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High-speed light-sheet microscopy for the in-situ acquisition of volumetric histological images of living tissue


Histological examinations typically require the excision of tissue, followed by its fixation, slicing, staining, mounting and imaging, with timeframes ranging from minutes to days. This process may remove functional tissue, may miss abnormalities through under-sampling, prevents rapid decision-making, and increases costs. Here, we report the feasibility of microscopes based on swept confocally aligned planar excitation technology for the volumetric histological imaging of intact living tissue in real time. The systems’ single-objective, light-sheet geometry and 3D imaging speeds enable roving image acquisition, which combined with 3D stitching permits the contiguous analysis of large tissue areas, as well as the dynamic assessment of tissue perfusion and function. Implemented in benchtop and miniaturized form factors, the microscopes also have high sensitivity, even for weak intrinsic fluorescence, allowing for the label-free imaging of diagnostically relevant histoarchitectural structures, as we show for pancreatic disease in living mice, for chronic kidney disease in fresh human kidney tissues, and for oral mucosa in a healthy volunteer. Miniaturized high-speed light-sheet microscopes for in-situ volumetric histological imaging may facilitate the point-of-care detection of diverse cellular-level biomarkers.

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Fig. 1: MediSCAPE system designs and image formation.
Fig. 2: Label-free imaging of a variety of fresh mouse tissues with MediSCAPE.
Fig. 3: In vivo mouse, label-free roving acquisition of pancreatic disease and the beating heart.
Fig. 4: Key diagnostic features in fresh human kidney tissue from a patient with chronic kidney disease.
Fig. 5: MediSCAPE 3D views of an atubular glomerulus in fresh kidney biopsy from a patient with CKD.
Fig. 6: In vivo imaging of human oral cavity.
Fig. 7: In vivo functional imaging of mouse brain and kidney.

Data availability

The main data supporting the results in this study are available within the paper and its Supplementary Information. The raw and analysed datasets generated during the study are too large to be publicly shared, yet they are available for research purposes from the corresponding authors on reasonable request.

Code availability

All custom MATLAB and ImageJ scripts used to process and stitch data are available from the authors upon request. Pairwise stitching code for stitching roving scans in ImageJ is available on the Hillman Lab GitHub


  1. Biopsy Devices - Global Analysis and Market Forecasts. 66 (GlobalData MediPoint, 2016).

  2. Jaafar, H. Intra-operative frozen section consultation: concepts, applications and limitations. Malays. J. Med. Sci. 13, 4–12 (2006).

    PubMed  PubMed Central  Google Scholar 

  3. Vieth, M., Ell, C., Gossner, L., May, A. & Stolte, M. Histological analysis of endoscopic resection specimens from 326 patients with Barrett’s esophagus and early neoplasia. Endoscopy 36, 776–781 (2004).

    CAS  PubMed  Article  Google Scholar 

  4. Wang, T. D. et al. Functional imaging of colonic mucosa with a fibered confocal microscope for real-time in vivo pathology. Clin. Gastroenterol. Hepatol. 5, 1300–1305 (2007).

    PubMed  PubMed Central  Article  Google Scholar 

  5. Goetz, M. & Kiesslich, R. Advances of endomicroscopy for gastrointestinal physiology and diseases. Am. J. Physiol. Gastrointest. Liver Physiol. 298, G797–G806 (2010).

    CAS  PubMed  Article  Google Scholar 

  6. van Dam, G. M. et al. Intraoperative tumour-specific fluorescence imaging in ovarian cancer by folate receptor-alpha targeting: first in-human results. Nat. Med. 17, 1315–1319 (2011).

    PubMed  Article  CAS  Google Scholar 

  7. Hsiung, P. L. et al. Detection of colonic dysplasia in vivo using a targeted heptapeptide and confocal microendoscopy. Nat. Med. 14, 454–458 (2008).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  8. Sun, Y. et al. Endoscopic fluorescence lifetime imaging for in vivo intraoperative diagnosis of oral carcinoma. Microsc. Microanal. 19, 791–798 (2013).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  9. Saar, B. G. et al. Video-rate molecular imaging in vivo with stimulated Raman scattering. Science 330, 1368–1370 (2010).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  10. Grosberg, L. E., Radosevich, A. J., Asfaha, S., Wang, T. C. & Hillman, E. M. Spectral characterization and unmixing of intrinsic contrast in intact normal and diseased gastric tissues using hyperspectral two-photon microscopy. PLoS ONE 6, e19925 (2011).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  11. You, S. et al. Intravital imaging by simultaneous label-free autofluorescence-multiharmonic microscopy. Nat. Commun. 9, 2125 (2018).

