3D Tissue Imaging for Dermatology: Seeing Skin Biology As It Truly Is

Written By Elisa Barbieri
“Skin is a 3D organ with layered architecture, nerves, and patchy inflammation. 3D tissue imaging and AI-powered analysis let you quantify innervation, map immune neighborhoods, and evaluate full-volume architecture that 2D slides often miss. Protocols optimized specifically for skin and studies in cleared human skin biopsies, melanoma, and keloid show why depth and continuity matter for dermatology.”

Why dermatology benefits most from 3D

Nerve fibers snake through epidermis and dermis, hair follicles curve and branch, and immune infiltrates cluster around appendages or along the dermal–epidermal junction. Thin sections distort connectivity and miss depth-dependent patterns, while cleared, intact biopsies capture the entire specimen for 3D tissue imaging, spatial profiling, and quantitative tissue analysis that are consistent across planes and depths.

If you are building or refining a workflow, start from a practical LSFM primer that covers staining strategies, optics, refractive index matching, and data handling, it outlines end-to-end considerations for cleared tissues in a way that translates well to skin:

https://pmc.ncbi.nlm.nih.gov/articles/PMC10583220/ PMC

Skin-specific clearing matters. Skin is rich in collagen and elastin, and it often contains pigment, so brain-oriented aqueous methods can underperform. Solvent approaches like iDISCO or BABB penetrate extracellular matrix efficiently and preserve epitopes for immunolabeling, and Skin-iDISCO+ provides a human-skin-tuned protocol for vasculature and other markers that is compatible with light-sheet or confocal imaging. Background on iDISCO and solvent clearing,

https://www.sciencedirect.com/science/article/pii/S0079633616300043

Protocol (PubMed): https://pubmed.ncbi.nlm.nih.gov/39709611/

Itch biology and innervation in inflammatory skin disease

Pruritic diseases are closely linked to peripheral innervation and its proximity to immune cells. In intact-volume human atopic dermatitis and psoriasis, optical clearing with volumetric imaging showed downregulation of epidermal innervation, a result that can be underestimated in thin sections because nerve trajectories are curved and discontinuous in 2D. Study link: https://pubmed.ncbi.nlm.nih.gov/30471253/

For translational readouts, 3D enables nerve volume, length, and branching per tissue volume, plus proximity to immune clusters, rather than per-slice counts that vary by plane. In Alpenglow analyses, whole-biopsy scans with 3D segmentation produced stable innervation metrics, and hundreds of virtual 4 µm sections were required before 2D averages approached the true 3D value, a direct illustration of sampling bias in slices. The workflow, stain to clearing to scout scan to high-resolution ROIs to ML segmentation, is detailed in the white paper figures.

Immune architecture and border metrics

Inflammation localizes near appendages, within papillary or reticular dermis, and along the dermal–epidermal border. Cleared-tissue 3D imaging returns cells to their native context, so you can compute distance-to-border distributions, 3D cell neighborhood features, and more across the entire biopsy, not a single plane. These metrics are less sensitive to the level chosen for sectioning and are easier to compare between lesions or time points.

Methods papers on cleared-tissue immune mapping cover marker selection, channel registration, and 3D measurement strategies that transfer well to skin: PubMed: https://pubmed.ncbi.nlm.nih.gov/34342351/)

Hair disorders

Hair follicles and sweat glands are inherently three-dimensional; they spiral, branch, and change caliber with depth. Quantifying perifollicular inflammation, miniaturization, or immune niches is more reliable when the entire follicular unit is visible along its course. With 3D histology, you can track the follicle from the infundibulum to the bulb, measure distances from immune cells to the outer root sheath, and assess vascular support in volume.

Reviews focused on clinical applications of optical clearing and 3D imaging in human tissue explain reagent choices and validation steps that keep antigens intact while enabling depth. Open summary, https://pmc.ncbi.nlm.nih.gov/articles/PMC9114043/


Melanoma, primary lesions and sentinel nodes

Primary melanoma. Optical clearing with volumetric immunostaining has demonstrated 3D visualization of tumor microenvironment in human melanoma and xenografts, including vasculature and immune context, which helps when pigmentation and complex architecture limit 2D interpretation. This establishes feasibility for pigmented lesions and supports volumetric biomarker studies. https://pmc.ncbi.nlm.nih.gov/articles/PMC9313268/

Sentinel lymph nodes: Light-sheet-based 3D imaging can increase sensitivity for micrometastasis detection compared to standard protocols by scanning entire nodes and rendering cell populations in volume. This improves confidence in staging since small deposits can be missed by sparse sectioning. https://www.ejcancer.com/article/S0959-8049(21)01126-6/fulltext



Keloid and fibrotic disorders

Keloids are extracellular-matrix rich, highly vascular, and heterogeneous in depth. Reports conflict in 2D because vessel tortuosity and density vary as you pass through the lesion. A 2025 study compared clearing methods in scar tissue and mapped keloid vasculature in 3D, providing a fuller picture of vessel organization, caliber, and branching that better reflects the biology of fibrosis.

https://pubmed.ncbi.nlm.nih.gov/40143403/



A practical pipeline for skin, from biopsy to insight

  1. Define the question. Pick markers that reflect your hypothesis and your readout, for example PGP 9.5 for innervation, CD45 plus T-cell subsets for inflammation, keratin or collagen for architecture, vascular markers when perfusion matters.

  2. Use skin-appropriate clearing. Favor solvent-based approaches for ECM-rich tissue, and follow Skin-iDISCO+ when labeling human cutaneous vasculature or other targets that require deep, even penetration. https://pubmed.ncbi.nlm.nih.gov/39709611/

  3. Scan whole tissue, then zoom. Acquire a low-resolution scout scan of the intact biopsy for orientation, select predefined regions for high-resolution imaging at the cellular scale. See Low to High Resolution in action.

  4. Quantify with AI-powered analysis. Convert images into volumetric metrics such as nerve fiber volume or length per tissue volume, lymphocyte distance to the dermal–epidermal junction, or immune density, then validate with inter-rater checks on representative volumes. Your white paper illustrates how 3D analysis stabilizes these metrics relative to 2D.


What 3D adds to digital dermatopathology

  • Whole-tissue architecture preserved. You see continuous glands, vessels, nerves, and tunnels, so rare or tortuous features are less likely to be missed, and the structure's identity is less ambiguous.

  • Quantitative tissue analysis at scale. Volumetric counts, distances, and neighborhood features are reproducible across lesions and visits, which supports endpoints for trials and translational studies.

  • Spatial profiling in three axes. Relationships that are invisible in 2D, such as nerve-to-immune proximity, become measurable features rather than anecdotal observations.

  • Skin-optimized clearing and LSFM are practical now. Primers and surveys explain the why and the how for skin compared with other tissues, including reagent selection and index matching. https://www.sciencedirect.com/science/article/pii/S0079633616300043 | https://pmc.ncbi.nlm.nih.gov/articles/PMC8815095/

References and resources, quick list

Elisa Barbieri
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Why 2D Slides Miss Critical Insights: The Case for 3D Tissue Imaging