Hyperpolarised magnetic resonance spectroscopy with lab-on-a-chip disease models

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Authors: Irene Marco‐Rius, Pernille Rose Jensen, Lotte Bonde Bertelsen
Cited by: 1
References: 51

Abstract

Hyperpolarised magnetic resonance spectroscopy (HP-MRS) enables real-time, non-invasive assessment of metabolism by increasing signal sensitivity by more than four orders of magnitude compared with conventional magnetic resonance spectroscopy (MRS). This signal enhancement is achieved by preparing nuclear spin populations in a non-equilibrium state prior to measurement, generating a substrate with a transient strongly amplified signal that enables detection of rapid metabolic conversion in real time. Integration of HP-MRS with cell-based microfluidic disease models (engineered systems in which living cells are cultured within controlled microscale environments that mimic key aspects of tissue physiology) enables dynamic metabolic profiling in physiologically relevant settings. These models are typically implemented as organ-on-a-chip platforms, where microfabricated channels enable precise control over perfusion, nutrient delivery, oxygenation and cellular interactions. Combined HP-MRS and chip-based microfluidic platforms enable direct, non-destructive assessment of metabolic transformations, with applications in biomarker discovery, treatment response assessment and personalised medicine. This At a Glance article reviews recent advances in chip-based microfluidic systems that are integrated with HP-MRS platforms, including designs compatible with benchtop and high-field nuclear magnetic resonance systems together with clinical magnetic resonance imaging systems. Key challenges for this technology include constraints imposed by signal decay time, variability in polarisation levels, injection reproducibility and the lack of standardised data processing.

Fields of Study & Subjects

Advanced MRI Techniques and Applications Advanced NMR Techniques and Applications Lanthanide and Transition Metal Complexes

Publication details

Journal / source
Disease Models & Mechanisms
Publisher
The Company of Biologists
Volume
19
Issue
6
Publication date
1 June 2026
Language
EN