MRI with generalized diffusion encoding reveals damaged white matter in patients previously hospitalized for COVID-19…, 2023, Boito et al.

MRI with generalized diffusion encoding reveals damaged white matter in patients previously hospitalized for COVID-19 and with persisting symptoms at follow-up
Boito, Deneb; Eklund, Anders; Tisell, Anders; Levi, Richard; Özarslan, Evren; Blystad, Ida

There is mounting evidence of the long-term effects of COVID-19 on the central nervous system, with patients experiencing diverse symptoms, often suggesting brain involvement. Conventional brain MRI of these patients shows unspecific patterns, with no clear connection of the symptomatology to brain tissue abnormalities, whereas diffusion tensor studies and volumetric analyses detect measurable changes in the brain after COVID-19. Diffusion MRI exploits the random motion of water molecules to achieve unique sensitivity to structures at the microscopic level, and new sequences employing generalized diffusion encoding provide structural information which are sensitive to intravoxel features.

In this observational study, a total of 32 persons were investigated: 16 patients previously hospitalized for COVID-19 with persisting symptoms of post-COVID condition (mean age 60 years: range 41-79, all male) at 7-month follow-up and 16 matched controls, not previously hospitalized for COVID-19, with no post-COVID symptoms (mean age 58 years, range 46-69, 11 males). Standard MRI and generalized diffusion encoding MRI were employed to examine the brain white matter of the subjects. To detect possible group differences, several tissue microstructure descriptors obtainable with the employed diffusion sequence, the fractional anisotropy, mean diffusivity, axial diffusivity, radial diffusivity, microscopic anisotropy, orientational coherence (Cc) and variance in compartment's size (Cmd) were analysed using the tract-based spatial statistics frame-work.

The tract-based spatial statistics analysis showed widespread statistically significant differences (P < 0.05, corrected for multiple comparisons using the familywise error rate) in all the considered metrics in the white matter of the patients compared to the controls. Fractional anisotropy, microscopic anisotropy and Co were lower in the patient group, while axial diffusivity, radial diffusivity, mean diffusivity and Cud were higher. Significant changes in fractional anisotropy, microscopic anisotropy and Cd affected approximately half of the analysed white matter voxels located across all brain lobes, while changes in Ce were mainly found in the occipital parts of the brain.

Given the predominant alteration in microscopic anisotropy compared to Co, the observed changes in diffusion anisotropy are mostly due to loss of local anisotropy, possibly connected to axonal damage, rather than white matter fibre coherence disruption. The increase in radial diffusivity is indicative of demyelination, while the changes in mean diffusivity and Cud are compatible with vasogenic oedema.

In summary, these widespread alterations of white matter microstructure are indicative of vasogenic oedema, demyelination and axonal damage. These changes might be a contributing factor to the diversity of central nervous system symptoms that many patients experience after COVID-19.

Link | PDF (Brain Communications)

 

The dataset can be explored interactively at https://neurovault.org/collections/13799/. In the eg below the colour-mapping indicates locations of significant group differences between patients and controls (fractional anisotropy* here).



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* From wikipedia: "FA is a measure often used in diffusion imaging where it is thought to reflect fiber density, axonal diameter, and myelination in white matter."

 

So scary for me and the human race so long as mass infection is the order of the day.

 

Post COVID group all male (16) . Matched controls not all male (11 male out of 16 )

It may make no difference at all , but given differences between male and female responses and manifestations are being discovered / acknowledged across multiple medical conditions it is perhaps disappointing and an illustration as to why it's been an issue for so long.

 

I can't judge the quality of the study, but new imaging and data processing techniques with small cohorts may not mean much. If you got creative and invented 100 new data processing techniques and applied them to a few random photos, I expect you'd find some meaningless connection that could be written up as "Look at this amazing discovery!"