Ultrasound RF Data for Discriminating Between Benign and Malignant Ovarian Masses

NCT ID: NCT06473766

Last Updated: 2025-06-18

Basic Information

• Recruitment Status: RECRUITING
• Clinical Phase: NA
• Total Enrollment: 50 participants
• Study Classification: INTERVENTIONAL
• Study Start Date: 2024-07-15
• Study Completion Date: 2025-09-30

Brief Summary

Ultrasound imaging provides useful information for the characterization of ovarian masses as benign or malignant. The most accurate mathematical model to categorize ovarian masses is the IOTA ADNEX model.This model estimates the risk of malignancy and performs similarly to subjective assessment by an experienced ultrasound examiner for discriminating between benign and malignant adnexal masses. The ability of IOTA ADNEX to discriminate between benign and malignant masses is very good (area under the receiver operator characteristic curve 0.937 (95% CI: 0.915-0.954). The ADNEX model maintains its accuracy even in the hands of operators with different experience and training.

According to IOTA terminology, 13% of ovarian masses detected on ultrasound examination are classified as solid. Solid ovarian masses have a risk of malignancy of 60%-75%2 and the discrimination between benign and malignant in this morphological category is challenging. Additionally, it has been estimated that 30% (25/84; 95% CI 18 to 44%) of solid malignant ovarian masses are metastases from non-ovarian tumors. The discrimination between primary ovarian cancer and metastatic tumors in the ovary is also clinically important for planning adequate therapeutic procedures. It is worth exploring the predictive performance of the diagnostic tools in identifying ovarian masses with ultrasound solid morphology.

Preliminary data (unpublished) on radiomics analysis and ovarian masses provided that benign and malignant ovarian masses with solid morphology have different radiomics features in a monocentric retrospective study. However, no statistically significant differences have been observed between primary ovarian cancer and metastases to the ovary.

A new technology is emerging in engineering ultrasound field: the analysis of ultrasound summed RF data- raw data generated by the interface of ultrasound beams with human tissues. To date, raw data are not utilized for conventional imaging and their eventual role in clinical practice is unknown. Indeed, summed RF data could better correlate with biological parameters then parameters identifiable in B-mode images. Summed RF data could also improve radiomic analysis.

Conditions

Ovarian Cancer

Study Design

• Allocation Method: NA
• Intervention Model: SINGLE_GROUP
• Primary Study Purpose: DIAGNOSTIC
• Blinding Strategy: NONE

Study Groups

Feasibility of RF data to compare RF data in ovarian masses

To evaluate the feasibility of RF data in patients with ovarian masses with solid ultrasound morphology

1. To compare RF data in benign and malignant ovarian masses with ultrasound solid morphology. Histology will be the reference standard.

2. To compare RF data in primary invasive and metastases to the ovary.

3. To describe the reliability of RF data between different images of the same solid ovarian tumor.

Group Type: EXPERIMENTAL

RF data extraction

Intervention Type: DIAGNOSTIC_TEST

To will be acquired:

10 S-Harmonic images (5 in longitudinal plane, 5 in orthogonal plane), 10 B-mode fundamental images (without Harmonic), 1 gray-scale video clip, 1 gray-scale 3D vol will be stored in Harmonic settings and RF-preset.

The Region of interest (ROI) of each image will be manually segmented by a trained gynecologist using the software Aliza version 1.48. The ROI will include only the solid component of the mass. Additional analysis will be performed by using a predefined ROI (area 2x2 cm2). Radiomic features will be extracted using the MODDICOM, an open-source in-house software solution developed by the Knowledge Based Oncology Labs (Rome, Italy) for quantitative imaging analysis fully compliant with the Image Biomarker Standardization Initiative recommendations. The features will be considered: intensity-based statistical and textural.

Interventions

RF data extraction

To will be acquired:

10 S-Harmonic images (5 in longitudinal plane, 5 in orthogonal plane), 10 B-mode fundamental images (without Harmonic), 1 gray-scale video clip, 1 gray-scale 3D vol will be stored in Harmonic settings and RF-preset.

The Region of interest (ROI) of each image will be manually segmented by a trained gynecologist using the software Aliza version 1.48. The ROI will include only the solid component of the mass. Additional analysis will be performed by using a predefined ROI (area 2x2 cm2). Radiomic features will be extracted using the MODDICOM, an open-source in-house software solution developed by the Knowledge Based Oncology Labs (Rome, Italy) for quantitative imaging analysis fully compliant with the Image Biomarker Standardization Initiative recommendations. The features will be considered: intensity-based statistical and textural.

Intervention Type: DIAGNOSTIC_TEST

Eligibility Criteria

Inclusion Criteria

1. Patients with a preoperative ultrasound diagnosis of a solid ovarian mass (solid according to IOTA terminology, i.e. 80% of the tumor consists of solid tissue).

2. Patients who will undergo surgery within 120 days after the ultrasound examination.

3. Patients at least 18 years old.

4. Informed consent signed.

Exclusion Criteria

1. Patients under 18 years of age.

2. Patient refusal

• Minimum Eligible Age: 18 Years
• Eligible Sex: FEMALE
• Accepts Healthy Volunteers: No

Sponsors

Samsung Medison

INDUSTRY

Sponsor Role: collaborator

Fondazione Policlinico Universitario Agostino Gemelli IRCCS

OTHER

Sponsor Role: lead

Responsible Party

Testa Antonia Carla

Principal Investigator

Responsibility Role: PRINCIPAL_INVESTIGATOR

Principal Investigators

Antonia Carla Testa, Professor

Role: PRINCIPAL_INVESTIGATOR

Fondazione Policlinico Universitario A. Gemelli, IRCCS, Rome

Locations

Fondazione Policlinico Universitario Agostino Gemelli IRCCS

Roma, , Italy

Site Status: RECRUITING

Countries

Italy

Central Contacts

Antonia Carla Testa, Professor

Role: CONTACT

antoniacarla.testa@policlinicogemelli.it

0630156399

Elena Teodorico, MD

Role: CONTACT

elena.teodorico@policlinicogemelli.it

Facility Contacts

ANTONIA CARLA TESTA, Professor

Role: primary

antoniacarla.testa@policlinicogemelli.it

Elena Teodorico, Dr

Role: backup

elena.teodorico@policlinicogemelli.it

Other Identifiers

6267

Identifier Type: -

Identifier Source: org_study_id