Abstract
We demonstrate that OCT images quantify subdiffractional tissue structure. Optical coherence tomography (OCT) measures stratified tissue morphology with spatial resolution limited by the temporal coherence length. Spectroscopic OCT processing, on the other hand, has enabled nanoscale sensitive analysis, presenting an unexplored question: how does subdiffractional information get folded into the OCT image and how does one best analyze to allow for unambiguous quantification of ultrastructure? We first develop an FDTD simulation to model spectral domain OCT with nanometer resolution. Using this, we validate an analytical relationship between the sample statistics through the power spectral density (PSD) of refractive index fluctuations and three measurable quantities (image mean, image variance, and spectral slope), and have found that each probes different aspects of the PSD (amplitude, integral and slope, respectively). Finally, we found that only the spectral slope, quantifying mass scaling, is monotonic with the sample autocorrelation shape.
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