PPubMed10 Jul 2018Cited 3×

Simulating optical coherence tomography for observing nerve activity: A finite difference time domain bi-dimensional model Computational model for OCT nerve activity detection

Francesca Troiani, Konstantin Nikolic, Timothy G. Constandinou, Sanjoy Bhattacharya

Abstract

'Sanjoy Bhattacharya'] We present a finite difference time domain (FDTD) model for computation of A line scans in time domain optical coherence tomography (OCT). The OCT output signal is created using two different simulations for the reference and sample arms, with a successive computation of the interference signal with external software. In this paper we present the model applied to two different samples: a glass rod filled with water-sucrose solution at different concentrations and a peripheral nerve. This work aims to understand to what extent time domain OCT can be used for non-invasive, direct optical monitoring of peripheral nerve activity.

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A bi‑dimensional FDTD model shows time‑domain OCT can simulate and detect peripheral nerve activity via refractive index changes.

What’s new

i.Developed a 2‑D finite‑difference time‑domain (FDTD) model to generate OCT A‑scans.
ii.Applied the model to both a glass rod with sucrose solutions and a peripheral nerve, demonstrating detection of refractive index changes linked to nerve activity.
iii.Implemented post‑processing in Matlab to compute interference and extract OCT signals, including Poisson noise handling.
iv.Provided quantitative comparison of simulated transmission coefficients with Fresnel theory.

How they did it

Separate FDTD simulations were run for the reference and sample arms using two pulse lengths (25 fs and 150 fs) to emulate different OCT light sources. The electric field outputs were combined in Matlab to form interference patterns, whose envelopes yielded A‑line OCT scans for glass‑rod and nerve models. Refractive indices for each tissue layer were assigned based on literature values.

What they found

Simulation of the nerve model required ~7 hours on a single Intel® Xeon® X5680 CPU.
The OCT signal distinguished interfaces (Ringer’s solution, epineurium, elastic fibres) and showed a measurable difference only in the axon region when simulating active vs. inactive nerve.
Concentration variations of 0.1 %, 0.01 % and 0.001 % sucrose in the glass‑rod model produced distinct differential OCT signals.
Simulated transmission coefficients matched theoretical Fresnel predictions across the wavelength range.

Caveats

✕Axonal structures could not be resolved individually due to axial and transverse resolution limits.
✕The model assumes constant refractive indices over the OCT bandwidth, neglecting material dispersion.
✕Only 2‑D simulations were performed, limiting direct extension to full 3‑D imaging.
✕Experimental validation is pending; results are based solely on simulations.

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Simulating optical coherence tomography for observing nerve activity: A finite difference time domain bi-dimensional model Computational model for OCT nerve activity detection

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