Risk of Malignancy in Sonographically Confirmed Ovarian Tumors

Diagnostic Performance of Magnetic Resonance Imaging for Pediatric Ovarian Neoplasms: A Multi-Institutional Review

STUDY OBJECTIVE

To assess the diagnostic performance of MRI to predict ovarian malignancy alone and compared with other diagnostic studies.

METHODS

A retrospective analysis was conducted of patients aged 2-21 years who underwent ovarian mass resection between 2009 and 2021 at 11 pediatric hospitals. Sociodemographic information, clinical and imaging findings, tumor markers, and operative and pathology details were collected. Diagnostic performance for detecting malignancy was assessed by calculating sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) for MRI with other diagnostic modalities.

RESULTS

One thousand and fifty-three patients, with a median age of 14.6 years, underwent resection of an ovarian mass; 10% (110/1053) had malignant disease on pathology, and 13% (136/1053) underwent preoperative MRI. MRI sensitivity, specificity, PPV, and NPV were 60%, 94%, 60%, and 94%. Ultrasound sensitivity, specificity, PPV, and NPV were 31%, 99%, 73%, and 95%. Tumor marker sensitivity, specificity, PPV, and NPV were 90%, 46%, 22%, and 96%. MRI and ultrasound concordance was 88%, with sensitivity, specificity, PPV, and NPV of 33%, 99%, 75%, and 94%. MRI sensitivity in ultrasound-discordant cases was 100%. MRI and tumor marker concordance was 88% with sensitivity, specificity, PPV, and NPV of 100%, 86%, 64%, and 100%. MRI specificity in tumor marker-discordant cases was 100%.

CONCLUSION

Diagnostic modalities used to assess ovarian neoplasms in pediatric patients typically agree. In cases of disagreement, MRI is more sensitive for malignancy than ultrasound and more specific than tumor markers. Selective use of MRI with preoperative ultrasound and tumor markers may be beneficial when the risk of malignancy is uncertain.

CONCISE ABSTRACT

This retrospective review of 1053 patients aged 2-21 years who underwent ovarian mass resection between 2009 and 2021 at 11 pediatric hospitals found that ultrasound, tumor markers, and MRI tend to agree on benign vs malignant, but in cases of disagreement, MRI is more sensitive for malignancy than ultrasound.

Evaluation of a symptom-based score in combination with CA125 to predict ovarian malignancy in women with adnexal mass

BACKGROUND

Adnexal masses are a common problem seen in women. The aim of this study was to determine the appropriate cut-off for symptom-based score to predict ovarian malignancy in women with adnexal mass and to evaluate it in combination with CA125.

METHODS

This was a prospective study involving 341 women with adnexal mass who underwent surgery. A symptom-based scoring system was administered to the women, preoperatively, and CA125 levels were documented. Receiver operating characteristic curve (ROC) analysis was used to determine the appropriate cut-off for the symptom-based scoring. Results for this symptom-based scoring and CA125 were correlated with surgical pathological findings.

RESULTS

Out of the 341 women with adnexal mass, 112 were diagnosed to have ovarian malignancy. The mean age of women was 43.6±13.8 years. Using ROC analysis, symptom score ≥9 was determined to be the appropriate cut-off. The area under curve (AUC) at this cut-off score was found to be 0.87 (95% CI 0.83-0.91). The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) at this cut-off was found to be 84.8%, 88.6%,78.5%, and 92.3%, respectively. Combining CA125 and symptom score resulted in higher sensitivity (96.4%) and NPV (97.4%) with specificity and PPV of 65.5% and 57.8%, respectively.

CONCLUSION

Symptom score in combination with CA125 has good ability to predict ovarian malignancy in women with adnexal masses.

A decision support system based on radiomics and machine learning to predict the risk of malignancy of ovarian masses from transvaginal ultrasonography and serum CA-125

BACKGROUND

To evaluate the performance of a decision support system (DSS) based on radiomics and machine learning in predicting the risk of malignancy of ovarian masses (OMs) from transvaginal ultrasonography (TUS) and serum CA-125.

METHODS

A total of 274 consecutive patients who underwent TUS (by different examiners and with different ultrasound machines) and surgery, with suspicious OMs and known CA-125 serum level were used to train and test a DSS. The DSS was used to predict the risk of malignancy of these masses (very low versus medium-high risk), based on the US appearance (solid, liquid, or mixed) and radiomic features (morphometry and regional texture features) within the masses, on the shadow presence (yes/no), and on the level of serum CA-125. Reproducibility of results among the examiners, and performance accuracy, sensitivity, specificity, and area under the curve were tested in a real-world clinical setting.

RESULTS

The DSS showed a mean 88% accuracy, 99% sensitivity, and 77% specificity for the 239 patients used for training, cross-validation, and testing, and a mean 91% accuracy, 100% sensitivity, and 80% specificity for the 35 patients used for independent testing.

CONCLUSIONS

This DSS is a promising tool in women diagnosed with OMs at TUS, allowing to predict the individual risk of malignancy, supporting clinical decision making.

Biodegradable nanoparticles as theranostics of ovarian cancer: an overview

Objectives

Above 10 million people are suffering from cancers every year. As per American Cancer Society, more than 22 440 new cases and 14 080 deaths were reported from ovarian cancer yearly worldwide. This review explores the current status, challenges and future perspectives of tumour-targeted theranostic nanoparticles (NPs).

