Multimodal imaging to analyze the biomechanical properties of kidney tumors, evaluating feasibility, inter-modality correspondence, and diagnostic value (UroCCR-115).

Abstract

Assessment of renal tissue and renal tumor stiffness may provide complementary information for tissue characterization; however, conventional imaging modalities such as multiphasic computed tomography (CT) do not directly quantify biomechanical properties. Elastography techniques, including magnetic resonance elastography (MRE) and ultrasound elastography (US-E), allow noninvasive measurement of tissue stiffness but are not routinely available in standard clinical practice. This study protocol aims to develop a CT-based stiffness mapping of renal parenchyma and renal tumors by investigating the relationship between CT attenuation values and elastography-derived stiffness measurements, using MRE and US-E as reference modalities. This monocentric, prospective, exploratory, non-randomized, and non-blinded diagnostic study will enroll 50 adults undergoing partial or radical nephrectomy for renal tumors at the University Hospital of Bordeaux. All participants will undergo a predefined multimodal imaging protocol-including contrast-enhanced CT, multiparametric magnetic resonance imaging (MRI) with -MRE and US-E-conducted between inclusion and the day before surgery. The primary objective is to construct a regression model predicting MRE-derived elasticity (μMRE) from CT density values using multiple machine-learning algorithms evaluated through repeated nested cross-validation. Secondary analyses will include voxel-level and region-of-interest correlations across modalities, feasibility and image-quality assessment of DWI-vMRE, repeatability of elastography measurements, identification of limiting factors such as BMI, sarcopenia, lesion location and architecture, evaluation of inter-modality de-correlation and associations with final histopathology (including subtype and grade). ClinicalTrials.gov identifier: NCT06525831. Protocol ID-RCB: 2024-A00959-38. Recruitment began on 7 March 2025.