Back

Improving stroke detection via Correlation Tensor MRI

Alves, R.; Henriques, R. N.; Kerkela, L.; Chavarrias, C.; Jespersen, S.; Shemesh, N.

2021-02-20 neuroscience
10.1101/2021.02.20.432088 bioRxiv
Show abstract

Noninvasively detecting and characterizing modulations in cellular scale micro-architecture is a desideratum for contemporary neuroimaging. Diffusion MRI (dMRI) has become the mainstay methodology for probing microstructure, and, in ischemia, its contrasts have revolutionized stroke management. However, the biological underpinnings of the contrasts observed in conventional dMRI in general and in ischemia in particular are still highly debated since the markers only indirectly reporter on microstructure. Here, we present Correlation Tensor MRI (CTI), a method that rather than measuring diffusion, harnesses diffusion correlations as its source of contrast. We show that CTI can resolve the sources of diffusional kurtosis, which in turn, provide dramatically enhanced specificity and sensitivity towards ischemia. In particular, the sensitivity towards ischemia nearly doubles, both in grey matter (GM) and white matter (WM), and unique signatures for neurite beading, cell swelling, and edema are inferred from CTI. The enhanced sensitivity and specificity endowed by CTI bodes well for future applications in biomedicine, basic neuroscience, and in the clinic.

Matching journals

The top 5 journals account 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.