Optimization for diffusion MRI

Diffusion MRI (dMRI) is a useful probe of tissue microstructure, which can be used to derive biomarkers for diagnostics and treatment. Diffusion measurements using continuous gradient waveforms significantly expand the capabilities of conventional diffusion MRI (Szczepankiewicz et al., 2021). However, implementing them on real-world MR scanners is challenging due to the plethora of constraints imposed by hardware limitations and physiology.


In collaboration with Filip Szczepankiewicz and others, I’ve developed the open-source library NOW which has established itself as the de facto standard tool for gradient waveform design for tensor-valued encoding in diffusion MRI. Since its introduction in Sjölund et al. (2015), the methodology and software has been extended and refined to capture additional effects, including motion compensation (Szczepankiewicz et al., 2021) and cross-term compensation (Szczepankiewicz and Sjölund, 2021). We have also demonstrated that NOW enables diffusional variance decomposition (DIVIDE) on clinical MRI systems Szczepankiewicz et al., 2019.


Sjölund J, Szczepankiewicz F, Nilsson M, Topgaard D, Westin C-F, and Knutsson H. Constrained optimization of gradient waveforms for generalized diffusion encoding. Journal of Magnetic Resonance 261 (2015), 157-168.

Szczepankiewicz F , Sjölund J, Ståhlberg F, Lätt J, and Nilsson M. Tensor-valued diffusion encoding for diffusional variance decomposition (DIVIDE): Technical feasibility in clinical MRI systems. PLoS One (2019).

Szczepankiewicz F, Sjölund J, Dall’Armellina E, Plein S, Schneider E J, Teh I, and Westin C-F, Motion-compensated gradient waveforms for tensor-valued diffusion encoding by constrained numerical optimization. Magn Reson Med (2021)

Szczepankiewicz F and Sjölund J, Cross-term-compensated gradient waveform design for tensor-valued diffusion MRI. Journal of Magnetic Resonance (2021)

Szczepankiewicz F, Westin C-F, and Nilsson, M, Gradient waveform design for tensor-valued encoding in diffusion MRI. Journal of Neuroscience Methods (2021)