title: A comparison between NASCET and ECST methods in the study of carotids: evaluation using Multi-Detector-Row CT angiography.
abstract: OBJECTIVE
  NASCET and ECST systems to quantify carotid artery stenosis use percent diameter ratios from conventional angiography. With the use of Multi-Detector-Row CT scanners it is possible to easily measure plaque area and residual lumen in order to calculate carotid stenosis degree. Our purpose was to compare NASCET and ECST techniques in the measurement of carotid stenosis degree by using MDCTA.
  
  
  METHODS
  From February 2007 to October 2007, 83 non-consecutive patients (68 males; 15 females) were studied using Multi-Detector-Row CT. Each patient was assessed by two experienced radiologists for stenosis degree by using both NASCET and ECST methods. Statistic analysis was performed to determine the entity of correlation (method of Pearson) between NASCET and ECST. The Cohen kappa test and Bland-Altman analysis were applied to assess the level of inter- and intra-observer agreement.
  
  
  RESULTS
  The correlation Pearson coefficient between NASCET and ECST was 0.962 (p<0.01). Intra-observer agreement in the NASCET evaluation, by using Cohen statistic was 0.844 and 0.825. Intra-observer agreement in the ECST evaluation was 0.871 and 0.836. Inter-observer agreement in the NASCET and ECTS were 0.822 and 0.834, respectively. Agreement analysis by using Bland-Altman plots showed a good intra-\inter-observer agreement for the NASCET and an optimal intra-\inter-observer agreement for the ECST.
  
  
  CONCLUSIONS
  Results of our study suggest that NASCET and ECST methods show a strength correlation according to quadratic regression. Intra-observer agreement results high for both NASCET and ECST.
authors.affiliation: Department of Science of the Images, Azienda Ospedaliero Universitaria di Cagliari, Monserrato (Cagliari), Italy. lucasaba@tiscali.it
authors.forename: Luca
authors.initials: L
authors.lastname: Saba
authors.forename: Giorgio
authors.initials: G
authors.lastname: Mallarini
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D000792:Angiography; D016893:Carotid Stenosis / Q000000981:diagnostic imaging* / Q000473:pathology; D002986:Clinical Trials as Topic; D003287:Contrast Media; D005260:Female; D006801:Humans; D007472:Iohexol / Q000031:analogs & derivatives; D008297:Male; D008875:Middle Aged; D011857:Radiographic Image Interpretation, Computer-Assisted; D012044:Regression Analysis; D012189:Retrospective Studies; D012720:Severity of Illness Index; D018709:Statistics, Nonparametric; D014057:Tomography, X-Ray Computed / Q000379:methods*
chemical_list: D003287:Contrast Media; D007472:Iohexol; C038192:iopromide