Non-invasive screening of glycemic state by statistical analysis of speckle images

Abstract

This work employs a laser speckle imaging-based technique in conjunction with analysis of different statistical orders on the acquired images to rapidly screen between groups of mice in different glycemic states across a range between 46 to 476 mg/dL. Nine mathematical parameters were extracted and tested from the captured images including speckle contrast, power spectrum density, derivatives, skewness, kurtosis, and more. Since the body and its organs are dependent on a continuous supply of glucose as a source of energy, we postulate that glycemic states alter body function through variations in metabolites composition and cell structure of the tissue. This alteration in turn modifies the spatial statistics of the acquired speckle patterns which can be analyzed to help differentiate between glycemic states. To this end, a total of fifteen mice were used in this study and were divided into three groups of five mice each, characterized by differing glycemic states: high glucose (>250 mg/dL, avg: 415 mg/dL), normal glucose (100–180 mg/dL, avg: 136 mg/dL), and low glucose (<100 mg/dL, avg: 65 mg/dL). Varying glucose concentration was achieved using different commonly used anesthetic drugs in the presence or absence of insulin; high glucose levels were achieved by anesthetic drugs ketamine/xylazine, while low glucose was achieved by insulin injection and thiopental as anesthetic. Following experiments, a commercial finger-stick glucometer device was used as a reference indicator on blood taken from the mouse tail vein. Results from experiments performed by illuminating the mouse tail by a laser beam indicate that five out of the nine mathematical features of the speckle images can distinguish between states and therefore may serve as a useful glycemic screening tool.