Abstract
Tagged magnetic resonance imaging (MRI) has been successfully applied for noninvasive quantification of in vivo brain deformation, enabling characterization of strain distributions under mild, noninjurious loading conditions. Previously, the double trigger (DT) method was proposed to improve temporal consistency, where an initial trigger initiates the MRI tagging pulse and a second trigger initiates image acquisition. However, this approach has two disadvantages: (1) the initial trigger was mechanical and susceptible to misalignment during connection to a fiber optic cable; (2) the time history of the tagged MRI acquisition was constrained to the interval between the initial and second triggers, thereby limiting the overall acquisition duration. In this work, a late trigger (LT) approach is proposed to eliminate mechanical triggering and the use of a fiber optic cable, reduce tag fading, and enable a longer duration time history. Gel phantom experiments demonstrate that both DT and LT approaches yield consistent strain patterns and angular kinematics. Similarly, angular motion and in-plane strain measured using in vivo two-dimensional (2D) tagged MRI show strong agreement between the DT and LT approaches; nonetheless, LT consistently provides improved tag contrast, signal-to-noise ratio (SNR), and anatomical delineation. In in vivo three-dimensional (3D) testing, LT method produces 95th percentile maximum principal strain (MPS95) strain values that closely align with those of the DT method across multiple brain regions. Collectively, the LT method demonstrates performance comparable to DT in both phantom and in vivo experiments, highlighting its potential as a physiologically robust and technically advantageous strategy for measuring brain deformation.
| Original language | English |
|---|---|
| Journal | Journal of Biomechanical Engineering |
| Volume | 148 |
| Issue number | 5 |
| DOIs | |
| State | Published - 1 May 2026 |
Keywords
- Magnetic Resonance Imaging/methods
- Brain/physiology
- Biomechanical Phenomena
- Rotation
- Phantoms, Imaging
- Head/physiology
- Humans
- Image Processing, Computer-Assisted
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