Borderline Ovarian Tumors Research Articles

Fertility-sparing surgery in children and adolescents with borderline ovarian tumors: a retrospective study

ObjectiveTo describe the characteristics of children and adolescents with borderline ovarian tumors (BOTs) and evaluate the efficacy and safety of fertility-sparing surgery (FSS) in these patients.MethodsPatients with BOTs younger than 20 years who underwent FSS were included in this study.ResultsA total of 34 patients were included, with a median patient age of 17 (range, 3–19) years; 97.1% (33/34) of cases occurred after menarche. Of the patients, 82.4% had mucinous borderline tumors (MBOTs), 14.7% had serous borderline tumors (SBOTs), and 2.9% had seromucinous borderline tumor (SMBOT). The median tumor size was 20.4 (range, 8–40)cm. All patients were at International Federation of Gynecology and Obstetrics stage I and all underwent FSS: cystectomy (unilateral ovarian cystectomy, UC, 14/34, 41.2% and bilateral ovarian cystectomy, BC, 1/34, 2.9%), unilateral salpingo-oophorectomy (USO; 18/34; 52.9%), or USO + contralateral ovarian cystectomy (1/34; 2.9%). The median follow-up time was 65 (range, 10–148) months. Recurrence was experienced by 10 of the 34 patients (29.4%). One patient with SBOT experienced progression to low-grade serous carcinoma after the third relapse. Two patients had a total of four pregnancies, resulting in three live births. The recurrence rate of UC was significantly higher in MBOTs than in USO (p = 0.005). The 5-year disease-free survival rate was 67.1%, and the 5-year overall survival rate was 100%.ConclusionsFertility-sparing surgery is feasible and safe for children and adolescents with BOTs. For patients with MBOTs, USO is recommended to lower the risk of recurrence.

Serous surface papillary borderline ovarian tumors: correlation of sonographic features with clinic pathological findings.

Serous surface papillary borderline ovarian tumor (SSPBOT) is a distinct subtype of serous borderline ovarian tumor characterized by solid tissue deposition confined to the ovarian surface. Because SSPBOT is rare, there are few published reports on the ultrasonographic features of this condition. In this retrospective study, we investigated 12 cases of SSPBOT. Ultrasound imaging of SSPBOT showed grossly normal ovaries that were encased partially or wholly by tumor deposits that were confined to the surface, with clear demarcation between normal ovarian tissue and surrounding tumors. Color Doppler imaging demonstrated the 'fireworks sign' in all cases of SSPBOT, corresponding to an intratumoral vascular bundle originating from the ovarian vessels and supplying hierarchical branching blood flow to the surrounding tumor. No patient with ovarian high-grade serous carcinoma showed these morphological and Doppler features. In our series, the fireworks sign appeared to be a characteristic feature of SSPBOT that could facilitate correct identification of this tumor. © 2023 International Society of Ultrasound in Obstetrics and Gynecology.

Evaluation of serum CA125, HE4 and CA724 and the risk of ovarian malignancy algorithm score in the diagnosis of high-grade serous ovarian cancer

AimTo develop a new algorithm for the detection of high-grade serous ovarian cancer (HGSOC). MethodsPatients diagnosed with HGSOC, borderline ovarian tumours (BOTs) or benign ovarian masses (BOMs) were enrolled between February 2019 and December 2020. Patients with BOTs or BOMs were grouped as non-HGSOC. The cases were divided randomly into a training cohort (two-thirds of cases) and a validation cohort (one-third of cases). Logistic regression was used to find risk factors for HGSOC and to create a new algorithm in the training cohort. Receiver operating characteristic curves were used to compare the diagnostic value of tumour biomarkers. Sensitivity and specificity of tumour markers and the new algorithm were calculated in the training cohort and validation cohort. ResultsThis study found significant differences in age; BRCA1/2 mutation status; CA125, CA724 and HE4 levels; and Risk of Ovarian Malignancy Algorithm score between the two groups.Logistic regression analysis showed that CA125 and BRCA1/2 were risk factors for HGSOC. A new algorithm combining CA125 and BRCA1/2 increased the specificity of CA125 for diagnosis of HGSOC. The new algorithm had sensitivity of 81.08% and specificity of 93.10% in the training cohort. ConclusionThe new algorithm using CA125 and BRCA1/2 helped to distinguish between patients with HGSOC and patients with non-HGSOC.

