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Proc Natl Acad Sci U S A. 2018 Mar 27;115(13):E2980-E2987. doi: 10.1073/pnas.1718304115. Epub 2018 Mar 5.

Linking imaging to omics utilizing image-guided tissue extraction.

Author information

1
Werner Siemens Imaging Center, Department of Preclinical Imaging and Radiopharmacy, Eberhard Karls University Tuebingen, 72076 Tuebingen, Germany.
2
Department of Empirical Inference, Max Planck Institute for Intelligent Systems, 72076 Tuebingen, Germany.
3
Project Group for Automation in Medicine and Biotechnology, Fraunhofer Institute for Manufacturing Engineering and Automation, 68167 Mannheim, Germany.
4
Werner Siemens Imaging Center, Department of Preclinical Imaging and Radiopharmacy, Eberhard Karls University Tuebingen, 72076 Tuebingen, Germany; Bernd.Pichler@med.uni-tuebingen.de.

Abstract

Phenotypic heterogeneity is commonly observed in diseased tissue, specifically in tumors. Multimodal imaging technologies can reveal tissue heterogeneity noninvasively in vivo, enabling imaging-based profiling of receptors, metabolism, morphology, or function on a macroscopic scale. In contrast, in vitro multiomics, immunohistochemistry, or histology techniques accurately characterize these heterogeneities in the cellular and subcellular scales in a more comprehensive but ex vivo manner. The complementary in vivo and ex vivo information would provide an enormous potential to better characterize a disease. However, this requires spatially accurate coregistration of these data by image-driven sampling as well as fast sample-preparation methods. Here, a unique image-guided milling machine and workflow for precise extraction of tissue samples from small laboratory animals or excised organs has been developed and evaluated. The samples can be delineated on tomographic images as volumes of interest and can be extracted with a spatial accuracy better than 0.25 mm. The samples remain cooled throughout the procedure to ensure metabolic stability, a precondition for accurate in vitro analysis.

KEYWORDS:

imaging; omics; tissue extraction

PMID:
29507209
PMCID:
PMC5879681
DOI:
10.1073/pnas.1718304115
[Indexed for MEDLINE]
Free PMC Article

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