Diffusion MRI (Magnetic Resonance Imaging) Using ADC (Apparent Diffusion Coefficient) Histograms in the Evaluation of Adnexal Tumor Aggressiveness

2016-04-19 17:53:21 | BioPortfolio


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.

Study Design

Observational Model: Case-Only, Time Perspective: Retrospective


Adnexal Tumor


Correlation of MRI results with clinical characteristics of the adnexal mass


CHU Brugmann


Not yet recruiting


Brugmann University Hospital

Results (where available)

View Results


Published on BioPortfolio: 2016-04-19T17:53:21-0400

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