Revealing 3D microanatomical structures of unlabeled thick cancer tissues using holotomography and virtual H&E staining

Juyeon Park, Su-Jin Shin, Geon Kim, Hyungjoo Cho, Dongmin Ryu, Daewoong Ahn, Ji Eun Heo, Jean R. Clemenceau, Isabel Barnfather, Minji Kim, Inyeop Jang, Ji-Youn Sung, Jeong Hwan Park, Hyun-seok Min, Kwang Suk Lee, Nam Hoon Cho, Tae Hyun Hwang () and YongKeun Park ()
Additional contact information
Juyeon Park: Korea Advanced Institute of Science and Technology (KAIST)
Su-Jin Shin: Yonsei University College of Medicine
Geon Kim: Korea Advanced Institute of Science and Technology (KAIST)
Hyungjoo Cho: Tomocube Inc.
Dongmin Ryu: Tomocube Inc.
Daewoong Ahn: Tomocube Inc.
Ji Eun Heo: Yonsei University College of Medicine
Jean R. Clemenceau: Mayo Clinic
Isabel Barnfather: Mayo Clinic
Minji Kim: Mayo Clinic
Inyeop Jang: Mayo Clinic
Ji-Youn Sung: Mayo Clinic
Jeong Hwan Park: Mayo Clinic
Hyun-seok Min: Tomocube Inc.
Kwang Suk Lee: Yonsei University College of Medicine
Nam Hoon Cho: Yonsei University College of Medicine
Tae Hyun Hwang: Mayo Clinic
YongKeun Park: Korea Advanced Institute of Science and Technology (KAIST)

Nature Communications, 2025, vol. 16, issue 1, 1-16

Abstract: Abstract In histopathology, acquiring subcellular-level three-dimensional (3D) tissue structures efficiently and without damaging the tissues during serial sectioning and staining remains a formidable challenge. We address this by integrating holotomography with deep learning and creating 3D virtual hematoxylin and eosin (H&E) images from label-free thick cancer tissues. This method involves measuring the tissues’ 3D refractive index (RI) distribution using holotomography, followed by processing with a deep learning-based image translation framework to produce virtual H&E staining in 3D. Applied to colon cancer tissues up to 50 µm thick—far surpassing conventional slide thickness—this technique provides direct methodological validation through chemical H&E staining. It reveals quantitative 3D microanatomical structures of colon cancer with subcellular resolution. Further validation of our method’s repeatability and scalability is demonstrated on gastric cancer samples across different institutional settings. This innovative 3D virtual H&E staining method enhances histopathological efficiency and reliability, marking a significant advancement in extending histopathology to the 3D realm and offering substantial potential for cancer research and diagnostics.

Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
https://www.nature.com/articles/s41467-025-59820-0 Abstract (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:nat:natcom:v:16:y:2025:i:1:d:10.1038_s41467-025-59820-0

Ordering information: This journal article can be ordered from
https://www.nature.com/ncomms/

DOI: 10.1038/s41467-025-59820-0

Access Statistics for this article

Nature Communications is currently edited by Nathalie Le Bot, Enda Bergin and Fiona Gillespie

More articles in Nature Communications from Nature
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().