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Angiomyolipoma with minimal fat on MDCT: can counts of negative-attenuation pixels aid diagnosis?
Claus Simpfendorfer1, Brian R Herts, Gaspar A Motta-Ramirez
1Section of Abdominal Imaging, Imaging Institute, Desk Hb6, Cleveland Clinic, Cleveland, OH 44195, USA.
Objective:
The purpose of this study was to determine whether counts of pixels with subzero attenuation on CT scans can aid in the diagnosis of renal angiomyolipoma with minimal fat.
Materials And Methods:
Of 33 angiomyolipomas identified among 719 renal masses resected from 702 patients over 4 years, 15 masses in 15 patients were prospectively diagnosed on the basis of the presence of fat at MDCT. The 18 patients with minimal-fat angiomyolipoma and a matched (age, sex, tumor size) cohort of patients with renal cell carcinoma were included in this study. Three radiologists independently counted the number of pixels with attenuation less than -10, -20, and -30 HU. Receiver operating characteristic analysis of the number of pixels at each cutoff was used to calculate sensitivity, specificity, and positive predictive value with the following criteria: 1, more than 10 pixels less than -20 HU; 2, more than 20 pixels less than -20 HU; 3, more than 5 pixels less than -30 HU.
Results:
Using criterion 1, reader A identified six angiomyolipomas; reader B, five; and reader C, two. The combined sensitivity was 24%; specificity, 98%; and positive predictive value, 69%. Using criterion 2, reader A identified three angiomyolipomas; reader B, four; and reader C, two. The combined sensitivity was 17%; specificity, 100%; and positive predictive value, 100%. Using criterion 3, reader A identified four angiomyolipomas; reader B, four; and reader C, two. The combined sensitivity was 18%; specificity, 100%; and positive predictive value, 100%.
Conclusion:
CT findings of more than 20 pixels with attenuation less than -20 HU and more than 5 pixels with attenuation less than -30 HU have a positive predictive value of 100% in detection of angiomyolipoma, but most angiomyolipomas with minimal fat cannot be reliably identified on the basis of an absolute pixel count.
Insights
Pixel counts on CT scans show promise for diagnosing minimal-fat renal angiomyolipomas, but most cases remain challenging. Specific criteria offer high positive predictive value but limited sensitivity for detecting these tumors.
Area of Science:
- Radiology
- Oncology
- Medical Imaging
Background:
- Renal angiomyolipomas (AMLs) are benign tumors often containing fat.
- Diagnosing AMLs with minimal fat can be challenging using standard CT imaging.
- Accurate differentiation of AMLs from other renal masses is crucial for appropriate patient management.
Purpose of the Study:
- To evaluate the utility of subzero pixel attenuation counts on CT scans for diagnosing renal angiomyolipomas with minimal fat.
- To determine if specific pixel count thresholds can aid in differentiating minimal-fat AMLs from renal cell carcinoma.
Main Methods:
- Retrospective analysis of 18 minimal-fat AMLs and matched renal cell carcinoma cases.
- Three radiologists independently quantified pixels with attenuation < -10, -20, and -30 HU.
- Receiver operating characteristic (ROC) analysis was performed to assess diagnostic performance.
Main Results:
- Using criterion of >20 pixels with attenuation < -20 HU, specificity was 100% and PPV was 100%.
- Using criterion of >5 pixels with attenuation < -30 HU, specificity was 100% and PPV was 100%.
- Combined sensitivity for detecting minimal-fat AMLs was low across all tested criteria (17-24%).
Conclusions:
- Specific CT criteria (e.g., >20 pixels < -20 HU, >5 pixels < -30 HU) demonstrate 100% positive predictive value for AML detection.
- However, absolute pixel counts are not reliable for identifying most minimal-fat angiomyolipomas due to low sensitivity.
- Further research may be needed to improve CT-based diagnosis of minimal-fat renal AMLs.
