Local wavefront mapping in tissue using computational adaptive optics OCT.

The identification and correction of wavefront aberrations is often necessary to achieve high-resolution optical images of biological tissues, as imperfections in the optical system and the tissue itself distort the imaging beam. Measuring the localized wavefront aberration provides information on where the beam is distorted and how severely. We have recently developed a method to estimate the single-pass wavefront aberrations from complex optical coherence tomography (OCT) data. Using this method, localized wavefront measurement and correction using computational OCT was performed in ex vivo tissues. The computationally measured wavefront varied throughout the imaged OCT volumes and, therefore, a local wavefront correction outperformed a global wavefront correction. The local wavefront measurement was also used to generate tissue aberration maps. Such aberration maps could potentially be used as a new form of tissue contrast.

Combined hardware and computational optical wavefront correction.

In many optical imaging applications, it is necessary to overcome aberrations to obtain high-resolution images. Aberration correction can be performed by either physically modifying the optical wavefront using hardware components, or by modifying the wavefront during image reconstruction using computational imaging. Here we address a longstanding issue in computational imaging: photons that are not collected cannot be corrected. This severely restricts the applications of computational wavefront correction. Additionally, performance limitations of hardware wavefront correction leave many aberrations uncorrected. We combine hardware and computational correction to address the shortcomings of each method. Coherent optical backscattering data is collected using high-speed optical coherence tomography, with aberrations corrected at the time of acquisition using a wavefront sensor and deformable mirror to maximize photon collection. Remaining aberrations are corrected by digitally modifying the coherently-measured wavefront during imaging reconstruction. This strategy obtains high-resolution images with improved signal-to-noise ratio of in vivo human photoreceptor cells with more complete correction of ocular aberrations, and increased flexibility to image at multiple retinal depths, field locations, and time points. While our approach is not restricted to retinal imaging, this application is one of the most challenging for computational imaging due to the large aberrations of the dilated pupil, time-varying aberrations, and unavoidable eye motion. In contrast with previous computational imaging work, we have imaged single photoreceptors and their waveguide modes in fully dilated eyes with a single acquisition. Combined hardware and computational wavefront correction improves the image sharpness of existing adaptive optics systems, and broadens the potential applications of computational imaging methods.

Wavefront measurement using computational adaptive optics.

In many optical imaging applications, it is necessary to correct for aberrations to obtain high quality images. Optical coherence tomography (OCT) provides access to the amplitude and phase of the backscattered optical field for three-dimensional (3D) imaging samples. Computational adaptive optics (CAO) modifies the phase of the OCT data in the spatial frequency domain to correct optical aberrations without using a deformable mirror, as is commonly done in hardware-based adaptive optics (AO). This provides improvement of image quality throughout the 3D volume, enabling imaging across greater depth ranges and in highly aberrated samples. However, the CAO aberration correction has a complicated relation to the imaging pupil and is not a direct measurement of the pupil aberrations. Here we present new methods for recovering the wavefront aberrations directly from the OCT data without the use of hardware adaptive optics. This enables both computational measurement and correction of optical aberrations.

Complementary use of polarization-sensitive and standard OCT metrics for enhanced intraoperative differentiation of breast cancer.

We report the development and implementation of an intraoperative polarization-sensitive optical coherence tomography (PS-OCT) system for enhancing breast cancer detection. A total of 3440 PS-OCT images were intraoperatively acquired from 9 human breast specimens diagnosed by H&E histology as healthy fibro-adipose tissue (n = 2), healthy stroma (n = 2), or invasive ductal carcinoma (IDC, n = 5). A standard OCT-based metric (coefficient of variation (CV)) and PS-OCT-based metrics sensitive to biological tissue from birefringence (i.e., retardation and degree of polarization uniformity (DOPU)) were derived from 398 statistically different and independent images selected by correlation coefficient analysis. We found the standard OCT-based metric and PS-OCT-based metrics were complementary for the differentiation of healthy fibro-adipose tissue, healthy stroma, and IDC. While the CV of fibro-adipose tissue was significantly higher (p<0.001) than those of either stroma or IDC, the CV difference between stroma and IDC was minimal. On the other hand, stroma was associated with significantly higher (p<0.001) retardation and significantly lower (p<0.001) DOPU as compared to IDC. By leveraging the complementary information acquired by the intraoperative PS-OCT system, healthy fibro-adipose tissue, healthy stroma, and IDC can be differentiated with an accuracy of 89.4%, demonstrating the potential of PS-OCT as an adjunct modality for enhanced intraoperative differentiation of human breast cancer.

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.

Computed Optical Interferometric Imaging: Methods, Achievements, and Challenges.

