Blood flow rate and velocity are important parameters for the study of vascular systems, and for the diagnosis, monitoring and evaluation of treatment of cerebro- and cardiovascular disease. For rapid imaging of cerebral and cardiac blood vessels, digital x-ray subtraction angiography has numerous advantages over other modalities. Roentgen-videodensitometric techniques measure blood flow and velocity from changes of contrast material density in x-ray angiograms. Many roentgen-videodensitometric flow measurement methods can also be applied to CT, MR and rotational angiography images. Hence, roentgen-videodensitometric blood flow and velocity measurement from digital x-ray angiograms represents an important research topic. This work contains a critical review and bibliography surveying current and old developments in the field. We present an extensive survey of English-language publications on the subject and a classification of published algorithms. We also present descriptions and critical reviews of these algorithms. The algorithms are reviewed with requirements imposed by neuro- and cardiovascular clinical environments in mind.

Several different algorithms have been reported for measurement of blood flow rates and velocities from digital x-ray angiograms. We compare four videodensitometric methods: (1) distance-density curve matching (DDCM), (2) distance-density curve matching with curve-fitting (DDCM-F), (3) bolus mass tracking with curve-fitting (BMT-F) and (4) fluid continuity method (FCM). We tested the flow algorithms with simulated angiograms and with images obtained from a programmable flow phantom under clinically realistic flow and contrast injection conditions including imperfect mixing. All methods perform well for simulated angiograms. On phantom angiograms with constant flow, all methods tended to underestimate flow velocities by at least 7% and demonstrate high variability between consecutive measurements. The FCM demonstrated relatively low variability, but a large negative bias. The DDCM method was moderately biased and had the highest variability. The BMT-F method demonstrated the lowest bias (-7.1%) and the lowest variability both within (27%) and between (27%) studies. No method yields reliable measurements near the peak contrast opacification, when little or no gradient of contrast is present. The extrapolating version of the BMT-F method was also the most robust for estimation of interframe displacements longer than the field of view.

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