Pathologist

Mar 11

3D digital pathology for intact tissue

Extend pathology beyond the selected section

Preserve whole-tissue architecture and examine margins, glands, immune structures, vessels, nerves, and rare features across the full sample volume. Alpenglow combines non-destructive 3D tissue imaging with AI-powered analysis to generate volumetric evidence for research pathology, spatial biomarker studies, and translational workflows.

View 3D pathology datasets Explore Aurora 3D^™

3D imaging gallery

3D Imaging of Human Duodenum Villi

Explore human duodenum tissue in 3D using eosin and TO-PRO-3 in an H&E-like visualization. Volumetric imaging preserves villous morphology and spatial organization across depth and can support quantitative analysis of villus dimensions, density, spacing, and regional variation.

This video presents a volumetric visualization of human duodenum tissue stained with eosin and the nuclear marker TO-PRO-3, then pseudocolored to create an H&E-like appearance.

3D tissue imaging reveals intestinal villi as continuous structures across the imaged volume, preserving information about their morphology, orientation, spacing, density, and regional organization. Viewing villi across depth also reduces the influence of sectioning angle and sampling location that can affect measurements from individual 2D sections.

With appropriate segmentation, the dataset can support quantitative analysis of villus number, height, width, volume, elongation, spacing, density, and variation across tissue regions.

These measurements are relevant to gastrointestinal research, including studies of celiac disease, where villous architecture may become shortened, flattened, fused, or otherwise disrupted. Quantifying these changes across a tissue volume could help characterize the distribution and heterogeneity of structural alterations.

The tissue was imaged on the Aurora 3D™ platform using the 3Di™ Hybrid Open-Top Light-Sheet (HOTLS) microscope.

Whole-biopsy 3D segmentation of prostate glands

3D segmentation of prostate glands using synthetic CK8 immunofluorescence derived from fluorescent H&E analogues. By combining image-translation models with traditional computer-vision methods, researchers achieved whole-biopsy 3D gland segmentation without manual labeling.

This study demonstrates annotation-free 3D segmentation of prostate glands using fluorescence-based microscopy and AI. A prostate specimen stained with a fluorescent analogue of H&E was converted into a synthetic CK8 immunofluorescence dataset via an image-sequence translation model trained on paired H&E analogue and real CK8 datasets. Traditional computer-vision algorithms were then applied to the synthetic CK8 images for segmentation of gland epithelium, lumen, and stromal regions. The synthetic CK8 image blocks were mosaicked to reconstruct a 3D CK8 dataset of the entire biopsy, enabling accurate gland segmentation. Gland lumen spaces were further segmented by filling regions enclosed by epithelia, with refinements from the cytoplasm (eosin) channel.

3D images acquired with the Aurora™ 3Di Hybrid Open Top Light Sheet (HOTLS) microscope.

With integration of 3Dm data management and 3Dai AI-powered segmentation, researchers can perform reproducible, high-content quantification. This 3D approach eliminates slice bias and ensures accurate analysis at scale.

REF: Xie W, Reder NP, Koyuncu C, Leo P, Hawley S, Huang H, Mao C, Postupna N, Kang S, Serafin R, Gao G, Han Q, Bishop KW, Barner LA, Fu P, Wright JL, Keene CD, Vaughan JC, Janowczyk A, Glaser AK, Madabhushi A, True LD, Liu JTC. Prostate Cancer Risk Stratification via Nondestructive 3D Pathology with Deep Learning-Assisted Gland Analysis. Cancer Res. 2022 Jan 15;82(2):334-345. doi: 10.1158/0008-5472.CAN-21-2843. Epub 2021 Dec 1. PMID: 34853071; PMCID: PMC8803395.

High-Resolution 3D Imaging of Human Dorsal Root Ganglion (DRG)

Zoomed 3D imaging of human DRG sample from AnaBios with computational H&E staining, ToPro-3 for nuclei, and eosin for protein structures.

This video showcases high-resolution Zoom imaging of a human dorsal root ganglion (DRG) sample provided by AnaBios. The dataset features computational H&E staining, with ToPro-3 highlighting cell nuclei and eosin capturing protein structures, creating a vivid map of DRG tissue composition.

