An end-to-end workflow for nondestructive 3D pathology

Adam K. Glaser, Jonathan T. C. Liu, Joshua C. Vaughan, Kevin W. Bishop, Lindsey A. Erion Barner, Qinghua Han, Elena Baraznenok, Lydia Lan, Chetan Poudel, Gan Gao, Robert B. Serafin, Sarah S. L. Chow, Andrew Janowczyk, David Brenes, Hongyi Huang, Dominie Miyasato, Lawrence D. True, Soyoung Kang

Published: 2024-01-23 DOI: 10.1038/s41596-023-00934-4

data processing

3D pathology

light-sheet microscopy

tissue preparation

fluorescent staining

AI 解读

Generation of mouse–human chimeric embryos

Genome-wide quantification of transcription factor binding at single-DNA-molecule resolution using methyl-transferase footprinting

Generation of CRISPR–Cas9-mediated genetic knockout human intestinal tissue–derived enteroid lines by lentivirus transduction and single-cell cloning

A puromycin-dependent activity-based sensing probe for histochemical staining of hydrogen peroxide in cells and animal tissues

Decoding personal biotic and abiotic airborne exposome

A clinically relevant model of focal embolic cerebral ischemia by thrombus and thrombolysis in rhesus monkeys

Bioengineering human intestinal mucosal grafts using patient-derived organoids, fibroblasts and scaffolds

Biomimetic tail-to-head terpene cyclizations using the resorcin[4]arene capsule catalyst

Neuroscience robotics for controlled induction and real-time assessment of hallucinations

