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Published in: European Radiology 2/2022

01-02-2022 | Computed Tomography | Oncology

Primary renal sarcomas: imaging features and discrimination from non-sarcoma renal tumors

Authors: Johannes Uhlig, Annemarie Uhlig, Sophie Bachanek, Mehmet Ruhi Onur, Sonja Kinner, Dominik Geisel, Michael Köhler, Heike Preibsch, Michael Puesken, Dominik Schramm, Matthias May, Pieter De Visschere, Marc-André Weber, Alexey Surov

Published in: European Radiology | Issue 2/2022

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Abstract

Objectives

To assess imaging features of primary renal sarcomas in order to better discriminate them from non-sarcoma renal tumors.

Methods

Adult patients diagnosed with renal sarcomas from 1995 to 2018 were included from 11 European tertiary referral centers (Germany, Belgium, Turkey). Renal sarcomas were 1:4 compared to patients with non-sarcoma renal tumors. CT/MRI findings were assessed using 21 predefined imaging features. A random forest model was trained to predict “renal sarcoma vs. non-sarcoma renal tumors” based on demographics and imaging features.

Results

n = 34 renal sarcomas were included and compared to n = 136 non-sarcoma renal tumors. Renal sarcomas manifested in younger patients (median 55 vs. 67 years, p < 0.01) and were more complex (high RENAL score complexity 79.4% vs. 25.7%, p < 0.01). Renal sarcomas were larger (median diameter 108 vs. 43 mm, p < 0.01) with irregular shape and ill-defined margins, and more frequently demonstrated invasion of the renal vein or inferior vena cava, tumor necrosis, direct invasion of adjacent organs, and contact to renal artery or vein, compared to non-sarcoma renal tumors (p < 0.05, each). The random forest algorithm yielded a median AUC = 93.8% to predict renal sarcoma histology, with sensitivity, specificity, and positive predictive value of 90.4%, 76.5%, and 93.9%, respectively. Tumor diameter and RENAL score were the most relevant imaging features for renal sarcoma identification.

Conclusion

Renal sarcomas are rare tumors commonly manifesting as large masses in young patients. A random forest model using demographics and imaging features shows good diagnostic accuracy for discrimination of renal sarcomas from non-sarcoma renal tumors, which might aid in clinical decision-making.

Key Points

Renal sarcomas commonly manifest in younger patients as large, complex renal masses.
Compared to non-sarcoma renal tumors, renal sarcomas more frequently demonstrated invasion of the renal vein or inferior vena cava, tumor necrosis, direct invasion of adjacent organs, and contact to renal artery or vein.
Using demographics and standardized imaging features, a random forest showed excellent diagnostic performance for discrimination of sarcoma vs. non-sarcoma renal tumors (AUC = 93.8%, sensitivity = 90.4%, specificity = 76.5%, and PPV = 93.9%).
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Metadata
Title
Primary renal sarcomas: imaging features and discrimination from non-sarcoma renal tumors
Authors
Johannes Uhlig
Annemarie Uhlig
Sophie Bachanek
Mehmet Ruhi Onur
Sonja Kinner
Dominik Geisel
Michael Köhler
Heike Preibsch
Michael Puesken
Dominik Schramm
Matthias May
Pieter De Visschere
Marc-André Weber
Alexey Surov
Publication date
01-02-2022
Publisher
Springer Berlin Heidelberg
Published in
European Radiology / Issue 2/2022
Print ISSN: 0938-7994
Electronic ISSN: 1432-1084
DOI
https://doi.org/10.1007/s00330-021-08201-4

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