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  12. Orringer, D. A. et al. Rapid intraoperative histology of unprocessed surgical specimens via fibre-laser-based stimulated Raman scattering microscopy. Nat. Biomed. Eng. (2017).

  13. Hollon, T. C. et al. Near real-time intraoperative brain tumour diagnosis using stimulated Raman histology and deep neural networks. Nat. Med. 26, 52–58 (2020).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  14. Konig, K. et al. Clinical two-photon microendoscopy. Microsc. Res. Tech. 70, 398–402 (2007).

    CAS  PubMed  Article  Google Scholar 

  15. 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).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  16. Xu, L. et al. Widespread receptor-driven modulation in peripheral olfactory coding. Science (2020).

  17. 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).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  18. Vaadia, R. D. et al. Characterization of proprioceptive system dynamics in behaving Drosophila larvae using high-speed volumetric microscopy. Curr. Biol. 29, 935–944.e4 (2019).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  19. Hillman, E. M. et al. High-speed 3D imaging of cellular activity in the brain using axially-extended beams and light sheets. Curr. Opin. Neurobiol. 50, 190–200 (2018).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  20. Yin, C. et al. Miniature in vivo MEMS-based line-scanned dual-axis confocal microscope for point-of-care pathology. Biomed. Opt. Express 7, 251–263 (2016).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  21. Liu, J. T. et al. Point-of-care pathology with miniature microscopes. Anal. Cell Pathol. 34, 81–98 (2011).

    Article  Google Scholar 

  22. Flusberg, B. A. et al. Fiber-optic fluorescence imaging. Nat. Methods 2, 941–950 (2005).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  23. Husain, S. A. et al. Reproducibility of deceased donor kidney procurement biopsies. Clin. J. Am. Soc. Nephrol. 15, 257–264 (2020).

    PubMed  PubMed Central  Article  Google Scholar 

  24. Deal, J. et al. Identifying molecular contributors to autofluorescence of neoplastic and normal colon sections using excitation-scanning hyperspectral imaging. J. Biomed. Opt. 24, 1–11 (2018).

    PubMed  Article  Google Scholar 

  25. Pavlova, I., Williams, M., El-Naggar, A., Richards-Kortum, R. & Gillenwater, A. Understanding the biological basis of autofluorescence imaging for oral cancer detection: high-resolution fluorescence microscopy in viable tissue. Clin. Cancer Res. 14, 2396–2404 (2008).

    PubMed  PubMed Central  Article  Google Scholar 

  26. Hu, W. Y. & Fu, L. Simultaneous characterization of pancreatic stellate cells and other pancreatic components within three-dimensional tissue environment during chronic pancreatitis. J. Biomed. Opt. (2013).

  27. Hingorani, S. R. et al. Trp53R172H and KrasG12D cooperate to promote chromosomal instability and widely metastatic pancreatic ductal adenocarcinoma in mice. Cancer Cell 7, 469–483 (2005).

    CAS  PubMed  Article  Google Scholar 

  28. Preibisch, S., Saalfeld, S. & Tomancak, P. Globally optimal stitching of tiled 3D microscopic image acquisitions. Bioinformatics 25, 1463–1465 (2009).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  29. Siegel, R. L., Miller, K. D., Fuchs, H. E. & Jemal, A. Cancer statistics, 2021. CA Cancer J. Clin. 71, 7–33 (2021).

    PubMed  Article  Google Scholar 

  30. Thekkek, N. et al. Vital-dye enhanced fluorescence imaging of GI mucosa: metaplasia, neoplasia, inflammation. Gastrointest. Endosc. 75, 877–887 (2012).

    PubMed  PubMed Central  Article  Google Scholar 

  31. Giacomelli, M. G. et al. Virtual hematoxylin and eosin transillumination microscopy using epi-fluorescence imaging. PLoS ONE 11, e0159337 (2016).

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  32. Skala, M. C. et al. In vivo multiphoton microscopy of NADH and FAD redox states, fluorescence lifetimes, and cellular morphology in precancerous epithelia. Proc. Natl Acad. Sci. USA 104, 19494–19499 (2007).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  33. Liang, W., Hall, G., Messerschmidt, B., Li, M. J. & Li, X. Nonlinear optical endomicroscopy for label-free functional histology in vivo. Light Sci. Appl. (2017).

  34. Drezek, R. et al. Autofluorescence microscopy of fresh cervical-tissue sections reveals alterations in tissue biochemistry with dysplasia. Photochem. Photobiol. 73, 636–641 (2001).

    CAS  PubMed  Article  Google Scholar 

  35. Neira, J. A. et al. Aggressive resection at the infiltrative margins of glioblastoma facilitated by intraoperative fluorescein guidance. J. Neurosurg. 127, 111–122 (2017).

    PubMed  Article  Google Scholar 

  36. Miller, S. E. et al. First-in-human intraoperative near-infrared fluorescence imaging of glioblastoma using cetuximab-IRDye800. J. Neurooncol. 139, 135–143 (2018).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  37. Abeytunge, S. et al. Confocal microscopy with strip mosaicing for rapid imaging over large areas of excised tissue. J. Biomed. Opt. 18, 61227 (2013).

    PubMed  Article  Google Scholar 

  38. Giacomelli, M. G. et al. Comparison of nonlinear microscopy and frozen section histology for imaging of Mohs surgical margins. Biomed. Opt. Express 10, 4249–4260 (2019).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  39. Fereidouni, F. et al. Microscopy with ultraviolet surface excitation for rapid slide-free histology. Nat. Biomed. Eng. 1, 957–966 (2017).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  40. 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).

    PubMed  PubMed Central  Article  Google Scholar 

  41. Glaser, A. K. et al. Light-sheet microscopy for slide-free non-destructive pathology of large clinical specimens. Nat. Biomed. Eng. (2017).

  42. Abadie, S. et al. 3D imaging of cleared human skin biopsies using light-sheet microscopy: a new way to visualize in-depth skin structure. Skin Res. Technol. 24, 294–303 (2018).

    CAS  PubMed  Article  Google Scholar 

  43. Noe, M. et al. Immunolabeling of cleared human pancreata provides insights into three-dimensional pancreatic anatomy and pathology. Am. J. Pathol. 188, 1530–1535 (2018).

    PubMed  PubMed Central  Article  Google Scholar 

  44. Hillman, E. M. & Moore, A. All-optical anatomical co-registration for molecular imaging of small animals using dynamic contrast. Nat. Photonics 1, 526–530 (2007).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  45. Xing, J. Liu S. and Zhao, W. FPGA-accelerated real-time volume rendering for 3D medical image. 2010 3rd International Conference on Biomedical Engineering and Informatics (2010).

  46. Jin, K., Lee, K. & Kim, G. in 3rd IEEE International Conference on Computer and Communications (ICCC) 2085–2088 (2017).

  47. Rivenson, Y. et al. Virtual histological staining of unlabelled tissue-autofluorescence images via deep learning. Nat. Biomed. Eng. 3, 466–477 (2019).

    CAS  PubMed  Article  Google Scholar 

  48. Kester, R. T., Tkaczyk, T. S., Descour, M. R., Christenson, T. & Richards-Kortum, R. High numerical aperture microendoscope objective for a fibre confocal reflectance microscope. Opt. Express 15, 2409–2420 (2007).

    PubMed  Article  Google Scholar 

  49. Barretto, R. P., Messerschmidt, B. & Schnitzer, M. J. In vivo fluorescence imaging with high-resolution microlenses. Nat. Methods 6, 511–512 (2009).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  50. McCaslin, A. F., Chen, B. R., Radosevich, A. J., Cauli, B. & Hillman, E. M. In vivo 3D morphology of astrocyte-vasculature interactions in the somatosensory cortex: implications for neurovascular coupling. J. Cereb. Blood Flow Metab. 31, 795–806 (2011).

    CAS  PubMed  Article  Google Scholar 

  51. Preibisch, S., Saalfeld, S. & Tomancak, P. Globally optimal stitching of tiled 3D microscopic image acquisitions. Bioinformatics 25, 1463–1465 (2009).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  52. Schindelin, J. et al. Fiji: an open-source platform for biological-image analysis. Nat. Methods 9, 676–682 (2012).

    CAS  PubMed  Article  Google Scholar 

  53. Horl, D. et al. BigStitcher: reconstructing high-resolution image datasets of cleared and expanded samples. Nat. Methods 16, 870–874 (2019).

