Mesoscopic 3D imaging of pancreatic cancer and Langerhans islets based on tissue autofluorescence
The possibility to assess pancreatic anatomy with microscopic resolution in three dimensions (3D) would significantly add to pathological analyses of disease processes. Pancreatic ductal adenocarcinoma (PDAC) has a bleak prognosis with over 90% of the patients dying within 5 years after diagnosis. C...
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Published in | Scientific reports Vol. 10; no. 1; p. 18246 |
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Main Authors | , , , , , , , , , |
Format | Journal Article |
Language | English |
Published |
London
Nature Publishing Group UK
26.10.2020
Nature Publishing Group |
Subjects | |
Online Access | Get full text |
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Summary: | The possibility to assess pancreatic anatomy with microscopic resolution in three dimensions (3D) would significantly add to pathological analyses of disease processes. Pancreatic ductal adenocarcinoma (PDAC) has a bleak prognosis with over 90% of the patients dying within 5 years after diagnosis. Cure can be achieved by surgical resection, but the efficiency remains drearily low. Here we demonstrate a method that without prior immunohistochemical labelling provides insight into the 3D microenvironment and spread of PDAC and premalignant cysts in intact surgical biopsies. The method is based solely on the autofluorescent properties of the investigated tissues using optical projection tomography and/or light-sheet fluorescence microscopy. It does not interfere with subsequent histopathological analysis and may facilitate identification of tumor-free resection margins within hours. We further demonstrate how the developed approach can be used to assess individual volumes and numbers of the islets of Langerhans in unprecedently large biopsies of human pancreatic tissue, thus providing a new means by which remaining islet mass may be assessed in settings of diabetes. Generally, the method may provide a fast approach to provide new anatomical insight into pancreatic pathophysiology. |
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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
ISSN: | 2045-2322 2045-2322 |
DOI: | 10.1038/s41598-020-74616-6 |