I saw the “sea anemone” sign: Puffy face of borderline ovarian tumors

The sea anemone sign is a radiologic sign seen on magnetic resonance imaging (MRI) studies that indicates the morphological development of serous borderline ovarian tumors (SBOTs), as papillary projections originating from the wall of the cystic lesion. The presence of T2 hypointense fibrous stroma in the center of the papilla is a helpful tip in the diagnosis of SBOTs. Those projections might also be assumed to have a frond-like appearance which can be seen as branching papillary projections, especially on T2-weighted imaging.The term “sea anemone” sign is described by Tanaka et al. who deemed it as a “hallmark” feature of surface SBOTs.

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

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. 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. 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. 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.

Borderline tumours of ovary and fertility preservation–Outcomes from a tertiary care center in India

ObjectiveBorderline ovarian tumors (BOT) are characterized by atypical epithelial proliferation without stromal invasion and majority are diagnosed in women of reproductive age group desirous of fertility preservation. MethodsA retrospective review of medical records of patients diagnosed with BOT and on regular follow up at the All India Institute of Medical Sciences New Delhi, during a nine-year study period from March 2014 to March 2023 was performed. Surgical treatment was classified as radical or fertility sparing surgery (FSS). Surgical staging was defined as complete, partial or un-staged. ResultsMedian age of 91 women was 34 years. Follow up period ranged from 4 to 222 months (median 77 months). Among 68 premenopausal women, 31 (46 %) underwent radical surgery and FSS in 37 (54 %) cases. Median time to conception in 29 women with future fertility wishes was 13 months (range, 4 to38 m). Seven of 29 cases (29 %) required ovulation induction. The pregnancy rate was 82.7 % and live birth rate was 80 %. Eight cases (8.7 %) had a recurrence (7- un-staged, 1- partially staged) and median time to recur was 36 months. There was no significant difference in recurrence between cystectomy/oophorectomy. Ovary was the site of recurrence in all surgically salvaged cases except peritoneal cavity in 1 case with mortality. Relapse free survival at 5 and 10 years in FSS and radical surgery group were similar. ConclusionFSS is a safe procedure and should be considered in young patients desirous of future fertility along with a comprehensive peritoneal staging. Reproductive outcomes are excellent.

Immunohistochemical expression of Beclin-1 and LC3B in benign and borderline ovarian tumors

Background Epithelial ovarian tumors account for ⁓90% of ovarian cancers. Recently conducted studies have demonstrated autophagy role in tumor development and progression. Autophagic markers include Beclin-1, essential for autophagosome formation and LC3B, required for the elongation step during autophagy. Aim To investigate Beclin-1 and LC3B expression in benign and borderline epithelial ovarian tumors along with its relation to clinicopathologic parameters. Materials and methods Thirty-six cases of epithelial ovarian neoplasms were subjected to hematoxylin and eosin staining and immunohistochemical staining with Beclin-1 and LC3B. Results Beclin-1 was expressed in the nucleus and/or the cytoplasm of tumor cells. The cytoplasmic expression of Beclin-1 was significantly more frequent in borderline cases compared with benign tumors. High Beclin-1 cytoplasmic expression was significantly associated with tumor size, gross appearance, and tumor histological type. Benign Brenner tumors were the only benign tumors expressing cytoplasmic Beclin-1 localization. Regarding LC3B expression, nuclear and cytoplasmic subcellular localizations were also detected. Cytoplasmic LC3B localization was significantly more frequent in the borderline groups. A significant relation was observed between high cytoplasmic LC3B expression and tumor size, tumor gross appearance, and histological type. The majority of benign Brenner tumors showed a high cytoplasmic LC3B expression. Conclusions The expression of Beclin-1 and LC3B varies in benign versus borderline epithelial ovarian tumors. Cytoplasmic expression is predominant in borderline tumors. Beclin-1 and LC3B cytoplasmic expression is significantly high in small-sized and solid benign tumors. Benign Brenner tumors are the only benign tumors showing cytoplasmic Beclin-1 and LC3B localization.

