Structural brain imaging as a diagnostic tool in dementia, why and how?

Diurnal cortisol, neuroinflammation, and neuroimaging visual rating scales in memory clinic patients

BACKGROUND

Neuroinflammation is a hallmark of the Alzheimer's disease (AD) pathogenic process. Cortisol dysregulation may increase AD risk and is related to brain atrophy. This cross-sectional study aims to examine interactions of cortisol patterns and neuroinflammation markers in their association with neuroimaging correlates.

METHOD

134 participants were recruited from the Karolinska University Hospital memory clinic (Stockholm, Sweden). Four visual rating scales were applied to magnetic resonance imaging or computed tomography scans: medial temporal lobe atrophy (MTA), global cortical atrophy (GCA), white matter lesions (WML), and posterior atrophy. Participants provided saliva samples for assessment of diurnal cortisol patterns, and underwent lumbar punctures for cerebrospinal fluid (CSF) sampling. Three cortisol measures were used: the cortisol awakening response, total daily output, and the ratio of awakening to bedtime levels. Nineteen CSF neuroinflammation markers were categorized into five composite scores: proinflammatory cytokines, other cytokines, angiogenesis markers, vascular injury markers, and glial activation markers. Ordinal logistic regressions were conducted to assess associations between cortisol patterns, neuroinflammation scores, and visual rating scales, and interactions between cortisol patterns and neuroinflammation scores in relation to visual rating scales.

RESULT

Higher levels of angiogenesis markers were associated with more severe WML. Some evidence was found for interactions between dysregulated diurnal cortisol patterns and greater neuroinflammation-related biomarkers in relation to more severe GCA and WML. No associations were found between cortisol patterns and visual rating scales.

CONCLUSION

This study suggests an interplay between diurnal cortisol patterns and neuroinflammation in relation to brain structure. While this cross-sectional study does not provide information on causality or temporality, these findings suggest that neuroinflammation may be involved in the relationship between HPA-axis functioning and AD.

Increased Resolution of Structural MRI at 3T Improves Estimation of Regional Cortical Degeneration in Individual Dementia Patients Using Surface Thickness Maps

BACKGROUND

Objective measurement of regional cortical atrophy in individual patients would be a highly desirable adjunct for diagnosis of degenerative dementias.

OBJECTIVE

We hypothesized that increasing the resolution of magnetic resonance scans would improve the sensitivity of cortical atrophy detection for individual patients.

METHODS

46 participants including 8 semantic-variant primary progressive aphasia (svPPA), seven posterior cortical atrophy (PCA), and 31 cognitively unimpaired participants underwent clinical assessment and 3.0T brain scans. SvPPA and PCA were chosen because there is overwhelming prior knowledge of the expected atrophy pattern. Two sets of T1-weighted images with 0.8 mm3 (HighRes) and conventional 1.0 mm3 (ConvRes) resolution were acquired. The cortical ribbon was segmented using FreeSurfer software to obtain surface-based thickness maps. Inter-sequence performance was assessed in terms of cortical thickness and sub-cortical volume reproducibility, signal-to-noise and contrast-to-noise ratios. For clinical cases, diagnostic effect size (Cohen's d) and lesion distribution (z-score and t-value maps) were compared between HighRes and ConvRes scans.

RESULTS

The HighRes scans produced higher image quality scores at 90 seconds extra scan time. The effect size of cortical thickness differences between patients and cognitively unimpaired participants was 15-20% larger for HighRes scans. HighRes scans showed more robust patterns of atrophy in expected regions in each and every individual patient.

CONCLUSIONS

HighRes T1-weighted scans showed superior precision for identifying the severity of cortical atrophy in individual patients, offering a proof-of-concept for clinical translation. Studying svPPA and PCA, two syndromes with well-defined focal atrophy patterns, offers a method to clinically validate and contrast automated algorithms.

Wavelet Based Filters for Artifact Elimination in Electroencephalography Signal: A Review

Electroencephalography (EEG) is a diagnostic test that records and measures the electrical activity of the human brain. Research investigating human behaviors and conditions using EEG has increased from year to year. Therefore, an efficient approach is vital to process the EEG dataset to improve the output signal quality. The wavelet is one of the well-known approaches for processing the EEG signal in time-frequency domain analysis. The wavelet is better than the traditional Fourier Transform because it has good time-frequency localized properties and multi-resolution analysis where the transient information of an EEG signal can be extracted efficiently. Thus, this review article aims to comprehensively describe the application of the wavelet method in denoising the EEG signal based on recent research. This review begins with a brief overview of the basic theory and characteristics of EEG and the wavelet transform method. Then, several wavelet-based methods commonly applied in EEG dataset denoising are described and a considerable number of the latest published EEG research works with wavelet applications are reviewed. Besides, the challenges that exist in current EEG-based wavelet method research are discussed. Finally, alternative solutions to mitigate the issues are recommended.

Cross-sectional assessment of mild cognitive impairment in pre-dialysis chronic kidney disease and its association with inflammation and changes seen on MRI: what the eyes cannot see

Introduction:

Mild cognitive impairment (MCI) is a prevalent and underdiagnosed condition in chronic kidney disease (CKD), that shares common pathophysiological factors such as chronic inflammation.

Objective:

To evaluate the association of MCI in CKD stages 1-5 using inflammatory markers and changes by magnetic resonance imaging (MRI).

Patients and Methods:

Cross-sectional study in adult patients with pre-dialysis CKD. MCI was assessed by the Montreal Cognitive Assessment (MoCA) and the estimated glomerular filtration rate (eGFR) by the Chronic Kidney Disease Epidemiology Collaboration equation. Sociodemographic and clinical data were collected from medical records. The cytokines IL-4, IL-6, IL-17, TNF-α and hs-CRP were determined. Brain MRI was performed in a 1.5 Tesla device, without paramagnetic contrast. A descriptive analysis followed by a comparison of abnormal versus normal MoCA scores among all studied variables. A linear regression analysis was performed using MoCA as a dependent variable, adjusted for confounding factors.

Results:

Of 111 invited patients, eighty completed the neuropsychological assessment and 56 underwent MRI, and were included in the study. Mean age was 56.3 ± 8.3 years and 51.8% (n = 29) had altered MoCA. When compared to the group with normal MoCA, the group with altered MoCA had higher levels of IL-6 and IL-17. There was no correlation between altered MoCA with eGFR or with MRI abnormalities.

Conclusão:

MCI assessed by MoCA was prevalent in patients with pre-dialysis CKD, it was associated with inflammation and showed no correlation with MRI changes.