Ultrasound RF Data for Discriminating Between Benign and Malignant Ovarian Masses

NCT06473766 | Recruiting

• 1 other identifier: 6267
• Study Type: interventional
• Target: 50
• Locations: 1 country
• Sites: 1

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 Preliminary data (unpublished) on radiomics analysis and ovarian masses provided that benign and malignant ovarian masses with solid morphology have different radiomics features in a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

Keywords

ovarian cancer; Ultrasound

Outcome Measures

Primary Outcomes (1)

• number of examinations readable

  Feasibility measured as number of examinations readable, (i.e. number of patients with successful process with diagnosed solid ovarian masses, and acquisition of readable RF data)

  At time of ultrasound examination

Study Arms (1)

Feasibility of RF data to compare RF data in ovarian masses

EXPERIMENTAL

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.

Diagnostic Test: RF data extraction

Interventions

RF data extraction 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.

Feasibility of RF data to compare RF data in ovarian masses

Eligibility Criteria

• Age: 18 Years+
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)

You may qualify if:

• 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).
• Patients who will undergo surgery within 120 days after the ultrasound examination.
• Patients at least 18 years old.
• Informed consent signed.

You may not qualify if:

• Patients under 18 years of age.
• Patient refusal

Sponsors & Collaborators

• Fondazione Policlinico Universitario Agostino Gemelli IRCCS: lead
• Samsung Medison: collaborator

Study Sites (1)

Fondazione Policlinico Universitario Agostino Gemelli IRCCS

Roma, 00168, Italy

RECRUITING

MeSH Terms

Conditions

Ovarian Neoplasms

Condition Hierarchy (Ancestors)

Endocrine Gland Neoplasms; Neoplasms by Site; Neoplasms; Ovarian Diseases; Adnexal Diseases; Genital Diseases, Female; Female Urogenital Diseases; Female Urogenital Diseases and Pregnancy Complications; Urogenital Diseases; Genital Neoplasms, Female; Urogenital Neoplasms; Genital Diseases; Endocrine System Diseases; Gonadal Disorders

Study Officials

• Antonia Carla Testa, Professor

  Fondazione Policlinico Universitario A. Gemelli, IRCCS, Rome

  PRINCIPAL INVESTIGATOR

Central Study Contacts

Antonia Carla Testa, Professor

CONTACT

0630156399; antoniacarla.testa@policlinicogemelli.it

Elena Teodorico, MD

CONTACT

elena.teodorico@policlinicogemelli.it

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: NA
• Masking: NONE
• Purpose: DIAGNOSTIC
• Intervention Model: SINGLE GROUP
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Principal Investigator

Study Record Dates

• First Submitted: June 19, 2024
• First Posted: June 25, 2024
• Study Start: July 15, 2024
• Primary Completion: July 31, 2025
• Study Completion: September 30, 2025
• Last Updated: June 18, 2025

Record last verified: 2024-06

Locations

IT (1)