Stenosis quantification from post-stenotic signal loss in phase-contrast MRA datasets of flow phantoms and renal arteries.
In this study a semi-automated and observer-independent algorithm for quantifying post-stenotic signal loss (PSL) in 3D phase-contrast (PC) magnetic resonance angiography (MRA) of patients with renal artery stenosis is presented. This algorithm was developed on MRA datasets of stenotic phantoms, which were included in a flow circuit with stationary flows. The length and the severity of the PSL (incorporating both length and degree of PSL) in the maximum intensity projections (MIPs) of MRA datasets were proposed for quantifying stenoses. The algorithm was tested in renal arteries of ten patients with renal artery stenosis and seven healthy volunteers. Digital subtraction angiography (DSA) was performed in the patients and served as the gold standard. Stenosis severity showed better correlation with the severity of the PSL than with the length, both for in vitro as in vivo. Spearman correlation coefficients (rS) showed statistically significant correlations between the severity of the PSL and parameters determined by DSA, i.e. percent diameter stenosis (rS = 0.90). The length of the PSL showed no correlation with the diameter stenosis (rS = 0.37).
Westenberg
J J
JJ
Division of Image Processing, Leiden University Medical Center, The Netherlands.
van der Geest
R J
RJ
Wasser
M N
MN
Doornbos
J
J
Pattynama
P M
PM
de Roos
A
A
Vanderschoot
J
J
Reiber
J H
JH
D000328:Adult; D000465:Algorithms; D001783:Blood Flow Velocity; D005260:Female; D006801:Humans; D007089:Image Enhancement / Q000379:methods*; D016014:Linear Models; D018810:Magnetic Resonance Angiography / Q000379:methods*; D008297:Male; D008875:Middle Aged; D019047:Phantoms, Imaging; D012016:Reference Values; D012077:Renal Artery / Q000473:pathology*; D012078:Renal Artery Obstruction / Q000175:diagnosis* / Q000503:physiopathology; D012079:Renal Circulation / Q000502:physiology*; D012680:Sensitivity and Specificity