Reduction of Uncertainty in Bolus Transit Time Measurement in Quantitative Fluorescence Angiography

Abstract During cerebral revascularization surgeries, blood flow values help surgeons to monitor the quality of the procedure, e.g., to avoid cerebral hyperperfusion syndrome due to excessively enhanced perfusion. The state-of-the-art technique is the ultrasonic flow probe that has to be placed around the blood vessel. This causes contact between probe and vessel, which, in the worst case, leads to rupture. The recently developed intraoperative indocyanine green (ICG) Quantitative Fluorescence Angiography (QFA) is an alternative technique that overcomes this risk. However, it has been shown by the developer that the calculated flow has deviations. After determining the bolus transit time as the most sensitive parameter in flow calculation, we propose a new two-step uncertainty reduction method for flow calculation. The first step is to generate more data in each measurement that results in functions of the parameters. Noise can then be reduced in a second step. Two methods for this step are compared. The first method fits the model for each parameter function separately and calculates flow from models, while the second one fits multiple parameter functions together. The latter method is proven to perform best by in silico tests. Besides, this method reduces the deviation of flow comparing to original QFA as expected. Our approach can be generally used in all QFA applications using two-point theory. Further development is possible if number of dimensions of the achieved parameter data are broadened that results in even more data for processing in the second step.