    PubMed  Article  CAS  Google Scholar 

Download references


We thank L. Hammond and D. Peterka at the Zuckerman Institute’s Cellular Imaging platform for help with confocal and slide imaging; the Histology Core facility services within the Molecular Pathology Shared Resource (CUMC Herbert Irving Comprehensive Cancer Center) for processing all histological samples; H. Remotti (Columbia) and J. Poneros (Columbia) for their support and valuable insights on possible application spaces; S. Sastra and C. Palermo (Columbia) for assistance with mouse pancreas experiments; M. Hortsch (University of Michigan Medical School) for sharing high-quality histology images of human tissues on their Virtual Microscopy Database (under CC BY-SA-NC); C. Kim and S. Kim for assistance with mouse work, and other members of the Hillman laboratory for their support and assistance, including H. Yu, W. Yan, M. Shaik, H. Yu, L. Grosberg and K. Stewart. Funding for this work was provided by the Columbia-Coulter Translational Research Partnership (37) and the Coulter Foundation Early Career programme to E.M.C.H.; the National Institutes of Health BRAIN initiative grants U01NS09429, UF1NS108213 to E.M.C.H. and U19NS104649 to R. Costa; NCI grant U01CA236554 to E.M.C.H. and D. Brenner; the National Science Foundation NSF-GRFP DGE - 1644869 to K.B.P., IGERT 0801530 to V.V. and CAREER CBET-0954796 to E.M.C.H.; the Simons Foundation Collaboration on the Global Brain 542951 to E.M.C.H.; the Department of Defense MURI W911NF-12-1-0594 to E.M.C.H.; and the Kavli Institute for Brain Science to E.M.C.H.

Author information

Authors and Affiliations



E.M.C.H. and K.B.P. conceived the use of MediSCAPE for clinical applications, planned experiments, analysed and discussed results. K.B.P., V.V. and E.M.C.H. designed and built the primary MediSCAPE system used in these studies, while the miniature MediSCAPE system was designed and built by W. Liang, M.J.C., K.B.P. and E.M.C.H. In vivo and fresh mouse tissue experiments were performed by K.B.P., M.J.C., W. Liang, W. Li, C.P.-C. and G.S.L., with assistance from H.T.Z. and Al.J.Y. Mouse pancreatic cancer models were provided by K.P.O. and imaged by K.B.P., Al.J.Y. and W. Liang. Human in vivo imaging was performed by M.J.C., W.Liang, W. Li, K.P.B. and E.M.C.H. Human tissue sample access, including regulatory documentation, was managed by S.M.C., who also provided extensive review of imaging data, histopathology and clinical interpretation of kidney and related images with K.B.P. K.P.O. provided extensive review and consultation on image interpretation for the pancreatic cancer data; An.J.Y. and E.P. provided consultation and review of human oral mucosa imaging. J.M.L. assisted with stitching stage-scans. Image analysis, stitching, rendering, figure and movie preparation were performed by K.B.P. and M.J.C. Manuscript was prepared and reviewed by K.B.P., E.M.C.H., S.M.C. and W. Liang.

Corresponding author

Correspondence to Elizabeth M. C. Hillman.

Ethics declarations

Competing interests

Columbia University holds intellectual property rights on SCAPE and MediSCAPE, some of which are licensed to Leica Microsystems. E.M.C.H., K.B.P., V.V., W. Li, W. Liang, G. S. Lee and C.P.C. could financially benefit from the commercial development of MediSCAPE. The other authors declare no competing interests.

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Nature Biomedical Engineering thanks Ralf Bauer, Matthias Gunzer and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Extended data

Extended Data Fig. 1 Dual colour autofluorescence visualization.

xy image planes acquired by MediSCAPE in fresh mouse brain cortex, including a prominent blood vessel. Contrast corresponds to autofluorescence excited by 488 nm light. Dual colour emission images are acquired simultaneously using an image splitter in front of the camera and positioning each colour channels side-by-side on the camera chip (along y). a and b show grayscale raw emission channels acquired with 525/50 nm and 618/50 nm bandpass filters respectively. These channels are converted to c, ‘yellow hot’ and d, blue colormaps and then merged, as shown in e. This colour-scheme was chosen to enable the highly overlapping colour channels to be more easily distinguished when merged than conventional RBG scaling, while also being more colour-blind accessible. Scale bars, 100 µm.