BORDERLINE OVARIAN TUMORS. MEDICAL AND PSYCHOLOGICAL REHABILITATION

Ovarian tumors are the most common diseases of the female reproductive system that require comprehensive treatment. Any tumor diseases often cause negative consequences for mental health. In order to prevent undesirable mental reactions in patients who have suffered from such a disease, it is necessary to apply rehabilitation measures. Restorative treatment methods accelerate regeneration of body functions, reduce the frequency of complications, thereby improving the prognosis of the disease. The aim of the study is to study the impact of medical and psychological rehabilitation on the quality of life in patients who have suffered a borderline ovarian tumor. Materials and methods. Medical and psychological rehabilitation, which consists of a set of measures, is important in the recovery of patients with borderline ovarian tumors. These methods help to cope faster with unpleasant and adverse symptoms caused by the disease. In this work, medical and psychological monitoring of 30 patients was carried out, the average age was 28 years, and all patients were diagnosed with borderline ovarian tumor. Research results. It was found that in patients with borderline ovarian tumors who underwent complex rehabilitation measures, the risk of mental disorders decreased. For the first time, a questionnaire entitled "Scale for assessing the severity of the risk for dependent behavior development in patients with borderline ovarian tumor" was used to evaluate the results. Conclusions. Patients who suffered a borderline ovarian tumor and underwent a course of medical and psychological rehabilitation are better adapted to all areas of daily life. Various techniques designed to work with stress significantly improve the quality of life in patients. After carrying out the complex of rehabilitation measures, the risk of mental disorders is minimal. Such patients did not have symptoms of anxiety and depression.

Metabolomic Analysis of Amino Acid and Organic Acid Profiles in Tissue From Ovarian Cancer Patients Using High-Performance Liquid Chromatography-Tandem Mass Spectrometry (HPLC-MS/MS) and Gas Chromatography-Tandem Mass Spectrometry (GC-MS/MS)

Targeted metabolomics studies on organic acids (OAs) and amino acids (AAs) were performed to search for biomarkers for ovarian cancer progression. Simultaneous AA profiling analysis method was developed through LC-MS/MS. Under optimal conditions, method showed good linearity (r ≥ 0.998) with limits of detection (LOD) ≤ 0.22 ng/mL and limits of quantification (LOQ) of ≤0.72 ng/mL. Repeatability varied from 1.4 to 17.3 relative standard deviation (%RSD) and accuracy varied from −20.6% to 12.1% relative error (% RE). Twenty-six AAs and 13 OAs were detected in the analyses of ovarian tissue from patients with benign ovarian tumors (BOT), borderline tumors (BT), and ovarian serous carcinoma (OSC). Star pattern recognition analysis was performed by normalizing each group to the BOT group. The star symbol plots in the BT and OSC groups were distinct and easily distinguished from those in the BOT group. The BT and the OSC groups exhibited higher 3-hydroxybutyric acid and lactic acid levels, lower pyruvic acid and OA levels in the TCA cycle, and alterations in AA metabolic patterns in comparison to the BOT group. Especially, citrulline and leucine were significantly reduced, while fumaric acid and malic acid significantly increased in the OSC group compared to the BT group. The BT and the OSC groups were completely separated in orthogonal partial least squares-discriminant analysis (OPLS-DA) and heatmap analysis. These findings, elevated ketone body levels, increased anaerobic glycolysis, reduced energy production related to mitochondrial dysfunction in the TCA cycle, and AA metabolic patterns associated with the impaired antioxidant system, may explain the characteristic metabolic reprogramming and Warburg effect related to the progression of the OSC into malignancy.

Reproductive outcomes in women opting for fertility preservation after fertility-sparing surgery for borderline ovarian tumors.

What are the reproductive outcomes of women who had fertility preservation (FP) using either oocyte or embryo vitrification after fertility-sparing surgery (FSS) for a borderline ovarian tumor (BOT)? A retrospective, single-center cohort study was conducted between January 2013 and December 2021. Patients with BOT who resorted to FP by vitrifying oocytes or embryos were included. Both clinical and reproductive parameters were reviewed. The primary outcome was live birth. In total, thirteen patients who performed 31 FP cycles were included. Of those, six patients achieved eight live births after a mean follow-up period of 79 months. Three further pregnancies are still ongoing. All pregnancies/live births were obtained without using their cryopreserved oocytes or embryos. Women who had FSS for BOT have favorable prospects of live offspring, even without the need to use their cryopreserved material. Fertility preservation in patients with BOT has to be considered as a tool to mitigate the risk of infertility that may arise in case of BOT recurrence requiring castrating surgery.

