A combined hemodynamic and metabolic model for in vivo hyperpolarized 13C MRI data analysis

Motivation: Accurate interpretation of hyperpolarized (HP) 13C-MRI data is vital for advancing metabolic imaging techniques, yet existing models often overlook critical factors like transcapillary extraction. Goal(s): This study aims to develop a comprehensive kinetic model that incorporates both perfusion and extraction, providing a more reliable assessment of metabolism in vivo. Approach: We introduce a generalized model and validate it using in vivo HP 13C-MRI data from healthy volunteers, comparing parameter estimation to traditional ratio-metric analyses. Results: Our model is able to quantify hemodynamics and metabolic rates across various scenarios and reveals that current approaches may misinterpret the contributions of metabolism and extraction. Impact: Our generalized model potentially enables more accurate quantification of metabolism in HP 13C-MRI by accounting for perfusion and extraction effects. This advancement may support better interpretation of metabolic data, potentially leading to improved diagnostics and therapeutic monitoring in clinical settings.

Authors

Publication Details

Journal
Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition
Published
2025-09-16
DOI
https://doi.org/10.58530/2025/4483
Primary Topic
Advanced NMR Techniques and Applications
Type
article
Field-Weighted Citation Impact
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article

A combined hemodynamic and metabolic model for in vivo hyperpolarized 13C MRI data analysis

Nichlas Riise Jespersen, Nikolaj Bøgh, Henrik Wiggers, Sune Nørhøj Jespersen et al.
Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition
Advanced NMR Techniques and Applications
article

A combined hemodynamic and metabolic model for in vivo hyperpolarized 13C MRI data analysis

Nichlas Riise Jespersen, Nikolaj Bøgh, Henrik Wiggers, Sune Nørhøj Jespersen, Esben Søvsø Szocska Hansen, Christoffer Laustsen, Nina Christensen
article en

Abstract

Motivation: Accurate interpretation of hyperpolarized (HP) 13C-MRI data is vital for advancing metabolic imaging techniques, yet existing models often overlook critical factors like transcapillary extraction. Goal(s): This study aims to develop a comprehensive kinetic model that incorporates both perfusion and extraction, providing a more reliable assessment of metabolism in vivo. Approach: We introduce a generalized model and validate it using in vivo HP 13C-MRI data from healthy volunteers, comparing parameter estimation to traditional ratio-metric analyses. Results: Our model is able to quantify hemodynamics and metabolic rates across various scenarios and reveals that current approaches may misinterpret the contributions of metabolism and extraction. Impact: Our generalized model potentially enables more accurate quantification of metabolism in HP 13C-MRI by accounting for perfusion and extraction effects. This advancement may support better interpretation of metabolic data, potentially leading to improved diagnostics and therapeutic monitoring in clinical settings.

Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition
Openalex Percentile: Top 77%
Advanced NMR Techniques and Applications
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A combined hemodynamic and metabolic model for in vivo hyperpolarized 13C MRI data analysis — Nichlas Riise Jespersen, Nikolaj Bøgh, et al. · Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition (2025) | TGRS Research Map | TGRS