Scanorama: integrating large and diverse single-cell transcriptomic datasets

Single-cell RNA sequencing (scRNA-seq)（单细胞RNA测序）

Data integration（数据集成）

Heterogeneity（异质性）

查看全部

Sections

Figures

References

Hinton, J. P. et al. A method to reuse archived H&E stained histology slides for a multiplex protein biomarker analysis. Methods Protoc. 2, 86 (2019).
Liu, J. T. C. et al. Harnessing non-destructive 3D pathology. Nat. Biomed. Eng. 5, 203–218 (2021).
Liu, J. T. C., Glaser, A. K., Poudel, C. & Vaughan, J. C. Nondestructive 3D pathology with light-sheet fluorescence microscopy for translational research and clinical assays. Annu. Rev. Anal. Chem. 16, 231–252 (2023).
Xie, W. et al. Prostate cancer risk stratification via nondestructive 3D pathology with deep learning–assisted gland analysis. Cancer Res. 82, 334–345 (2022).
Serafin, R. et al. Nondestructive 3D pathology with analysis of nuclear features for prostate cancer risk assessment. J. Pathol. 260, 390–401 (2023).
Erion Barner, L. A. et al. AI-triaged 3D pathology to improve detection of esophageal neoplasia while reducing pathologist workloads. Mod. Pathol. 36, 100322 (2023).
Klingberg, A. et al. Fully automated evaluation of total glomerular number and capillary tuft size in nephritic kidneys using lightsheet microscopy. J. Am. Soc. Nephrol. 28, 452–459 (2017).
Ertürk, A. et al. Three-dimensional imaging of solvent-cleared organs using 3DISCO. Nat. Protoc. 7, 1983–1995 (2012).
Renier, N. et al. iDISCO: a simple, rapid method to immunolabel large tissue samples for volume imaging. Cell 159, 896–910 (2014).
McGorty, R. et al. Open-top selective plane illumination microscope for conventionally mounted specimens. Opt. Express 23, 16142–16153 (2015).
McGorty, R., Xie, D. & Huang, B. High-NA open-top selective-plane illumination microscopy for biological imaging. Opt. Express 25, 17798–17810 (2017).
Glaser, A. K. et al. Light-sheet microscopy for slide-free non-destructive pathology of large clinical specimens. Nat. Biomed. Eng. 1, 1–10 (2017).
Glaser, A. K. et al. Multi-immersion open-top light-sheet microscope for high-throughput imaging of cleared tissues. Nat. Commun. 10, 2781 (2019).
Barner, L. A., Glaser, A. K., Huang, H., True, L. D. & Liu, J. T. C. Multi-resolution open-top light-sheet microscopy to enable efficient 3D pathology workflows. Biomed. Opt. Express 11, 6605–6619 (2020).
Glaser, A. K. et al. A hybrid open-top light-sheet microscope for versatile multi-scale imaging of cleared tissues. Nat. Methods 19, 613–619 (2022).
Power, R. M. & Huisken, J. A guide to light-sheet fluorescence microscopy for multiscale imaging. Nat. Methods 14, 360–373 (2017).
Hillman, E. M. C., Voleti, V., Li, W. & Yu, H. Light-sheet microscopy in neuroscience. Annu. Rev. Neurosci. 42, 295–313 (2019).
Stelzer, E. H. K. et al. Light sheet fluorescence microscopy. Nat. Rev. Methods Prim. 1, 1–25 (2021).
Daetwyler, S. & Fiolka, R. P. Light-sheets and smart microscopy, an exciting future is dawning. Commun. Biol. 6, 1–11 (2023).
Dunsby, C. Optically sectioned imaging by oblique plane microscopy. Opt. Express 16, 20306–20316 (2008).
Li, T. et al. Axial plane optical microscopy. Sci. Rep. 4, 7253 (2014).
Bouchard, M. B. et al. Swept confocally-aligned planar excitation (SCAPE) microscopy for high-speed volumetric imaging of behaving organisms. Nat. Photonics 9, 113–119 (2015).
Kumar, M., Kishore, S., Nasenbeny, J., McLean, D. L. & Kozorovitskiy, Y. Integrated one- and two-photon scanned oblique plane illumination (SOPi) microscopy for rapid volumetric imaging. Opt. Express 26, 13027–13041 (2018).
Voleti, V. et al. Real-time volumetric microscopy of in vivo dynamics and large-scale samples with SCAPE 2.0. Nat. Methods 16, 1054–1062 (2019).
Yang, B. et al. Epi-illumination SPIM for volumetric imaging with high spatial-temporal resolution. Nat. Methods 16, 501–504 (2019).
Millett-Sikking, A. & York, A. AndrewGYork/high_na_single_objective_lightsheet: Work-in-progress. Available at http://zenodo.org/records/3376243 (2019).
Hoffmann, M. & Judkewitz, B. Diffractive oblique plane microscopy. Optica 6, 1166–1170 (2019).
Kim, J. et al. Oblique-plane single-molecule localization microscopy for tissues and small intact animals. Nat. Methods 16, 853–857 (2019).
Sapoznik, E. et al. A versatile oblique plane microscope for large-scale and high-resolution imaging of subcellular dynamics. eLife 9, e57681 (2020).
Yang, B. et al. DaXi—high-resolution, large imaging volume and multi-view single-objective light-sheet microscopy. Nat. Methods 19, 461–469 (2022).
Bria, A. & Iannello, G. TeraStitcher—a tool for fast automatic 3D-stitching of teravoxel-sized microscopy images. BMC Bioinforma. 13, 316 (2012).
