title: Histogram analysis of small solid renal masses: differentiating minimal fat angiomyolipoma from renal cell carcinoma.
abstract: OBJECTIVE
  The objective of our study was to retrospectively determine whether minimal fat renal angiomyolipoma can be differentiated from clear cell or papillary renal cell carcinoma (RCC) in small renal masses using attenuation measurement histogram analysis on unenhanced CT.
  
  
  METHODS
  Twenty minimal fat renal angiomyolipomas were compared with 22 clear cell RCCs and 23 papillary RCCs using an institutional database. All masses were histologically confirmed and all minimal fat renal angiomyolipomas lacked radiographic evidence of macroscopic fat. Using attenuation measurement histogram analysis, two blinded radiologists determined the percentage of negative pixels within each renal mass. The percentages of negative pixels below attenuation thresholds of 0, -5, -10, -15, -20, -25, and -30 HU were recorded. Sensitivity, specificity, positive predictive value, negative predictive value, and receiver operator characteristic curves for the diagnosis of minimal fat renal angiomyolipoma were generated for each threshold. The Student t test was used to compare radiologists and cohorts. Previously published attenuation and pixel-counting thresholds reported as having a specificity of near 100% for discriminating between minimal fat renal angiomyolipomas and RCCs were analyzed.
  
  
  RESULTS
  The mean maximal transverse lesion diameter was 1.8 cm for minimal fat renal angiomyolipomas (SD, 0.5 cm; range, 1.1-3.0 cm), 2.1 cm for clear cell RCCs (SD, 0.5 cm; range, 1.0-2.9 cm), and 2.1 cm for papillary RCCs (SD, 0.7 cm; range, 1.3-3.9 cm). No significant difference in the percentage of negative pixels was found between minimal fat renal angiomyolipomas and clear cell RCCs or between minimal fat renal angiomyolipomas and papillary RCCs at any of the selected attenuation thresholds for either radiologist (p = 0.210-0.499). Radiologist 1 and radiologist 2 used significantly different region-of-interest sizes (p < 0.001), but neither radiologist could differentiate minimal fat renal angiomyolipoma from RCC. No previously published threshold allowed discrimination between minimal fat renal angiomyolipoma and RCC with 100% specificity.
  
  
  CONCLUSIONS
  Attenuation measurement histogram analysis cannot reliably differentiate minimal fat renal angiomyolipoma from RCC.
authors.affiliation: Department of Radiology, Division of Abdominal Imaging, Duke University Medical Center, Durham, NC, USA. hchaudry27@gmail.com
authors.forename: Humaira S
authors.initials: HS
authors.lastname: Chaudhry
authors.forename: Matthew S
authors.initials: MS
authors.lastname: Davenport
authors.forename: Christopher M
authors.initials: CM
authors.lastname: Nieman
authors.forename: Lisa M
authors.initials: LM
authors.lastname: Ho
authors.forename: Amy M
authors.initials: AM
authors.lastname: Neville
mesh_terms: D000328:Adult; D000368:Aged; D018207:Angiomyolipoma / Q000000981:diagnostic imaging* / Q000473:pathology; D002292:Carcinoma, Renal Cell / Q000000981:diagnostic imaging* / Q000473:pathology; D003937:Diagnosis, Differential; D005260:Female; D006801:Humans; D007680:Kidney Neoplasms / Q000000981:diagnostic imaging* / Q000473:pathology; D008297:Male; D008875:Middle Aged; D011237:Predictive Value of Tests; D011857:Radiographic Image Interpretation, Computer-Assisted; D012189:Retrospective Studies; D012680:Sensitivity and Specificity; D014057:Tomography, X-Ray Computed