Extended Data Fig. 2 Label-free imaging of fresh mouse tissue with miniaturized MediSCAPE.

xy (top) and yz (bottom) cross-sections in various fresh mouse tissue acquired with the miniaturized MediSCAPE system with 488 nm excitation and dual colour emission channels labelled as shown. Cross- sections show a, tubules in the kidney cortex, b, capsule and underlying cords of hepatocytes in the liver, c, cardiac muscle in the heart and d, crypts of Lieberkühn in the colon mucosa. White dotted lines in the xy planes indicate the location of corresponding yz planes shown. e. 3D rendering (Imaris) of a stitched field of view created from 16 seconds of continuous volume acquisition at 11.2 VPS while roving across the colon mucosa. Insets to the right show single planes from the ROI indicated (yellow dotted box). Yellow dotted lines in the xy cross-section show the locations of corresponding depth cross- sections. Only emission at ~525 nm is shown here, in grayscale. All scale bars, 100 µm.

Extended Data Fig. 3 Autofluorescence in diabetic human kidney tissue imaged with MediSCAPE.

Autofluorescence captured by MediSCAPE reveals features common to and beyond those seen on routine histology. a, PAS histology image of kidney cortex tissue from an older, diabetic patient with features of mild diabetic nephropathy. Scale bar, 200 µm. b, a MediSCAPE xy slice from a stage-scanned volume of the same piece of tissue (while fresh) showing autofluorescence excited at 488 nm. Yellow arrows point to the kidney capsule, white arrows indicate urinary casts, seen in both SCAPE and PAS images. Dotted line squares indicate regions of interest shown in more detail in c, highlighting features more evident by SCAPE than PAS histology. Scale bar, 200 µm. c(i), A focal subcapsular collection of tubules with autofluorescent cytoplasmic granules (teal arrow). Urinary cast material (white arrows) is also evident in the xy plane, and further evidenced by characteristically strong autofluorescence in the yz plane. c(ii). Tubules with accentuated peritubular autofluorescence (red arrow). c(iii) Glomerulus with focal autofluorescent granules. Scale bars, 50 µm.

Extended Data Fig. 4 MediSCAPE label-free imaging of elastic fibres and fat cells in human perirenal fat.

a, 3D rendering (ImageJ 3DViewer) of a section of normal human perirenal fat showing highly fluorescent elastic fibres and fat cells. b, a yz cross-section from the plane indicated shows layering of fibres over fat cells, which can be distinguished as circular yellow droplets. c, lateral cross-sections with corresponding tissue depth indicated on the bottom left corner. Fat cells are indicated with red arrows and intersecting vessels also labelled. All scale bars, 100 µm.

Extended Data Fig. 5 MediSCAPE images of proflavine-stained fresh human kidney biopsy including pseudocolour H&E.

a, xy slice in a stage-scanned field of view showing proflavine, a nuclear dye (green), and red autofluorescence emission (blue), both acquired simultaneously with 488 nm excitation. Autofluorescence is shown on a log scale for better visualization. b, Pseudocolored xy slice from panel a, approximating H&E histology with proflavine shown in purple and autofluorescence shown in pink. c, Inset showing a glomerulus (white arrow) and tubules in greater detail with true H&E histology of an adjacent region shown in d for comparison. See Supplementary Movie 10 for a depth fly-through. All scale bars, 100 µm.

Extended Data Fig. 6 Stained human kidney tissues imaged with MediSCAPE.

Fresh human kidney tissues showing features of arterionephrosclerosis were stained with nuclear dye, either b, 1% methylene blue (exc. 637 nm, em. >685 nm) or d-k, 0.01% proflavine (exc. 488 nm, em. 525/50 nm). imaged by MediSCAPE, then processed for histology where the same tissue block faces were stained with PAS and/or H&E. a-c, demonstrate how the 4 main renal histologic components which must be routinely evaluated with both PAS and H&E histology appear in a, PAS histology, b, an xy slice of a MediSCAPE volume stained with methylene blue and c, H&E histology. These components are indicated as following: glomeruli (white arrows), arteries (red arrows), tubules (black arrows), and interstitium (blue arrows). Methylene blue in the MediSCAPE image defines cellular cytoplasmic, nuclear and extracellular compartments, similar to H&E but better highlights arterial elastic lamina and tubular and interstitial compartments, similar to PAS histologic sections. A second biopsy piece from the same patient shows scarred tubulointerstitium in a focal area of fibrosis (green arrows) in both d, MediSCAPE and e, corresponding H&E histology. f, a 3D rendering (Imaris) of the larger stage-scanned volume acquired on MediSCAPE, shows the 3D structure of fibrosis (green arrow), arteries and glomeruli (white arrows). The lengthwise white dotted line indicates the origin of the xz depth section shown in g. h, A non-sclerotic glomerulus is shown in more detail across 20um in depth. See Supplementary Movie 11 for a moving 3D render and depth fly-throughs of lateral and depth cross-sections of the full 3D volume. A second region of the same tissue shows i, globally- sclerotic glomeruli (yellow arrows) and urinary casts (light blue arrow) in a xy slice and depth slice taken at the white dotted line. j, H&E histology of a deeper section of the same region and k, MediSCAPE xy cross-section of the entire stage-scanned volume also shows globally-sclerotic glomeruli (yellow arrows) and normal glomeruli (white arrows). All scale bars, 100 µm.

