title: Differentiation of benign and malignant parotid tumors using deconvolution-based perfusion CT imaging: feasibility of the method and initial results.
abstract: OBJECTIVE
  We evaluated the feasibility of perfusion CT (CTP) of the parotid gland and attempted to differentiate benign from malignant tumors.
  
  
  METHODS
  CTP was performed in 17 patients with benign tumors and 10 patients with malignant parotid tumors. Data were postprocessed by using deconvolution-based perfusion analysis. Postprocessing-generated maps showed blood flow (BF), blood volume (BV), mean transit time (MTT), and capillary permeability surface product (PS). Regions of interest were placed through the tumor site and the contralateral healthy parotid tissue. Ratios of the perfusion values between the tumors and the contralateral healthy structures were also calculated. Pearson correlation coefficients were determined to compare the agreement between the two readers.
  
  
  RESULTS
  Perfusion maps of all tumors were successfully obtained. High Pearson correlation coefficients comparing the two readers' visually measured abnormalities were observed (r=0.79-0.86, P=0.001) for all perfusion maps, The MTT and PS values between malignant and benign tumors were not significantly different. The BF and BV values were statistically significant different between the benign and malignant tumors (0.00<P<0.02). Only the BV ratio criterion between malignant and benign neoplasms was statistically significant (P<0.004).
  
  
  CONCLUSIONS
  CTP of the parotid gland is feasible and may differentiate malignant from non-malignant lesions by means of absolute BF, BV and BV ratio values.
authors.affiliation: Department of Diagnostic and Interventional Radiology, Johann Wolfgang Goethe University Hospital, Frankfurt, Germany. sbisdas@yahoo.com
authors.forename: S
authors.initials: S
authors.lastname: Bisdas
authors.forename: M
authors.initials: M
authors.lastname: Baghi
authors.forename: J
authors.initials: J
authors.lastname: Wagenblast
authors.forename: R
authors.initials: R
authors.lastname: Knecht
authors.forename: C H
authors.initials: CH
authors.lastname: Thng
authors.forename: T S
authors.initials: TS
authors.lastname: Koh
authors.forename: T J
authors.initials: TJ
authors.lastname: Vogl
mesh_terms: D000230:Adenocarcinoma / Q000000981:diagnostic imaging; D000235:Adenolymphoma / Q000000981:diagnostic imaging; D008949:Adenoma, Pleomorphic / Q000000981:diagnostic imaging; D000368:Aged; D001810:Blood Volume / Q000502:physiology; D002199:Capillary Permeability / Q000502:physiology; D003528:Carcinoma, Adenoid Cystic / Q000000981:diagnostic imaging; D003287:Contrast Media; D003937:Diagnosis, Differential; D005240:Feasibility Studies; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D007479:Iopamidol / Q000031:analogs & derivatives; D008297:Male; D008875:Middle Aged; D010306:Parotid Gland / Q000098:blood supply / Q000000981:diagnostic imaging; D010307:Parotid Neoplasms / Q000098:blood supply / Q000000981:diagnostic imaging* / Q000503:physiopathology; D011856:Radiographic Image Enhancement / Q000379:methods; D012039:Regional Blood Flow / Q000502:physiology; D013997:Time Factors; D014057:Tomography, X-Ray Computed / Q000379:methods*
chemical_list: D003287:Contrast Media; C057937:iomeprol; D007479:Iopamidol