Medizinische Universität Graz Austria/Österreich - Forschungsportal - Medical University of Graz

Gewählte Publikation:

SHR Neuro Krebs Kardio Lipid Stoffw Microb

Giardina, G; Micko, A; Bovenkamp, D; Krause, A; Placzek, F; Papp, L; Krajnc, D; Spielvogel, CP; Winklehner, M; Höftberger, R; Vila, G; Andreana, M; Leitgeb, R; Drexler, W; Wolfsberger, S; Unterhuber, A.
Morpho-Molecular Metabolic Analysis and Classification of Human Pituitary Gland and Adenoma Biopsies Based on Multimodal Optical Imaging.
Cancers (Basel). 2021; 13(13): Doi: 10.3390/cancers13133234 [OPEN ACCESS]
Web of Science PubMed PUBMED Central FullText FullText_MUG


Führende Autor*innen der Med Uni Graz
Micko Alexander
Co-Autor*innen der Med Uni Graz
Wolfsberger Stefan

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Pituitary adenomas count among the most common intracranial tumors. During pituitary oncogenesis structural, textural, metabolic and molecular changes occur which can be revealed with our integrated ultrahigh-resolution multimodal imaging approach including optical coherence tomography (OCT), multiphoton microscopy (MPM) and line scan Raman microspectroscopy (LSRM) on an unprecedented cellular level in a label-free manner. We investigated 5 pituitary gland and 25 adenoma biopsies, including lactotroph, null cell, gonadotroph, somatotroph and mammosomatotroph as well as corticotroph. First-level binary classification for discrimination of pituitary gland and adenomas was performed by feature extraction via radiomic analysis on OCT and MPM images and achieved an accuracy of 88%. Second-level multi-class classification was performed based on molecular analysis of the specimen via LSRM to discriminate pituitary adenomas subtypes with accuracies of up to 99%. Chemical compounds such as lipids, proteins, collagen, DNA and carotenoids and their relation could be identified as relevant biomarkers, and their spatial distribution visualized to provide deeper insight into the chemical properties of pituitary adenomas. Thereby, the aim of the current work was to assess a unique label-free and non-invasive multimodal optical imaging platform for pituitary tissue imaging and to perform a multiparametric morpho-molecular metabolic analysis and classification.

Find related publications in this database (Keywords)
pituitary gland and adenomas
multimodal imaging
Raman spectroscopy
second harmonic generation
two-photon excitation fluorescence
multiphoton microscopy
optical coherence tomography
image analysis
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