High-throughput optical imaging is playing an increasingly important role in biological imaging. The technique enables biological dynamics to be studied at a variety of different spatiotemporal scales.1–3 One area that is poised to benefit from this capability is the study of collective or emergent behavior in embryonic development, tissue regeneration, and cancer.4, 5 Existing modalities for high-speed volumetric imaging at cellular or sub-cellular resolution are typically based on the detection of fluorescence signals. Consequently, they are subject to photobleaching and phototoxicity constraints and, as a result of this, have limited scope in settings that preclude the use of exogenous contrast agents (e.g., many clinical settings).
Our approach for high-throughput volumetric OCM is designed to provide uniform high resolution and signal-to-noise ratio (SNR) over depth without requiring a time-consuming scan of the focus. We have employed an astigmatic optical system to equalize signal collection versus depth, combined with CAO to compensate the resolution penalty that usually accompanies imaging with astigmatic optics.
Interferometric detection with OCT allows the complex optical field that is backscattered from within a sample (due to spatial variations in the refractive index) to be measured. An OCT dataset can therefore be treated as a digital hologram.11 As in digital holography,12, 13 this allows optical image formation and optimization to continue after data acquisition.14–16 CAO provides a method by which aberration correction can be carried out via numerical manipulation of the Fourier domain of an OCT dataset.17 This is analogous to the operation of hardware adaptive optics (HAO), in which the phase of the Fourier domain signal is physically manipulated at the time of imaging. As with HAO, CAO can be applied in ‘sensorless mode’ by using image metrics to optimize the correction,17 in ‘guide-star mode’ (in which point-like scatterers in the sample are used to sense the aberrations present),18, 19 and via the implementation of a sub-aperture wavefront-sensing method.20
We have found that CAO can also be leveraged to provide an alternative approach by which to address the problem of reduced signal collection with increased distance from the point of focus.17, 23 The ability to correct aberration effects after data is acquired relaxes the typical aberration-free design constraints on optical systems. These systems can instead be designed for optimal signal collection versus depth. We compared the resolution and signal strength of reconstructed data acquired with a standard Gaussian beam—see Figure 2(a)—to our astigmatic optical system: see Figure 2(b). Although the use of CAO-OCM reconstruction on both of these systems offers comparable resolution—see Figure 2(c)—the astigmatic system offers an overall SNR advantage for imaging over a relatively large (∼ 1mm) depth range: see Figure 2(d). This advantage occurs as a result of the ability to adjust the axial separation of the two astigmatic line foci and thereby enhance photon collection at these depths. Although photon collection is reduced at the nominal Gaussian beam focal plane, an SNR improvement can be seen at both shallower (<800μm) and deeper (>1200μm) positions in the sample, resulting in an overall reduction to the signal dynamic range. This increases the depth range over which volumetric imaging with uniform high resolution and SNR can be achieved.
We have shown that CAO can help facilitate large-volume OCM imaging by leveraging aberrated optical-system design to optimize photon collection across all depths. This imaging paradigm could enable high-throughput volumetric OCM with isotropic cellular resolution over millimeter-scale 3D fields of view. With further work, this could enable the use of OCM for volumetric imaging of emergent behavior in embryonic development, tissue regeneration, and cancer. The system could also serve as a multimodal bridge by which to connect label-free methods and existing high-throughput fluorescence-imaging techniques. In our future work, we aim to leverage high-throughput volumetric OCM for the study of collective cell migration dynamics in 3D environments.
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