# Texture Analysis of Near-Infrared Vein Images During Reactive Hyperemia in Healthy Subjects
## 4 Discussion  
### Interpretation of Classical Texture Parameters  
Several imaging modalities, such as computed tomography (CT), magnetic resonance imaging (MRI), and phleography, have been used to detect venous congestion in specific  
Figure 3: Median values of textural parameters extracted from the regions of interest in near-infrared vein images over time. Parameters include contrast (blue), correlation (red), energy (green), homogeneity (yellow), entropy (purple), fractal dimension (brown), and lacunarity (grey). Dashed vertical lines indicate the beginning and end of suprasystolic occlusion (minute 5 to minute 8).  
clinical contexts [34; 35; 36]. However, their use is often limited by availability, cost, or invasiveness. In contrast, simpler and noninvasive techniques such as Doppler ultrasound [37] and photoplethysmography (PPG) [38; 39] are widely applied in clinical and research settings to assess venous congestion and refill dynamics. While Doppler ultrasound and PPG are valuable for capturing hemodynamic parameters such as flow velocity or volume changes, they do not provide spatial or structural insights into superficial venous patterns. The present approach may therefore serve as a complementary tool in vascular research, particularly when integrated with established flow-based techniques in future validation studies. The NIRI-based vein finder used in this study offers a complementary perspective by capturing structural and textural changes in superficial veins in response to congestion. It produces images that reflect the amount of infrared light absorbed by the skin [40], where veins appear darker due to higher absorption by hemoglobin, while the overlying skin appears in varying shades of gray. Even though venous occlusion can be achieved with lower cuff pressures [41; 42], we aimed at evoking a reactive hyperemia phenomenon, since this maneuver creates a faster venous filling, which could also change textural characteristics. As expected, the venous congestion resulting from occlusion at 200 mmHg translated to the significant increase in vein width. Here, we integrated textural analysis, aiming to understand whether passive venous filling alters the internal texture of vein projections. This approach is not only novel but also potentially more accessible than manual geometric quantifications.  
Among the texture parameters assessed, only correlation changed significantly during occlusion. This parameter, derived from the GLCM, reflects the predictability or regularity of gray-level patterns [43; 44; 45]. Its increase likely reflects a smoother, more homogeneous distribution of intensities within the distended veins, possibly due to greater intraluminal filling. Conversely, the contrast, energy, homogeneity, and entropy parameters did not change statistically. This suggests that despite mechanical distension, the overall variability and intensity gradients within the vein ROIs remained relatively stable. Similarly, fractal dimension, a measure of geometric complexity and self-similarity, did not vary, indicating preservation of the hierarchical organization of the vein pattern across scales. Notably, lacunarity, which captures heterogeneity and the distribution of gaps within a structure, decreased steadily throughout the protocol, with a significant reduction in the recovery phase. This may indicate a more uniform and less fragmented appearance of venous filling after reactive hyperemia, although further investigation is required to interpret this behavior physiologically.