Scholler, J. et al. Efficient image analysis for large-scale next generation histopathology using pAPRica. Preprint at bioRxiv http://doi.org/10.1101/2023.01.27.525687 (2023).
The HDF Group, N. & Koziol, Q. HDF5-Version 1.12.0. http://www.osti.gov/biblio/1631295 (2020).
Miles, A. et al. zarr-developers/zarr-python: v2.16.0. http://zenodo.org/records/8169545 (2023).
Moore, J. et al. OME-NGFF: a next-generation file format for expanding bioimaging data-access strategies. Nat. Methods 18, 1496–1498 (2021).
Saalfeld, S. et al. saalfeldlab/n5: n5-2.5.1. http://zenodo.org/records/6578232 (2022).
Hörl, D. et al. BigStitcher: reconstructing high-resolution image datasets of cleared and expanded samples. Nat. Methods 16, 870–874 (2019).
Schindelin, J. et al. Fiji: an open-source platform for biological-image analysis. Nat. Methods 9, 676–682 (2012).
Elfer, K. N. et al. DRAQ5 and eosin (‘D&E’) as an analog to hematoxylin and eosin for rapid fluorescence histology of fresh tissues. PLoS One 11, e0165530 (2016).
Rivenson, Y., de Haan, K., Wallace, W. D. & Ozcan, A. Emerging advances to transform histopathology using virtual staining. BME Front. 2020, 9647163 (2020).
Chen, Z., Yu, W., Wong, I. H. M. & Wong, T. T. W. Deep-learning-assisted microscopy with ultraviolet surface excitation for rapid slide-free histological imaging. Biomed. Opt. Express 12, 5920–5938 (2021).
Boktor, M. et al. Virtual histological staining of label-free total absorption photoacoustic remote sensing (TA-PARS). Sci. Rep. 12, 10296 (2022).
Yang, X. et al. Virtual stain transfer in histology via cascaded deep neural networks. ACS Photonics 9, 3134–3143 (2022).
Rana, A. et al. Use of deep learning to develop and analyze computational hematoxylin and eosin staining of prostate core biopsy images for tumor diagnosis. JAMA Netw. Open 3, e205111 (2020).
Giacomelli, M. G. et al. Virtual hematoxylin and eosin transillumination microscopy using epi-fluorescence imaging. PLoS One 11, e0159337 (2016).
Serafin, R., Xie, W., Glaser, A. K. & Liu, J. T. C. FalseColor-Python: a rapid intensity-leveling and digital-staining package for fluorescence-based slide-free digital pathology. PLoS One 15, e0233198 (2020).
Ahlers, J. et al. napari: a multi-dimensional image viewer for Python. http://zenodo.org/records/8115575 (2023).
Bankhead, P. et al. QuPath: open source software for digital pathology image analysis. Sci. Rep. 7, 16878 (2017).
Jansen, I. et al. Three-dimensional histopathological reconstruction of bladder tumours. Diagn. Pathol. 14, 25 (2019).
Liimatainen, K., Latonen, L., Valkonen, M., Kartasalo, K. & Ruusuvuori, P. Virtual reality for 3D histology: multi-scale visualization of organs with interactive feature exploration. BMC Cancer 21, 1133 (2021).
Barner, L. A., Glaser, A. K., True, L. D., Reder, N. P. & Liu, J. T. C. Solid immersion meniscus lens (SIMlens) for open-top light-sheet microscopy. Opt. Lett. 44, 4451–4454 (2019).
Barner, L. A. et al. Multiresolution nondestructive 3D pathology of whole lymph nodes for breast cancer staging. J. Biomed. Opt. 27, 036501 (2022).
Reder, N. P. et al. Open-top light-sheet microscopy image atlas of prostate core needle biopsies. Arch. Pathol. Lab. Med. 143, 1069–1075 (2019).
Reddi, D. M. et al. Nondestructive 3D pathology image atlas of Barrett esophagus with open-top light-sheet microscopy. Arch. Pathol. Lab. Med. 147, 1164–1171 (2023).
Horowitz, L. F. et al. Microdissected “cuboids” for microfluidic drug testing of intact tissues. Lab Chip 21, 122–142 (2021).
Bera, K., Schalper, K. A., Rimm, D. L., Velcheti, V. & Madabhushi, A. Artificial intelligence in digital pathology—new tools for diagnosis and precision oncology. Nat. Rev. Clin. Oncol. 16, 703–715 (2019).
Lee, M. Y. et al. Fluorescent labeling of abundant reactive entities (FLARE) for cleared-tissue and super-resolution microscopy. Nat. Protoc. 17, 819–846 (2022).
Gao, G. et al. Comprehensive surface histology of fresh resection margins with rapid Open-Top Light-Sheet (OTLS) microscopy. IEEE Trans. Biomed. Eng. 70, 2160–2171 (2023).
Huisman, A., Ploeger, L. S., Dullens, H. F. J., Beekhuis, J. T. C. & van Diest, P. J. A restaining method to restore faded fluorescence in tissue specimens for quantitative confocal microscopy. Cytom. A 71, 875–881 (2007).
Mayerich, D., Abbott, L. & McCormick, B. Knife-edge scanning microscopy for imaging and reconstruction of three-dimensional anatomical structures of the mouse brain. J. Microsc. 231, 134–143 (2008).
Li, A. et al. Micro-optical sectioning tomography to obtain a high-resolution atlas of the mouse brain. Science 330, 1404–1408 (2010).
Gong, H. et al. Continuously tracing brain-wide long-distance axonal projections in mice at a one-micron voxel resolution. NeuroImage 74, 87–98 (2013).
