Ultrasound RF Data for Discriminating Between Benign and Malignant Ovarian Masses
- Conditions
- Ovarian Cancer
- Interventions
- Diagnostic Test: RF data extraction
- Registration Number
- NCT06473766
- 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Preliminary data (unpublished) on radiomics analysis and ovarian masses provided that benign and malignant ovarian masses with solid morphology have different radiomics features in a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.
- Detailed Description
Not available
Recruitment & Eligibility
- Status
- NOT_YET_RECRUITING
- Sex
- Female
- Target Recruitment
- 50
- 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.
- Patients under 18 years of age.
- Patient refusal
Study & Design
- Study Type
- INTERVENTIONAL
- Study Design
- SINGLE_GROUP
- Arm && Interventions
Group Intervention Description Feasibility of RF data to compare RF data in ovarian masses RF data extraction 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.
- Primary Outcome Measures
Name Time Method number of examinations readable 30 minutes 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)
- Secondary Outcome Measures
Name Time Method
Trial Locations
- Locations (1)
Fondazione Policlinico Universitario Agostino Gemelli IRCCS
🇮🇹Roma, Italy