## 4 Discussion  
The goals of improving fluorescent assessments and their interpretation are similar to those in science in general; achieving objectivity, reproducibility, and comparability. In this  
Figure 5: Top left image showing the phantom using the Stryker 1688 camera. The red line indicates the position of the adjacent graph with a fluorescent intensity distribution. The middle and lowest images both show the fluorescent image of a segment of colon during a transanal total mesorectal excision before and after correction. The blue and orange lines indicate the location on the intensity distributions plotted in the two adjacent graphs for the central and peripheral part of the image both before (blue) and after (orange) correction. The corrected result is therefore a more realistic representation of the fluorescence distribution in the tissue. study, a fluorescence imaging standard was used that incorporated ICG to test the center-periphery effect of five commercially available imaging systems indicated for use with ICG. The results of this study demonstrate a considerable variation in light distribution within the FoV; with decreasing fluorescence intensity toward the periphery down to 60% in relation to the highest intensity. Among the five different commercially available NIR camera systems, considerable variability exists regarding fluorescence intensity and sensitivity. These features should be considered and if possible corrected for while interpreting the fluorescent signal clinically and selecting ROIs for quantification. Recent reviews have stated that inflow parameters have superior clinical performance over intensity parameters, due to immunity to changes in camera distance and angulation [12; 20]. Our findings emphasize these results, as dynamic flow parameters are less likely to be affected by the RoS selection and thus inhomogeneous illumination fields. Despite the fact that for quantification the camera is kept stable in terms of distance, movement due to breathing or peristalsis is problematic and challenging to eliminate. Furthermore, by utilizing normalization and correction for the light distribution, one could modify the slope parameter to be based on relative changes in fluorescence intensity, significantly reducing the impact of several of the above-mentioned challenges that affect the measurement and differences in camera systems. This study addresses the periphery-center effect in the flat field only and does not take different distances or the morphology of the tissue into account. In this study, it was decided to standardize the distance and optical properties to remove the confounding effects which lightscattering and absorption can have on fluorescence. These factors require other, more sophisticated solutions. The aim of this study was to quantify the impact of the periphery-center effect in the flat field and to correct it as a first step. Recent work has demonstrated that significant variations in performance between NIR cameras exist, with each camera system being used at different distances and speeds of movement [21]. The results indicated in this study were focused on defining the ideal optical distance (FoV) and distance per camera demonstrating that each device has its own ideal set-up. Our results demonstrate that there are significant variations among different camera systems. It is likely that other camera systems not included in our testing would also exhibit these differences. This makes it challenging to establish consistent fluorescent parameter thresholds across different camera systems. It is important to note that most commercial systems are designed primarily to provide surgeons with information about perfusion, rather than to quantify the signal or for inter-system compatibility. Currently the control over system parameters such as gain, camera integration time, and illumination intensity is limited.