Ovarian CancerRFDATANCT06473766
Ultrasound RF Data for Discriminating Between Benign and Malignant Ovarian Masses
A study testing RF data extraction in people with Ovarian Cancer, run by Fondazione Policlinico Universitario Agostino Gemelli IRCCS at 1 site in Italy.
Trial 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… Read more about this study
- Who is it for?
- Ages 18 years and older, women only
- Conditions the study is for
- Ovarian Cancer
- What is being tested?
- RF data extraction
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 50 participants
- Where
- 1 siteItaly
- Study dates
- 15 Jul 2024to 30 Sep 2025
- Phase
- Interventional
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 years and older
- Women only
- No healthy volunteers
- Adult, Older adult
Who may be able to join
- 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.
Who cannot join
- Patients under 18 years of age.
- Patient refusal
Trial locations and contacts
1 site in 1 country.
Elena Teodorico, MD contact
Italy1 site, 1 recruiting
- Recruiting
Fondazione Policlinico Universitario Agostino Gemelli IRCCS
Roma, 00168
ANTONIA CARLA TESTA, Professor, antoniacarla.testa@policlinicogemelli.it
Elena Teodorico, Dr, elena.teodorico@policlinicogemelli.it
About this study
Official title: Ultrasound RF Data for Discriminating Between Benign and Malignant Ovarian Masses With Solid Ultrasound Morphology, a Feasibility Study
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.
Read more
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
- Being tested
- RF data extraction
- Keywords
- ovarian cancer, Ultrasound
- Medical subject headings
- Ovarian Neoplasms
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
RF data extractionDiagnostic 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.
| Study group | Role | What they receive |
|---|---|---|
| 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. Receives: Diagnostic Test: RF data extraction |
What is being measured
The primary outcome is the main question the study is designed to answer.
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)
Measured: At time of ultrasound examination
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted25 Jun 2024
- Study start15 Jul 2024
- Primary completion31 Jul 2025 (estimated)
- Study completion30 Sep 2025 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Ovarian CancerStudies of the same condition, open and under way.
- More trials run by Fondazione Policlinico Universitario Agostino Gemelli IRCCSThe sponsor's other registered studies.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Diagnosis
- Allocation
- Not applicable
- Intervention model
- Single group
- Masking
- None (open label)
- Enrolment
- 50 participants (estimated)
Sponsor and investigators
- Sponsor type
- University, hospital or other
- Collaborators
- Samsung Medison
- Responsible party
- Principal investigator, Testa Antonia Carla, Fondazione Policlinico Universitario Agostino Gemelli IRCCS
- Investigators
- Antonia Carla Testa, Professor, Principal investigator, Fondazione Policlinico Universitario A. Gemelli, IRCCS, Rome
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT06473766
- Sponsor's protocol ID
- 6267
- Acronym
- RFDATA
- Status last verified
- Jun 2024
- First submitted
- 19 Jun 2024
- Last updated
- 18 Jun 2025
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
Study at a glance
From the registry record, last updated by the sponsor on 18 Jun 2025. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Ultrasound RF Data for Discriminating Between Benign and Malignant Ovarian Masses With Solid Ultrasound Morphology, a Feasibility Study
- ClinicalTrials.gov ID
- NCT06473766
- Acronym / sponsor ID
- RFDATA / 6267
- Conditions
- Ovarian Cancer
- Keywords
- ovarian cancer, Ultrasound
- Study type
- Interventional
- Recruitment status
- Unknown status
- Enrolment
- 50 participants (estimated)
- Lead sponsor
- Fondazione Policlinico Universitario Agostino Gemelli IRCCSUniversity, hospital or other
- Collaborators
- Samsung Medison
- Study start
- 15 Jul 2024 (actual)
- Primary completion
- 31 Jul 2025 (estimated)
- Study completion
- 30 Sep 2025 (estimated)
- First posted
- 25 Jun 2024 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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.
Study design
- Primary purpose
- Diagnosis
- Allocation
- Not applicable
- Intervention model
- Single group
- Masking
- None (open label)
- Number of arms
- 1
| Arm | Type | Receives |
|---|---|---|
| Feasibility of RF data to compare RF data in ovarian masses | Experimental | Diagnostic Test: RF data extractionTo 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. |
Who may qualify
- Ages
- 18 years and older
- Sex
- Female only
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
Key inclusion criteria (4 listed)
- 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.
Key exclusion criteria (2 listed)
- Patients under 18 years of age.
- Patient refusal
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| RF data extractionTo 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. | Diagnostic test | Feasibility of RF data to compare RF data in ovarian masses |
Primary outcome
number of examinations readable
Time frame: At time of ultrasound examination
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)
Results and safety
Results are not available in the source record.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 18 Jun 2025.
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
Elena Teodorico, MD contact
Antonia Carla Testa, Professor principal investigator
Fondazione Policlinico Universitario A. Gemelli, IRCCS, Rome
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing RF data extraction in people with Ovarian Cancer, run by Fondazione Policlinico Universitario Agostino Gemelli IRCCS at 1 site in Italy.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 4 inclusion and 2 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: status not confirmed, as of the sponsor's last update on 18 Jun 2025. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in Italy. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
Results are not available in the source record.
How can a doctor refer a patient or contact the research team?
Contact Antonia Carla Testa, Professor (0630156399, antoniacarla.testa@policlinicogemelli.it), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
number of examinations readable (time frame: At time of ultrasound examination). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 18 Jun 2025.