Captured with the Aurora™ 3Di Hybrid Open Top Light Sheet (HOTLS) microscope, this dataset exemplifies how 3D histology combined with digital pathology delivers insights that extend beyond conventional 2D slices.

High-resolution DRG imaging opens new opportunities in neuroscience research, sensory biology, and pain studies, where quantifying neuronal distribution and structure is critical.

Visit AnaBios DRG resource to learn more about their DRG samples and research programs.

Contact us to learn how Alpenglow’s 3D spatial biology platform can advance your research with large-scale, quantitative imaging datasets.

Low-Resolution 3D Imaging of Human Dorsal Root Ganglion (DRG)

Scout 3D imaging of a human DRG sample from AnaBios with computational H&E staining, ToPro-3 for nuclei, and eosin for protein structures.

This video presents low-resolution (Scout) imaging of a human dorsal root ganglion (DRG) sample provided by AnaBios. The dataset features computational H&E staining, with ToPro-3 labeling cell nuclei and eosin capturing protein structures, providing a broad overview of DRG tissue composition.

Scout imaging on the Aurora™ 3Di Hybrid Open Top Light Sheet (HOTLS) microscope, enables rapid, whole-sample visualization before zooming into high-resolution regions of interest.

Low-resolution DRG imaging is a critical first step in neuroscience research, sensory biology, and pain studies, allowing researchers to identify areas for detailed analysis. Together with high-resolution DRG datasets, it demonstrates the flexibility of Alpenglow’s 3D spatial biology platform for translational discovery.

Visit AnaBios DRG resource to learn more about their DRG samples and research programs.

Contact us to learn how Alpenglow’s 3D spatial biology platform can advance your research with large-scale, quantitative imaging datasets.

Scout-to-Zoom 3D Computational H&E Imaging of TLS in NSCLC

Scout-to-Zoom 3D computational H&E imaging identifies and quantifies tertiary lymphoid structures within an NSCLC tissue volume, preserving their morphology, depth, and surrounding tumor context.

This dataset presents 3D computational H&E imaging of tertiary lymphoid structures in a human non-small cell lung cancer sample.

TO-PRO-3 labels nuclei, while eosin highlights protein-rich tissue architecture. Together, the fluorescent signals are computationally rendered to create an H&E-like view of the intact tissue volume.

The Scout-to-Zoom workflow begins with rapid volumetric imaging at 2 µm per pixel to identify nuclear aggregates and other regions of interest across the tissue. Selected regions are then acquired at high resolution at 0.167 µm per pixel, revealing cellular morphology and TLS organization in greater detail.

In this NSCLC sample, Scout imaging identified dense nuclear aggregates that were examined using Zoom imaging and classified as two distinct tertiary lymphoid structures approximately 200 µm below the tissue surface. Their volumes and surface areas were quantified in 3D.

The dataset supports measurement of TLS number, volume, surface area, cellular density, distribution, and spatial relationships with surrounding tumor and stromal regions. Preserving each structure across depth reduces the sampling and orientation effects associated with individual 2D sections.

Explore how 3D tissue imaging supports immuno-oncology research across tumor architecture, immune-cell organization, and spatial relationships.

The tissue was imaged using the Aurora 3D™ Spatial Biology Solution, including the 3Di™ Hybrid Open-Top Light-Sheet microscope.

3D Imaging and TLS Quantification in NSCLC

Computational H&E staining combined with non-destructive 3D imaging reveals the true complexity of tertiary lymphoid structures (TLS) in NSCLC. Unlike thin 2D sections that risk misclassification, Alpenglow’s 3Di platform captures entire TLS morphology, volume, and cellular composition, delivering accurate insights into immune architecture and tumor context.

Tertiary lymphoid structures (TLS) are critical immune aggregates that influence prognosis and response to immunotherapy in non-small cell lung cancer (NSCLC). Traditional single cross-section imaging often misrepresents TLS size, cellular composition, and maturity classification due to sampling bias.

