Transcranial Doppler could help to differentiate the types of dementia? A pilot study when CSF biomarkers are not available.

Our objective was to find a mean flow velocity (MFV) cut-off point to differentiate between normal and cognitive impaired patients using Clinical Dementia Rating (CDR) as a comparison method. To evaluate MFV (in cm/s) and pulsatility index (PI) from the left middle cerebral artery (MCA) and basilar artery using transcranial Doppler in a pilot study from an outpatient cognition unit and compare with cognitively normal older adults (at the age of sixty or older) from the Geriatric Ambulatory of Fluminense Federal University. We hypothesized that there is a MFV and PI cut-off point to potentially distinguish between normal and impaired cognition. Sixty-one patients with cognitive decline, including 18 with amnestic mild cognitive impairment (aMCI), 31 with probable Alzheimer disease (AD), 12 with vascular dementia (VD), and 10 cognitively normal older adults were included in the study. Patients with dementia (both AD and VD, p < 0.01) and aMCI (p < 0.05) had lower MFV than the control group in the MCA (32.2 cm/s, 31.9 cm/s, and 36.6 cm/s, respectively) and dementia patients had higher PI compared to control (AD and VD, both p < 0.05). Basilar MFV showed to be no difference between the patients and the control group. A cut off value of 39.1 cm/s was found in a ROC curve (area under de curve value 0.85, 95% CI 0.75-0.95) for mean MCA MFV to be predictive of cognitive impairment (CDR ≥ 0.5). In this study, the values of MCA MFV below 39.1 cm/s were predictive of cognitive impairment according to CDR. TCD is an inexpensive method that could be used in a clinical scenario to help differentiate normal cognition from cognitive decline. Multicentric and longitudinal studies should be done to validate that.

Aerobic training modulates salience network and default mode network metabolism in subjects with mild cognitive impairment.

Aerobic training (AT) is a promising intervention to improve cognitive functioning. However, its modulatory effects on brain networks are not yet entirely understood. Sixty-five subjects with mild cognitive impairment performed a moderate intensity, 24-week AT program. Differences in resting regional brain glucose metabolism (rBGM) with FDG-PET were assessed before and after AT on a voxel-by-voxel basis. Structural equation modeling was used to create latent variables based on regions with significant rBGM changes and to test a hypothetical model about the inter-relationships between these changes. There were significant rBGM reductions in both anterior temporal lobes (ATL), left inferior frontal gyrus, left anterior cingulate cortex, right hippocampus, left meddle frontal gyrus and bilateral caudate nuclei. In contrast, there was an increase in rBGM in the right precuneus and left inferior frontal gyrus. Latent variables reflecting the salience network and ATL were created, while the precuneus represented the default mode network. In the model, salience network rBGM was decreased after AT. In contrast, rBGM in the default mode network increased as a final outcome. This result suggested improved salience network efficacy and increased control over other brain functional networks. The ATL network decreased its rBGM and connected to the salience network and default mode network with positive and negative correlations, respectively. The model fit values reached statistical significance, demonstrating that this model explained the variance in the measured data. In mild cognitive impairment subjects, AT modulated rBGM in salience network and default mode network nodes. Such changes were in the direction of the normally expected resting-state metabolic patterns of these networks.