Ultrasonographic features and ovarian reserve in ovarian endometrioma: Implications for risk stratification

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This study investigated the relationship between ultrasonographic features of ovarian endometriomas and ovarian reserve, aiming to improve risk stratification for patients.

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Abstract

OBJECTIVE: To investigate the association between ultrasonographic features of ovarian endometrioma (OMA) and diminished ovarian reserve, and to evaluate the predictive value of these ultrasound markers. METHODS: This prospective observational study enrolled 268 OMA patients (January 2023-January 2025), who underwent transvaginal ultrasound at enrollment. Maximum cyst diameter, laterality, cyst structure, echo pattern, and antral follicle count (AFC) were recorded. Patients were divided into diminished ovarian reserve [anti-Müllerian hormone (AMH) < 1.1 ng/mL] and normal ovarian reserve (NOR) (AMH ≥ 1.1 ng/mL) groups. Intergroup comparisons, Spearman correlation, multivariate logistic regression, and ROC analysis were performed. RESULTS: Of 268 patients, 180 were in NOR group and 88 in DOR group. The DOR group had larger cysts, more bilateral lesions, more multilocular/septated cysts, fewer typical homogeneous echoes, and lower total AFC (all P < 0.05). Cyst diameter was negatively correlated with AMH (r = -0.27, P < 0.001); total AFC was positively correlated with AMH (r = 0.65, P < 0.001). Age (OR = 1.209), cyst diameter (OR = 1.352), and bilateral lesions (OR = 2.941) were independent risk factors for diminished ovarian reserve, while total AFC was a protective factor (OR = 0.648) (all P < 0.05). Total AFC showed the best single predictor performance (AUC = 0.793), and the combined model achieved the highest predictive efficacy (AUC = 0.845). CONCLUSION: A combined ultrasound-marker model showed good discriminatory ability for identifying women with diminished ovarian reserve. The model may assist risk stratification and support earlier fertility counseling and consideration of ART in women with multiple adverse ultrasound features.

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MeSH descriptors

Endometriosis Endometriosis Endometriosis Endometriosis Endometriosis Endometriosis Endometriosis Endometriosis Endometriosis Endometriosis Endometriosis Endometriosis Endometriosis Endometriosis Endometriosis Endometriosis Endometriosis Endometriosis Endometriosis Endometriosis

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