Polarization-sensitive interferometric synthetic aperture microscopy

Birefringence mapping of biological tissues based on polarization sensitive non-interferometric quantitative phase imaging technique

OBJECTIVE

Oral cancer is a leading cause of mortality globally, particularly affecting developing regions where oral hygiene is often overlooked. The optical properties of tissues are vital for diagnostics, with polarization imaging emerging as a label-free, contrast-enhancing technique widely employed in medical and scientific research over past few decades.

MATERIALS AND METHODS

We present a novel polarization sensitive quantitative phase imaging of biological tissues by incorporating the conventional polarization microscope and transport of intensity equation-based phase retrieval algorithm. This integration provides access to the birefringence mapping of biological tissues. The inherent optical anisotropy in biological tissues induces the polarization dependent refractive index variations which can provide the detailed insights into the birefringence characteristics of their extracellular constituents. Experimental investigations were conducted on both normal and cancerous oral tissue samples by recording a set of three polarization intensity images for each case with a step size of 2 μm.

RESULTS

A noteworthy increment in birefringence quantification was observed in cancerous as compared to the normal tissues, attributed to the proliferation of abnormal cells during cancer progression. The mean birefringence values were calculated for both normal and cancerous tissues, revealing a significant increase in birefringence of cancerous tissues (2.1 ± 0.2) × 10-2 compared to normal tissues (0.8 ± 0.2) × 10-2. Data were collected from 8 patients in each group under identical experimental conditions.

CONCLUSION

This polarization sensitive non-interferometric optical approach demonstrated effective discrimination between cancerous and normal tissues, with various parameters indicating elevated values in cancerous tissues.

Recent Advances and Current Trends in Transmission Tomographic Diffraction Microscopy

Optical microscopy techniques are among the most used methods in biomedical sample characterization. In their more advanced realization, optical microscopes demonstrate resolution down to the nanometric scale. These methods rely on the use of fluorescent sample labeling in order to break the diffraction limit. However, fluorescent molecules' phototoxicity or photobleaching is not always compatible with the investigated samples. To overcome this limitation, quantitative phase imaging techniques have been proposed. Among these, holographic imaging has demonstrated its ability to image living microscopic samples without staining. However, for a 3D assessment of samples, tomographic acquisitions are needed. Tomographic Diffraction Microscopy (TDM) combines holographic acquisitions with tomographic reconstructions. Relying on a 3D synthetic aperture process, TDM allows for 3D quantitative measurements of the complex refractive index of the investigated sample. Since its initial proposition by Emil Wolf in 1969, the concept of TDM has found a lot of applications and has become one of the hot topics in biomedical imaging. This review focuses on recent achievements in TDM development. Current trends and perspectives of the technique are also discussed.

Computational refocusing in phase-unstable polarization-sensitive optical coherence tomography

We present computational refocusing in polarization-sensitive optical coherence tomography (PS-OCT) to improve spatial resolution in the calculated polarimetric parameters and extend the depth-of-field in phase-unstable, fiber-based PS-OCT systems. To achieve this, we successfully adapted short A-line range phase-stability adaptive optics (SHARP), a computational aberration correction technique compatible with phase-unstable systems, into a Stokes-based PS-OCT system with inter-A-line polarization modulation. Together with the spectral binning technique to mitigate system-induced chromatic polarization effects, we show that computational refocusing improves image quality in tissue polarimetry of swine eye anterior segment ex vivo with PS-OCT. The benefits, drawbacks, and potential applications of computational refocusing in anterior segment imaging are discussed.

Computational refocusing of Jones matrix polarization-sensitive optical coherence tomography and investigation of defocus-induced polarization artifacts

Here we demonstrate a long-depth-of-focus imaging method using polarization sensitive optical coherence tomography (PS-OCT). This method involves a combination of Fresnel-diffraction-model-based phase sensitive computational refocusing and Jones-matrix based PS-OCT (JM-OCT). JM-OCT measures four complex OCT images corresponding to four polarization channels. These OCT images are computationally refocused as preserving the mutual phase consistency. This method is validated using a static phantom, postmortem zebrafish, and ex vivo porcine muscle samples. All the samples demonstrated successful computationally-refocused birefringence and degree-of-polarization-uniformity (DOPU) images. We found that defocusing induces polarization artifacts, i.e., incorrectly high birefringence values and low DOPU values, which are substantially mitigated by computational refocusing.

