Coronary blood flow measurement using an angiographic first pass distribution technique: a feasibility study.
Due to the well-documented problems associated with visual interpretation of coronary angiograms, more physiologic means of assessing coronary artery stenosis are being investigated. One physiologic parameter that has been suggested is coronary flow reserve (CFR). A digital subtraction angiographic technique based on first pass distribution analysis (FPA) is proposed as a means of measuring CFR and absolute coronary flow. The theory of the FPA method is first outlined, and the implementation of a preliminary version of the FPA algorithm is described. Experiments verifying the utility of this algorithm for measuring absolute flow through a flow phantom, and through the canine circumflex artery are reported. It was determined that the preliminary FPA algorithm is capable of measuring canine coronary flow ratios (R) with accuracy and precision characteristics meeting or exceeding those reported for the parametric imaging technique (RFPA = 0.933.Rtrue, SEE = 0.16, r = 0.984). Accurate absolute flow (Q) measurements were obtained in all of the phantom experiments (QFPA = 1.054.Qtrue, r = 0.993), and in one of the three dogs that were studied (QFPA = 0.977.Qtrue, r = 0.935). The difficulty encountered in the other two dog experiments is attributed to the effects of system temporal lag, and would likely be corrected through the use of improved cameras. The feasibility of the general FPA method for measuring relative flow is established, and the potential for routine, absolute flow measurement is demonstrated.
Hangiandreou
N J
NJ
Department of Medical Physics, University of Wisconsin--Madison 53706.
Folts
J D
JD
Peppler
W W
WW
Mistretta
C A
CA
D000465:Algorithms; D000818:Animals; D017023:Coronary Angiography / Q000295:instrumentation / Q000379:methods*; D003326:Coronary Circulation; D003327:Coronary Disease / Q000000981:diagnostic imaging; D004285:Dogs; D005240:Feasibility Studies; D006801:Humans; D008433:Mathematics; D008955:Models, Cardiovascular; D012044:Regression Analysis