Denoising strategies for higher resolution Q-space trajectory imaging with limited scanner hardware

Q-space trajectory imaging (QTI) enables detailed characterization of tissue microstructure. Achieving high spatial resolution is challenging due to low signal-to-noise ratio (SNR), particularly on clinical MRI systems with limited gradient capabilities and coil options. This study assessed the potential of denoising methods to improve the resolution of QTI in the brain on a radiotherapy-dedicated MRI scanner.

Using a 3T scanner with a 33 mT/m gradient system, we evaluated four denoising approaches: three methods based on principal component analysis (PCA) and Air Recon DL. Diffusion MRI of phantom and in vivo brain was acquired at voxel sizes from 3 × 3 × 3 to 1.25 × 1.25 × 1.25 mm³ using both diagnostic and radiotherapy coil setups. Precision and bias were analyzed, leading to in vivo brain QTI tested at resolutions 2 × 2 × 3 (radiotherapy coil) and 2 × 2 × 2 mm³ (diagnostic coil).

Denoising complex images was required to mitigate noise floor bias and increase resolution. The denoising methods varied in performance in terms of signal variance at high b-values. One PCA method enabled a decreased voxel size of 2 × 2 × 3 (radiotherapy coil), improving the parameter contrast-to-noise ratio, particularly for fractional anisotropy (+ 30%) and isotropic kurtosis (+ 16%).

Complex-valued denoising enhances the resolution of QTI at low SNR, improving feasibility for use on constrained scanner hardware.