RESUMEN
The vascular function of a vessel can be qualitatively and intraoperatively checked by recording the blood dynamics inside the vessel via fluorescence angiography (FA). Although FA is the state of the art in proving the existence of blood flow during interventions such as bypass surgery, it still lacks a quantitative blood flow measurement that could decrease the recurrence rate and postsurgical mortality. Previous approaches show that the measured flow has a significant deviation compared to the gold standard reference (ultrasonic flow meter). In order to systematically address the possible sources of error, we investigated the error in transit time measurement of an indicator. Obtaining in vivo indicator dilution curves with a known ground truth is complex and often not possible. Further, the error in transit time measurement should be quantified and reduced. To tackle both issues, we first computed many diverse indicator dilution curves using an in silico simulation of the indicator's flow. Second, we post-processed these curves to mimic measured signals. Finally, we fitted mathematical models (parabola, gamma variate, local density random walk, and mono-exponential model) to re-continualize the obtained discrete indicator dilution curves and calculate the time delay of two analytical functions. This re-continualization showed an increase in the temporal accuracy up to a sub-sample accuracy. Thereby, the Local Density Random Walk (LDRW) model performed best using the cross-correlation of the first derivative of both indicator curves with a cutting of the data at 40% of the peak intensity. The error in frames depends on the noise level and is for a signal-to-noise ratio (SNR) of 20 dB and a sampling rate of f s = 60 Hz at f s - 1 · 0 . 25 ( ± 0 . 18 ) , so this error is smaller than the distance between two consecutive samples. The accurate determination of the transit time and the quantification of the error allow the calculation of the error propagation onto the flow measurement. Both can assist surgeons as an intraoperative quality check and thereby reduce the recurrence rate and post-surgical mortality.
RESUMEN
Today the vascular function after interventions as Bypass surgeries are checked qualitatively by observing the blood dynamics inside the vessel via Indocyanine Green (ICG) Fluorescence Angiography. This state-of-the-art should be upgraded and has to be improved and converted towards a quantitatively measured blood flow. Previous approaches show that the blood flow measured from fluorescence angiography cannot be easily calibrated to a gold standard reference. In order to systematically address the possible source of error we investigate as a first step the discretization error in a camera-based measurement of the vessel's geometry. In order to generate an error-free ground truth, a vessel model has been developed based on mathematical functions. This database is then used to determine the error in discretizing the centerline of the structure and estimate its effects on the accuracy of the flow calculation. As result the model is implemented according to the conditions which are set up to ensure transferability on camera-based segmentations of vessels. In this paper the relative discretization error for estimating the centerline length of segmented vessels could be calculated in the range of 6.3%. This would reveal significant error propagated to the estimation of the blood flow value derived by camera-based angiography.