Fertility potential and safety assessment of residual ovarian cortex in young women diagnosed with epithelial borderline and early-stage malignant ovarian tumors

ObjectiveTo establish the safety and quality of ovarian cortex surrounding epithelial ovarian tumors in women eligible for fertility-sparing surgery by identifying occult malignant lesions and characterizing the ovarian follicle pool. MethodsMulticentric retrospective study of 48 subjects (15–45 years), diagnosed with borderline ovarian tumors (BOTs) or early-stage epithelial ovarian cancers (EOCs) and eligible for fertility-sparing surgery. Histological samples of ovarian cortex surrounding tumors were analyzed to characterize the follicle pool, find any occult malignant lesion using tumor-specific markers (cytokeratin 7 and mucin 1), and quantify tumor-infiltrating lymphocytes (TILs) by CD3 and tumor associated macrophages (TAMs) by CD68. ResultsOccult ovarian lesions were observed in 6 out of 45 cases investigated (14.6%), including one mucinous stage-I BOT (1/14), one serous stage-I BOT (1/13), 3 advanced-stage serous BOTs (3/11) and one early-stage serous EOC (1/7). Notably, follicle density was significantly lower in subjects diagnosed with ovarian tumors compared to controls (p < 0.001) and at a younger age. Significantly higher follicle atresia was encountered in the ovarian tumor group then in controls (20.1 ± 8.8% vs 9.2 ± 9.4%, p < 0.001) at all ages. Both TILs and TAMs were found in ovarian tumors irrespective of histotype, but no link was established with the status of the ovarian reserve. ConclusionsPersonalized counseling for fertility preservation is required in the event of BOTs and early-stage EOCs. Fertility-sparing surgery and adjuvant gamete preservation should be considered, balancing the oncological risks according to tumor stage and histotype and fertility potential, especially at a younger age.

Extensive Xanthomatous Change in an Ovarian Serous Borderline Tumor: More Than Just a Mere Coincidence

AbstractSerous borderline tumors of the ovary fall in between the benign and malignant category. These tumors are often diagnosed early, and the prognosis is usually favorable. However, there are variations in the histopathological findings of borderline ovarian tumors. Xanthomatous change is one such rare change in which deposition of lipid-rich material is seen morphologically as xanthoma cells within tumor tissue and reports of this are sparse. There is postulated literature on xanthomatous change being a contributing factor for progression of cancer. We present a case of a 75-year-old postmenopausal female with complaint of pain abdomen since 3 days, diagnosed radiologically as right ovarian mucinous cystadenoma/cystadenocarcinoma. Histopathology revealed a serous borderline tumor with extensive xanthomatous change. This case presents important thoughts on exploring the connection of xanthomatous change with borderline ovarian tumors, which till date is a matter of debate.

Abstract A107: Characterizing the genomic and immunologic landscape of serous borderline tumors and low-grade serous ovarian cancer

Abstract A107: Characterizing the genomic and immunologic landscape of serous borderline tumors and low-grade serous ovarian cancer

Accuracy of machine learning in the preoperative identification of ovarian borderline tumors: a meta-analysis

The objective of this study is to explore the diagnostic value of machine learning (ML) in borderline ovarian tumors through meta-analysis. Pubmed, Embase, Web of Science, and Cochrane Library databases were comprehensively retrieved from database inception untill February 16, 2023. The Prediction Model Risk of Bias Assessment Tool (PROBAST) was adopted to evaluate the risk of bias in the original studies. Sub-group analyses of ML were conducted according to clinical features and radiomics features. We separately discussed the discriminative value of ML for borderline vs benign and borderline vs malignant tumors. Eighteen studies involving 12,778 subjects were included in our analysis. The modeling variables mainly consisted of radiomics features (n=13) and a small number of clinical features (n=5). When distinguishing between borderline and benign tumors, the ML model based on radiomic features achieved a c-index of 0.782 (95% CI: 0.732-0.831), sensitivity of 0.75 (95% CI: 0.67-0.82), and specificity of 0.75 (95% CI: 0.67-0.81) in the validation set. When distinguishing between borderline and malignant tumors, the ML model based on radiomic features achieved a c-index of 0.916 (95% CI: 0.891-0.940), sensitivity of 0.86 (95% CI: 0.78-0.91), and specificity of 0.88 (95% CI: 0.82-0.92) in the validation set. In addition, we analyzed the discriminatory ability of radiologists and found that their sensitivity was 0.26 (95% CI: 0.12-0.46) and specificity was 0.94 (95% CI: 0.90-0.97). ML has tremendous potential in the preoperative diagnosis and differentiation of borderline ovarian tumors and may be more accurate than radiologists in diagnosing and differentiating borderline ovarian tumors.

Sentinel Node Mapping in Ovarian Tumors: A Study Using Lymphoscintigraphy and SPECT/CT.

Ovarian cancer in the early stage requires a complete surgical staging, including radical lymphadenectomy, implying subsequent risk of morbidity and complications. Sentinel lymph node (SLN) mapping is a procedure that attempts to reduce radical lymphadenectomy-related complications and morbidities. Our study evaluates the feasibility of SLN mapping in patients with ovarian tumors by the use of intraoperative Technetium-99m-Phytate (Tc-99m-Phytate) and postoperative lymphoscintigraphy using tomographic (single-photon emission computed tomography/computed tomography (SPECT/CT)) acquisition. Thirty-two patients with ovarian mass participated in this study. Intraoperative injection of the radiopharmaceutical was performed just after laparotomy and before the removal of tumor in utero-ovarian and suspensory ligaments of the ovary just beneath the peritoneum. Subsequently, pelvic and para-aortic lymphadenectomy was performed for malignant masses, and the presence of tumor in the lymph nodes was assessed through histopathological examination. Conversely, lymphadenectomy was not performed in patients with benign lesions or borderline ovarian tumors. Lymphoscintigraphy was performed within 24 hr using tomographic acquisition (SPECT/CT) of the abdomen and pelvis. Final pathological examination showed 19 patients with benign pathology, 5 with borderline tumors, and 6 with malignant ovarian tumors. SPECT/CT identified SLNs in para-aortic-only areas in 6 (20%), pelvic/para-aortic areas in 14 (47%), and pelvic-only areas in 7 (23%) cases. Notably, additional unusual SLN locations were revealed in perirenal, intergluteal, and posterior to psoas muscle regions in three patients. We were not able to calculate the false negative rate due to the absence of patients with involved lymph nodes. SLN mapping using intraoperative injection of radiotracers is safe and feasible. Larger studies with more malignant cases are needed to better evaluate the sensitivity of this method for lymphatic staging of ovarian malignancies.

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

ObjectivesTo 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 DesignA 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. ResultsThree 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). ConclusionsSatisfactory 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.

Expression of selected epithelial–mesenchymal transition (EMT) transcription factors in serous borderline ovarian tumors and type I ovarian cancers

Expression of selected epithelial–mesenchymal transition (EMT) transcription factors in serous borderline ovarian tumors and type I ovarian cancers

Radiomics nomogram for preoperative differentiation of early-stage serous borderline ovarian tumors and serous malignant ovarian tumors.

This study aimed to construct a radiomics nomogram and validate its performance in the preoperative differentiation between early-stage (I and II) serous borderline ovarian tumors (SBOTs) and serous malignant ovarian tumors (SMOTs). Data were collected from 80 patients with early-stage SBOTs and 102 with early-stage SMOTs (training set: n = 127; validation set: n = 55). Univariate and multivariate analyses were performed to identify the independent clinicoradiological factors. A radiomics signature model was constructed using radiomics features extracted from multidetector computed tomography images of the venous phase, in which the least absolute shrinkage and selection operator regression was employed to lessen the dimensionality of the data and choose the radiomics features. A nomogram model was established by combining independent clinicoradiological factors with the radiomics signature. The performance of nomogram calibration, discrimination, and clinical usefulness was evaluated using training and validation sets. In terms of clinicoradiological characteristics, age (p = 0.001), the diameter of the solid component (p = 0.009), and human epididymis protein 4 level (p < 0.001) were identified as the independent risk factors of SMOT, for which the area under the curves (AUCs) were calculated to be 0.850 and 0.836 in the training and validation sets, respectively. Nine features were finally selected to construct the radiomics signature model, which exhibited AUCs of 0.879 and 0.826 for the training and validation sets, respectively. The nomogram model demonstrated considerable calibration and discrimination with AUCs of 0.940 and 0.909 for the training and validation sets, respectively. The nomogram model displayed more prominent clinical usefulness than the clinicoradiological and radiomics signature models according to the decision curve analysis. The nomogram model can be employed as an individualized preoperative non-invasive tool for differentiating early-stage SBOTs from SMOTs.

