## 2 Methods
### OCT Imaging and Data Processing  
Volumetric OCT data sets of the wound area were acquired using a custom-built dermal swept-source OCT system. A detailed description of the OCT system can be found elsewhere [64]. The system employs an akinetic light source (Insight Photonic Solutions,  
\begin{table}
\begin{tabular}{l l l} \hline \hline
**Study Group** & **Non-Diabetic Animals** & **Diabetic Animals** \\ \hline Control (no treatment) & 6 & 6 \\ Chitosan hydrogel & 6 & 5 \\ Fibrin sealant & 6 & 6 \\ VEGF/PDGF + fibrin sealant & 6 & 6 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Study groups and number of animals included in the analysis.  
Inc., Lafayette, CO, USA) operating at a central wavelength of 1322 nm with a spectral bandwidth of 62 nm. Considering the numerical aperture of the optical fiber and focal length of the scan lens (Thorlabs LSM02, \(f=18\) mm, Thorlabs GmbH, Bergkirchen, Germany), the system provides a lateral resolution of \(\sim\)13 um and a depth of focus of \(\sim\)200 um. Split-spectrum amplitude decorrelation [65] was used to generate the angiography images from the acquired spectral OCT data. In vivo data acquisition was performed over a rectangular skin patch covering an area of 4.86 mm \(\times\) 4.86 mm. Imaging data was recorded with 768 A-scans per B-scan and 4 consecutive B-scans at each of 768 positions in slow scanning direction. After applying the thresholded structural image data as a mask, maximum projection of the angiography data in axial direction produced en-face angiograms with a size of 768 pixel \(\times\) 768 pixel. Binary angiograms were created by applying Sato filter of curvilinear structures [66] and contrast limited adaptive histogram equalization [67], followed by thresholding using [PERSON]'s method [68].  
For characterization of the vascular network, four OCTA parameters were analyzed: (1) The vessel density giving the percentage of pixels that belong to vessels and being calculated from the binarized angiograms. (2) The vessel length determined from a morphological skeleton of the binarized angiogram and normalized to a skin area of 1 mm\({}^{2}\). (3) The number of bifurcations in the vascular network normalized to vessel length. (4) The vessel tortuosity, sometimes also referred to as distance metric [69], which was calculated as the weighted average of the path length divided by the linear distance between the endpoints of each vessel segment. It was determined from angiograms from which the shortest vessel segments had been removed. The wound site itself was excluded from the analysis of the four vascular parameters.  
Figure 1 illustrates the post-processing steps applied: In the 2D OCT angiogram (Figure 1a), the region of interest was manually marked to exclude the wound site itself and any areas covered by the splint (Figure 1b). After applying the Sato filter of curvilinear structures (Figure 1c), thresholding produced the binary angiogram (Figure 1d) that was used to calculate vessel density. Skeletonization of this binary angiogram led to the image that was evaluated for vessel length and number of bifurcations (Figure 1e). The skeletonized angiogram was cleaned from very short vessel segments (Figure 1f) before determining the vessel tortuosity.  
Figure 1: Post-processing of the optical coherence tomography angiograms. (**a**) Original OCT angiogram. (**b**) Region of interest with excluded wound area and image area covered by the plastic ring. (**c**) Angiogram after application of the Sato filter of curvilinear structures. (**d**) Thresholded angiogram. (**e**) Angiogram after skeletonization. (**f**) Skeletonized angiogram after removal of short vessel segments as used for calculating the vessel tortuosity.