Age-Related Decline in Brain Myelination: Quantitative Macromolecular Proton Fraction Mapping, T2-FLAIR Hyperintensity Volume, and Anti-Myelin Antibodies Seven Years Apart

Age-related myelination decrease is considered one of the likely mechanisms of cognitive decline. The present preliminary study is based on the longitudinal assessment of global and regional myelination of the normal adult human brain using fast macromolecular fraction (MPF) mapping. Additional markers were age-related changes in white matter (WM) hyperintensities on FLAIR-MRI and the levels of anti-myelin autoantibodies in serum. Eleven healthy subjects (33-60 years in the first study) were scanned twice, seven years apart. An age-related decrease in MPF was found in global WM, grey matter (GM), and mixed WM-GM, as well as in 48 out of 82 examined WM and GM regions. The greatest decrease in MPF was observed for the frontal WM (2-5%), genu of the corpus callosum (CC) (4.0%), and caudate nucleus (5.9%). The age-related decrease in MPF significantly correlated with an increase in the level of antibodies against myelin basic protein (MBP) in serum (r = 0.69 and r = 0.63 for global WM and mixed WM-GM, correspondingly). The volume of FLAIR hyperintensities increased with age but did not correlate with MPF changes and the levels of anti-myelin antibodies. MPF mapping showed high sensitivity to age-related changes in brain myelination, providing the feasibility of this method in clinics.

Extent of FLAIR Hyperintense Vessels May Modify Treatment Effect of Thrombolysis: A Post hoc Analysis of the WAKE-UP Trial

Background and Aims: Fluid-attenuated inversion recovery (FLAIR) hyperintense vessels (FHVs) on MRI are a radiological marker of vessel occlusion and indirect sign of collateral circulation. However, the clinical relevance is uncertain. We explored whether the extent of FHVs is associated with outcome and how FHVs modify treatment effect of thrombolysis in a subgroup of patients with confirmed unilateral vessel occlusion from the randomized controlled WAKE-UP trial.

Methods: One hundred sixty-five patients were analyzed. Two blinded raters independently assessed the presence and extent of FHVs (defined as the number of slices with visible FHV multiplied by FLAIR slice thickness). Patients were then separated into two groups to distinguish between few and extensive FHVs (dichotomization at the median <30 or ≥30).

Results: Here, 85% of all patients (n = 140) and 95% of middle cerebral artery (MCA) occlusion patients (n = 127) showed FHVs at baseline. Between MCA occlusion patients with few and extensive FHVs, no differences were identified in relative lesion growth (p = 0.971) and short-term [follow-up National Institutes of Health Stroke Scale (NIHSS) score; p = 0.342] or long-term functional recovery [modified Rankin Scale (mRS) <2 at 90 days poststroke; p = 0.607]. In linear regression analysis, baseline extent of FHV (defined as a continuous variable) was highly associated with volume of hypoperfused tissue (β = 2.161; 95% CI 0.96–3.36; p = 0.001). In multivariable regression analysis adjusted for treatment group, stroke severity, lesion volume, occlusion site, and recanalization, FHV did not modify functional recovery. However, in patients with few FHVs, the odds for good functional outcome (mRS) were increased in recombinant tissue plasminogen activator (rtPA) patients compared to those who received placebo [odds ratio (OR) = 5.3; 95% CI 1.2–24.0], whereas no apparent benefit was observed in patients with extensive FHVs (OR = 1.1; 95% CI 0.3–3.8), p-value for interaction was 0.11.

Conclusion: While the extent of FHVs on baseline did not alter the evolution of stroke in terms of lesion progression or functional recovery, it may modify treatment effect and should therefore be considered relevant additional information in those patients who are eligible for intravenous thrombolysis.

Clinical Trial Registration: Main trial (WAKE-UP): ClinicalTrials.gov, NCT01525290; and EudraCT, 2011-005906-32. Registered February 2, 2012.

Automatic segmentation of white matter hyperintensities from brain magnetic resonance images in the era of deep learning and big data - A systematic review

BACKGROUND

White matter hyperintensities (WMH), of presumed vascular origin, are visible and quantifiable neuroradiological markers of brain parenchymal change. These changes may range from damage secondary to inflammation and other neurological conditions, through to healthy ageing. Fully automatic WMH quantification methods are promising, but still, traditional semi-automatic methods seem to be preferred in clinical research. We systematically reviewed the literature for fully automatic methods developed in the last five years, to assess what are considered state-of-the-art techniques, as well as trends in the analysis of WMH of presumed vascular origin.

METHOD

We registered the systematic review protocol with the International Prospective Register of Systematic Reviews (PROSPERO), registration number - CRD42019132200. We conducted the search for fully automatic methods developed from 2015 to July 2020 on Medline, Science direct, IEE Explore, and Web of Science. We assessed risk of bias and applicability of the studies using QUADAS 2.

RESULTS

The search yielded 2327 papers after removing 104 duplicates. After screening titles, abstracts and full text, 37 were selected for detailed analysis. Of these, 16 proposed a supervised segmentation method, 10 proposed an unsupervised segmentation method, and 11 proposed a deep learning segmentation method. Average DSC values ranged from 0.538 to 0.91, being the highest value obtained from an unsupervised segmentation method. Only four studies validated their method in longitudinal samples, and eight performed an additional validation using clinical parameters. Only 8/37 studies made available their methods in public repositories.

CONCLUSIONS

We found no evidence that favours deep learning methods over the more established k-NN, linear regression and unsupervised methods in this task. Data and code availability, bias in study design and ground truth generation influence the wider validation and applicability of these methods in clinical research.