Extended Data Fig. 7 Comparison of topical dyes applied to fresh mouse colon mucosa.

Single xy (top) and yz (bottom) slices in samples of fresh mouse colon mucosa imaged with MediSCAPE. Contrast is derived from a, 0.01% proflavine, a nuclear dye (exc. 488 nm, em. 525/50 nm), b, 1% methylene blue, a clinically-used nuclear dye (exc. 637 nm, em. >685 nm), and c, fluorescein sodium, an FDA-approved topical and IV dye (exc. 488 nm, em. 525/50 nm). Yellow dotted lines indicate locations of corresponding cross-sections and yellow arrows indicate nuclei in insets. Depth penetration of topically applied dyes is both stain- and tissue-dependent, as shown in yz depth sections. Also shown for comparison is d, autofluorescence (exc. 488 nm, em. 525/50 nm) imaged with MediSCAPE with e, corresponding en face and depth-sectioned H&E histology of a similar region in the same colon tissue. White arrows, crypts of Lieberkühn. Red arrows, goblet cells. Scale bars 100 µm.

Supplementary information

Supplementary Information

Supplementary Notes 1 and 2, Movies 1–18, Tables 1 and 2, and References.

Reporting Summary

Supplementary Movie 1

Fresh mouse kidney imaged with low and high magnification on MediSCAPE.

Supplementary Movie 2

Autofluorescence in fresh mouse heart, brain, lung and liver imaged with MediSCAPE.

Supplementary Movie 3

Autofluorescence in fresh mouse spleen, bladder, muscle and colon imaged with MediSCAPE.

Supplementary Movie 4

Autofluorescence in normal pancreas and pancreatic ductal adenocarcinoma (PDA) imaged with MediSCAPE.

Supplementary Movie 5

Fresh mouse kidney, liver, heart and colon imaged with a miniaturized version of MediSCAPE.

Supplementary Movie 6

Label-free in vivo mouse kidney imaged with MediSCAPE at 9.3 VPS.

Supplementary Movie 7

Stitched roving scan of in vivo label-free pancreatic tissue in a mouse model of pancreatic ductal adenocarcinoma (PDA) imaged with MediSCAPE.

Supplementary Movie 8

Label-free MediSCAPE imaging of in vivo mouse heart imaged at 12.9 VPS.

Supplementary Movie 9

MediSCAPE autofluorescence image of fresh human kidney biopsy with chronic kidney disease.

Supplementary Movie 10

3D H&E pseudocolour MediSCAPE image stack of fresh normal human kidney tissue stained with proflavine.

Supplementary Movie 11

A 3D rendering and flythrough of proflavine-stained human kidney tissue imaged with MediSCAPE.

Supplementary Movie 12

3D rendering of MediSCAPE roving data acquired in vivo on the human tongue.

Supplementary Movie 13

3D rendering of stitched MediSCAPE roving data acquired in vivo on the human tongue.

Supplementary Movie 14

3D rendering of MediSCAPE roving data acquired in vivo on the human lip.

Supplementary Movie 15

Depth flythrough of mini-MediSCAPE roving data acquired in vivo on the human tongue and inner lip.

Supplementary Movie 16

Roving MediSCAPE imaging of in vivo mouse brain vasculature with IV FITC-dextran.

Supplementary Movie 17

In vivo time lapse of ischaemia-reperfusion in mouse kidney acquired with MediSCAPE.

Supplementary Movie 18

In vivo imaging of FNa infusion in mouse kidney in real-time with MediSCAPE.

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Patel, K.B., Liang, W., Casper, M.J. et al. High-speed light-sheet microscopy for the in-situ acquisition of volumetric histological images of living tissue. Nat. Biomed. Eng 6, 569–583 (2022).

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