Computational adaptive optics for polarization-sensitive optical coherence tomography

Defocus aberration in optical systems, including optical coherence tomography (OCT) systems employing Gaussian illumination, gives rise to the well-known compromise between transverse resolution and depth-of-field. This results in blurry images when out-of-focus, whilst other low-order aberrations (e.g., astigmatism, coma, etc.) present in both the OCT system and biological samples further reduce image resolution and contrast. Computational adaptive optics (CAO) is a computed optical interferometric imaging technique that modifies the phase of the OCT data in the spatial frequency domain to correct optical aberrations and provide improvement of the image quality throughout the three-dimensional (3D) volume. In this Letter, we report the first implementation of CAO for polarization-sensitive OCT to correct defocus and other low-order aberrations, providing enhanced polarization-sensitive imaging contrast (i.e., intensity and phase retardation) on a 3D OCT phantom, molded plastics, ex vivo chicken breast tissue, and ex vivo human breast cancer tissue.

Vectorial birefringence imaging by optical coherence microscopy for assessing fibrillar microstructures in the cornea and limbus

The organization of fibrillar tissue on the micrometer scale carries direct implications for health and disease but remains difficult to assess in vivo. Polarization-sensitive optical coherence tomography measures birefringence, which relates to the microscopic arrangement of fibrillar tissue components. Here, we demonstrate a critical improvement in leveraging this contrast mechanism by employing the improved spatial resolution of focus-extended optical coherence microscopy (1.4 µm axially in air and 1.6 µm laterally, over more than 70 µm depth of field). Vectorial birefringence imaging of sheep cornea ex vivo reveals its lamellar organization into thin sections with distinct local optic axis orientations, paving the way to resolving similar features in vivo.

Clinical translation of handheld optical coherence tomography: practical considerations and recent advancements

Since the inception of optical coherence tomography (OCT), advancements in imaging system design and handheld probes have allowed for numerous advancements in disease diagnostics and characterization of the structural and optical properties of tissue. OCT system developers continue to reduce form factor and cost, while improving imaging performance (speed, resolution, etc.) and flexibility for applicability in a broad range of fields, and nearly every clinical specialty. An extensive array of components to construct customized systems has also become available, with a range of commercial entities that produce high-quality products, from single components to full systems, for clinical and research use. Many advancements in the development of these miniaturized and portable systems can be linked back to a specific challenge in academic research, or a clinical need in medicine or surgery. Handheld OCT systems are discussed and explored for various applications. Handheld systems are discussed in terms of their relative level of portability and form factor, with mention of the supporting technologies and surrounding ecosystem that bolstered their development. Additional insight from our efforts to implement systems in several clinical environments is provided. The trend toward well-designed, efficient, and compact handheld systems paves the way for more widespread adoption of OCT into point-of-care or point-of-procedure applications in both clinical and commercial settings.

Computational optical coherence tomography [Invited]

Optical coherence tomography (OCT) has become an important imaging modality with numerous biomedical applications. Challenges in high-speed, high-resolution, volumetric OCT imaging include managing dispersion, the trade-off between transverse resolution and depth-of-field, and correcting optical aberrations that are present in both the system and sample. Physics-based computational imaging techniques have proven to provide solutions to these limitations. This review aims to outline these computational imaging techniques within a general mathematical framework, summarize the historical progress, highlight the state-of-the-art achievements, and discuss the present challenges.

Automated interferometric synthetic aperture microscopy and computational adaptive optics for improved optical coherence tomography

In this paper, we introduce an algorithm framework for the automation of interferometric synthetic aperture microscopy (ISAM). Under this framework, common processing steps such as dispersion correction, Fourier domain resampling, and computational adaptive optics aberration correction are carried out as metrics-assisted parameter search problems. We further present the results of this algorithm applied to phantom and biological tissue samples and compare with manually adjusted results. With the automated algorithm, near-optimal ISAM reconstruction can be achieved without manual adjustment. At the same time, the technical barrier for the nonexpert using ISAM imaging is also significantly lowered.