Construction of a Model for the Differential Diagnosis of SArcoma/myoma Based on the RAdiomics Features: Single-center Observational Study

NCT ID: NCT06805019

Last Updated: 2025-02-03

Basic Information

• Recruitment Status: RECRUITING
• Total Enrollment: 176 participants
• Study Classification: OBSERVATIONAL
• Study Start Date: 2022-11-07
• Study Completion Date: 2025-06-30

Brief Summary

Uterine sarcomas are rare and aggressive tumors originating from the muscular wall of the uterus. They have a high risk of recurrence and death, regardless of the stage of the disease at diagnosis. The therapy is surgical and involves hysterectomy preferably via laparotomy in consideration of the high risk of neoplastic dissemination through the rupture and fragmentation of the neoplasm as occurs through removal by other surgical routes which involve core drilling of the mass (laparoscopic, vaginal , hysteroscopic).

Uterine myoma represents a very frequent benign pathology in women, with an incidence of approximately 70%-80%. Asymptomatic cases do not require treatment, while symptomatic cases can be treated through the administration of generally antiestrogenic drugs to block growth and symptoms. Only a small part is removed surgically.

Currently the diagnosis of uterine sarcoma is almost always defined in the post-operative setting with the definitive histological examination, due to the lack of typical sonographic and radiological characteristics of certainty capable of differentiating benign neoplastic forms (myoma) from malignant ones of the uterus (sarcoma).

Magnetic resonance imaging is currently the most reliable imaging modality for characterizing such uterine masses. Unfortunately, although it offers useful information, it is not able to discriminate with good precision a benign uterine lesion from a malignant one.

CT is a method widely used in the staging of oncological diseases and therefore also in sarcomas. It is usually prescribed when there is an ultrasound doubt of a sarcoma before proceeding with surgery.

However, although it is important in the definition of secondaries, it has very low sensitivity (60%) and specificity in the differential diagnosis between sarcoma and myoma.

Radiomics is a novel approach that translates medical images into data by extracting a large number of quantitative features describing tissue characteristics, shape and texture, combining quantitative data analysis with biological and clinical endpoint.

Capturing information from imaging that goes beyond the different biomedical imaging formats themselves is the great promise of this growing field.

The application of radiomics analysis to CT with the aim of preoperatively discriminating between sarcoma (malignant) and myoma (benign) could be a valid support in the preoperative evaluation and therapeutic decision-making process in order to personalize the most appropriate therapeutic approach .

Conditions

Uterine Sarcoma; Uterine Myoma

Study Design

• Observational Model Type: COHORT
• Study Time Perspective: RETROSPECTIVE

Eligibility Criteria

Inclusion Criteria

• Histological diagnosis of uterine sarcoma or myoma
• Patients with pre-operative CT performed for diagnostic suspicion no more than 30 days before surgery
• Age between 18 and 80 years
• Patients followed in the clinical care path in our center
• Obtaining informed consent

Exclusion Criteria

• Low quality of CT images.
• Patients affected by other active neoplasms or diagnosed less than 5 years before the diagnosis of uterine sarcoma or myoma.

• Minimum Eligible Age: 18 Years
• Maximum Eligible Age: 80 Years
• Eligible Sex: FEMALE
• Accepts Healthy Volunteers: No

Sponsors

IRCCS Azienda Ospedaliero-Universitaria di Bologna

OTHER

Sponsor Role: lead

Responsible Party

Responsibility Role: SPONSOR

Locations

IRCCS Azienda Ospedaliero-Universitaria

Bologna, Bologna, Italy

Site Status: RECRUITING

Countries

Italy

Central Contacts

Anna Myriam Perrone, MD

Role: CONTACT

myriam.perrone@unibo.it

051 2144368

Facility Contacts

Anna Myriam Perrone, MD

Role: primary

myriam.perrone@unibo.it

051 2144368

Other Identifiers

589/2022/Oss/AOUBo

Identifier Type: -

Identifier Source: org_study_id