Using Alpenglow’s 3Di spatial imaging platform and computational H&E staining, TLS can be visualized and quantified across entire tumor biopsies in 3D, non-destructively.

Computational H&E staining replicates the contrast of standard histology while preserving the intact tissue. In this NSCLC study, samples were stained with:

TO-PRO-3: nuclear marker for hematoxylin contrast
Eosin to highlight cytoplasm and extracellular matrix

After staining, the tissues were optically cleared and imaged at whole-block scale using Scout mode, followed by imaging at subcellular resolution in Zoom mode. This workflow maintains architectural context while enabling single-cell segmentation in 3D.

Key advantages:

Accurate detection and measurement of TLS in whole tissue samples
3D quantification of TLS volume, surface area, and cellular density
Improved classification of TLS maturity and organization
Enhanced biological insight through visualization of spatial context with surrounding tumor, stroma, and vasculature

In one NSCLC sample, what appeared as a single TLS in 2D was revealed in 3D to be two distinct structures with unique volumes and surface areas. Such insights demonstrate the power of combining computational H&E with 3D imaging to reveal structures invisible to conventional pathology.

By moving beyond 2D, researchers gain a more accurate and comprehensive understanding of TLS in oncology samples—opening new opportunities for translational research, biomarker development, and therapeutic discovery.

Read the TLS white paper.

3D Imaging of a Rabbit Retina: High-Resolution Tissue Mapping

High-resolution 3D imaging of a cleared rabbit retina stained with TO-PRO-3 and eosin, preserving architecture across retinal, choroid, and scleral layers.

This dataset presents a high-resolution 3D visualization of a cleared rabbit retina, captured intact on the Aurora™ 3Di Hybrid Open Top Light Sheet (HOTLS) microscope. By avoiding physical sectioning, the imaging preserves the true spatial architecture of the tissue.

Stains used:

TO-PRO-3 (Magenta, pseudocolor): Labels nuclei
Eosin (Green, pseudocolor): Highlights cytoplasmic structures

The fly-through reveals the full thickness of the sample (≈1 × 1 × 4 mm), capturing the retina, choroid, and sclera in their native spatial organization. This volumetric dataset enables accurate morphological and contextual analysis at cellular resolution, overcoming the limitations of 2D histology.

When combined with 3Dm data management and 3Dai AI-powered segmentation, the dataset can be further analyzed for nuclear density, layer-specific organization, and cellular distribution. Applications include ophthalmology research, retinal disease modeling, and translational studies focused on vision science.

3D Imaging of Prostate Organoids

3D imaging of prostate organoids stained with TO-PRO-3 and eosin reveals spatial heterogeneity, cellular interactions, and microenvironmental detail.

At the frontier of cellular research, three-dimensional fluorescence imaging is redefining how scientists study prostate organoids. Unlike traditional 2D microscopy, which flattens complex structures, 3D imaging preserves the full architecture of these miniature organs, exposing biological subtleties that thin slices overlook.

Stains used:

TO-PRO-3: Highlights nuclei
Eosin: Labels cytoplasmic structures (pseudocolored for enhanced detail)

Using the Aurora™ 3Di Hybrid Open Top Light Sheet (HOTLS) microscope, organoids are imaged layer by layer, generating vivid, information-rich datasets. With integration into 3Dm data management and 3Dai AI-powered segmentation, researchers can quantify nuclear organization, cytoplasmic morphology, and spatial heterogeneity across entire organoids.

This volumetric approach provides unmatched clarity into cellular interactions, microenvironmental gradients, and spatial variability, offering transformative insights for prostate cancer modeling, drug testing, and precision medicine.

By moving beyond 2D limitations, 3D digital pathology empowers organoid studies with true biological context.

Exploring Prostate Organoids in 3D with LUMI

3D imaging of prostate organoids with LUMI shows ROI selection, multi-well scanning, and high-resolution analysis using TO-PRO-3 and eosin staining.

