Borderline ovarian tumours: management in the era of fertility-sparing surgery

Oncologic and reproductive outcomes after fertility-sparing surgery for bilateral borderline ovarian tumors: A retrospective study

OBJECTIVES

To investigate the oncological safety and fertility outcomes of different fertility-sparing surgery procedures for bilateral borderline ovarian tumors (BOTs) and to identify the safest and most effective approach to help patients conceive with minimal risk.

STUDY DESIGN

A retrospective study of 144 patients (≤40 years) with pathologically confirmed bilateral BOTs were included in the study.The effects of surgery type on fertility outcome and recurrence were compared. Cox regression analysis was employed to determine potential prognostic factors. Survival analysis utilized the Kaplan-Meier method.

RESULTS

Three therapeutic modalities were applied in our study, including bilateral ovarian cystectomy (BOC; n = 29), unilateral adnexectomy + contralateral cystectomy (UAC; n = 4) and radical surgery (n = 61). Totally 33 cases (22.9 %) relapsed during the follow-up period. In 37 % of cases administered conservative surgery, relapses were diagnosed in the first 2 years. Only conservative surgery and adjuvant chemotherapy were risk factors for recurrence. Meanwhile, a pregnancy rate of 55.4 % was obtained in patients with bilateral BOTs. The pregnancy rate was slightly higher but no significant (P = 0.539) difference in patients treated with BOC (n = 17, 63 %) compared with UAC (n = 29, 55.8 %) group. GnRHa treatment significantly improved the clinical pregnancy rate in this study(P = 0.029).

CONCLUSIONS

Satisfactory pregnancy rate can be achieved after conservative surgery in patients with bilateral BOTs. BOC is worth recommending for bilateral borderline ovarian tumors and a critical factor in fertility is the preservation of maximum healthy ovarian tissue. Patients should make a pregnancy plan in 2 years after the first surgery. GnRHa increase the rate of successful clinical pregnancies.

Ultrasound-based deep learning radiomics model for differentiating benign, borderline, and malignant ovarian tumours: a multi-class classification exploratory study

BACKGROUND

Accurate preoperative identification of ovarian tumour subtypes is imperative for patients as it enables physicians to custom-tailor precise and individualized management strategies. So, we have developed an ultrasound (US)-based multiclass prediction algorithm for differentiating between benign, borderline, and malignant ovarian tumours.

METHODS

We randomised data from 849 patients with ovarian tumours into training and testing sets in a ratio of 8:2. The regions of interest on the US images were segmented and handcrafted radiomics features were extracted and screened. We applied the one-versus-rest method in multiclass classification. We inputted the best features into machine learning (ML) models and constructed a radiomic signature (Rad_Sig). US images of the maximum trimmed ovarian tumour sections were inputted into a pre-trained convolutional neural network (CNN) model. After internal enhancement and complex algorithms, each sample's predicted probability, known as the deep transfer learning signature (DTL_Sig), was generated. Clinical baseline data were analysed. Statistically significant clinical parameters and US semantic features in the training set were used to construct clinical signatures (Clinic_Sig). The prediction results of Rad_Sig, DTL_Sig, and Clinic_Sig for each sample were fused as new feature sets, to build the combined model, namely, the deep learning radiomic signature (DLR_Sig). We used the receiver operating characteristic (ROC) curve and the area under the ROC curve (AUC) to estimate the performance of the multiclass classification model.

RESULTS

The training set included 440 benign, 44 borderline, and 196 malignant ovarian tumours. The testing set included 109 benign, 11 borderline, and 49 malignant ovarian tumours. DLR_Sig three-class prediction model had the best overall and class-specific classification performance, with micro- and macro-average AUC of 0.90 and 0.84, respectively, on the testing set. Categories of identification AUC were 0.84, 0.85, and 0.83 for benign, borderline, and malignant ovarian tumours, respectively. In the confusion matrix, the classifier models of Clinic_Sig and Rad_Sig could not recognise borderline ovarian tumours. However, the proportions of borderline and malignant ovarian tumours identified by DLR_Sig were the highest at 54.55% and 63.27%, respectively.

CONCLUSIONS

The three-class prediction model of US-based DLR_Sig can discriminate between benign, borderline, and malignant ovarian tumours. Therefore, it may guide clinicians in determining the differential management of patients with ovarian tumours.

