Abstract:

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 20dB and a sampling rate of fs = 60 Hz at f−1 · 0.25(±0.18), so this error is smaller than the distance between two consecutive s 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.

Abstract:

Patients suffering from a cerebrovascular disease, which causes the hypoperfusion of the brain, can undergo revascularization surgery as treatment. It is often performed as an open surgery and its goal is to restore the vascular function, in particular the flow of blood. There- fore, an anastomosis (connection of arteries) is installed to augment flow into a hypoperfused area. Complications occur in approximately 10% of the cases, partly related to an insufficient flow augmentation. Hence, the blood flow should be checked intraoperatively to assess the intervention’s quality and intervene rapidly to prevent a negative patient outcome. The current state-of-the-art measurement device is the ultrasonic transit time flow probe. It provides a quantitative flow value but needs to be placed around the vessel. This is cumber- some and holds the risk of contamination, vessel compromise, and rupture. An alternative method is the indocyanine green (ICG) fluorescence angiography (FA), which is a camera-based method. It is the state-of-the-art method in the high resolution anatomical visualization and it is able to provide the surgeon with a qualitative functional imaging of vessels in the field of view. Approaches to quantify the blood flow via ICG FA failed to obtain trustworthy flow values so far. This thesis analyzes and improves the capability of ICG FA to provide quantitative values by 1. clarifying on how accurate the measurement can be. 2. proposing methods to improve the accuracy. 3. deriving the existence of a systemic error. 4. proposing a method to compensate for the systemic error. 5. providing an end-to-end workflow from video data input to flow value output. 6. validating the proposed methods and the workflow in an ex vivo and in vivo study. The proposed measurement in this thesis is based on the systemic mean transit time theorem for single input and single output systems. To calculate the flow, the transit time of a bolus for a certain distance and the cross sectional area of the vessel need to be obtained. Methods were developed to obtain the blood volume flow, and to identify and quantify the sources of errors in this measurement. The statistical errors in measuring the transit distance and transit time of the ICG bolus as well as the cross sectional area of the vessel are often neglected in research and thus were quantified in this thesis using in silico models. It revealed that the error is too large and requires methods to reduce it.....