A Multi-Spectral Image Database for In-Vivo Hand Perfusion Evaluation

Abstract

The increasing prevalence of vascular diseases encourages the development of minimally invasive approaches to assess tissue perfusion. A significant challenge facing current state-of-The-Art methods is their validation against clinical data. In this study, we introduce an open-source database designed to evaluate tissue perfusion during the application of an occlusion protocol. The database comprises sequences of multi-spectral images (visible and near-infrared region) from the subjects' predominant hand and their photoplethysmography data for validation. Our study recruited 45 healthy participants, including 21 females, with an age range between 18-24 years old (standard deviation equal to 1.73). The database was evaluated using two methods for estimating skin perfusion parameters based on multi-spectral images: A Kubelka-Munk model, and a linear regression. Meanwhile, for validation purposes, the changes in oxygenated and deoxygenated hemoglobin were evaluated by photoplethysmography data as baseline perfusion parameters. The Pearson correlation between plethysmography-based perfusion parameters and those extracted from multi-spectral images was evaluated in all cases as a validation metric. Our findings demonstrated a strong Pearson correlation (rho >0.7) between changes in oxygenated and deoxygenated hemoglobin and multi-spectral based perfusion parameters, suggesting that the database is useful for further research related to in-vivo perfusion assessment. The primary objective of this database is to provide open-source data from a controlled occlusion protocol to evaluate new approaches based on multi-spectral images in the visible and near-infrared regions. In addition, the validation by photoplethysmography data facilitates the development and assessment of innovative tissue perfusion estimation techniques.