Origins of subdiffractional contrast in optical coherence tomography

Area of Science:

• Biomedical Optics
• Medical Imaging
• Nanotechnology

Background:

• Optical coherence tomography (OCT) provides high-resolution imaging of tissue morphology.
• Current OCT resolution is limited by temporal coherence length, leaving subdiffractional information unexplored.
• Spectroscopic OCT processing offers nanoscale sensitivity, raising questions about analyzing subdiffractional data.

Purpose of the Study:

• To investigate how subdiffractional information is incorporated into OCT images.
• To develop methods for unambiguous quantification of ultrastructure from OCT data.
• To explore the relationship between sample statistics and OCT image properties.

Main Methods:

• Developed a finite-difference time-domain (FDTD) simulation for spectral domain OCT with nanometer resolution.
• Validated an analytical relationship between sample statistics (refractive index fluctuations) and OCT image properties.
• Analyzed the power spectral density (PSD) of refractive index fluctuations.

Main Results:

• Established that image mean, variance, and spectral slope probe different aspects of the PSD.
• Demonstrated that the spectral slope quantifies mass scaling.
• Found the spectral slope is uniquely monotonic with the sample autocorrelation shape.

Conclusions:

• OCT images inherently contain quantifiable subdiffractional tissue structure information.
• The spectral slope derived from OCT data provides a robust measure of ultrastructure.
• This work enables more precise nanoscale analysis of biological tissues using OCT.