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Abstract 1450: 3D holotomography-enabled virtual multiplexed staining of thick medical kidney tissue for comprehensive renal pathology.
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Abstract
Renal pathology relies on multiple special stains—including H&E, PAS, AFOG, and PAM—to assess glomerular, tubular, and interstitial changes. These stains require serial sections, are prone to variability, and involve destructive processing, limiting consistency and preventing true 3D interpretation. Holotomography (HT) enables label-free 3D refractive index (RI) imaging of thick tissues, and generative translation models can synthesize stain-equivalent contrast directly from RI inputs. We developed a virtual multiplexed staining framework that generates four major renal stains from a single label-free input, including for thick sections where conventional staining becomes unreliable.Medical kidney samples (thin and thick sections up to 50 μm) were imaged with 3D HT to obtain RI volumes. A conditional generative model was trained on paired RI–stain patches (H&E, PAS, AFOG, PAM) after registration and QC. Similarity metrics—SSIM, PSNR, LPIPS, PCC—were computed on held-out regions. The model was applied to (i) label-free RI and (ii) chemically stained slides to produce cross-stain predictions, enabling direct comparison. Whole-slide virtual staining was performed on 0.5-mm kidney regions.The framework reproduced diagnostic features across stains, with structural similarity typically >0.85. Virtual stains restored key elements—including basement membranes, mesangial matrix, tubular epithelium, and interstitial collagen—closely matching chemical references. Large-region predictions preserved coherent architecture. Virtual PAS and AFOG highlighted basement membranes, glycogen-rich areas, collagen deposition, and casts, supporting interpretation of glomerular injury and interstitial fibrosis. Robust performance was maintained in thick tissues (10–50 μm), where chemical stains often show uneven penetration; virtual stains preserved uniform contrast and delineated overlapping structures. Multiplexing enabled consistent visualization of basement membrane thickening, mesangial expansion, and inflammation within the same section, removing serial-section artifacts.Holotomography with generative translation enables reliable, label-free virtual multiplexed staining, producing H&E, PAS, AFOG, and PAM–equivalent images from a single unstained or singly stained input. The method preserves renal microanatomy and remains robust in thick sections where conventional staining can fail. By eliminating serial sectioning and repeated chemical processing, it provides a unified, non-destructive workflow that improves reproducibility and enables direct cross-stain comparison. This positions virtual multiplexed staining as a scalable, pathology-ready technology for renal disease assessment, translational research, and computational pathology pipelines.
Citation Format:
Siwon Jeong, Juyeon Park, Hyun-Seok Min, Minsun Jung, YongKeun Park. 3D holotomography-enabled virtual multiplexed staining of thick medical kidney tissue for comprehensive renal pathology [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 1450.
American Association for Cancer Research (AACR)
Title: Abstract 1450: 3D holotomography-enabled virtual multiplexed staining of thick medical kidney tissue for comprehensive renal pathology.
Description:
Abstract
Renal pathology relies on multiple special stains—including H&E, PAS, AFOG, and PAM—to assess glomerular, tubular, and interstitial changes.
These stains require serial sections, are prone to variability, and involve destructive processing, limiting consistency and preventing true 3D interpretation.
Holotomography (HT) enables label-free 3D refractive index (RI) imaging of thick tissues, and generative translation models can synthesize stain-equivalent contrast directly from RI inputs.
We developed a virtual multiplexed staining framework that generates four major renal stains from a single label-free input, including for thick sections where conventional staining becomes unreliable.
Medical kidney samples (thin and thick sections up to 50 μm) were imaged with 3D HT to obtain RI volumes.
A conditional generative model was trained on paired RI–stain patches (H&E, PAS, AFOG, PAM) after registration and QC.
Similarity metrics—SSIM, PSNR, LPIPS, PCC—were computed on held-out regions.
The model was applied to (i) label-free RI and (ii) chemically stained slides to produce cross-stain predictions, enabling direct comparison.
Whole-slide virtual staining was performed on 0.
5-mm kidney regions.
The framework reproduced diagnostic features across stains, with structural similarity typically >0.
85.
Virtual stains restored key elements—including basement membranes, mesangial matrix, tubular epithelium, and interstitial collagen—closely matching chemical references.
Large-region predictions preserved coherent architecture.
Virtual PAS and AFOG highlighted basement membranes, glycogen-rich areas, collagen deposition, and casts, supporting interpretation of glomerular injury and interstitial fibrosis.
Robust performance was maintained in thick tissues (10–50 μm), where chemical stains often show uneven penetration; virtual stains preserved uniform contrast and delineated overlapping structures.
Multiplexing enabled consistent visualization of basement membrane thickening, mesangial expansion, and inflammation within the same section, removing serial-section artifacts.
Holotomography with generative translation enables reliable, label-free virtual multiplexed staining, producing H&E, PAS, AFOG, and PAM–equivalent images from a single unstained or singly stained input.
The method preserves renal microanatomy and remains robust in thick sections where conventional staining can fail.
By eliminating serial sectioning and repeated chemical processing, it provides a unified, non-destructive workflow that improves reproducibility and enables direct cross-stain comparison.
This positions virtual multiplexed staining as a scalable, pathology-ready technology for renal disease assessment, translational research, and computational pathology pipelines.
Citation Format:
Siwon Jeong, Juyeon Park, Hyun-Seok Min, Minsun Jung, YongKeun Park.
3D holotomography-enabled virtual multiplexed staining of thick medical kidney tissue for comprehensive renal pathology [abstract].
In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA.
Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 1450.
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