Detection and differentiation of semi-transparent materials simulating biological structures using optical coherence tomography: a phantom study

Optical coherence tomography (OCT) is a promising approach for this imaging task but is challenged by the near-transparent nature of these structures. Our aim is to detect and differentiate semi-transparent materials using OCT texture analysis, toward label-free neurography and lymphography. Approach: We have recently demonstrated an innovative OCT texture analysis-based approach that used speckle statistics to image lymphatics and nerves in-vivo that does not rely on negative contrast. However, these two near-transparent structures could not be easily differentiated from each other in the texture analysis parameter space. Here, we perform a rigorous follow-up study to improve upon this differentiation in controlled phantoms mimicking the optical properties of these tissues.

We demonstrate a novel OCT texture analysis-based lymphatics-nerves differentiation methodology in tissue-simulating phantoms. Future work will focus on longitudinal in-vivo lymphangiography and neurography in response to cancer therapeutics toward adaptive personalized medicine.

The results of the three-parameter Rayleigh distribution fit to the OCT images of six types of tissue-mimicking materials varying in transparency and biophysical properties demonstrate clear differences between them, suggesting routes for improved lymphatics-nerves differentiation. Conclusions: We demonstrate a novel OCT texture analysis-based lymphatics-nerves differentiation methodology in tissue-simulating phantoms. Future work will focus on longitudinal in-vivo lymphangiography and neurography in response to cancer therapeutics toward adaptive personalized medicine.

Lymphatic and peripheral nervous system imaging is of prime importance for monitoring various important pathologic processes including cancer development and metastasis, and response to therapy. Aim: Optical coherence tomography (OCT) is a promising approach for this imaging task but is challenged by the near-transparent nature of these structures. Our aim is to detect and differentiate semi-transparent materials using OCT texture analysis, toward label-free neurography and lymphography. Approach: We have recently demonstrated an innovative OCT texture analysis-based approach that used speckle statistics to image lymphatics and nerves in-vivo that does not rely on negative contrast. However, these two near-transparent structures could not be easily differentiated from each other in the texture analysis parameter space. Here, we perform a rigorous follow-up study to improve upon this differentiation in controlled phantoms mimicking the optical properties of these tissues. Results: The results of the three-parameter Rayleigh distribution fit to the OCT images of six types of tissue-mimicking materials varying in transparency and biophysical properties demonstrate clear differences between them, suggesting routes for improved lymphatics-nerves differentiation. Conclusions: We demonstrate a novel OCT texture analysis-based lymphatics-nerves differentiation methodology in tissue-simulating phantoms. Future work will focus on longitudinal in-vivo lymphangiography and neurography in response to cancer therapeutics toward adaptive personalized medicine.