Adnexal Tumor Clinical Trial
Official title:
Diffusion Magnetic Resonance Imaging Using ADC (Apparent Diffusion Coefficient) Histograms in the Evaluation of Adnexal Tumor Aggressiveness
Diffusion-weighted sequences have been routinely performed for years to study the pelvis.
They have been so far mainly qualitatively interpreted, that is to say as the absence or
presence of an hypersignal at a high b value. The quantitative analysis involves placing the
region of interest (ROI) on the apparent diffusion coefficient (ADC) map. The manual
placement is very operator dependent, and does not reflect the entirety of the studied mass.
In all fields of Magnetic Resonance Imaging, a multiparametric approach integrating diffusion
analysis is flourishing. However, the quantitative analysis of the diffusion is still little
studied for tumor heterogeneity analysis, including in the gynecological sphere.
The investigators will therefore retrospectively evaluate the apparent diffusion coefficient
(ADC) histograms, extracted from the diffusion ponderation sequences, of the magnetic imaging
resonance analysis of adnexal masses and confront the results with the anatomo-pathology
results, for patients having undergone surgery, and/or with the clinical and imagery
follow-up results.
The investigators goal will be to improve the performance of conventional MRI in the analysis
of adnexal masses.
The expected benefits of this study are:
- a correlation with the histology analysis or the clinical monitoring
- an improved prediction of the malignancy of the tumor
- an improved magnetic resonance imaging performance for adnexal masses, with better
surgical therapeutic management
- an improved negative predictive value, thereby ultimately limiting unnecessary surgical
explorations.
n/a
| Status | Clinical Trial | Phase | |
|---|---|---|---|
| Recruiting |
NCT05974618 -
Prospective Validation of the ADNEX Model for Discrimination Between Benign and Malignant Adnexal Masses in Pregnancy: International Ovarian Tumour Analysis in Pregnancy Study (p-IOTA)
|