New MRI technique spots brain disease in minutes, not hours
Researchers have cracked a mathematical code that makes brain MRI scans 10-20 times faster while actually detecting disease better. The breakthrough could transform how hospitals screen for conditions like multiple sclerosis, potentially reducing scan times from 30 minutes to just 1-2 minutes and cutting imaging costs significantly.
Originaltitel: Geometry of the cumulant series in diffusion MRI
Water diffusion gives rise to micron-scale sensitivity of diffusion MRI (dMRI) to cellular-level tissue structure. Precision medicine and quantitative imaging depend on uncovering the information content of dMRI and establishing its parsimonious hardware-independent fingerprint. Based on the rotational SO(3) symmetry, we study the geometry of the dMRI signal and the topology of its acquisition, identify irreducible components and a full set of invariants for the cumulant tensors, and relate them to tissue properties. Including all kurtosis invariants improves multiple sclerosis classification in a cohort of 1189 subjects. We design the shortest acquisitions based on icosahedral vertices to determine the most used invariants in only 1-2 minutes for whole brain. Representing dMRI via scalar invariant maps with definite symmetries will underpin machine learning classifiers of pathology, development, and aging, while fast protocols will enable translation of advanced dMRI into clinic.