A new model-based technique for enhanced small-vessel measurements in X-ray cine-angiograms

Arterial diameter estimation from X-ray cine angiograms is important for qu antifying coronary artery disease (CAD) and for evaluating therapy, However , diameter measurement in vessel cross sections less than or equal to 1.0 m m is associated with large measurement errors. We present a novel diameter estimator which reduces both magnitude and variability of measurement error . We use a parametric nonlinear imaging model for X-ray cine angiography an d estimate unknown model parameters directly from the image data. Our techn ique allows us to exploit additional diameter information contained within the intensity profile amplitude, a feature which is overlooked by existing methods, This method uses a two-step procedure: the first step estimates th e imaging model parameters directly from the angiographic frame and the sec ond step uses these measurements to estimate the diameter of vessels in the same image. In Monte-Carlo simulation over a range of imaging conditions, our approach consistently produced lower estimation error and variability t han conventional methods. With actual X-ray images, our estimator is also b etter than existing methods for the diameters examined (0.4-4.0 mm), These improvements are most significant in the range of narrow vessel widths asso ciated with severe coronary artery disease.