Endometrial Cancer, Endometrium Tumor, Uterine Cancer
Conditions
Keywords
radiomics, endometrial cancer, molecular/genetic profiling, radiogenomics, ultrasound
Brief summary
Molecular/genomic profiling is the most accurate method to assess the prognosis of endometrial cancer patients. Interestingly, the adoption of radiomics showed important results, across various oncologic specialties. Radiomic allows extracting mineable high-dimensional data from clinical images, thus providing a number of noteworthy information of the tumor tissues. We aim to correlate radiomic features obtained from ultrasound images with the molecular/genomic profiling to identify new hallmarks for stratification of endometrial cancer patients into different classes of risk The central hypothesis is that combining radiomic features might allow identifying various classes of risk for endometrial cancer. The rationale for the proposed research is that once validated, radiomics applied to ultrasonographic images would be an effective, innovative, and cheap method for tailor operative and postoperative treatment modality in endometrial cancer.
Interventions
DIAGNOSTIC_TESTRadiomics
To correlate radiomic features obtained from ultrasound images with the molecular/genomic profiling to identify new hallmarks for stratification of endometrial cancer patients into different classes of risk
Sponsors
Fondazione IRCCS Istituto Nazionale dei Tumori, Milano
Study design
Allocation
NA
Intervention model
SINGLE_GROUP
Primary purpose
DIAGNOSTIC
Masking
NONE
Eligibility
Sex/Gender
FEMALE
Age
18 Years to No maximum
Healthy volunteers
No
Inclusion criteria
(i) preoperative endometrial cancer (any histology); (ii) preoperative ultrasonographic examination; (iii) surgical treatment; (iv) age \>= 18 years; (v) signed informed consent for research purposes.
Exclusion criteria
(i) consent withdraw; (ii) lack of available (tumor) tissue for molecular/genomic profiling.
Design outcomes
Primary
| Measure | Time frame |
|---|---|
| To detail the mechanism by which radiomic features predict the classification of endometrial cancer into various classes of risk. | 1-18 months |
| Determinate the scaled impact of radiomic features assessed on ultrasonographic images of endometrial tumors. | 1-36 months |
Secondary
| Measure | Time frame |
|---|---|
| Assess the intraobserver and interobserver reproducibility of radiomic features on ultrasonographic images of endometrial tumors | 19-36 months |
Countries
Italy
Outcome results
None listed