Prostate organoids are complex 3D models that demand a high-resolution, volumetric approach to imaging. This video demonstrates how LUMI (Light-Sheet User Microscope Interface) simplifies the process by combining low-resolution scanning with smart region selection and ultra-high-resolution imaging of specific areas.

Workflow with LUMI Smart Microscopy:

Fast pre-scan: Capture the entire organoid sample at low resolution.
ROI definition: Select regions of interest directly on the whole 3D raw image data.
Multi-ROI scanning: Efficiently image multiple organoids using LUMI’s multi-well setup.

In this example, prostate organoids are stained with TO-PRO-3 and eosin, then pseudocolored to enhance structural details. The result is a precise, multi-scale analysis of organoid organization, bridging low-resolution overview with single-cell clarity.

By pairing LUMI’s interface with the Aurora™ 3Di Hybrid Open Top Light Sheet (HOTLS) microscope, researchers gain seamless control over imaging workflows. Integration with 3Dm data management and 3Dai AI-powered segmentation further enables quantitative analysis of organoid growth, structure, and cellular interactions.

Applications extend to cancer biology, drug testing, and translational research, where prostate organoids serve as powerful disease models. LUMI accelerates these workflows, making 3D organoid imaging more accessible, reproducible, and insightful.

3D Imaging of Glioblastoma in Whole Mouse Brain

Whole mouse brain imaged in 3D with TO-PRO-3 and eosin. Scout and Zoom workflows capture glioblastoma ROI, segmentation, and high-resolution morphology.

This dataset presents a full 3D visualization of a whole mouse brain stained with TO-PRO-3 and eosin, revealing nuclei and protein structures. The workflow begins with low-resolution Scout imaging (2 μm/pixel) to capture the entire organ, followed by stepwise refinement to focus on the glioblastoma region.

Workflow highlights:

Whole-organ imaging (Scout): Broad view at 2 μm/pixel resolution
Tumor identification: Selecting the glioblastoma region of interest (ROI)
Segmentation and mesh construction: ROI highlighted in yellow, mesh built around glioblastoma pixels to calculate tumor volume and capture morphology
High-resolution imaging (Zoom): ROI imaged at 0.34 μm/pixel, showing TO-PRO-3 in purple and eosin in pink

Captured using the Aurora 3Di Hybrid Open Top Light Sheet (HOTLS) microscope, this dataset showcases the dual-path Scout + Zoom workflow, allowing researchers to transition seamlessly from organ-level context to subcellular resolution. Integration with 3Dm data management and 3Dai AI-powered segmentation supports accurate volume calculations, morphology analysis, and reproducible quantification.

This powerful approach provides actionable data for oncology research, supporting drug discovery and therapeutic development in glioblastoma and other brain tumors. By combining whole-brain imaging with quantitative segmentation, Alpenglow’s 3D spatial biology platform provides insights that are not possible with conventional 2D histology.

Fly-Through 3D Image of H&E-Stained Liver Biopsy

A 3D fly-through of liver tissue stained with computational hematoxylin and eosin, showcasing structures beyond traditional 2D pathology.

This dataset presents a 3D fly-through visualization of a human liver biopsy digitally stained with computational hematoxylin and eosin (H&E). Unlike traditional thin-section histology, this approach preserves the intact architecture of the tissue, enabling 3D histology that reveals spatial relationships and structures hidden in 2D slides.

By leveraging the Aurora™ 3Di Hybrid Open Top Light Sheet (HOTLS) microscope and advanced staining methods, researchers can visualize tissue morphology in full volumetric context. Integration with 3Dm data management and 3Dai AI-powered analysis enables quantitative assessment of hepatocyte organization, vascular networks, and microanatomical features critical to liver pathology.

This application demonstrates how digital pathology combined with computational H&E expands conventional workflows, delivering reproducible, high-content imaging datasets for translational research, drug development, and disease modeling.

Contact us to learn how Alpenglow’s 3D spatial biology platform can advance your research with large-scale, quantitative imaging datasets.

3D fluorescence imaging of colorectal cancer FFPE tissue

3D fluorescence imaging of human colorectal cancer FFPE tissue reveals spatial organization across depth that cannot be captured with single 2D histology sections.

