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 quant ifying post-stenotic signal loss (PSL) in 3D phase-contrast (PC) magnetic r esonance angiography (MRA) of patients with renal artery stenosis is presen ted. This algorithm was developed on MRA datasets of stenotic phantoms, whi ch were included in a flow circuit with stationary flows. The length and th e severity of the PSL (incorporating both length and degree of PSL) in the maximum intensity projections (MIPs) of MRA datasets were proposed for quan tifying stenoses. The algorithm was tested in renal arteries of ten patient s with renal artery stenosis and seven healthy volunteers. Digital subtract ion 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 correl ation coefficients (r(S)) showed statistically significant correlations bet ween the severity of the PSL and parameters determined by DSA, i.e. percent diameter stenosis (r(S) = 0.90). The length of the PSL showed no correlati on with the diameter stenosis (r(S) = 0.37).