Comparison of methods for instantaneous angiographic blood flow measurement

Abstract

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.

X-ray videodensitometric methods for blood flow and velocity measurement: A critical review of literature

“…A similar method was used to compute flow velocity in a flow phantom by Hoffmann et al 122 This algorithm has been found to have performance superior to that of the bolus mass tracking approach, 117 but later research did not support that observation. 123 That disparity was explained by the differences between the implementations of the algorithms and between the parameters of measured flows. 123 The process of finding the optimal match of shifted distance-density curves is similar to mathematical crosscorrelation used in the cross-correlation of time-density curves method ͑Sec.…”

“…123 That disparity was explained by the differences between the implementations of the algorithms and between the parameters of measured flows. 123 The process of finding the optimal match of shifted distance-density curves is similar to mathematical crosscorrelation used in the cross-correlation of time-density curves method ͑Sec. III A 2͒.…”

“…Subsequently, Shpilfoygel et al 123 proposed to extend the curve-fitting approach to the bolus mass tracking method ͑Refs. 115, 116͒ by fitting lines to profiles of bolus mass differences…”

Intra-vascular blood velocity and volumetric flow rate calculated from dynamic 4D CT angiography using a time of flight technique

“…The method is a combination of our prior demonstrations of functional angiography [10] and blood velocity [4] calculations in 4D CT, which were based upon videodensitometric methods first described in conventional angiography and have been extensively reviewed [11,12].…”

Blood Flow and Velocity Estimation Based on Vessel Transit Time by Combining 2D and 3D X-Ray Angiography

“…-Techniques based on measuring the distance that contrast medium travels between two frames [3,2]. -Optical flow based methods [4,5,2].…”