Multiparametric MRI for Diagnosing Small Renal Tumors

Renal cell carcinoma represents annually 3-5% of all new cancer diagnoses. In France, its incidence is about 10,000 cases/year. It has been increasing for the past thirty years, probably related to incidental imaging findings. The average age of diagnosis is 65 years. Although the mortality rate started to decrease, partly due to an earlier diagnosis, the overall survival at 5 years is 63% but significantly higher for localized stages (58% of diagnoses): 90%. To date, the standard of care for small renal masses is partial nephrectomy. However, in the specific setting of small renal masses, 20% of them are benign and surgery results in overtreatment. Moreover, for selected patients with comorbidities and potentially low risk tumors, a surveillance strategy can be offered. No preoperative image based tumor characterization has been validated so far, and the kidney tumor biopsy is currently the only way to rule out patients for overtreatment. However, kidney tumor biopsy is invasive, time-consuming, sometimes inconclusive, especially in case of small size tumors, and its low accuracy in predicting tumor aggressiveness based on the Fuhrman grade was several times reported in the literature. Kidney tumor biopsy results may also be impacted by the intra-tumoral heterogeneity. Thus, non-invasive techniques able to differentiate the inherent characteristics of tumors would be useful to offer the most appropriate therapeutic options. Morphological ultrasound or CT imaging appear limited because of the lack of discriminatory power between the different tumor subtypes. Based on the data of retrospective studies, the hypothesis is that MR parameters using chemical shift, diffusion and/or contrast injection techniques may be a reproducible diagnostic test with sufficient diagnostic accuracy to differentiate benign from malignant tumors and better estimate the tumor aggressiveness. To date, no prospective multi-center study on multiparametric (mp) MR imaging of renal tumors has been reported. Although CT-scan explorations are the standard of care in case of renal tumors, MRI offers several advantages over CT including: improved contrast resolution, functional imaging techniques, and the lack of ionizing radiation, which is of particular significance due to growing concerns over cumulative radiation exposure from multi-phase and repeat CT examinations. In particular, the non-ionizing property of MRI may be critical for patients who undergo repeated screening examinations for renal cell carcinoma including those patients under surveillance. By becoming the reference standard for renal mass imaging in clinical practice, multiparametric MRI may help defining the treatment strategy in a non-invasive fashion, resulting in a better selection of patients eligible for nephrectomy, other therapeutic options or surveillance based on tumor aggressiveness estimate, limiting the costs of care and improving patients' quality of life. The originality of this project lies in the opportunity to simultaneously assess the performances of mpMRI in diagnosing renal tumors in a routine clinical practice. In this context, the research will therefore contribute to the development of practical new technologies, strategies and tools for managing renal tumors. MpMRI will be performed in a time-efficient manner and to provide important information that is not available with standard renal MRI or CT-scan. Critical information provided through mpMRI will be used to adjust the therapeutic decision and more adequately select patients eligible for nephrectomy, other therapeutic options or surveillance. Another innovative aspect of the project is to bring together as teamwork several medical disciplines such as radiology, urology, oncology and pathology. The project has been developed and will be conducted within the framework of the French research network on kidney cancer UroCCR (www.uroccr.fr). INCa has been supporting this multidisciplinary network since 2011 and the web-based shared clinical and biological national database on kidney cancer UroCCR will be used.