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Linking imaging to omics utilizing image-guided tissue extraction

 
: Disselhorst, Jonathan A.; Krueger, Marcel A.; Ud-Dean, S.M. Minhaz; Bezrukov, Ilja; Jarboui, Mohamed A.; Trautwein, Christoph; Traube, Andreas; Spindler, Christian; Cotton, Jonathan M.; Leibfritz, Dieter; Pichler, Bernd J.

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Proceedings of the National Academy of Sciences of the United States of America : PNAS 115 (2018), Nr.13, S.E2980-E2987
ISSN: 0027-8424
ISSN: 1091-6490
Englisch
Zeitschriftenaufsatz
Fraunhofer IPA ()
Tumordiagnostik; Medizintechnik; Bilderkennung; Minimal invasive Chirurgie; Laborautomatisierung

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.

: http://publica.fraunhofer.de/dokumente/N-487864.html