Neurological update: neuroimaging in dementia

Cognitive complaints in older adults: relationships between self and informant report, objective test performance, and symptoms of depression

This study explored the relationships between objective measures of cognitive functioning, self and informant reports of cognitive problems in daily life, and depression screening in older adults who had been referred because of reported or suspected cognitive changes. We used archival data from 100, predominantly White (97%), typically educated (M = 13.25 years), older adults (M = 70.38 years) who received an outpatient neuropsychological evaluation. We characterized the cognitive performance using the CVLT-II Total score. We characterized patient and collateral reports using the BRIEF-A MI index, a normed scale of cognitive problems in daily life. We also incorporated a depression screener (PHQ-9) into our analyses. Multiple linear regression analysis revealed that only the informant reported problems in daily life, using the BRIEF-A MI index, was a significant predictor of objective cognitive deficits, as defined by CVLT-II Total scores. Self BRIEF-A MI index scores were not significant predictors of CVLT-II Total performance after we accounted for depression using the patient's PHQ-9 score. Additionally, elevated depression widened the discrepancy between raters, with elevated depression associated with worsening sself-report scores compared to informant-reported scores. As informant-reported problems were the strongest predictor of cognitive deficits, we recommend routine collection of collateral informant reports in the neuropsychological evaluation of older adults referred for cognitive concerns. We also recommend incorporating self-ratings of daily life functioning and screening for depression to contextualize patient complaints and address their concerns, even in the absence of objective cognitive dysfunction.

Understanding ethnic diversity in open dementia neuroimaging data sets

Ethnic differences in dementia are increasingly recognized in epidemiological measures and diagnostic biomarkers. Nonetheless, ethnic diversity remains limited in many study populations. Here, we provide insights into ethnic diversity in open-access neuroimaging dementia data sets. Data sets comprising dementia populations with available data on ethnicity were included. Statistical analyses of sample and effect sizes were based on the Cochrane Handbook. Nineteen databases were included, with 17 studies of healthy groups or a combination of diagnostic groups if breakdown was unavailable and 12 of mild cognitive impairment and dementia groups. Combining all studies on dementia patients, the largest ethnic group was Caucasian (20 547 participants), with the next most common being Afro-Caribbean (1958), followed by Asian (1211). The smallest effect size detectable within the Caucasian group was 0.03, compared to Afro-Caribbean (0.1) and Asian (0.13). Our findings quantify the lack of ethnic diversity in openly available dementia data sets. More representative data would facilitate the development and validation of biomarkers relevant across ethnicities.

Exploring the Frontiers of Neuroimaging: A Review of Recent Advances in Understanding Brain Functioning and Disorders

Neuroimaging has revolutionized our understanding of brain function and has become an essential tool for researchers studying neurological disorders. Functional magnetic resonance imaging (fMRI) and electroencephalography (EEG) are two widely used neuroimaging techniques to review changes in brain activity. fMRI is a noninvasive technique that uses magnetic fields and radio waves to produce detailed brain images. An EEG is a noninvasive technique that records the brain's electrical activity through electrodes placed on the scalp. This review overviews recent developments in noninvasive functional neuroimaging methods, including fMRI and EEG. Recent advances in fMRI technology, its application to studying brain function, and the impact of neuroimaging techniques on neuroscience research are discussed. Advances in EEG technology and its applications to analyzing brain function and neural oscillations are also highlighted. In addition, advanced courses in neuroimaging, such as diffusion tensor imaging (DTI) and transcranial electrical stimulation (TES), are described, along with their role in studying brain connectivity, white matter tracts, and potential treatments for schizophrenia and chronic pain. Application. The review concludes by examining neuroimaging studies of neurodevelopmental and neurological disorders such as autism spectrum disorder (ASD), attention deficit hyperactivity disorder (ADHD), Alzheimer's disease (AD), and Parkinson's disease (PD). We also described the role of transcranial direct current stimulation (tDCS) in ASD, ADHD, AD, and PD. Neuroimaging techniques have significantly advanced our understanding of brain function and provided essential insights into neurological disorders. However, further research into noninvasive treatments such as EEG, MRI, and TES is necessary to continue to develop new diagnostic and therapeutic strategies for neurological disorders.

