T1-weighting in Steady-State FLASH MRI–Diffusion Is Not Only Supportive but Mandatory for the Contrast

Weinmüller S, Chellapandian DC, Endres J, Leupold J, Gritsch F, Wagner F, Schneider R, Zaiß M (2026)

Publication Type: Journal article

Publication year: 2026

Journal

DOI: 10.1002/mrm.70443

Abstract

Purpose: FLASH imaging is widely assumed to produce a T1-weighted steady-state contrast using RF- and gradient-spoiling. We observed substantial overestimation of CSF signals in simulations, when diffusion was neglected and realistic proton density was applied. This work investigates the role of diffusion in steady-state FLASH contrast formation and its implications for simulation-based modeling and measurement. Methods: FLASH sequences were simulated using phase graph simulations using a synthetic brain phantom with and without diffusion and realistic PD values to show the contrast change. The impact of neglecting diffusion in synthetic training data was evaluated using a segmentation network trained on simulated data and tested on in vivo measurement. Experimental validation of the contrast change was performed using a 3D-printed brain phantom using silicone oil as a low-diffusivity compartment. Results: Without diffusion, simulations showed CSF signal intensities higher than WM, resulting in a contrast change. Diffusion suppresses higher-order echoes in long T2 tissues and is essential for achieving the T1-weighted steady-state contrast. A NN trained without diffusion fails to generalize to in vivo data and measurements with silicone oil compartments confirm the contrast changes in low-diffusivity media. Conclusion: Diffusion is essential for realistic FLASH simulations of long T2 tissues such as CSF. Steady-state FLASH contrast arises from the interplay of RF-, gradient-spoiling, and “multi-TR-relaxation-spoiling” governed by T2-decay and diffusion effects. For many quadratic phase cycling schemes, diffusion is required to obtain realistic T1-weighted contrast in MR simulations and should not be neglected in simulations or simulation-based deep learning applications.

Authors with CRIS profile

Involved external institutions

Siemens AG Germany (DE) Universitätsklinikum Freiburg Germany (DE)

How to cite

APA:

Weinmüller, S., Chellapandian, D.C., Endres, J., Leupold, J., Gritsch, F., Wagner, F.,... Zaiß, M. (2026). T1-weighting in Steady-State FLASH MRI–Diffusion Is Not Only Supportive but Mandatory for the Contrast. Magnetic Resonance in Medicine. https://doi.org/10.1002/mrm.70443

MLA:

Weinmüller, Simon, et al. "T1-weighting in Steady-State FLASH MRI–Diffusion Is Not Only Supportive but Mandatory for the Contrast." Magnetic Resonance in Medicine (2026).

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