Three-dimensional high-resolution optical imaging systems are generally restricted by the trade-off between resolution and depth-of-field as well as imperfections in the imaging system or sample. Computed optical interferometric imaging is able to overcome these longstanding limitations using methods such as interferometric synthetic aperture microscopy (ISAM) and computational adaptive optics (CAO) which manipulate the complex interferometric data. These techniques correct for limited depth-of-field and optical aberrations without the need for additional hardware. This paper aims to outline these computational methods, making them readily available to the research community. Achievements of the techniques will be highlighted, along with past and present challenges in implementing the techniques. Challenges such as phase instability and determination of the appropriate aberration correction have been largely overcome so that imaging of living tissues using ISAM and CAO is now possible. Computed imaging in optics is becoming a mature technology poised to make a significant impact in medicine and biology.

Automated computational aberration correction method for broadband interferometric imaging techniques.

Numerical correction of optical aberrations provides an inexpensive and simpler alternative to the traditionally used hardware-based adaptive optics techniques. In this Letter, we present an automated computational aberration correction method for broadband interferometric imaging techniques. In the proposed method, the process of aberration correction is modeled as a filtering operation on the aberrant image using a phase filter in the Fourier domain. The phase filter is expressed as a linear combination of Zernike polynomials with unknown coefficients, which are estimated through an iterative optimization scheme based on maximizing an image sharpness metric. The method is validated on both simulated data and experimental data obtained from a tissue phantom, an ex vivo tissue sample, and an in vivo photoreceptor layer of the human retina.

Intraoperative optical coherence tomography for assessing human lymph nodes for metastatic cancer.

BACKGROUND: Evaluation of lymph node (LN) status is an important factor for detecting metastasis and thereby staging breast cancer. Currently utilized clinical techniques involve the surgical disruption and resection of lymphatic structure, whether nodes or axillary contents, for histological examination. While reasonably effective at detection of macrometastasis, the majority of the resected lymph nodes are histologically negative. Improvements need to be made to better detect micrometastasis, minimize or eliminate lymphatic disruption complications, and provide immediate and accurate intraoperative feedback for in vivo cancer staging to better guide surgery. METHODS: We evaluated the use of optical coherence tomography (OCT), a high-resolution, real-time, label-free imaging modality for the intraoperative assessment of human LNs for metastatic disease in patients with breast cancer. We assessed the sensitivity and specificity of double-blinded trained readers who analyzed intraoperative OCT LN images for presence of metastatic disease, using co-registered post-operative histopathology as the gold standard. RESULTS: Our results suggest that intraoperative OCT examination of LNs is an appropriate real-time, label-free, non-destructive alternative to frozen-section analysis, potentially offering faster interpretation and results to empower superior intraoperative decision-making. CONCLUSIONS: Intraoperative OCT has strong potential to supplement current post-operative histopathology with real-time in situ assessment of LNs to preserve both non-cancerous nodes and their lymphatic vessels, and thus reduce the associated risks and complications from surgical disruption of lymphoid structures following biopsy.

Correction of aberrations in the human eye using computational methods.

Phase-sensitive imaging and computational correction of patient-specific optical aberrations enable high-resolution imaging of the human retina to aid diagnosis and treatment of eye diseases.

Polarization-sensitive interferometric synthetic aperture microscopy.

Three-dimensional optical microscopy suffers from the well-known compromise between transverse resolution and depth-of-field. This is true for both structural imaging methods and their functional extensions. Interferometric synthetic aperture microscopy (ISAM) is a solution to the 3D coherent microscopy inverse problem that provides depth-independent transverse resolution. We demonstrate the extension of ISAM to polarization sensitive imaging, termed polarization-sensitive interferometric synthetic aperture microscopy (PS-ISAM). This technique is the first functionalization of the ISAM method and provides improved depth-of-field for polarization-sensitive imaging. The basic assumptions of polarization-sensitive imaging are explored, and refocusing of birefringent structures is experimentally demonstrated. PS-ISAM enables high-resolution volumetric imaging of birefringent materials and tissue.

Real-time Imaging of the Resection Bed Using a Handheld Probe to Reduce Incidence of Microscopic Positive Margins in Cancer Surgery.

