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Updated: Apr 30, 2026

Tumor Hypoxia Assessment: In Vivo 3D Oxygen Imaging Through Electron Paramagnetic Resonance

Tumor Hypoxia Assessment: In Vivo 3D Oxygen Imaging Through Electron Paramagnetic Resonance

Published on: February 14, 2025

Accelerated 4D quantitative single point EPR imaging using model-based reconstruction.

Hyungseok Jang¹, Shingo Matsumoto, Nallathamby Devasahayam

¹Department of Radiology, Wisconsin Institute for Medical Research, University of Wisconsin, Madison, Wisconsin, USA.

Magnetic Resonance in Medicine

|May 8, 2014

Summary

This summary is machine-generated.

Accelerated electron paramagnetic resonance imaging (EPRI) uses k-space extrapolation and model-based reconstruction to improve speed and resolution. This enhances the ability to image tissue oxygenation and hypoxia dynamics.

Keywords:

Electron paramagnetic resonance imaging k-space extrapolation model-based reconstruction quantitative imaging single-point imaging

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Last Updated: Apr 30, 2026

Tumor Hypoxia Assessment: In Vivo 3D Oxygen Imaging Through Electron Paramagnetic Resonance

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Rapid Scan Electron Paramagnetic Resonance Opens New Avenues for Imaging Physiologically Important Parameters In Vivo

Rapid Scan Electron Paramagnetic Resonance Opens New Avenues for Imaging Physiologically Important Parameters In Vivo

Published on: September 26, 2016

Area of Science:

Medical Imaging
Biophysics
Biomedical Engineering

Background:

Electron paramagnetic resonance imaging (EPRI) is a noninvasive technique for imaging tissue oxygenation.
Current EPRI methods have limited spatial and temporal resolution due to short spin-spin relaxation times, hindering the study of small hypoxic tissues and hypoxia dynamics.
Accelerated imaging is critical for overcoming these limitations in EPRI.

Purpose of the Study:

To develop accelerated imaging methods for single-point electron paramagnetic resonance imaging.
To improve the spatial and temporal resolution of EPRI for better hypoxia detection.
To enable more accurate differentiation of hypoxia dynamics.

Main Methods:

Combined a bilateral k-space extrapolation technique with model-based reconstruction for accelerated single-point imaging.
Utilized dense sampling in the parameter domain, measuring T2 (*) decay of a free induction delay.
Implemented principal component analysis for accurate T2 (*) estimation.

Main Results:

Demonstrated reliable T2 (*) estimation with high acceleration factors (8x, 15x, 30x) in simulations and phantom experiments.
Achieved high acceleration rates for various matrix sizes (61x61x61, 95x95x95, 127x127x127).
Validated the capability of the proposed methods for accelerated EPRI.

Conclusions:

Bilateral k-space extrapolation and model-based reconstruction significantly improve scan times in single-point EPRI.
The developed methods allow for higher spatial resolution imaging.
Enhanced EPRI capabilities for studying tissue oxygenation and hypoxia.