Abstract
The authors present their algorithmic approach to the detection, characterization, and staging of renal masses. Based on classification of urographic findings, the patient may be triaged to the appropriate cross-sectional or invasive imaging modality that will result in the most cost-effective management.
MeSH terms
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Abscess / diagnosis
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Adult
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Angiography
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Calcinosis / diagnosis
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Carcinoma, Renal Cell / diagnosis
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Diagnosis, Differential
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Hematuria / etiology
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Humans
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Kidney / abnormalities
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Kidney Diseases / diagnosis*
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Kidney Diseases / diagnostic imaging
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Kidney Diseases, Cystic / diagnosis
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Kidney Neoplasms / diagnosis
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Kidney Neoplasms / secondary
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Kidney Pelvis
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Neoplasm Staging / methods
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Nephritis / etiology
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Polycystic Kidney Diseases / diagnosis
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Pyelonephritis, Xanthogranulomatous / diagnosis
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Tomography, X-Ray Computed
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Ultrasonography
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Wilms Tumor / diagnosis