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World Journal of Urology

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01.06.2010 | Topic Paper

Imaging of advanced renal cell carcinoma

verfasst von: Ullrich G. Mueller-Lisse, Ulrike L. Mueller-Lisse

Erschienen in: World Journal of Urology | Ausgabe 3/2010

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Abstract

Objectives

To describe current radiological cross-sectional imaging in the detection and staging of advanced renal cell carcinoma (RCC), defined here as RCC reaching beyond the renal capsule, whether by immediate extension or by metastasis.

Methods

Review and summary of current radiological and urological literature, including original articles and reviews, retrieved from the medical data base “PubMed”.

Results

Multi-detector-row computed tomography (MDCT) shows a sensitivity of up to 100% and specificity of about 90% for retroperitoneal disease, venous tumour thrombus, and metastasis, but limited accuracy for lymphadenopathy in RCC. Magnetic resonance imaging (MRI) is applied as a problem-solving modality, with particular strength in imaging metastasis to brain and bone. However, dynamic, contrast-enhanced- (DCE-) and arterial-spin-labelling (ASL-) MRI may help to monitor early response to angiogenesis inhibitor drugs. Ultrasonography (US) shows limited capability of identifying retroperitoneal disease, venous tumour thrombus extension, and metastasis. Positron Emission Tomography with 18-fluoro-desoxy-glucose (FDG-PET) demonstrates modest accuracy for metastasis of RCC, with positive studies being suspicious, while negative studies cannot reliably exclude disease.

Conclusions

MDCT represents the diagnostic mainstay for the detection and staging of RCC. In the wake of new systemic therapies for advanced RCC, including angiogenesis inhibitor drugs, monitoring treatment response may become a new task for cross-sectional imaging.

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Titel: Imaging of advanced renal cell carcinoma
verfasst von: Ullrich G. Mueller-Lisse
Ulrike L. Mueller-Lisse
Publikationsdatum: 01.06.2010
Verlag: Springer-Verlag
Erschienen in: World Journal of Urology / Ausgabe 3/2010
Print ISSN: 0724-4983
Elektronische ISSN: 1433-8726
DOI: https://doi.org/10.1007/s00345-010-0557-z

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