Abstract
Adaptive optics optical coherence tomography (AO-OCT) enables high-resolution, 3-dimensional imaging of cone photoreceptors in the living human retina. Histological studies have shown that short-wavelength-sensitive (S) cones are structurally distinct from medium- (M) and long-wavelength-sensitive (L) cones. However, current in vivo methods for classifying cones-such as retinal densitometry and optoretinography-are technically demanding because they require measuring cone function. Quantifying structural differences with AO-OCT may provide a simpler and faster alternative and offer new biomarkers for understanding how disease differentially affects photoreceptor subtypes. Here, we present a quantitative method that applies a support vector machine (SVM) classifier to structural measurements of AO-OCT volumes to identify individual S cones. We measured six structural parameters related to the inner and outer segments of each cone. Among 13,836 cones analyzed across six subjects, we found S cones exhibited significantly longer inner segments, shorter outer segments, and wider diameters at the inner/outer segment junction than M and L cones. Although M and L cones are widely regarded as morphologically indistinguishable, we also found that L cones, on average, had longer outer segments than M cones. These structural differences were consistent across five of the six subjects at a single retinal eccentricity of 3.7° and across eccentricities from 2° to 12° temporal in one subject. Our SVM model used these features to achieve high classification accuracy for S cones. Validation of classification performance against optoretinography on the same eyes yielded F1 scores ranging from 0.78 to 0.93 in five of the six subjects.