Bilateral Breast Gradient Insert Prototype for Strong Diffusion Encoding at 3 T.

Authors

Gerrit Cornelis Arends, Edwin Versteeg, Feng Jia, Dennis W J Klomp, Maxim Zaitsev, Sebastian Littin, Chantal M W Tax

Published in

Magnetic resonance in medicine. Oct 17, 2026. Epub Oct 17, 2026.

Abstract

Diffusion MRI has shown promise for breast cancer screening, lesion characterization, and treatment response monitoring without contrast agents, but further translation is constrained by the gradient performance of conventional systems. The aim of this work is to develop a single-axis high-performance bilateral plug-and-play breast gradient insert to enable strong-gradient diffusion MRI.
An in-house breast gradient insert and bed-tabletop was constructed entirely from commercially available materials, providing a cost-effective solution compatible with existing MRI systems. Its wiring pattern was optimized for torque and force balancing, power dissipation, and target field performance. Evaluation included gradient field characterization, peripheral nerve stimulation simulation verification, and temperature and eddy current assessment. The setup was used for imaging of a diffusion phantom based on soy lecithin across a range of b values.
Gradient efficiency ranged from 0.61 to 2.8 mT/m/A, enabling diffusion MRI using local strengths up to 420 mT/m (150 A). No peripheral nerve stimulation was observed during tests on five healthy volunteers. Eddy currents were successfully characterized, revealing a linear first order component with an amplitude of 0.03% of the applied gradient field. Imaging experiments demonstrated the feasibility of acquiring b = 10 000 s/mm² volumes with a TE of 78 ms, compared with 161 ms when using the scanner gradients (40 mT/m).
This work demonstrates a dedicated bilateral breast gradient insert for safe and feasible strong-gradient breast diffusion MRI and represents a first step toward dedicated hardware for breast cancer detection and characterization without contrast agents.

PMID:
42892701
Bibliographic data and abstract were imported from PubMed on 18 Oct 2026.

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