Modifiable risk factors for dementia and dementia risk profiling. A user manual for Brain Health Services-part 2 of 6

We envisage the development of new Brain Health Services to achieve primary and secondary dementia prevention. These services will complement existing memory clinics by targeting cognitively unimpaired individuals, where the focus is on risk profiling and personalized risk reduction interventions rather than diagnosing and treating late-stage disease. In this article, we review key potentially modifiable risk factors and genetic risk factors and discuss assessment of risk factors as well as additional fluid and imaging biomarkers that may enhance risk profiling. We then outline multidomain measures and risk profiling and provide practical guidelines for Brain Health Services, with consideration of outstanding uncertainties and challenges. Users of Brain Health Services should undergo risk profiling tailored to their age, level of risk, and availability of local resources. Initial risk assessment should incorporate a multidomain risk profiling measure. For users aged 39-64, we recommend the Cardiovascular Risk Factors, Aging, and Incidence of Dementia (CAIDE) Dementia Risk Score, whereas for users aged 65 and older, we recommend the Brief Dementia Screening Indicator (BDSI) and the Australian National University Alzheimer's Disease Risk Index (ANU-ADRI). The initial assessment should also include potentially modifiable risk factors including sociodemographic, lifestyle, and health factors. If resources allow, apolipoprotein E ɛ4 status testing and structural magnetic resonance imaging should be conducted. If this initial assessment indicates a low dementia risk, then low intensity interventions can be implemented. If the user has a high dementia risk, additional investigations should be considered if local resources allow. Common variant polygenic risk of late-onset AD can be tested in middle-aged or older adults. Rare variants should only be investigated in users with a family history of early-onset dementia in a first degree relative. Advanced imaging with 18-fluorodeoxyglucose positron emission tomography (FDG-PET) or amyloid PET may be informative in high risk users to clarify the nature and burden of their underlying pathologies. Cerebrospinal fluid biomarkers are not recommended for this setting, and blood-based biomarkers need further validation before clinical use. As new technologies become available, advances in artificial intelligence are likely to improve our ability to combine diverse data to further enhance risk profiling. Ultimately, Brain Health Services have the potential to reduce the future burden of dementia through risk profiling, risk communication, personalized risk reduction, and cognitive enhancement interventions.

Improved neuropathological identification of traumatic brain injury through quantitative neuroimaging and neural network analyses: Some practical approaches for the neurorehabilitation clinician

BACKGROUND

Quantitative neuroimaging analyses have the potential to provide additional information about the neuropathology of traumatic brain injury (TBI) that more thoroughly informs the neurorehabilitation clinician.

OBJECTIVE

Quantitative neuroimaging is typically not covered in the standard radiological report, but often can be extracted via post-processing of clinical neuroimaging studies, provided that the proper volume acquisition sequences were originally obtained.

METHODS

Research and commercially available quantitative neuroimaging methods provide region of interest (ROI) quantification metrics, lesion burden volumetrics and cortical thickness measures, degree of focal encephalomalacia, white matter (WM) abnormalities and residual hemorrhagic pathology. If present, diffusion tensor imaging (DTI) provides a variety of techniques that aid in evaluating WM integrity. Using quantitatively identified structural and ROI neuropathological changes are most informative when done from a neural network approach.

RESULTS

Viewing quantitatively identifiable damage from a neural network perspective provides the neurorehabilitation clinician with an additional tool for linking brain pathology to understand symptoms, problems and deficits as well as aid neuropsychological test interpretation. All of these analyses can be displayed in graphic form, including3-D image analysis. A case study approach is used to demonstrate the utility of quantitative neuroimaging and network analyses in TBI.

CONCLUSIONS

Quantitative neuroimaging may provide additional useful information for the neurorehabilitation clinician.

Brain Metabolism and Microglia Activation in Mild Cognitive Impairment: A Combined [18F]FDG and [11C]-(R)-PK11195 PET Study

BACKGROUND

Mild cognitive impairment (MCI) is a transitional condition between normal cognition and dementia. [18F]FDG-PET reveals brain hypometabolism patterns reflecting neuronal/synaptic dysfunction, already in the prodromal MCI phase. Activated microglia is part of the pathogenetic processes leading to neurodegeneration.

OBJECTIVE

Using [11C]-(R)-PK11195 and [18F]FDG-PET, we aimed to in vivo investigate the presence of microglial activation, and the relationship with brain glucose metabolism, in single MCI subjects.

METHODS

Eight MCI subjects underwent both [18F]FDG-PET and [11C]-(R)-PK11195 PET. We used validated quantification methods to obtain brain hypometabolism maps and microglia activation peaks in single subjects. We investigated both the spatial overlap and the relationship between brain glucose hypometabolism and microglia activation, by means of Dice similarity coefficient and using Pearson's correlation at single subject level.

RESULTS

Each MCI showed a specific brain hypometabolism pattern indicative of different possible etiologies, as expected in MCI population (i.e., Alzheimer's disease-like, frontotemporal dementia-like, hippocampal-type, normal aging type). [11C]-(R)-PK11195 PET analysis revealed a spatial concordance with regional hypometabolism in all subjects with several clusters of significant microglia activation showing an inverse correlation with the regional metabolism. This was proportional to the strength of between-signals correlation coefficient (β  =  -0.804; p = 0.016).

CONCLUSION

Microglia activation is present in the prodromal MCI phase of different underlying etiologies, showing spatial concordance and inverse correlation with brain glucose metabolism at single-subject level. These findings suggest a possible contribution of activated microglia to neurodegeneration, showing important implications for local immune activity in the early neurodegenerative processes.