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The goal of this innovative project is to evaluate the correspondence between several imaging modalities for characterizing the elasticity of healthy and pathological renal tissue which could help improve the realism of 3D prints used by urological surgeons and allow the identification of new, complementary imaging biomarkers. The main objective is to develop a predictive model of the biomechanical properties of normal and pathological kidney tissue, as assessed by the reference method (Magnetic Resonance (MR)-elastography).
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Medical imaging plays a key role in the diagnostic and therapeutic management of renal cell carcinomas. It can be used to confirm the presence of a tumor, localize it, suggest malignancy or even histological subtype, guide sampling, perform TNM staging, assist in surgical scheduling, monitor therapeutic efficacy in the event of systemic treatment, guide ablathermy procedures and look for relapses after curative treatments have ended. Imaging of kidney tumors relies on three complementary imaging modalities: ultrasound (US), Computed Tomography based on X-ray absorption (CT-scan) and magnetic resonance imaging (MRI). The most commonly performed examination remains the CT scan, which is used to print 3D models. However, the correlation between renal parenchyma densities and renal tumors (before and during the scan acquisition times after injection) and elasticity parameters measured by US and MRI has never been explored.
This trial aim to evaluate the correspondence between several imaging modalities for characterizing the elasticity of healthy and pathological kidney tissue. It will also improve the realism of 3D models used by surgeons, and identify new complementary imaging biomarkers.
To achieve this aim, 50 patients will undergo DWI -elastography (Diffusion Weigthed Imaging-elastography) and MR-elastography sequences, as well as an US before the surgery. After surgery, a fragment of the resected specimen will be used to perform mechanical tests to determine the real hardness of the tissue.
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50 participants in 1 patient group
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JAMBON EVA, Dr
Data sourced from clinicaltrials.gov
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