title: [Can the degree of renal artery stenosis be automatically quantified?].
abstract: The objective of the reported study is to validate a computer system, QUASAR, dedicated to the quantification of renal artery stenoses. This system estimates automatically the reference diameter and calculates the minimum diameter to compute a degree of stenosis. A hundred and eighty images of atheromatous stenoses between 10% and 80% were collected from two French independent protocols. For the 49 images of the EMMA protocol, the results from QUASAR were compared with the visual estimation of an initial investigator and with the results from a reference method based on a panel of fixe experienced experts. For the 131 images of the ASTARTE protocol, the results from QUASAR were compared with those from a semi-automatic quantification system and with those from a system based on densitometric analysis. The present work validates QUASAR in a population of narrow atheromatous stenoses (> 50%). In the context of the EMMA protocol, QUASAR is not significantly different from the mean of the fixe experts. It is unbiased and more precise than the estimation of a single investigator. In the context of the ASTARTE protocol, there is no significant difference between the three methods for the stenoses higher than 50%, however, globally, QUASAR surestimates significantly (up to 10%) the degree of stenosis.
authors.affiliation: Service d'informatique médicale et d'hypertension artérielle, hôpital Broussais, Paris.
authors.forename: I
authors.initials: I
authors.lastname: Cherrak
authors.forename: M C
authors.initials: MC
authors.lastname: Jaulent
authors.forename: M
authors.initials: M
authors.lastname: Azizi
authors.forename: P F
authors.initials: PF
authors.lastname: Plouin
authors.forename: P
authors.initials: P
authors.lastname: Degoulet
authors.forename: G
authors.initials: G
authors.lastname: Chatellier
mesh_terms: D000368:Aged; D000792:Angiography; D001161:Arteriosclerosis / Q000175:diagnosis / Q000000981:diagnostic imaging; D003199:Computer Systems; D016001:Confidence Intervals; D003720:Densitometry; D003936:Diagnosis, Computer-Assisted / Q000379:methods; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods; D015588:Observer Variation; D019047:Phantoms, Imaging; D012077:Renal Artery / Q000000981:diagnostic imaging; D012078:Renal Artery Obstruction / Q000175:diagnosis* / Q000000981:diagnostic imaging; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity