title: Perfusion CT can predict tumoral grading of pancreatic adenocarcinoma.
abstract: OBJECTIVE
  To describe perfusion CT features of locally advanced pancreatic ductal adenocarcinoma and to evaluate correlation with tumor grading.
  
  
  METHODS
  Thirty-two patients with locally advanced pancreatic adenocarcinoma were included in this study. Lesions were evaluated by P-CT and biopsy after patient's informed consent. P-CT parameters have been assessed on a large single and on 6 small intratumoral ROIs. Values obtained have been compared and related to the tumor grading using Mann-Whitney U test. Sensibility, specificity, positive predictive value (PPV), negative predictive value (NPV) and accuracy in predicting tumor grading have been calculated for cut-off values chosen by using ROC curves.
  
  
  RESULTS
  Out of 32 lesions, 12 were classified as low grade and 20 as high grade. A statistically significant difference between high and low grade neoplasms were demonstrated for PEI and BV parameters. PEI and BV cut-off values were respectively 17.8 HU and 14.8 ml/100g. PEI identified high grade neoplasms with a 65% sensitivity, 92% specificity, 93% PPV, 61% NPV and 75% accuracy. BV identified high grade neoplasms with a 80% sensitivity, 75% specificity, 84% PPV, 69% NPV, 78% accuracy. Considering both PEI and BV, P-CT identified high grade lesions with a 60% sensitivity, 100% specificity, 100% PPV, 60% NPV and 75% accuracy.
  
  
  CONCLUSIONS
  PEI and BV perfusion CT parameters proved their efficiency in identifying high grade pancreatic adenocarcinoma.
authors.affiliation: Department of Radiology, University Hospital G.B. Rossi Piazzale L.A. Scuro 10, 37134 University of Verona, Verona, Italy. mirko.donofrio@univr.it
authors.forename: M
authors.initials: M
authors.lastname: D'Onofrio
authors.forename: A
authors.initials: A
authors.lastname: Gallotti
authors.forename: W
authors.initials: W
authors.lastname: Mantovani
authors.forename: S
authors.initials: S
authors.lastname: Crosara
authors.forename: E
authors.initials: E
authors.lastname: Manfrin
authors.forename: M
authors.initials: M
authors.lastname: Falconi
authors.forename: A
authors.initials: A
authors.lastname: Ventriglia
authors.forename: G A
authors.initials: GA
authors.lastname: Zamboni
authors.forename: R
authors.initials: R
authors.lastname: Manfredi
authors.forename: R
authors.initials: R
authors.lastname: Pozzi Mucelli
mesh_terms: D000230:Adenocarcinoma / Q000000981:diagnostic imaging / Q000473:pathology*; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000465:Algorithms; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D060787:Neoplasm Grading; D010190:Pancreatic Neoplasms / Q000000981:diagnostic imaging / Q000473:pathology*; D055420:Perfusion Imaging / Q000379:methods*; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D014057:Tomography, X-Ray Computed / Q000379:methods*