Abstract
Background
Patients with type 2 diabetes (T2D) have almost a two‐fold greater risk of developing Alzheimer’s disease. Recent studies suggest that one link between the two conditions may be the processes underlying amyloidosis. Our previous studies have demonstrated that cognitive impairment (CI) is not limited to the brain but also affects the retina. In this pilot study, we quantified blood flow within the optic nerve head (ONH) using the XyCAM RI (Vasoptic Medical Inc.), an investigational non‐invasive, laser speckle‐based retinal imager, in cognitively healthy subjects (HC) and patients with mild cognitive impairment (MCI) and T2D.
Method
Thirty‐six individuals (8 HC, 16 T2D, and 12 MCI) were imaged using the XyCAM RI. One imaging session of 6 seconds duration was conducted on each eye of each subject. Only one eye (OS) was used in the analysis. Retinal blood flow (RBF) was agregated in a circular region of interest (ROI), spanning all vessels around the optic nerve head (ONH) (Figure 1). RBF was determined for one complete cardiac cycle without motion artifacts at its trough, mean, and peak per eye. The details of the RBF metrics extracted are included in the Table 1 legend.
Result
Patients with MCI had a longer TtS and SSVI than HC (p=0.007 and p=0.046 as per the independent sample t‐test, respectively, Table 1). Also, a significantly higher SSVI in MCI subjects demonstrated increased contractility compared to HC and T2D subjects. The Kruskal‐Wallis test confirmed that there is a statistically significant difference in the TtS between HC, MCI, and T2D (p=0.043). The average BFVI results are reported in Table 2.
Conclusion
Individuals with MCI and T2D have different RBF characteristics compared to cognitively healthy subjects. These results may be related to systemic changes in parameters such as arterial stiffness and increased blood pressure, which have been correlated with declined cognition. While our results obtained from a limited study population are suggestive, larger studies are needed to confirm the clinical applicability of our approach and the use of RBF‐based metrics as potential biomarkers of amyloidosis status.