Mapping nanoscale topographic features in thick tissues with speckle diffraction tomography

Kang et al. Light: Science & Applications (2023)12:200 https://doi.org/10.1038/s41377-023-01240-0 ARTICLE Official journal of the CIOMP 2047-7538 www.nature.com/lsa Open Access Mapping nanoscale topographic features in thick tissues with speckle diffraction tomography Sungsam Kang Zahid Yaqoob , Renjie Zhou2 ✉, Marten Brelen3, Heather K. Mak3, Yuechuan Lin1, Peter T. C. So 1,6 ✉ 1 1,4,5 and 1234567890():,; 1234567890():,; 1234567890():,; 1234567890():,; Abstract Resolving three-dimensional morphological features in thick specimens remains a significant challenge for label-free imaging. We report a new speckle diffraction tomography (SDT) approach that can image thick biological specimens with ~500 nm lateral resolution and ~1 μm axial resolution in a reflection geometry. In SDT, multiple-scattering background is rejected through spatiotemporal gating provided by dynamic speckle-field interferometry, while depthresolved refractive index maps are reconstructed by developing a comprehensive inverse-scattering model that also considers specimen-induced aberrations. Benefiting from the high-resolution and full-field quantitative imaging capabilities of SDT, we successfully imaged red blood cells and quantified their membrane fluctuations behind a turbid medium with a thickness of 2.8 scattering mean-free paths. Most importantly, we performed volumetric imaging of cornea inside an ex vivo rat eye and quantified its optical properties, including the mapping of nanoscale topographic features of Dua’s and Descemet’s membranes that had not been previously visualized. Introduction Quantitative phase imaging (QPI) has been developed to delineate structural and dynamical properties of transparent cells and thin tissues by exploring the intrinsic image contrast from refractive index (RI) and thickness variations1. As a label-free imaging method, QPI has enabled many unique biomedical studies2, such as elucidating cell growth mechanisms by quantifying mass changes at the femtogram level3,4, discriminating blood disease states5–8, and probing electrical activity through measuring nanometer-scale cell membrane fluctuations9–11. In addition, distinctive RI contrast between normal and abnormal cells and tissues has been reported for various diseases, demonstrating the potential of using RI as an intrinsic diagnostic biomarker12–15. Optical diffraction tomography (ODT)16,17 is an extension of QPI Correspondence: Renjie Zhou () or Zahid Yaqoob () 1 Laser Biomedical Research Center, G. R. Harrison Spectroscopy Laboratory, Massachusetts Institute of Technology, Cambridge, MA 02139, USA 2 Department of Biomedical Engineering, The Chinese University of Hong Kong, Hong Kong, China Full list of author information is available at the end of the article that enables volumetric imaging of biological samples by mapping their three-dimensional (3D) RI maps, therefore further advancing studies in cell organelle dynamics18,19, pharmacology20, immunology21, neuroscience22, and infectious disease pathology7. In ODT, multiple quantitative phase images are first measured under different conditions, including illumination angle17 or wavelength scanning23, translating sample laterally with a line focus beam24 or axially with the coherence-gating effect25. By solving an inverse-scattering problem while taking optical diffraction into consideration26, RI reconstructions are obtained from the complex field measurements, thus enabling the observation of high-resolution features in living cells27,28. The ability to image thick biological tissues in vivo is essential for many cutting-edge biological studies and clinical diagnostic applications29. However, most of the current ODT approaches are implemented using transmission geometry, which result in 3D optical transfer functions that suffer from limited axial frequency support at low lateral spatial frequencies. To better resolve axial features in 3D, one can solve the ill-posed problem by © The Author(s) 2023 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. Kang et al. Light: Science & Applications (2023)12:200 computationally extending information into the missingcone region via various regularization approaches30,31. Furthermore, conventional ODT methods only consider single-scattering fields by applying the first-order Born or Rytov approximation, thus limiting their applicability to studying weakly scattering objects27. Recently, technical advances have been made to overcome this barrier by considering the higher-order scattering fields in the reconstruction models32–35. However, due to the limitations of the reconstruction model and apparatus, ODT is still largely restricted to imaging thin objects such as cells and thin tissue slices. To allow for in vivo imaging with extended imaging depth, the following issues must be addressed: first, a full-field reflection-mode measurement geometry needs to be implemented; second, a comprehensive inverse-scattering model that accounts for the temporal dispersion and spatial aberration of the backscattered field from thick inhomogeneous media needs to be developed; and third, the multiple-scattering background needs to be suppressed to isolate the signal originating from a specific deep layer. In recent years, several reflection-mode QPI approaches have been developed to partially address these limitations by providing inherent depth-sectioning capability through the use of low temporal coherent light sources36, confocal detection37, and interference of speckle fields38. These reflection-mode QPI systems have been applied to observe cell membrane dynamics and to investigate the mechanical properties of cells6. To address the aberration and scattering inherently present in thick biological tissues, several 3D QPI techniques have been proposed, including automated computational aberration correction39, rejecting the multiple-scattering fields by accurately controlling the phase shift between the interfering waves40, reflection matrix-based computational adaptive optics41, and oblique back-illumination42. Here, we report a new reflection-mode 3D QPI method, termed speckle diffraction tomography (SDT), which enables quantification of depth-depende (...truncated)