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. 2020 Oct 19;10(1):17619.
doi: 10.1038/s41598-020-71737-w.

3D histopathology of human tumours by fast clearing and ultramicroscopy

Inna Sabdyusheva Litschauer  1   2 , Klaus Becker  3   4 , Saiedeh Saghafi  3   4 , Simone Ballke  5 , Christine Bollwein  5 , Meraaj Foroughipour  3   4 , Julia Gaugeler  3   4 , Massih Foroughipour  3   4 , Viktória Schavelová  3   4 , Viktória László  6 , Balazs Döme  6 , Christine Brostjan  6 , Wilko Weichert  5 , Hans-Ulrich Dodt  7   8
Affiliations

3D histopathology of human tumours by fast clearing and ultramicroscopy

Inna Sabdyusheva Litschauer et al. Sci Rep. .

Abstract

Here, we describe a novel approach that allows pathologists to three-dimensionally analyse malignant tissues, including the tumour-host tissue interface. Our visualization technique utilizes a combination of ultrafast chemical tissue clearing and light-sheet microscopy to obtain virtual slices and 3D reconstructions of up to multiple centimetre sized tumour resectates. For the clearing of tumours we propose a preparation technique comprising three steps: (a) Fixation and enhancement of tissue autofluorescence with formalin/5-sulfosalicylic acid. (b) Ultrafast active chemical dehydration with 2,2-dimethoxypropane and (c) refractive index matching with dibenzyl ether at up to 56 °C. After clearing, the tumour resectates are imaged. The images are computationally post-processed for contrast enhancement and artefact removal and then 3D reconstructed. Importantly, the sequence a-c is fully reversible, allowing the morphological correlation of one and the same histological structures, once visualized with our novel technique and once visualized by standard H&E- and IHC-staining. After reverting the clearing procedure followed by standard H&E processing, the hallmarks of ductal carcinoma in situ (DCIS) found in the cleared samples could be successfully correlated with the corresponding structures present in H&E and IHC staining. Since the imaging of several thousands of optical sections is a fast process, it is possible to analyse a larger part of the tumour than by mechanical slicing. As this also adds further information about the 3D structure of malignancies, we expect that our technology will become a valuable addition for histological diagnosis in clinical pathology.

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Conflict of interest statement

The authors declare no competing interests.

