title: Evaluation of perirenal fat as a predictor of cT 1a renal cortical neoplasm histopathology and surgical outcomes.
abstract: OBJECTIVE
  With the increasing detection of small renal cortical neoplasms (RCNs), the preoperative prediction of histopathology has become increasingly important. Because perirenal fat (PF) is known to be metabolically active, we evaluated PF as a predictor of renal tumor histopathology.
  
  
  METHODS
  We retrospectively evaluated patients who underwent laparoscopic nephron-sparing procedures for cT(1a) RCN at two institutions. PF was measured using the digital measuring tool function on standard imaging software, at the level of the renal hilum as the perpendicular distance between the posterior surface of the kidney and the external margin of the psoas muscle. The Mann-Whitney test and logistic regression were used to examine PF, selected demographic, clinical, and operative parameters, and their association with tumor histopathology.
  
  
  RESULTS
  Data from 250 patients were included in this study. There were 157 (63%) men and 93 (37%) women with a median body mass index (BMI) of 28 kg/m(2). Median tumor size was 2.4 cm, and the median PF distance was 12 mm. Significant correlations were noted between PF and sex and BMI. No significant correlations were found between PF and the operative parameters. Results of a multivariate logistic regression analysis revealed that PF (P<0.01), age (P<0.04), and tumor location (P<0.04) were significant predictors of clear-cell renal-cell carcinoma (RCC) histopathology.
  
  
  CONCLUSIONS
  In this study, PF, location of tumor, and age were significant predictors of clear-cell RCC histopathology. The correlation of PF and histopathology may be useful in preoperative decision-making and surgical planning in the management of small RCN.
authors.affiliation: The Smith Institute for Urology, North Shore Long Island Jewish Health System, New Hyde Park, New York, USA.
authors.forename: Zhamshid
authors.initials: Z
authors.lastname: Okhunov
authors.forename: Adam C
authors.initials: AC
authors.lastname: Mues
authors.forename: Myriam
authors.initials: M
authors.lastname: Kline
authors.forename: Georgios
authors.initials: G
authors.lastname: Haramis
authors.forename: Bin
authors.initials: B
authors.lastname: Xu
authors.forename: Gabriella
authors.initials: G
authors.lastname: Mirabile
authors.forename: Manish
authors.initials: M
authors.lastname: Vira
authors.forename: Jaime
authors.initials: J
authors.lastname: Landman
mesh_terms: D000273:Adipose Tissue / Q000473:pathology*; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D005260:Female; D006801:Humans; D007680:Kidney Neoplasms / Q000000981:diagnostic imaging / Q000473:pathology* / Q000601:surgery*; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D009367:Neoplasm Staging; D011300:Preoperative Care; D011379:Prognosis; D014057:Tomography, X-Ray Computed; D016896:Treatment Outcome; D055815:Young Adult