Advances in fertility preserving surgery for borderline ovarian tumors

Correlation analysis of recurrent factors in borderline ovarian tumors undergoing fertility preservation surgery

Objective

To explore the relapse - related factors of fertility preservation surgery for borderline ovarian tumors.

Methods

Patients of childbearing age who underwent fertility preservation surgery for borderline ovarian tumors in Sheng jing Hospital of China Medical University from April 20 1 8 to April 20 2 3 were selected. Clinical data were collected and their clinical characteristics were statistically analyzed. It is to explore the risk factors of postoperative recurrence.

Results

A total of 30 8 patients were included in this study, of which 1 was lost to follow - up and 47 relapsed (4 7/3 0 7, 15. 3 1%). The results of multivariate analysis showed that the pathological features of micro papillary structure, intra operative as cites, bilateral tumors, and the increased ratio of neu tro phil to lymphocyte before surgery are independent risk factors for the recurrence of borderline ovarian tumors.

Conclusion

The prognosis of women of childbearing age with borderline ovarian tumors undergoing conservation function surgery is good. However, patients with high - risk recurrence factors should be paid special attention and closely followed up after surgery.

A comprehensive review of the new FIGO classification of ovulatory disorders

BACKGROUND

The World Health Organization (WHO) system for the classification of disorders of ovulation was produced 50 years ago and, by international consensus, has been updated by the International Federation of Gynecology and Obstetrics (FIGO).

OBJECTIVE AND RATIONALE

This review outlines in detail each component of the FIGO HyPO-P (hypothalamic, pituitary, ovarian, PCOS) classification with a concise description of each cause, and thereby provides a systematic method for diagnosis and management.

SEARCH METHODS

We searched the published articles in the PubMed database in the English-language literature until October 2022, containing the keywords ovulatory disorders; ovulatory dysfunction; anovulation, and each subheading in the FIGO HyPO-P classification. We did not include abstracts or conference proceedings because the data are usually difficult to assess.

OUTCOMES

We present the most comprehensive review of all disorders of ovulation, published systematically according to the logical FIGO classification.

WIDER IMPLICATIONS

Improving the diagnosis of an individual's ovulatory dysfunction will significantly impact clinical practice by enabling healthcare practitioners to make a precise diagnosis and plan appropriate management.

Validation of the diagnostic efficacy of O-RADS in adnexal masses

The aim of this study was to validate the performance of the Ovarian-Adnexal Reporting and Data Systems (O-RADS) series models proposed by the American College of Radiology (ACR) in the preoperative diagnosis of adnexal masses (AMs). Two experienced sonologists examined 218 patients with AMs and gave the assessment results after the examination. Pathological findings were used as a reference standard. Of the 218 lesions, 166 were benign and 52 were malignant. Based on the receiver operating characteristic (ROC) curve, we defined a malignant lesion as O-RADS > 3 (i.e., lesions in O-RADS categories 4 and 5 were malignant). The area under the curve (AUC) of O-RADS (v2022) was 0.970 (95% CI 0.938-0.988), which wasn't statistically significantly different from the O-RADS (v1) combined Simple Rules Risk (SRR) assessment model with the largest AUC of 0.976 (95% CI 0.946-0.992) (p = 0.1534), but was significantly higher than the O-RADS (v1) (AUC = 0.959, p = 0.0133) and subjective assessment (AUC = 0.918, p = 0.0255). The O-RADS series models have good diagnostic performance for AMs. Where, O-RADS (v2022) has higher accuracy and specificity than O-RADS (v1). The accuracy and specificity of O-RADS (v1), however, can be further improved when combined with SRR assessment.

Clinical Analysis of 137 Cases of Ovarian Tumors in Pregnancy

Ovarian tumors do not really typically occur in association with pregnant; however, once they do, the treatment is critical. It is important to note that around 6% of ovarian tumors in pregnancies are cancerous. The problems induced by ovarian tumors in pregnancy particularly necessitate rapid medical intervention and are much more frequent than cancer. Medication choices and survival of ovary tumor patients could be influenced by varied diagnoses of ovarian masses. So, we present an upgraded logistic regression (ULR) approach in this paper. Initially, the collection of 137 patient datasets was employed in screening test to identify the ovarian tumor as benign-tumor and malignant-tumor by using contrast-enhanced ultrasonography (CEU) method. Then, the screening test images are preprocessed using wavelet transform (WT) approach. The preprocessed data are extracted by using local binary pattern (LBP) and laws' texture energy (LTE) techniques. Finally, the clinical analysis of the ovarian tumor can be obtained by the proposed ULR approach. The performances were examined and compared with existing approaches to achieve the proposed approach with greatest correctness. The findings are depicted by utilizing the MATLAB tool.