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

Recruiting
Conditions
Uterine Sarcoma
Uterine Myoma
Registration Number
NCT06805019
Lead Sponsor
IRCCS Azienda Ospedaliero-Universitaria di Bologna
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 .

Detailed Description

Not available

Recruitment & Eligibility

Status
RECRUITING
Sex
Female
Target Recruitment
176
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.

Study & Design

Study Type
OBSERVATIONAL
Study Design
Not specified
Primary Outcome Measures
NameTimeMethod
ROC analysis parameters6 months

Sensitivity, specificity, PPV, NPV, AUC of the classifier (radiomics model) compared to the gold standard (histological report) to discriminate between myoma and sarcoma.

Secondary Outcome Measures
NameTimeMethod
ROC analysis parameters6 months

Sensitivity, specificity, PPV, NPV, AUC of the classifier (radiomics model) to discriminate between aggressive sarcomas that have relapsed and sarcomas that have not relapsed in the first year of follow up.

Trial Locations

Locations (1)

IRCCS Azienda Ospedaliero-Universitaria

🇮🇹

Bologna, Italy

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