Fertility preservation in women with benign gynaecological conditions

Although a wealth of data has been published regarding fertility preservation (FP) in women with malignant diseases who receive gonadotoxic treatment, the role of FP in non-malignant conditions has been studied to a much lesser extent. These include benign haematological, autoimmune, and genetic disorders, as well as a multitude of benign gynaecological conditions (BGCs) that may compromise ovarian reserve and/or reproductive potential due to pathogenic mechanisms or as a result of medical or surgical treatments. Alongside accumulating data that document the reproductive potential of cryopreserved oocytes and ovarian tissue, there is potential interest in FP for women with BGCs at risk of infertility; however, there are currently insufficient data about FP in women with BGCs to develop guidelines for clinical practice. The purpose of this article is to appraise the available evidence regarding FP for BGC and discuss potential strategies for FP based on estimated ovarian impairment and on short-term and long-term reproductive goals of patients. Cost-effectiveness considerations and patients' perspectives will also be discussed.

Identifying Borderline Ovarian Tumor Recurrence Using Routine Ultrasound Follow-Up

Borderline ovarian tumors (BOTs) are non-invasive tumors frequently diagnosed in young patients. Surgical removal of the uterus, fallopian tubes, ovaries, and omentum is considered definitive management, however fertility-sparing approach is a recognized option. Surveillance is important due to known recurrence, but there is controversy over the effectiveness of follow-up modalities. The objective is to determine the efficacy of ultrasound screening in identifying tumor recurrence. This retrospective chart review evaluated all patients consulted and/or treated surgically at our institution from January 2015 to June 2020 diagnosed with BOT. Patients were excluded if concurrently diagnosed with another gynecologic malignancy, did not have yearly ultrasound follow-up, or were lost to follow-up. This study included 56 patients, 17 of whom underwent fertility preserving surgery. The overall rate of recurrence was 10.7%; with recurrence rates of 23.5% for the fertility preserving surgery population and 5.1% for the definitive surgery population. Ultrasound first identified 5 of the 6 (83.3%) recurrences. Overall time to recurrence was 51.5 months. In conclusion, recurrences were identified on routine ultrasound screening prior to symptom onset or detection via physical exam in 83.3% of cases. While the best modality of follow-up remains controversial, this review provides evidence supporting the use of routine ultrasound follow-up for early detection of BOT recurrence.

Role of RAS signaling in ovarian cancer

The RAS family of proteins is among the most frequently mutated genes in human malignancies. In ovarian cancer (OC), the most lethal gynecological malignancy, RAS, especially KRAS mutational status at codons 12, 13, and 61, ranges from 6-65% spanning different histo-types. Normally RAS regulates several signaling pathways involved in a myriad of cellular signaling cascades mediating numerous cellular processes like cell proliferation, differentiation, invasion, and death. Aberrant activation of RAS leads to uncontrolled induction of several downstream signaling pathways such as RAF-1/MAPK (mitogen-activated protein kinase), PI3K phosphoinositide-3 kinase (PI3K)/AKT, RalGEFs, Rac/Rho, BRAF (v-Raf murine sarcoma viral oncogene homolog B), MEK1 (mitogen-activated protein kinase kinase 1), ERK (extracellular signal-regulated kinase), PKB (protein kinase B) and PKC (protein kinase C) involved in cell proliferation as well as maintenance pathways thereby driving tumorigenesis and cancer cell propagation. KRAS mutation is also known to be a biomarker for poor outcome and chemoresistance in OC. As a malignancy with several histotypes showing varying histopathological characteristics, we focus on reviewing recent literature showcasing the involvement of oncogenic RAS in mediating carcinogenesis and chemoresistance in OC and its subtypes.

Evaluation of Clinicopathologic Factors and Surgery Management on Borderline Ovarian Tumor Outcomes

Background: Borderline ovarian tumor (BOT) is a tumor most prevalent in young woman with desire to fertility. There are some controversies on the patient characteristic besides to the factors affecting the recurrence rate among different races. Objectives: The aim of this study is to evaluate clinicopathologic features of the tumor to discover the controversies on the topic. Methods: Medical data of the all referred patients to Motahari clinic from January 2010 till October 2020 were recorded. Patient clinicopathologic characteristics affecting on outcome were evaluated. By using SPSS software, data were tested by chi-square and fish exact test. Also, log rank test was used for survival analysis Results: Totally 145 patients were enrolled. 61.4% versus 38.6% of the patients underwent fertility sparing surgery and radical surgery respectively with common characteristics of mostly belong to stage 1A disease (61.8% vs. 66.1%), unilateral (93.3% vs. 89.3%), serous histology (51.7% vs. 66.1%). The characteristics were different in the aspects of age and tumor size. In the aspect of recurrence rate, higher FIGO stage, younger age, tumor size less than 10cm, performing laparoscopy and fertility sparing surgery were with higher rate of recurrence (P-value < 0.05) while histology type of the tumor, lateralization, micropapillary, microinvasion, noninvasive peritoneal implants, receiving adjuvant chemotherapy and performing lymphadenectomy were not statistically significant for recurrence (P-value > 0.05). Two patients had malignant transformation. Conclusions: Fertility sparing surgery was with more recurrence rate in borderline ovarian tumor patients. However, micropapillary, microinvasion were not significantly with higher recurrence rate in our study but they are challenging issues in border line ovarian tumors among different studies. Due to most prevalence of border line ovarian tumors in young women and desire of fertility preservation, we should notice more to clinicopathologic and surgery types affecting on recurrence of BOTs.