Diagnostic efficacy of combining diffusion-weighted magnetic resonance imaging with serum Mucin 1, Mucin 13, and Mucin 16 in distinguishing borderline from malignant epithelial ovarian tumors.

To enhance ovarian tumor diagnosis beyond conventional methods, this study explored combining diffusion-weighted magnetic resonance imaging (DWI-MRI) and serum biomarkers (Mucin 1 [MUC1], MUC13, and MUC16) for distinguishing borderline from malignant epithelial ovarian tumors. A total of 126 patients, including 71 diagnosed with borderline (BEOTs) and 55 with malignant epithelial ovarian tumors (MEOTs), underwent preoperative DWI-MRI. Region of interest (ROI) was manually drawn along the solid component's boundary of the largest tumor, focusing on areas with potentially the lowest apparent diffusion coefficient (ADC). For entirely cystic tumors, a free-form ROI enclosed the maximum number of septa while targeting the lowest ADC. Serum biomarkers were determined using enzyme-linked immunosorbent assay. Basic morphological traits proved inadequate for malignancy diagnosis, warranting this investigation. BEOTs had an ADC mean of (1.670±0.250) × 103 mm2 /s, while MEOTs had a lower ADC mean of (1.332±0.481) × 103 mm2 /s, with a sensitivity of 63.6% and specificity of 90.1%. Median MUC1 (167.0 U/mL vs. 87.3 U/mL), MUC13 (12.44ng/mL vs. 7.77ng/mL), and MUC16 (180.6 U/mL vs. 36.1 U/mL) levels were higher in MEOTs patients. The biomarker performance was: MUC1, sensitivity 50.9%, specificity 100%; MUC13, sensitivity 56.4%, specificity 78.9%; MUC16, sensitivity 83.64%, specificity 100%. Combining serum biomarkers and ADC mean resulted in a sensitivity of 96.4% and specificity of 100%. The integration of DWI-MRI with serum biomarkers (MUC1, MUC13, and MUC16) achieves exceptional diagnostic accuracy, offering a powerful tool for the precise differentiation between borderline and malignant epithelial ovarian tumors.

CT-Based Radiomics and Machine Learning for Differentiating Benign, Borderline, and Early-Stage Malignant Ovarian Tumors.

To explore the value of CT-based radiomics model in the differential diagnosis of benign ovarian tumors (BeOTs), borderline ovarian tumors (BOTs), and early malignant ovarian tumors (eMOTs). The retrospective research was conducted with pathologically confirmed 258 ovarian tumor patients from January 2014 to February 2021. The patients were randomly allocated to a training cohort (n = 198) and a test cohort (n = 60). By providing a three-dimensional (3D) characterization of the volume of interest (VOI) at the maximum level of images, 4238 radiomic features were extracted from the VOI per patient. The Wilcoxon-Mann-Whitney (WMW) test, least absolute shrinkage and selection operator (LASSO), and support vector machine (SVM) were employed to select the radiomic features. Five machine learning (ML) algorithms were applied to construct three-class diagnostic models. Leave-one-out cross-validation (LOOCV) was implemented to evaluate the performance of the radiomics models. The test cohort was used to verify the generalization ability of the radiomics models. The receiver-operating characteristic (ROC) was used to evaluate diagnostic performance of radiomics model. Global and discrimination performance of five models was evaluated by average area under the ROC curve (AUC). The average ROC indicated that random forest (RF) diagnostic model in training cohort demonstrated the best diagnostic performance (micro/macro average AUC, 0.98/0.99), which was then confirmed with by LOOCV (micro/macro average AUC, 0.89/0.88) and external validation (test cohort) (micro/macro average AUC, 0.81/0.79). Our proposed CT-based radiomics diagnostic models may effectively assist in preoperatively differentiating BeOTs, BOTs, and eMOTs.