Leveraging metabolism as a cellular state reporter for liver health and disease via hyperpolarized magnetic resonance spectroscopy
Year: 2025
Type: dissertation
Abstract: [eng] Tissue-engineered cellular models represent an innovative, ethical, and controlled research tool, offering an ideal platform to study disease mechanisms and test emerging therapies in vitro. However, their application is limited by the difficulty associated with reproducing the metabolic environment of native organs. Hyperpolarized Magnetic Resonance Spectroscopic Imaging (HP-MRSI) has emerged as a technique capable of evaluating cellular metabolism non-invasively. Despite its potential, the integration of HP-MRSI with tissue engineering has not yet been achieved, mainly due to technical challenges related to their compatibility and the reproducibility of metabolic environments in vitro. This thesis explores these incompatibilities, identifying the main challenges to combine tissue engineering with HP-MRSI. A milestone of this work is the creation and characterization of 3D cellular models and culture platforms compatible with HP-MRSI. Furthermore, this study has successfully identified metabolic signatures of Metabolic-Associated Fatty Liver Disease (MAFLD) in vivo, opening new possibilities to reproduce them in vitro, using HP-MRSI to model disease progression in the laboratory. The conclusions of this thesis establish a foundation for the future use of HP-MRSI in 3D cell models, with the potential to reduce dependence on animal models in preclinical research. Through the application of HP-MRSI to in vitro studies, this work paves the way for more efficient and ethical research into metabolic diseases to develop new treatments. The integration of these technologies represents a significant advancement in the field of metabolic imaging and biomedical research.
Author: Herrero Gómez, Alba
Language: English
Subfield: Radiology, Nuclear Medicine and Imaging
Field: Medicine
Domain: Health Sciences
Open Access status: green
Funder: Generalitat de Catalunya
OpenAlex ID: W7124380506
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