title: MDCT-based scoring system for differentiating angiomyolipoma with minimal fat from renal cell carcinoma.
abstract: BACKGROUND
  Subtype-related various computed tomography (CT) features of renal cell carcinoma (RCC) are a confusing factor in differentiating angiomyolipoma with minimal fat (AMLmf) from RCC. To overcome RCC heterogeneity, a scoring system, which integrates multiple discrimitive parameters can be helpful for differentiating AMLmf from RCC.
  
  
  OBJECTIVE
  To develop a MDCT-based scoring system for differentiating AMLmf from RCC.
  
  
  METHODS
  In 407 patients with pathologically confirmed 48 AMLmfs and 359 RCCs (247 clear cell RCCs, 67 papillary RCCs, and 45 chromophobe RCCs), MDCT features (ratio of long-to-short diameter, enhancement characteristics, tumor attenuation on unenhanced scan, tumor margin, calcification), age, and sex were compared between AMLmf and RCCs. Based on logistic regression, a scoring system for diagnosing AMLmf over RCC was built, and its diagnostic accuracy was evaluated.
  
  
  RESULTS
  Scores suggesting AMLmf, i.e. the logit function as used in logistic regression analysis, were calculated as follows: Score = e(6.16.A-0.003.B+1.20.C+0.97.D+2.13.E-0.05.F)/1+e(6.16.A-0.003.B+1.20.C+0.97.D+2.13.E-0.05.F), where A = ratio of long-to-short diameter, B = enhancement amount in early excretory phase, C = homogeneous enhancement, D = tumor attenuation on unenhanced scan, E = sex, and F = age. Area under receiver-operating characteristics curve of scoring system was 0.919. With a score of 0.204 or higher, the scoring system yielded greatest accuracy (90%, 368/407) for diagnosing AMLmf over RCC, which was greater than that of any single MDCT or clinical parameter (53-85%) (P < 0.05). With a score of 0.317 or higher, sensitivity and specificity were 68% (32/48) and 95% (340/359).
  
  
  CONCLUSIONS
  MDCT-based scoring system can improve diagnostic performance of MDCT in differentiating AMLmf from RCC and help patients with AMLmf to avoid unnecessary surgery with high specificity.
authors.affiliation: Department of Radiology, Research Institute of Radiology Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea.
authors.forename: Mi-hyun
authors.initials: MH
authors.lastname: Kim
authors.forename: JungBok
authors.initials: J
authors.lastname: Lee
authors.forename: Gyunggoo
authors.initials: G
authors.lastname: Cho
authors.forename: Kyoung-Sik
authors.initials: KS
authors.lastname: Cho
authors.forename: Jungmi
authors.initials: J
authors.lastname: Kim
authors.forename: Jeong Kon
authors.initials: JK
authors.lastname: Kim
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D018207:Angiomyolipoma / Q000175:diagnosis*; D002292:Carcinoma, Renal Cell / Q000175:diagnosis*; D003937:Diagnosis, Differential; D005260:Female; D006801:Humans; D007680:Kidney Neoplasms / Q000175:diagnosis*; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D061330:Multidetector Computed Tomography; D015999:Multivariate Analysis; D012189:Retrospective Studies; D012680:Sensitivity and Specificity
keywords: Kidney neoplasm; angiomyolipoma; multidetector computed tomography; renal cell carcinoma