Xiaoqiu Dong

This study aimed to develop and validate a multimodal deep learning model that leverages 2D grayscale ultrasound (US) images alongside readily available clinical data to improve diagnostic performance for ovarian cancer (OC). A retrospectiv…

PURPOSE: The objective of this study was to develop a deep learning model, using the ConvNeXt algorithm, that can effectively differentiate between ovarian endometriosis cysts (OEC) and benign mucinous cystadenomas (MC) by analyzing ultraso…

BACKGROUND: Based on the ovarian-adnexal reporting and data system (O-RADS), we constructed a nomogram model to predict the malignancy potential of adnexal masses with sophisticated ultrasound morphology. METHODS: In a multicenter retrospe…

We investigated contrast-enhanced ultrasonography (CEUS) characteristics related to the perfusion pattern and parameters of the time-intensity curve of ovarian endometrial cysts (OECs) pre- and post-sclerotherapy. Forty-three patients with …

To investigate the characteristics of ultrasound contrast before and after the treatment of ovarian endometriosis cyst. 43 OEC patients collected in our hospital pre hardening treatment, which were all unilateral and solitary, untreated. Be…

OBJECTIVES: The purpose of this study was to assess contrast-enhanced sonography features before and after interventional treatment of ovarian endometrial cysts. METHODS: We retrospectively analyzed 53 patients with ovarian endometrial cys…

OBJECTIVES: To detect the differentially expressed genes and subsequently identify disease-related signatures and potential biomarkers for patients with ovarian endometriomas in the serum before and after the ultrasound-guided ethanol scler…

Objective To investigate the ovarian function change after anhydrous ethanol sclerotherapy for ovarian endometriotic cysts guided by ultrasound. Methods One hundred cases of ovarian chocolate cyst were retrospectively analyzed after Anhydro…