title: Application of CT perfusion imaging to the histological differentiation of adrenal gland tumors.
abstract: BACKGROUND
  CT perfusion imaging has been used in diagnosis and classification of tumors widely and in assess tumor angiogenesis in some organs. However, there are few reports describing CT perfusion imaging of adrenal gland tumors.
  
  
  OBJECTIVE
  This study aimed to evaluate the application of CT perfusion imaging in analysis of angiogenesis in adrenal tumors and in diagnosis of adrenal tumors.
  
  
  METHODS
  Forty four patients with adrenal gland tumors (26 with adenomas and 18 with nonadenomas) were enrolled in this study. CT scan of adrenal glands was performed with the perfusion of non-ionic contrast medium Ultravist. The obtained images were processed with deconvolution algorithms-based perfusion software and then perfusion parameter maps and values (blood flow, blood volume, mean transit time, and permeability surface-area production) were generated and analyzed respectively.
  
  
  RESULTS
  Univariate multivariate logistic regression indicated that blood volume (OR: 1.261, 95% CI: 1.056, 1.505, P=0.010) was associated with the likelihood of adrenal adenoma. Receiver operating characteristic analysis showed that the blood volume value of ≥9.325 ml min(-1) 100 g(-1) predicted adrenal adenoma with sensitivity of 76.9% and specificity of 73.2%. In addition, permeability surface-area production in adenoma was higher than in non-adenoma (27.11±15.45 vs. 16.76±14.44 ml min(-1) 100 g(-1), P<0.05). The other parameters had no clear prognostic significance.
  
  
  CONCLUSIONS
  CT perfusion imaging can quantitatively distinguish adrenal gland tumors with different histological characteristics. Especially, blood volume can be used in differentiating adrenal adenomas from nonadenomas.
authors.affiliation: Department of Imaging, The Fourth Affiliated Hospital, Harbin Medical University, Harbin 150001, China.
authors.forename: Hai-yan
authors.initials: HY
authors.lastname: Qin
authors.forename: Hao-ran
authors.initials: HR
authors.lastname: Sun
authors.forename: Ya-jun
authors.initials: YJ
authors.lastname: Li
authors.forename: Bao-zhong
authors.initials: BZ
authors.lastname: Shen
mesh_terms: D000236:Adenoma / Q000000981:diagnostic imaging* / Q000473:pathology; D000310:Adrenal Gland Neoplasms / Q000000981:diagnostic imaging* / Q000473:pathology; D000465:Algorithms; D001810:Blood Volume; D003287:Contrast Media; D003937:Diagnosis, Differential; D005260:Female; D006801:Humans; D007472:Iohexol / Q000031:analogs & derivatives; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D009389:Neovascularization, Pathologic / Q000000981:diagnostic imaging* / Q000473:pathology; D012372:ROC Curve; D011857:Radiographic Image Interpretation, Computer-Assisted; D012680:Sensitivity and Specificity; D012984:Software; D014057:Tomography, X-Ray Computed / Q000379:methods*
chemical_list: D003287:Contrast Media; D007472:Iohexol; C038192:iopromide