T2-weighted MRI-based radiomics for discriminating between benign and borderline epithelial ovarian tumors: a multicenter study

Background

Preoperative differentiation between benign and borderline epithelial ovarian tumors (EOTs) is challenging and can significantly impact clinical decision making. The purpose was to investigate whether radiomics based on T2-weighted MRI can discriminate between benign and borderline EOTs preoperatively.

Methods

A total of 417 patients (309, 78, and 30 samples in the training and internal and external validation sets) with pathologically proven benign and borderline EOTs were included in this multicenter study. In total, 1130 radiomics features were extracted from manually delineated tumor volumes of interest on images. The following three different models were constructed and evaluated: radiomics features only (radiomics model); clinical and radiological characteristics only (clinic-radiological model); and a combination of them all (combined model). The diagnostic performances of models were assessed using receiver operating characteristic (ROC) analysis, and area under the ROC curves (AUCs) were compared using the DeLong test.

Results

The best machine learning algorithm to distinguish borderline from benign EOTs was the logistic regression. The combined model achieved the best performance in discriminating between benign and borderline EOTs, with an AUC of 0.86 ± 0.07. The radiomics model showed a moderate AUC of 0.82 ± 0.07, outperforming the clinic-radiological model (AUC of 0.79 ± 0.06). In the external validation set, the combined model performed significantly better than the clinic-radiological model (AUCs of 0.86 vs. 0.63, p = 0.021 [DeLong test]).

Conclusions

Radiomics, based on T2-weighted MRI, can provide critical diagnostic information for discriminating between benign and borderline EOTs, thus having the potential to aid personalized treatment options.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13244-022-01264-x.

Fertility Sparing Surgery and Borderline Ovarian Tumours

Simple Summary

Fertility-sparing surgery (FSS) is now a widely acceptable treatment for the management of Borderline Ovarian Tumours (BOTs) in women of reproductive age. However, many clinicians face the dilemma of balancing the risks of disease recurrence with progression to lethal malignancy whilst preserving fertility, in the absence of clear standardized guidelines. The aim of this study was to evaluate the oncological outcomes in women who underwent FSS for the management of primary, or recurrent presentation of BOTs, to provide clinicians with further evidence of the safety and feasibility of FSS. Oncological outcomes following a novel method of FSS in the form of laparoscopic ultrasound guided ovarian wedge resection has also been introduced, which has the potential to change the way BOTs are managed in the future in women of reproductive age.

Abstract

To determine the oncological outcomes following fertility-sparing surgery (FSS) for the management of Borderline Ovarian Tumours (BOTs). A retrospective analysis of participants diagnosed with BOTs between January 2004 and December 2020 at the West London Gynaecological Oncology Centre was conducted. A total of 172 women were diagnosed; 52.3% (90/172) underwent FSS and 47.7% (82/172) non-FSS. The overall recurrence rate of disease was 16.9% (29/172), of which 79.3% (23/29) presented as the recurrence of serous or sero-mucinous BOTs and 20.7% (6/29) as low-grade serous carcinoma (LGSC). In the FSS group, the recurrence rate of BOTs was 25.6% (23/90) presenting a median 44.0 (interquartile range (IQR) 41.5) months, of which there were no episodes of recurrence presenting as LGSC reported. In the non-FSS group, all recurrences of disease presented as LGSC, with a rate of 7.7% (6/78), following a median of 47.5 months (IQR 47.8). A significant difference between the type of surgery performed (FSS v Non-FSS) and the association with recurrence of BOT was observed (Pearson Chi-Square: p = 0.000; x = 20.613). Twelve women underwent ultrasound-guided ovarian wedge resection (UGOWR) as a novel method of FSS. Recurrence of BOT was not significantly associated with the type of FSS performed (Pearson Chi- Square: x = 3.166, p = 0.379). Non-FSS is associated with negative oncological outcomes compared to FSS, as evidenced by the higher rate of recurrence of LGSC. This may be attributed to the indefinite long-term follow up with ultrasound surveillance all FSS women undergo, enabling earlier detection and treatment of recurrences.