Wong, T. T. W. et al. Label-free automated three-dimensional imaging of whole organs by microtomy-assisted photoacoustic microscopy. Nat. Commun. 8, 1386 (2017).
Yu, W. et al. Translational rapid ultraviolet-excited sectioning tomography for whole-organ multicolor imaging with real-time molecular staining. eLife 11, e81015 (2022).
Kolluru, C. et al. Imaging peripheral nerve micro-anatomy with MUSE, 2D and 3D approaches. Sci. Rep. 12, 10205 (2022).
Chen, Y. et al. Rapid pathology of lumpectomy margins with open-top light-sheet (OTLS) microscopy. Biomed. Opt. Express 10, 1257–1272 (2019).
Murray, E. et al. Simple, scalable proteomic imaging for high-dimensional profiling of intact systems. Cell 163, 1500–1514 (2015).
Kim, S.-Y. et al. Stochastic electrotransport selectively enhances the transport of highly electro molecules. Proc. Natl Acad. Sci. USA 112, E6274–E6283 (2015).
Park, Y.-G. et al. Protection of tissue physicochemical properties using polyfunctional crosslinkers. Nat. Biotechnol. 37, 73–83 (2019).
Zhao, S. et al. Cellular and molecular probing of intact human organs. Cell 180, 796–812.e19 (2020).
Ku, T. et al. Elasticizing tissues for reversible shape transformation and accelerated molecular labeling. Nat. Methods 17, 609–613 (2020).
Susaki, E. A. et al. Versatile whole-organ/body staining and imaging based on electrolyte-gel properties of biological tissues. Nat. Commun. 11, 1982 (2020).
Belle, M. et al. A simple method for 3D analysis of immunolabeled axonal tracts in a transparent nervous system. Cell Rep. 9, 1191–1201 (2014).
Pan, C. et al. Shrinkage-mediated imaging of entire organs and organisms using uDISCO. Nat. Methods 13, 859–867 (2016).
Cai, R. et al. Whole-mouse clearing and imaging at the cellular level with vDISCO. Nat. Protoc. 18, 1197–1242 (2023).
Weiss, K. R., Voigt, F. F., Shepherd, D. P. & Huisken, J. Tutorial: practical considerations for tissue clearing and imaging. Nat. Protoc. 16, 2732–2748 (2021).
Laurino, A. et al. A guide to perform 3D histology of biological tissues with fluorescence microscopy. Int. J. Mol. Sci. 24, 6747 (2023).
Susaki, E. A. et al. Whole-brain imaging with single-cell resolution using chemical cocktails and computational analysis. Cell 157, 726–739 (2014).
Tainaka, K. et al. Whole-body imaging with single-cell resolution by tissue decolorization. Cell 159, 911–924 (2014).
Susaki, E. A. et al. Advanced CUBIC protocols for whole-brain and whole-body clearing and imaging. Nat. Protoc. 10, 1709–1727 (2015).
Jing, D. et al. Tissue clearing of both hard and soft tissue organs with the PEGASOS method. Cell Res. 28, 803–818 (2018).
Liu, Y., Levenson, R. M. & Jenkins, M. W. Slide over: advances in slide-free optical microscopy as drivers of diagnostic pathology. Am. n J. Pathol. 192, 180–194 (2022).
Abeytunge, S. et al. Confocal microscopy with strip mosaicing for rapid imaging over large areas of excised tissue. J. Biomed. Opt. 18, 61227 (2013).
Tao, Y. K. et al. Assessment of breast pathologies using nonlinear microscopy. Proc. Natl Acad. Sci. USA 111, 15304–15309 (2014).
Tu, H. et al. Stain-free histopathology by programmable supercontinuum pulses. Nat. Photonics 10, 534–540 (2016).
Yoshitake, T. et al. Direct comparison between confocal and multiphoton microscopy for rapid histopathological evaluation of unfixed human breast tissue. J. Biomed. Opt. 21, 126021 (2016).
van Royen, M. E. et al. Three-dimensional microscopic analysis of clinical prostate specimens. Histopathology 69, 985–992 (2016).
Olson, E., Levene, M. J. & Torres, R. Multiphoton microscopy with clearing for three dimensional histology of kidney biopsies. Biomed. Opt. Express 7, 3089–3096 (2016).
Balázs, B., Deschamps, J., Albert, M., Ries, J. & Hufnagel, L. A real-time compression library for microscopy images. Preprint at bioRxiv http://doi.org/10.1101/164624 (2017).
Di, S. & Cappello, F. Fast error-bounded lossy HPC data compression with SZ. 2016 IEEE International Parallel and Distributed Processing Symposium (IPDPS) (pp. 730–739. IEEE, Piscataway, New Jersey, USA, 2016).
Masselink, W. et al. Broad applicability of a streamlined ethyl cinnamate-based clearing procedure. Development 146, dev166884 (2019).
ven der Walt, S. et al. scikit-image: image processing in Python. PeerJ 2, e453 (2014).
Gohlke, C. cgohlke/tifffile: v2023.7.18. http://zenodo.org/record/8165780 (2023).
Harris, C. R. et al. Array programming with NumPy. Nature 585, 357–362 (2020).
Crameri, F., Shephard, G. E. & Heron, P. J. The misuse of colour in science communication. Nat. Commun. 11, 5444 (2020).
Hunter, J. D. Matplotlib: a 2D graphics environment. Comput. Sci. Eng. 9, 90–95 (2007).

An end-to-end workflow for nondestructive 3D pathology

Supplementary information

Supplementary Information

Reporting Summary

Supplementary Video

推荐阅读