We report a large field of view FOV low-cost smart fundus camera with non-mydriatic and spectral band illumination features for the purpose of diagnosing central nervous system diseases such as Alzheimer’s disease. By combining a customized optical lens group, ring light emitting diode light source, Li-battery, and Raspberry Pi we can port the spectrally selected light source through a 4 mm diameter pupil. Taking advantage of the open hardware platform and Linux operating system, we integrate two narrowband filters explicitly selected based on the unique spectrums of biomarkers (580 nm and 660 nm) with a Raspberry Pi camera module to obtain high quality images for the purpose of enhancing the visibility of retinal vasculature and nerve fiber layer.
The development of effective therapies for cognitive impairment (CI), especially due to Alzheimer’s disease, demands diagnosing the condition during the prodromal phase. The diagnosis of CI involves expensive and invasive methods, such as positron emission tomography and cerebrospinal fluid assessment via spinal tap. Hence, a comparatively lower cost and noninvasive method of diagnosis is imperative. The human retina is an extension of the brain characterized by similarities in vascular and neural structures. The complications of CI are not only limited to the brain but also affect the retina for which the loss of retinal ganglion cells has been associated with neurodegeneration in the brain. The loss of retinal ganglion cells in individuals with CI may be related to reduced vascular demand and a potential remodeling of the retinal vascular branching complexity. Retinal imaging biomarkers may provide a low cost and noninvasive alternative for the diagnosis of CI. In this study, the retinal vascular branching complexity of patients with CI was characterized using the singularity spectrum multifractal dimension and lacunarity parameter. A reduced vascular branching complexity was observed in subjects with CI when compared to age- and sex-matched cognitively healthy controls. Significant associations were also found between retinal vascular and functional parameters.
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