Key result
CT histogram analysis differentiated angiomyolipoma without visible fat from renal cell carcinoma with an area under the ROC curve of 0.706, yielding 100% specificity and 20% sensitivity.
Why the study?
Does CT histogram analysis differentiate angiomyolipoma without visible fat from renal cell carcinoma in patients with renal masses?
Observational (n=144)
Does CT histogram analysis differentiate angiomyolipoma without visible fat from renal cell carcinoma in patients with renal masses?
Effect estimate: AUC 0.706
p-value: p=<.01
CT histogram analysis of unenhanced images may be a useful non-invasive tool for differentiating angiomyolipoma without visible fat from renal cell carcinoma.
CT histogram analysis offers high specificity but low sensitivity for renal mass differentiation; leaves open its clinical role pending validation.
PURPOSE: To retrospectively evaluate the diagnostic performance of computed tomographic (CT) histogram analysis for differentiating angiomyolipoma (AML) without visible fat from renal cell carcinoma (RCC) at CT, by using pathologic analysis and clinical diagnosis as the reference standard. MATERIALS AND METHODS: This retrospective study was approved by the institutional review board; informed consent was waived. The authors reviewed the medical records of 144 patients with pathologic confirmation of RCC or AML (105 men, 39 women; mean age, 52 years). Analysis of unenhanced CT histograms was performed on 34 AMLs without visible fat at CT and 110 size-matched RCCs. The percentages of voxels and pixels were compared in the two groups according to the CT number categories. The diagnostic performance of CT histogram analysis in differentiating AML from RCC was determined by using receiver operating characteristic (ROC) analysis. RESULTS: The percentages of voxels and pixels with a CT number less than -30 HU (2.7% and 3.4% vs 0.1% and 0.0%), less than -20 HU (4.3% and 5.1% vs 0.2% and 0.1%), less than -10 HU (7.0% and 8.1% vs 0.6% and 0.4%), and less than 0 HU (12.0% and 13.9% vs 2.0% and 2.0%) were significantly greater in the AML group than in the RCC group (P < .01), respectively. The area under the ROC curve was as high as 0.706 when a pixel percentage with a CT number less than -10 HU was used as a differentiating parameter. Corresponding to the specificity of 100% for differentiating AML from RCC, the sensitivity was as high as 20% when a pixel percentage of 6% with a CT number less than -10 HU was used as a criterion. CONCLUSION: CT histogram analysis may be useful for differentiating AML without visible fat from RCC at CT.
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Kim et al. (2007) conducted an observational in Angiomyolipoma without visible fat and renal cell carcinoma (n=144). CT histogram analysis was evaluated on Differentiation of AML from RCC using pixel percentage with CT number < -10 HU (AUC 0.706, p=<.01). CT histogram analysis differentiated angiomyolipoma without visible fat from renal cell carcinoma with an area under the ROC curve of 0.706, yielding 100% specificity and 20% sensitivity.
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