Figures

Figure 1
Figure 1
Tissue processing with pathoDISCO. (a) Workflow of reversible tissue clearing and 3D-imaging of the solid tumours. (b) Volume shrinkage comparison (in %) for samples, cleared with pathoDISCO and 3DISCO (n = 16). (c) Timeline of tissue processing from surgery to 3D-reconstruction.
Figure 2
Figure 2
Ultramicroscopy setup. Recording of the large tissue sample. (a) Ultramicroscopy setup: Sapphire laser unit for fluorescence excitation (not shown), a beam splitter cube (BSC), 45 degrees silver mirrors (M), two light sheet generator units (LSG), two linear stages (LS) that move the LSG units along the beam propagation axis (z) for superimposing the center of the light sheet in the center of the biological sample, a computer controlled stage for moving the sample through the light sheet vertically (VS), a quartz container (QC), filled with imaging media (DBE). The detecting unit contains × 2, × 4 or × 16 objective equipped with a modulator (MO) for compensating refractive index mismatch, a tube lens (TL) equipped with a band pass filters (BPF) wheel, and a CMOS Camera. (b,c) Cancer sample recording with × 2 magnification.
Figure 3
Figure 3
Computational improvement of cancer sample recordings. (a) Image processing chain for cancer biopsies. The UM image stacks are contrast enhanced by contrast limited histogram equilibration (CLAHE), followed by stripe artifact removal using a matched 2D Fourier transform slope filter and unsharp masking. (b1) Representative slice of an UM data set obtained from a breast cancer biopsy before post-processing. (b2) Same as in (b1) after contrast enhancement using CLAHE. The visibility of information encoded in small brightness differences is clearly enhanced. (b3) Stripe artifacts generated during UM recording have been removed via a matched 2D Fourier domain slope filter. (b4) Finally, the image is slightly sharpened via unsharp-masking to further enhance the visibility of fine details. (c) UM recordings often exhibit stripe shaped artefacts originating from light absorbing structures that are persistent to the clearing procedure. By obstructing the light sheet these structures produce visible shadows that can include an angle α with the horizontal image edges depending on the camera orientation. (d) To remove the stripe artefact the images are Fourier transformed and multiplied with a filter mask cutting out a pie-slice shaped piece of the spectrum matching the angular direction α of the stipes. After inverse transformation and rescaling a stripe suppressed image is obtained. (e1) Design of the pie shaped filter. The angular direction α of the stripes corresponds to an angle of 90-α in the 2D power spectrum. The angular direction and the shape of the pie slice filter can be optimized in the software by varying α and the distances d1, d2, w1, and w2. This allows to match bandwidth and direction sensitivity of the filter in order to find a parameter combination providing best possible stripe suppression at minimal costs of blurring artefacts or ringing. (e2) To reduce ringing artefacts due to a hard frequency cutoffs, the edges of the pie shaped filter exhibit a smooth Gaussian transition profile. All image processing steps were performed using custom-made software written in MATLAB (MathWorks, Germany) and Visual Basic.Net (Microsoft, USA). The programs can be obtained from klaus.becker@twien.ac.at upon reasonable request.
Figure 4
Figure 4
3D-histopathology applied to human breast neoplasms. Highlighting cancer-relevant tissue structures. (a,b) Uncleared breast tissue specimen. (c) Same specimen after chemical tissue clearing. (d–f) Representative images of 3D-reconstructions of specimen. (d1) Selected plane of DCIS sample recorded with × 2 magnification. (d2) Same 3D-reconstruction with highlighted blood vessels. (e1) Selected plane of 3D-reconstruction of breast carcinoma specimen recorded with × 16 magnification. (e2) Same 3D-reconstruction, with highlighted blood vessels and sites of mitotic activity. (f1) 3D reconstruction of breast carcinoma sample recorded with × 16 magnification. (f2) Separately visualized blood vessels of the same sample (see movies to Fig. 4 in Supplementary material).
Figure 5
Figure 5
Post-processing of cleared specimen with standard histology methods. Comparison of obtained images. (a) Cleared specimen. (b) 4-dots labelling (red arrows) of the optical “area of interest”, found within the UM-recording. (c) Same sample, embedded in paraffin. (d,e) Optical sections of 3D-reconstruction of the specimen (see movie to Fig. 5d in Supplementary material), corresponding to (f,g) H&E-stained histological sections (× 2 magnification). (h) Whole-specimen cut with microtome and stained with H&E.
Figure 6
Figure 6
3D imaging of low-grade invasive lobular adenocarcinoma of breast. (a–c) Representative 3D reconstructions of the sample recorded with × 2 and × 4 magnification, captured from different perspectives; sites of high cellular density corresponding to the invasive carcinoma are visualized as dark areas. (d) Optical section of 3D reconstruction of the sample recorded with × 4 magnification. (e) Corresponding physical section of the specimen (post-clearing), processed with standard histology, stained with H&E and recorded with × 5 magnification (see movies to Fig. 6 in Supplementary material).
Figure 7
Figure 7
Comparison of tissue compounds preservation of specimen processed with pathoDISCO and standard histology. (a) Cleared sample labelled with histo-marker. (b) Post-clearing paraffin-embedded sample with 4-dots labelling. Arrows showing the sites of 4-dots labelling; (c) whole specimen slice, proceeded with standard FFPE/H&E; (e) zoom-in, showing the loss of intra-ductal cellular mass due to the mechanical tissue processing. (d,f,g) Several optical planes of the 3D reconstruction of the sample, recorded with UM at × 16 magnification (see movies to Fig. 7 in Supplementary material).
Figure 8
Figure 8
Comparison of post-UM and routinely processed FFPE-samples, acquired with × 40 magnification. (a) Sample, processed with standard histology, and stained with H&E; (b) post-UM sample, processed with FFPE and stained with H&E; (c) same sample, processed with standard histology and stained routinely with anti-cKpan (pan-keratin) and (e) anti-PR (progesterone receptor) antibodies; (d) Post-UM sample, processed with FFPE and stained with anti-cKpan (pan-keratin) and (f) anti-PR (progesterone receptor) antibodies at the pathology department.
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