Back

Multidimensional T1-T2 Relaxation Imaging In Vivo on a Portable 0.064~T MRI Scanner

Wilczynski, E.; Najmudeen Magdoom, K.; Avram, A. V.; Williamson, N. H.; Benjamini, D.; Horovitz, S. G.; Basser, P. J.

2026-09-09 bioengineering
10.64898/2026.09.04.749459 bioRxiv
Show abstract

Purpose: To demonstrate the feasibility of whole-brain multidimensional T1-T2 relaxation imaging on a portable 0.064 T MRI scanner. Methods: A two-dimensional inversion-recovery, fast spin-echo acquisition was used to jointly encode T1 and T2 relaxation. Joint relaxation distributions were reconstructed voxel-wise using marginal-distribution constrained optimization (MADCO). The approach was evaluated in a quantitative relaxation MRI phantom and subsequently applied in vivo in a healthy volunteer. Joint distributions, marginal distributions, distribution-derived measures, and statistical dependencies between the two relaxation dimensions were examined. Results: Phantom joint relaxation estimates showed good overall agreement with mono-exponential relaxation measurements and previously reported values at 0.064 T. The in vivo acquisition provided whole-brain coverage over a broad range of relaxation weightings and tissue contrasts. Reconstructed joint T1-T2 distributions showed spatially organized features across the relaxation space, including broad and overlapping relaxation components that were not fully represented by single-value relaxation maps or by either 1D marginal distribution alone. Selected regions of the joint relaxation space produced component maps with distinct spatial patterns. Statistical analysis further showed a dependence between the two relaxation dimensions, supporting the presence of added information in the joint distribution that is lost when treating T1 and T2 separately. Conclusion: Whole-brain multidimensional T1-T2 relaxation imaging is clinically feasible on a portable 0.064 T MRI scanner. Joint relaxation distributions provide information beyond single-value relaxation mapping and may support further developments of quantitative multidimensional imaging at ultra-low field.

Matching journals

The top 1 journal accounts for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.