Wide local excision (WLE) is a common surgical intervention for solid tumors such as those in melanoma, breast, pancreatic, and gastrointestinal cancer. However, adequate margin assessment during WLE remains a significant challenge, resulting in surgical reinterventions to achieve adequate local control. Currently, no label-free imaging method is available for surgeons to examine the resection bed in vivo for microscopic residual cancer. Optical coherence tomography (OCT) enables real-time high-resolution imaging of tissue microstructure. Previous studies have demonstrated that OCT analysis of excised tissue specimens can distinguish between normal and cancerous tissues by identifying the heterogeneous and disorganized microscopic tissue structures indicative of malignancy. In this translational study involving 35 patients, a handheld surgical OCT imaging probe was developed for in vivo use to assess margins both in the resection bed and on excised specimens for the microscopic presence of cancer. The image results from OCT showed structural differences between normal and cancerous tissue within the resection bed following WLE of the human breast. The ex vivo images were compared with standard postoperative histopathology to yield sensitivity of 91.7% [95% confidence interval (CI), 62.5%-100%] and specificity of 92.1% (95% CI, 78.4%-98%). This study demonstrates in vivo OCT imaging of the resection bed during WLE with the potential for real-time microscopic image-guided surgery.

Computational high-resolution optical imaging of the living human retina.

High-resolution in vivo imaging is of great importance for the fields of biology and medicine. The introduction of hardware-based adaptive optics (HAO) has pushed the limits of optical imaging, enabling high-resolution near diffraction-limited imaging of previously unresolvable structures1,2. In ophthalmology, when combined with optical coherence tomography, HAO has enabled a detailed three-dimensional visualization of photoreceptor distributions3,4 and individual nerve fibre bundles5 in the living human retina. However, the introduction of HAO hardware and supporting software adds considerable complexity and cost to an imaging system, limiting the number of researchers and medical professionals who could benefit from the technology. Here we demonstrate a fully automated computational approach that enables high-resolution in vivo ophthalmic imaging without the need for HAO. The results demonstrate that computational methods in coherent microscopy are applicable in highly dynamic living systems.

Differentiation of ex vivo human breast tissue using polarization-sensitive optical coherence tomography.

Successful treatment of breast cancer typically requires surgical removal of the tumor. Optical coherence tomography (OCT) has been previously developed for real-time imaging of the surgical margin. However, it can be difficult to distinguish between normal stromal tissue and cancer tissue based on scattering intensity and structure alone. Polarization-sensitive optical coherence tomography (PS-OCT) is sensitive to form birefringence of biological tissue. We report on the development of a high-speed PS-OCT system and imaging of ex vivo human breast tissue, showing enhanced contrast between healthy and cancerous tissues based upon collagen content confirmed with corresponding histology. These results demonstrate the feasibility of using PS-OCT to supplement structural OCT as a possible method for intraoperative tumor margin evaluation.

Stability in computed optical interferometric tomography (part I): stability requirements.

As imaging systems become more advanced and acquire data at faster rates, increasingly dynamic samples can be imaged without concern of motion artifacts. For optical interferometric techniques such as optical coherence tomography, it often follows that initially, only amplitude-based data are utilized due to unstable or unreliable phase measurements. As systems progress, stable phase maps can also be acquired, enabling more advanced, phase-dependent post-processing techniques. Here we report an investigation of the stability requirements for a class of phase-dependent post-processing techniques - numerical defocus and aberration correction with further extensions to techniques such as Doppler, phase-variance, and optical coherence elastography. Mathematical analyses and numerical simulations over a variety of instabilities are supported by experimental investigations.

Stability in computed optical interferometric tomography (Part II): in vivo stability assessment.

Stability is of utmost importance to a wide range of phase-sensitive processing techniques. In Doppler optical coherence tomography and optical coherence elastography, in addition to defocus and aberration correction techniques such as interferometric synthetic aperture microscopy and computational/digital adaptive optics, a precise understanding of the system and sample stability helps to guide the system design and choice of imaging parameters. This article focuses on methods to accurately and quantitatively measure the stability of an imaging configuration in vivo. These methods are capable of partially decoupling axial from transverse motion and are compared against the stability requirements for computed optical interferometric tomography laid out in the first part of this article.

Three-dimensional motion correction using speckle and phase for in vivo computed optical interferometric tomography.

Over the years, many computed optical interferometric techniques have been developed to perform high-resolution volumetric tomography. By utilizing the phase and amplitude information provided with interferometric detection, post-acquisition corrections for defocus and optical aberrations can be performed. The introduction of the phase, though, can dramatically increase the sensitivity to motion (most prominently along the optical axis). In this paper, we present two algorithms which, together, can correct for motion in all three dimensions with enough accuracy for defocus and aberration correction in computed optical interferometric tomography. The first algorithm utilizes phase differences within the acquired data to correct for motion along the optical axis. The second algorithm utilizes the addition of a speckle tracking system using temporally- and spatially-coherent illumination to measure motion orthogonal to the optical axis. The use of coherent illumination allows for high-contrast speckle patterns even when imaging apparently uniform samples or when highly aberrated beams cannot be avoided.