Key findings

Most of the ovarian malignancy cases are uncovered after the disease is in a difficult state due to poor screening techniques and non-specific symptoms. In this manner, forceful and fruitful treatment is required that will indicate insignificant lethal impacts to solid tissue. In the current research, stealth biodegradable NPs are produced as vehicles for imaging and treatment of ovarian cancer as the controlled and targeted delivery of chemotherapeutic as well as imaging agents. To enhance the dependability of the colloidal suspension as well as to increase their circulation lifetime, NPs are introduced by incorporating the functional poly(ethylene glycol) on their surface, which also provides a site to conjugation of focusing on agents to ovarian tissue.

Summary

Biodegradable theranostic NPs can be fabricated and surface engineered without any alteration in drug-loading capacity, safety and efficacy. These NPs have shown promising results in imaging as well as treatment of ovarian cancer.

Performance of the Risk of Malignancy Index for Discriminating Malignant Tumors in Women With Adnexal Masses

OBJECTIVES

We examined the performance of 4 risk of malignancy index (RMI) variants in a medium-resource gynecologic cancer center.

METHODS

A total of 158 women referred for adnexal masses were evaluated before surgery by the 4 RMI variants. Physicians with varied experience in ultrasound assessment of adnexal masses performed ultrasound examinations. We compared the performance of the 4 RMI variants using receiver operating characteristic curve analyses followed by calculation of sensitivity, specificity, and positive and negative likelihood ratios using the pathologic diagnosis of the masses as the reference standard.

RESULTS

Among the 158 women with adnexal masses included in this study, 51 (32%) had malignant tumors; 26 (51%) of them were stage I. All RMI variants performed similarly (accuracy range, 74%-83%), regardless of menopausal status. Considering all women included, the positive likelihood ratios of the 4 RMI variants ranged from 3.52 to 4.41. In subset analyses, all RMI variants had decreased sensitivity for stage I malignant tumors and for those of nonepithelial histologic types.

CONCLUSIONS

The 4 RMI variants performed acceptably in a medium-resource setting where ultrasound examiners were physicians with varied experience. This finding indicates a good tradeoff between performance and feasibility, since ultrasound RMI protocols are of low complexity.

Strategies to diagnose ovarian cancer: new evidence from phase 3 of the multicentre international IOTA study

Background:

To compare different ultrasound-based international ovarian tumour analysis (IOTA) strategies and risk of malignancy index (RMI) for ovarian cancer diagnosis using a meta-analysis approach of centre-specific data from IOTA3.

Methods:

This prospective multicentre diagnostic accuracy study included 2403 patients with 1423 benign and 980 malignant adnexal masses from 2009 until 2012. All patients underwent standardised transvaginal ultrasonography. Test performance of RMI, subjective assessment (SA) of ultrasound findings, two IOTA risk models (LR1 and LR2), and strategies involving combinations of IOTA simple rules (SRs), simple descriptors (SDs) and LR2 with and without SA was estimated using a meta-analysis approach. Reference standard was histology after surgery.

Results:

The areas under the receiver operator characteristic curves of LR1, LR2, SA and RMI were 0.930 (0.917–0.942), 0.918 (0.905–0.930), 0.914 (0.886–0.936) and 0.875 (0.853–0.894). Diagnostic one-step and two-step strategies using LR1, LR2, SR and SD achieved summary estimates for sensitivity 90–96%, specificity 74–79% and diagnostic odds ratio (DOR) 32.8–50.5. Adding SA when IOTA methods yielded equivocal results improved performance (DOR 57.6–75.7). Risk of Malignancy Index had sensitivity 67%, specificity 91% and DOR 17.5.

Conclusions:

This study shows all IOTA strategies had excellent diagnostic performance in comparison with RMI. The IOTA strategy chosen may be determined by clinical preference.

Current diagnostic approach to patients with adnexal masses: which tools are relevant in routine praxis?

OBJECTIVE

The aim of the study was to investigate which anamnestic, laboratory and ultrasound parameters used in routine practice could predict the nature of adnexal mass, thus enabling referral to relevant specialist.

METHODS

Study involved the women treated for adnexal tumors throughout a period of 2 years. On admission, detailed anamnestic and laboratory data were obtained, expert ultrasound scan was performed, and power Doppler index (PDI), risk of malignancy index (RMI) and body mass index (BMI) were calculated for all patients. Obtained data were related to histopathological findings, and statistically analyzed.

RESULTS

The study included 689 women (112 malignant, 544 benignant, and 33 borderline tumors). Malignant and borderline tumors were more frequent in postmenopausal women (P=0.000). Women who had benignant tumors had the lowest BMI (P=0.000). There were significant (P<0.05) differences among tumor types regarding erythrocyte sedimentation rate, CA125 and carcinoembryonic antigen (CEA) levels. Among ultrasound findings, larger tumor diameter and ascites were more frequent in malignant tumors (P=0.000). Women with malignant tumors had highest values of RMI and PDI (P=0.000).

CONCLUSIONS

Anamnestic data, ultrasound parameters and laboratory analyses were all found to be good discriminating factors among malignant, benignant and borderline tumors.

From bench to bedside: discovery of ovarian cancer biomarkers using high-throughput technologies in the past decade

Ovarian cancer is the most lethal gynecological malignancy and survival of this disease has remained relatively unchanged over the past 30 years. A contributing factor to this has been the lack of reliable biomarkers for the clinical management of ovarian cancer. Rapid advances in high-throughput technologies over the past decade has allowed for new and exciting opportunities for biomarker discovery in the field of ovarian cancer, especially with respect to serum biomarkers that can be used for various clinical applications. This review highlights the major genomic and proteomic studies dedicated to ovarian cancer biomarker discovery over the past decade. An emphasis will be placed on the HE4, Risk of Malignancy Algorithm (ROMA) and OVA1™ serum-based tests/algorithms that have recently been approved by the US FDA as ovarian cancer biomarkers.