ones shown by the classic MRI endometrioma features (“T2 shading”, 75.86% Se and 35.71% Sp; “T2 dark spots”, 55.17% Se and 64.29% Sp). Conclusion: Whole-lesion MRI TA has the potential to offer a superior discrimination criterion between endometriomas and HCs compared to the classic evaluation of the two lesions’ MRI signal behaviors.
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Cited by (10)
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- Ultrasound radiomics-based artificial intelligence model to assist in the differential diagnosis of ovarian endometrioma and ovarian dermoid cyst 2024
- Characteristics of the reproductive potential of women with ovarian endometrioma 2024
- Noninvasive diagnostic imaging for endometriosis part 2: a systematic review of recent developments in magnetic resonance imaging, nuclear medicine and computed tomography 2023
- Transvaginal Ultrasound vs. Magnetic Resonance Imaging (MRI) Value in Endometriosis Diagnosis 2022
- Quantitative Imaging Parameters in the Diagnosis of Endometriomas 2021
- Ultrasonography in the Differentiation of Endometriomas from Hemorrhagic Ovarian Cysts: The Role of Texture Analysis 2021
- Endometriosis - Recent Advances, New Perspectives and Treatments 2021
Source provenance
- europepmc
- last seen: 2026-06-04T01:30:01.192114+00:00
- openalex
- last seen: 2026-06-04T00:00:01.174412+00:00
- pubmed
- last seen: 2026-05-13T22:21:42.008780+00:00
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