This video demonstrates three-dimensional fluorescence imaging of human colorectal cancer (CRC) FFPE tissue, acquired using a volumetric workflow designed to preserve tissue architecture across depth.

As described in the linked CRC immune-exclusion study, intact CRC FFPE blocks are deparaffinized, fluorescently labeled, optically cleared, and imaged in three dimensions to avoid sampling bias inherent to conventional histology.

Large tissue volumes on the order of ~300 mm³ are first captured at 2 µm per pixel to retain full spatial context. From this dataset, a focused region of interest (~0.5 mm³) is selected and re-imaged at 0.33 µm per pixel, enabling high-resolution visualization of cellular and structural features within their native environment.

In this example, nuclei are labeled with TO-PRO-3, while eosin provides general protein contrast, allowing clear differentiation between tumor parenchyma and stromal compartments.

By traversing the full depth of the tissue, this volumetric view reveals spatial heterogeneity, compartmental organization, and boundary shifts that are not detectable in a single 2D section. As shown in the linked analysis, accurate characterization of stromal and parenchymal distributions in CRC can require dozens of 2D sections, whereas a single 3D dataset preserves this information inherently.

This example illustrates why 3D tissue imaging is critical for studying tumor microenvironments and immune phenotypes, and why volumetric data provide a more reliable foundation for quantitative spatial analysis than traditional slide-based workflows.

Volumetric pathology readouts

Examine pathology features across depth, not one plane

Extend tissue review beyond selected sections to evaluate biological features continuously across the sample. Intact 3D imaging preserves morphology, spatial relationships, and tissue-scale organization for research pathology and digital pathology programs.

Why 3D tissue imaging matters Explore ground-truth 3D data

Broader tissue sampling

Examine more tissue volume across regions and depths, reducing reliance on a small number of selected planes when studying heterogeneous or unevenly distributed biology.

Published example

Whole-lymph-node OTLS enabled volumetric assessment of breast cancer metastases, revealing metastatic extent that could be underestimated from selected 2D sections.

Read the Journal of Biomedical Optics study

Boundaries and structural continuity

Follow tissue regions, lesion boundaries, glands, vessels, nerves, and branching structures continuously through the volume rather than reconstructing them from disconnected fragments.

Published example

GlaSkeN used OTLS to preserve complete prostate gland networks and quantify branching, curvature, torsion, and connectivity. 3D architectural features were associated with biochemical recurrence across two cohorts.

Read the Modern Pathology study

Rare and spatially restricted features

Locate focal lesions, sparse cells, localized immune structures, and other features that may occur outside a selected 2D section.

Published example

TRICARE analyzed complete 3D pathology datasets to identify high-risk tissue levels for pathologist review in prostate biopsies and Barrett's esophagus specimens.

Read the Nature Biomedical Engineering study

Quantitative marker and spatial review

Measure cells, structures, regions, marker distributions, and spatial relationships across intact tissue to support research, biomarker development, reference datasets, and computational pathology workflows.

Published example

SIGHT used generative immunolabeling to automate delineation of benign and prostate-cancer-enriched regions within 3D pathology datasets.

Read the Modern Pathology study

Next step

Bring your pathology question into 3D

Share your tissue type, structures of interest, marker strategy, and intended quantitative readouts. Alpenglow can help define a non-destructive 3D histology workflow for research pathology, biomarker studies, and computational pathology programs.

Building AI or diagnostic reference datasets? Explore ground-truth 3D tissue data for volumetric imaging, expert annotation, and quantitative tissue measurements.

Discuss your pathology study

Tell the Alpenglow team which tissue features, spatial relationships, and measurements you need to review across the intact sample.

Discuss a pathology study Explore imaging services

Elisa Barbieri

Pathologist

Extend pathology beyond the selected section

Read the TLS white paper.

Examine pathology features across depth, not one plane

Broader tissue sampling

Boundaries and structural continuity

Rare and spatially restricted features

Quantitative marker and spatial review

Bring your pathology question into 3D

Discuss your pathology study

Imaging Facility Director

Research Group Leader