title: Textural differences in apparent diffusion coefficient between low- and high-stage clear cell renal cell carcinoma.
abstract: OBJECTIVE
  The purpose of this article is to evaluate differences in texture measures on apparent diffusion coefficient (ADC) maps between low- and high-stage clear cell renal cell carcinomas (RCCs).
  
  
  METHODS
  In this retrospective study, 61 patients with clear cell RCC at pathologic examination and who underwent preoperative MRI with diffusion-weighted imaging were included. Clear cell RCCs were clinically staged on review of preoperative MRI by a board-certified radiologist blinded to the pathologic findings. Whole lesions were segmented on ADC maps by two readers independently, from which first-order texture features (i.e., mean and skewness) and second-order texture features (i.e., cooccurrence matrix measures) were calculated. Texture metrics were compared between low- and high-stage clear cell RCC.
  
  
  RESULTS
  In 61 patients, there were 62 clear cell RCCs (33 low stage [stages I and II] and 29 high stage [stages III and IV]) at pathologic examination. Staging accuracy of qualitative interpretation was 100% for low-stage lesions and 37.9% (11/29) for high-stage lesions. There was no statistically significant difference in mean ADC between high- and low-stage clear cell RCCs (1.77×10(-3) vs 1.80×10(-3) mm2/s; p=0.7). However, high-stage clear cell RCCs were larger (6.96±2.93 vs 3.49±1.57 cm; p<0.0001) and had statistically significantly (p≤0.0001) higher ADC skewness (0.02±0.33 vs -0.52±0.65) and cooccurrence matrix correlation (0.64±0.11 vs 0.49±0.13). Multivariate logistic regression identified size, skewness, and cooccurrence matrix correlation as significant independent predictors of high stage (AUC=0.92). Interreader correlation in texture metrics ranged from 0.82 to 0.89.
  
  
  CONCLUSIONS
  First- and second-order ADC texture metrics differ between low- and high-stage clear cell RCCs. A model that includes size and ADC texture measures may help to stage clear cell RCCs noninvasively.
authors.affiliation: 1 Department of Radiology, New York University Langone Medical Center, New York, NY.
authors.forename: Andrea S
authors.initials: AS
authors.lastname: Kierans
authors.forename: Henry
authors.initials: H
authors.lastname: Rusinek
authors.forename: Andrew
authors.initials: A
authors.lastname: Lee
authors.forename: Mohammed B
authors.initials: MB
authors.lastname: Shaikh
authors.forename: Michael
authors.initials: M
authors.lastname: Triolo
authors.forename: William C
authors.initials: WC
authors.lastname: Huang
authors.forename: Hersh
authors.initials: H
authors.lastname: Chandarana
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000465:Algorithms; D002292:Carcinoma, Renal Cell / Q000473:pathology*; D038524:Diffusion Magnetic Resonance Imaging / Q000379:methods*; D005260:Female; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D007680:Kidney Neoplasms / Q000473:pathology*; D008297:Male; D008875:Middle Aged; D009367:Neoplasm Staging; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity
keywords: clear cell renal cell carcinoma; diffusion-weighted imaging; renal cell carcinoma; texture analysis