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An end-to-end workflow for nondestructive 3D pathology.
Bishop, Kevin W; Erion Barner, Lindsey A; Han, Qinghua; Baraznenok, Elena; Lan, Lydia; Poudel, Chetan; Gao, Gan; Serafin, Robert B; Chow, Sarah S L; Glaser, Adam K; Janowczyk, Andrew; Brenes, David; Huang, Hongyi; Miyasato, Dominie; True, Lawrence D; Kang, Soyoung; Vaughan, Joshua C; Liu, Jonathan T C.
Afiliação
  • Bishop KW; Department of Mechanical Engineering, University of Washington, Seattle, WA, USA.
  • Erion Barner LA; Department of Bioengineering, University of Washington, Seattle, WA, USA.
  • Han Q; Department of Mechanical Engineering, University of Washington, Seattle, WA, USA.
  • Baraznenok E; Department of Mechanical Engineering, University of Washington, Seattle, WA, USA.
  • Lan L; Department of Bioengineering, University of Washington, Seattle, WA, USA.
  • Poudel C; Department of Mechanical Engineering, University of Washington, Seattle, WA, USA.
  • Gao G; Department of Bioengineering, University of Washington, Seattle, WA, USA.
  • Serafin RB; Department of Mechanical Engineering, University of Washington, Seattle, WA, USA.
  • Chow SSL; Department of Biology, University of Washington, Seattle, WA, USA.
  • Glaser AK; Department of Chemistry, University of Washington, Seattle, WA, USA.
  • Janowczyk A; Department of Mechanical Engineering, University of Washington, Seattle, WA, USA.
  • Brenes D; Department of Mechanical Engineering, University of Washington, Seattle, WA, USA.
  • Huang H; Department of Mechanical Engineering, University of Washington, Seattle, WA, USA.
  • Miyasato D; Allen Institute for Neural Dynamics, Seattle, WA, USA.
  • True LD; Department of Biomedical Engineering, Emory University, Atlanta, GA, USA.
  • Kang S; Department of Oncology, Division of Precision Oncology, University Hospital of Geneva, Geneva, Switzerland.
  • Vaughan JC; Department of Diagnostics, Division of Clinical Pathology, University Hospital of Geneva, Geneva, Switzerland.
  • Liu JTC; Department of Mechanical Engineering, University of Washington, Seattle, WA, USA.
Nat Protoc ; 19(4): 1122-1148, 2024 Apr.
Article em En | MEDLINE | ID: mdl-38263522
ABSTRACT
Recent advances in 3D pathology offer the ability to image orders of magnitude more tissue than conventional pathology methods while also providing a volumetric context that is not achievable with 2D tissue sections, and all without requiring destructive tissue sectioning. Generating high-quality 3D pathology datasets on a consistent basis, however, is not trivial and requires careful attention to a series of details during tissue preparation, imaging and initial data processing, as well as iterative optimization of the entire process. Here, we provide an end-to-end procedure covering all aspects of a 3D pathology workflow (using light-sheet microscopy as an illustrative imaging platform) with sufficient detail to perform well-controlled preclinical and clinical studies. Although 3D pathology is compatible with diverse staining protocols and computationally generated color palettes for visual analysis, this protocol focuses on the use of a fluorescent analog of hematoxylin and eosin, which remains the most common stain used for gold-standard pathological reports. We present our guidelines for a broad range of end users (e.g., biologists, clinical researchers and engineers) in a simple format. The end-to-end workflow requires 3-6 d to complete, bearing in mind that data analysis may take longer.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Imageamento Tridimensional / Microscopia Tipo de estudo: Guideline Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Imageamento Tridimensional / Microscopia Tipo de estudo: Guideline Idioma: En Ano de publicação: 2024 Tipo de documento: Article