title: Carotid artery stenosis quantification: concordance analysis between radiologist and semi-automatic computer software by using Multi-Detector-Row CT angiography.
abstract: OBJECTIVE
  Carotid artery stenosis quantification is still considered a leading parameter in the choice of the therapeutic option. Our purpose was to asses the concordance between radiologist and a semi-automatic computer software in the stenosis quantification of carotid artery studied by using a Multi-Detector-Row CT angiography (MDCTA).
  
  
  METHODS
  45 patients studied by using a 40-detector row CT scanner were retrospectively analyzed. Carotid artery stenosis was quantified by one high experienced radiologist in vessel analysis and by using a dedicated software. Carotid artery stenosis was calculated according to the ECST method. Bland-Altman statistics was used to measure the inter- and intra-concordance between radiologist and software and correlation coefficient between measures were performed by using nonparametric Spearmann correlation statistic. A p value<0.05 was considered to mean statistical significance.
  
  
  RESULTS
  A strength correlation according to linear regression (correlation Spearman'ρ coefficient=0.975; p<0.0001) between radiologist and software of vessel analysis was observed. Between first and second stenosis of carotid artery quantification performed by radiologist and software of vessel analysis we observed a Spearman'ρ coefficient=0.943 (p<0.0001) and a Spearman'ρ coefficient=0.9879; (p<0.0001) respectively.
  
  
  CONCLUSIONS
  Our results indicated that there is a strength correlation according to linear regression between stenosis of carotid artery quantification performed by radiologist and semi-automatic software. Reproducibility between measurements performed by semi-automatic software are higher compared to radiologist.
authors.affiliation: Department of Radiology, Policlinico Universitario, A.O.U. Cagliari, s.s. 554 Monserrato, Cagliari 09045, Italy. lucasaba@tiscali.it
authors.forename: Luca
authors.initials: L
authors.lastname: Saba
authors.forename: Roberto
authors.initials: R
authors.lastname: Sanfilippo
authors.forename: Roberto
authors.initials: R
authors.lastname: Montisci
authors.forename: Giancarlo
authors.initials: G
authors.lastname: Calleo
authors.forename: Giorgio
authors.initials: G
authors.lastname: Mallarini
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000792:Angiography / Q000379:methods*; D016893:Carotid Stenosis / Q000000981:diagnostic imaging*; D003287:Contrast Media; D005260:Female; D006801:Humans; D007479:Iopamidol / Q000031:analogs & derivatives; D016014:Linear Models; D008297:Male; D008875:Middle Aged; D011857:Radiographic Image Interpretation, Computer-Assisted; D012189:Retrospective Studies; D012984:Software; D018709:Statistics, Nonparametric; D014057:Tomography, X-Ray Computed / Q000379:methods*
chemical_list: D003287:Contrast Media; C057937:iomeprol; D007479:Iopamidol