Accuracy and precision of depth-resolved estimation of attenuation coefficients in optical coherence tomography

Parametric imaging of the attenuation coefficient $$ using optical coherence tomography (OCT) is a promising approach for evaluating abnormalities in tissue. To date, a standardized measure of accuracy and precision of $$ by the depth-resolved estimation (DRE) method, as an alternative to least squares fitting, is missing.

We present a robust theoretical framework to determine accuracy and precision of the DRE of $$.

We derive and validate analytical expressions for the accuracy and precision of $$ determination by the DRE using simulated OCT signals in absence and presence of noise. We compare the theoretically achievable precisions of the DRE method and the least-squares fitting approach.

Our analytical expressions agree with the numerical simulations for high signal-to-noise ratios and qualitatively describe the dependence on noise otherwise. A commonly used simplification of the DRE method results in a systematic overestimation of the attenuation coefficient in the order of $$, where $$ is the pixel stepsize. When $$, $$ is reconstructed with higher precision by the depth-resolved method compared to fitting over the length of an axial fitting range $$.

We derived and validated expressions for the accuracy and precision of DRE of $$. A commonly used simplification of this method is not recommended as being used for OCT-attenuation reconstruction. We give a rule of thumb providing guidance in the choice of estimation method.