title: Multiparametric MR imaging of sinonasal diseases: time-signal intensity curve- and apparent diffusion coefficient-based differentiation between benign and malignant lesions.
abstract: OBJECTIVE
  The sinonasal region is a platform for a broad spectrum of benign and malignant diseases, and image-based differentiation between benign and malignant diseases in this area is often difficult. Here, we evaluated multiparametric MR imaging with combined use of TICs and ADCs for the differentiation between benign and malignant sinonasal tumors and tumorlike diseases.
  
  
  METHODS
  TICs obtained from dynamic contrast-enhanced MR imaging and ADCs were analyzed on a lesion-by-lesion (overall TIC and ADC) and pixel-by-pixel (TIC and ADC mapping) basis in patients with benign (n = 21) or malignant (n = 23) sinonasal tumors and tumorlike diseases. The TICs were semiautomatically classified into 5 distinctive patterns (flat, slow uptake, rapid uptake with low washout ratio, rapid uptake with high washout ratio, and miscellaneous). ADCs were determined by using b-values of 500 and 1000 s/mm(2).
  
  
  RESULTS
  Malignant sinonasal tumors had small (<25%) areas of the type 1 flat TIC profile as determined by pixel-by-pixel TIC analysis and large (≥50%) areas of low or extremely low ADCs (≤1.2 × 10(-3) mm(2/)s) as determined by ADC mapping. Consequently, stepwise classification on the basis of TICs and ADCs successfully (at 100% accuracy) discriminated malignant from benign sinonasal diseases in the present patient cohort.
  
  
  CONCLUSIONS
  Multiparametric MR imaging by using TICs and ADCs may help differentiate benign and malignant sinonasal diseases.
authors.affiliation: Department of Radiology and Cancer Biology, Nagasaki University School of Dentistry, Nagasaki, Japan.
authors.forename: M
authors.initials: M
authors.lastname: Sasaki
authors.forename: M
authors.initials: M
authors.lastname: Sumi
authors.forename: S
authors.initials: S
authors.lastname: Eida
authors.forename: Y
authors.initials: Y
authors.lastname: Ichikawa
authors.forename: T
authors.initials: T
authors.lastname: Sumi
authors.forename: T
authors.initials: T
authors.lastname: Yamada
authors.forename: T
authors.initials: T
authors.lastname: Nakamura
mesh_terms: D000465:Algorithms; D003937:Diagnosis, Differential; D038524:Diffusion Magnetic Resonance Imaging / Q000379:methods*; D005260:Female; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008297:Male; D008875:Middle Aged; D010255:Paranasal Sinus Neoplasms / Q000473:pathology*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity