Computerized Cognitive Training in Mild Cognitive Impairment: Findings in African Americans and Caucasians

BACKGROUND

African Americans with MCI may be at increased risk for dementia compared to Caucasians. The effect of race on the efficacy of cognitive training in MCI is unclear.

METHODS

We used data from a two-site, 78-week randomized trial of MCI comparing intensive, home-based, computerized training with Web-based cognitive games or Web-based crossword puzzles to examine the effect of race on outcomes. The study outcomes were changes from baseline in cognitive and functional scales as well as MRI-measured changes in hippocampal volume and cortical thickness. Analyses used linear models adjusted for baseline scores. This was an exploratory study.

RESULTS

A total of 105 subjects were included comprising 81 whites (77.1%) and 24 African Americans (22.8%). The effect of race on the change from baseline in ADAS-Cog-11 was not significant. The effect of race on change from baseline to week 78 in the Functional Activities Questionnaire (FAQ) was significant with African American participants' FAQ scores showing greater improvements at weeks 52 and 78 (P = 0.009, P = 0.0002, respectively) than white subjects. Within the CCT cohort, FAQ scores for African American participants showed greater improvement between baseline and week 78, compared to white participants randomized to CCT (P = 0.006). There was no effect of race on the UPSA. There was no effect of race on hippocampal or cortical thickness outcomes.

CONCLUSIONS

Our preliminary findings suggest that web-based cognitive training programs may benefit African Americans with MCI at least as much as Caucasians, and highlight the need to further study underrepresented minorities in AD prevention trials. (Supported by the National Institutes of Health, National Institute on Aging; ClinicalTrials.gov number, NCT03205709.).

Expectancy Does Not Predict 18-month Treatment Outcomes with Cognitive Training in Mild Cognitive Impairment

BACKGROUND

Computerized cognitive training (CCT) has emerged as a potential treatment option for mild cognitive impairment (MCI). It remains unclear whether CCT's effect is driven in part by expectancy of improvement.

OBJECTIVES

This study aimed to determine factors associated with therapeutic expectancy and the influence of therapeutic expectancy on treatment effects in a randomized clinical trial of CCT versus crossword puzzle training (CPT) for older adults with MCI.

DESIGN

Randomized clinical trial of CCT vs CPT with 78-week follow-up.

SETTING

Two-site study - New York State Psychiatric Institute and Duke University Medical Center.

PARTICIPANTS

107 patients with MCI.

INTERVENTION

12 weeks of intensive training with CCT or CPT with follow-up booster training over 78 weeks.

MEASUREMENTS

Patients rated their expectancies for CCT and CPT prior to randomization.

RESULTS

Patients reported greater expectancy for CCT than CPT. Lower patient expectancy was associated with lower global cognition at baseline and older age. Expectancy did not differ by sex or race. There was no association between expectancy and measures of everyday functioning, hippocampus volume, or apolipoprotein E genotype. Expectancy was not associated with change in measures of global cognition, everyday functioning, and hippocampus volume from baseline to week 78, nor did expectancy interact with treatment condition.

CONCLUSIONS

While greater cognitive impairment and increased age was associated with low expectancy of improvement, expectancy was not associated with the likelihood of response to treatment with CPT or CCT.

Personalized Computational Causal Modeling of the Alzheimer Disease Biomarker Cascade

BACKGROUND

Mathematical models of complex diseases, such as Alzheimer's disease, have the potential to play a significant role in personalized medicine. Specifically, models can be personalized by fitting parameters with individual data for the purpose of discovering primary underlying disease drivers, predicting natural history, and assessing the effects of theoretical interventions. Previous work in causal/mechanistic modeling of Alzheimer's Disease progression has modeled the disease at the cellular level and on a short time scale, such as minutes to hours. No previous studies have addressed mechanistic modeling on a personalized level using clinically validated biomarkers in individual subjects.

OBJECTIVES

This study aimed to investigate the feasibility of personalizing a causal model of Alzheimer's Disease progression using longitudinal biomarker data.

DESIGN/SETTING/PARTICIPANTS/MEASUREMENTS

We chose the Alzheimer Disease Biomarker Cascade model, a widely-referenced hypothetical model of Alzheimer's Disease based on the amyloid cascade hypothesis, which we had previously implemented mathematically as a mechanistic model. We used available longitudinal demographic and serial biomarker data in over 800 subjects across the cognitive spectrum from the Alzheimer's Disease Neuroimaging Initiative. The data included participants that were cognitively normal, had mild cognitive impairment, or were diagnosed with dementia (probable Alzheimer's Disease). The model consisted of a sparse system of differential equations involving four measurable biomarkers based on cerebrospinal fluid proteins, imaging, and cognitive testing data.

RESULTS

Personalization of the Alzheimer Disease Biomarker Cascade model with individual serial biomarker data yielded fourteen personalized parameters in each subject reflecting physiologically meaningful characteristics. These included growth rates, latency values, and carrying capacities of the various biomarkers, most of which demonstrated significant differences across clinical diagnostic groups. The model fits to training data across the entire cohort had a root mean squared error (RMSE) of 0.09 (SD 0.081) on a variable scale between zero and one, and were robust, with over 90% of subjects showing an RMSE of < 0.2. Similarly, in a subset of subjects with data on all four biomarkers in at least one test set, performance was high on the test sets, with a mean RMSE of 0.15 (SD 0.117), with 80% of subjects demonstrating an RMSE < 0.2 in the estimation of future biomarker points. Cluster analysis of parameters revealed two distinct endophenotypic groups, with distinct biomarker profiles and disease trajectories.

CONCLUSION

Results support the feasibility of personalizing mechanistic models based on individual biomarker trajectories and suggest that this approach may be useful for reclassifying subjects on the Alzheimer's clinical spectrum. This computational modeling approach is not limited to the Alzheimer Disease Biomarker Cascade hypothesis, and can be applied to any mechanistic hypothesis of disease progression in the Alzheimer's field that can be monitored with biomarkers. Thus, it offers a computational platform to compare and validate various disease hypotheses, personalize individual biomarker trajectories and predict individual response to theoretical prevention and therapeutic intervention strategies.

MRI-based Deep Learning Assessment of Amyloid, Tau, and Neurodegeneration Biomarker Status across the Alzheimer Disease Spectrum

Background PET can be used for amyloid-tau-neurodegeneration (ATN) classification in Alzheimer disease, but incurs considerable cost and exposure to ionizing radiation. MRI currently has limited use in characterizing ATN status. Deep learning techniques can detect complex patterns in MRI data and have potential for noninvasive characterization of ATN status. Purpose To use deep learning to predict PET-determined ATN biomarker status using MRI and readily available diagnostic data. Materials and Methods MRI and PET data were retrospectively collected from the Alzheimer's Disease Imaging Initiative. PET scans were paired with MRI scans acquired within 30 days, from August 2005 to September 2020. Pairs were randomly split into subsets as follows: 70% for training, 10% for validation, and 20% for final testing. A bimodal Gaussian mixture model was used to threshold PET scans into positive and negative labels. MRI data were fed into a convolutional neural network to generate imaging features. These features were combined in a logistic regression model with patient demographics, APOE gene status, cognitive scores, hippocampal volumes, and clinical diagnoses to classify each ATN biomarker component as positive or negative. Area under the receiver operating characteristic curve (AUC) analysis was used for model evaluation. Feature importance was derived from model coefficients and gradients. Results There were 2099 amyloid (mean patient age, 75 years ± 10 [SD]; 1110 male), 557 tau (mean patient age, 75 years ± 7; 280 male), and 2768 FDG PET (mean patient age, 75 years ± 7; 1645 male) and MRI pairs. Model AUCs for the test set were as follows: amyloid, 0.79 (95% CI: 0.74, 0.83); tau, 0.73 (95% CI: 0.58, 0.86); and neurodegeneration, 0.86 (95% CI: 0.83, 0.89). Within the networks, high gradients were present in key temporal, parietal, frontal, and occipital cortical regions. Model coefficients for cognitive scores, hippocampal volumes, and APOE status were highest. Conclusion A deep learning algorithm predicted each component of PET-determined ATN status with acceptable to excellent efficacy using MRI and other available diagnostic data. © RSNA, 2023 Supplemental material is available for this article.

Column-based cortical depth analysis of the diffusion anisotropy and radiality in submillimeter whole-brain diffusion tensor imaging of the human cortical gray matter in vivo

High-resolution diffusion tensor imaging (DTI) can noninvasively probe the microstructure of cortical gray matter in vivo. In this study, 0.9-mm isotropic whole-brain DTI data were acquired in healthy subjects with an efficient multi-band multi-shot echo-planar imaging sequence. A column-based analysis that samples the fractional anisotropy (FA) and radiality index (RI) along radially oriented cortical columns was then performed to quantitatively analyze the FA and RI dependence on the cortical depth, cortical region, cortical curvature, and cortical thickness across the whole brain, which has not been simultaneously and systematically investigated in previous studies. The results showed characteristic FA and RI vs. cortical depth profiles, with an FA local maximum and minimum (or two inflection points) and a single RI maximum at intermediate cortical depths in most cortical regions, except for the postcentral gyrus where no FA peaks and a lower RI were observed. These results were consistent between repeated scans from the same subjects and across different subjects. They were also dependent on the cortical curvature and cortical thickness in that the characteristic FA and RI peaks were more pronounced i) at the banks than at the crown of gyri or at the fundus of sulci and ii) as the cortical thickness increases. This methodology can help characterize variations in microstructure along the cortical depth and across the whole brain in vivo, potentially providing quantitative biomarkers for neurological disorders.

Changes in resting state networks in high school football athletes across a single season

OBJECTIVE

The aim of this pilot cohort study was to examine changes in the organization of resting-state brain networks in high school football athletes and its relationship to exposure to on-field head impacts over the course of a single season.

METHODS

Seventeen male high school football players underwent functional magnetic resonance imaging and computerized neurocognitive testing (CNS Vital Signs) before the start of contact practices and again after the conclusion of the season. The players were equipped with helmet accelerometer systems (Head Impact Telemetry System) to record head impacts in practices and games. Graph theory analysis was applied to study intranetwork local efficiency and strength of connectivity within six anatomically defined brain networks.

RESULTS

We observed a significant decrease in the local efficiency (-24.9 ± 51.4%, r = 0.7, p < 0.01) and strength (-14.5 ± 26.8%, r = 0.5, p < 0.01) of functional connectivity within the frontal lobe resting-state network and strength within the parietal lobe resting-state network (-7.5 ± 17.3%, r = 0.1, p < 0.01), as well as a concomitant increase in the local efficiency (+55.0 +/- 59.8%, r = 0.5, p < 0.01) and strength (+47.4 +/- 47.3%, r = 0.5, p < 0.01) within the mediotemporal networks. These alterations in network organization were associated with changes in performance on verbal memory (p < 0.05) and executive function (p < 0.05). We did not observe a significant relationship between the frequency or cumulative magnitude of impacts sustained during the season and neurocognitive or imaging outcomes (p > 0.05).

CONCLUSION

Our findings suggest the efficiency and strength of resting-state networks are altered across a season of high school football, but the association of exposure levels to subconcussive impacts is unclear.

ADVANCES IN KNOWLEDGE

The efficiency of resting-state networks is dynamic in high school football athletes; such changes may be related to impacts sustained during the season, though further study is needed.

Prenatal heroin exposure alters brain morphology and connectivity in adolescent mice

The United States is experiencing a dramatic increase in maternal opioid misuse and, consequently, the number of individuals exposed to opioids in utero. Prenatal opioid exposure has both acute and long-lasting effects on health and wellbeing. Effects on the brain, often identified at school age, manifest as cognitive impairment, attention deficit, and reduced scholastic achievement. The neurobiological basis for these effects is poorly understood. Here, we examine how in utero exposure to heroin affects brain development into early adolescence in a mouse model. Pregnant C57BL/6J mice received escalating doses of heroin twice daily on gestational days 4-18. The brains of offspring were assessed on postnatal day 28 using 9.4 T diffusion MRI of postmortem specimens at 36 μm resolution. Whole-brain volumes and the volumes of 166 bilateral regions were compared between heroin-exposed and control offspring. We identified a reduction in whole-brain volume in heroin-exposed offspring and heroin-associated volume changes in 29 regions after standardizing for whole-brain volume. Regions with bilaterally reduced standardized volumes in heroin-exposed offspring relative to controls include the ectorhinal and insular cortices. Regions with bilaterally increased standardized volumes in heroin-exposed offspring relative to controls include the periaqueductal gray, septal region, striatum, and hypothalamus. Leveraging microscopic resolution diffusion tensor imaging and precise regional parcellation, we generated whole-brain structural MRI diffusion connectomes. Using a dimension reduction approach with multivariate analysis of variance to assess group differences in the connectome, we found that in utero heroin exposure altered structure-based connectivity of the left septal region and the region that acts as a hub for limbic regulatory actions. Consistent with clinical evidence, our findings suggest that prenatal opioid exposure may have effects on brain morphology, connectivity, and, consequently, function that persist into adolescence. This work expands our understanding of the risks associated with opioid misuse during pregnancy and identifies biomarkers that may facilitate diagnosis and treatment.

Impact of Computerized Cognitive Training on Default Mode Network Connectivity in Subjects at Risk for Alzheimer's Disease: A 78-week Randomized Controlled Trial

BACKGROUND

Mild cognitive impairment (MCI) represents a high risk group for Alzheimer's disease (AD). Computerized Cognitive Games Training (CCT) is an investigational strategy to improve targeted functions in MCI through the modulation of cognitive networks.

OBJECTIVE

The goal of this study was to examine the effect of CCT versus a non-targeted active brain exercise on functional cognitive networks.

METHODS

107 patients with MCI were randomized to CCT or web-based crossword puzzles. Resting-state functional MRI (fMRI) was obtained at baseline and 18 months to evaluate differences in fMRI measured within- and between-network functional connectivity (FC) of the default mode network (DMN) and other large-scale brain networks: the executive control, salience, and sensorimotor networks.

RESULTS

There were no differences between crosswords and games in the primary outcome, within-network DMN FC across all subjects. However, secondary analyses suggest differential effects on between-network connectivity involving the DMN and SLN, and within-network connectivity of the DMN in subjects with late MCI. Paradoxically, in both cases, there was a decrease in FC for games and an increase for the crosswords control (p < 0.05), accompanied by lesser cognitive decline in the crosswords group.

CONCLUSION

Results do not support a differential impact on within-network DMN FC between games and crossword puzzle interventions. However, crossword puzzles might result in cognitively beneficial remodeling between the DMN and other networks in more severely impaired MCI subjects, parallel to the observed clinical benefits.

Computerized Games versus Crosswords Training in Mild Cognitive Impairment

BACKGROUND

Mild cognitive impairment (MCI) increases the risk of dementia. The efficacy of cognitive training in patients with MCI is unclear.

METHODS

In a two-site, single-blinded, 78-week trial, participants with MCI - stratified by age, severity (early/late MCI), and site - were randomly assigned to 12 weeks of intensive, home-based, computerized training with Web-based cognitive games or Web-based crossword puzzles, followed by six booster sessions. In mixed-model analyses, the primary outcome was change from baseline in the 11-item Alzheimer's Disease Assessment Scale-Cognitive (ADAS-Cog) score, a 70 point scale in which higher scores indicate greater cognitive impairment at 78 weeks, adjusted for baseline. Secondary outcomes included change from baseline in neuropsychological composite score, University of California San Diego Performance-Based Skills Assessment (functional outcome) score, and Functional Activities Questionnaire (functional outcome) score at 78 weeks, adjusted for baseline. Changes in hippocampal volume and cortical thickness on magnetic resonance imaging were assessed.

RESULTS

Among 107 participants (n=51 [games]; n=56 [crosswords]), ADAS-Cog score worsened slightly for games and improved for crosswords at week 78 (least squares [LS] means difference, -1.44; 95% confidence interval [CI], -2.83 to -0.06; P=0.04). From baseline to week 78, mean ADAS-Cog score worsened for games (9.53 to 9.93) and improved for crosswords (9.59 to 8.61). The late MCI subgroup showed similar results (LS means difference, -2.45; SE, 0.89; 95% CI, -4.21 to -0.70). Among secondary outcomes, the Functional Activities Questionnaire score worsened more with games than with crosswords at week 78 (LS means difference, -1.08; 95% CI, -1.97 to -0.18). Other secondary outcomes showed no differences. Decreases in hippocampal volume and cortical thickness were greater for games than for crosswords (LS means difference, 34.07; SE, 17.12; 95% CI, 0.51 to 67.63 [hippocampal volume]; LS means difference, 0.02; SE, 0.01; 95% CI, 0.00 to 0.04 [cortical thickness]).

CONCLUSIONS

Home-based computerized training with crosswords demonstrated superior efficacy to games for the primary outcome of baseline-adjusted change in ADAS-Cog score over 78 weeks. (Supported by the National Institutes of Health, National Institute on Aging; ClinicalTrials.gov number, NCT03205709.).

Data-driven causal model discovery and personalized prediction in Alzheimer's disease

With the explosive growth of biomarker data in Alzheimer’s disease (AD) clinical trials, numerous mathematical models have been developed to characterize disease-relevant biomarker trajectories over time. While some of these models are purely empiric, others are causal, built upon various hypotheses of AD pathophysiology, a complex and incompletely understood area of research. One of the most challenging problems in computational causal modeling is using a purely data-driven approach to derive the model’s parameters and the mathematical model itself, without any prior hypothesis bias. In this paper, we develop an innovative data-driven modeling approach to build and parameterize a causal model to characterize the trajectories of AD biomarkers. This approach integrates causal model learning, population parameterization, parameter sensitivity analysis, and personalized prediction. By applying this integrated approach to a large multicenter database of AD biomarkers, the Alzheimer’s Disease Neuroimaging Initiative, several causal models for different AD stages are revealed. In addition, personalized models for each subject are calibrated and provide accurate predictions of future cognitive status.

Validity of the Web-Based, Self-Directed, NeuroCognitive Performance Test in Mild Cognitive Impairment

BACKGROUND

Digital cognitive tests offer several potential advantages over established paper-pencil tests but have not yet been fully evaluated for the clinical evaluation of mild cognitive impairment.

OBJECTIVE

The NeuroCognitive Performance Test (NCPT) is a web-based, self-directed, modular battery intended for repeated assessments of multiple cognitive domains. Our objective was to examine its relationship with the Alzheimer's Disease Assessment Scale-Cognition Subscale (ADAS-Cog) and Mini-Mental State Examination (MMSE) as well as with established paper-pencil tests of cognition and daily functioning in mild cognitive impairment (MCI).

METHODS

We used Spearman correlations, regressions and principal components analysis followed by a factor analysis (varimax rotated) to examine our objectives.

RESULTS

In MCI subjects, the NCPT composite is significantly correlated with both a composite measure of established tests (r = 0.77, p <  0.0001) as well as with the ADAS-Cog (r = 0.55, p <  0.0001). Both NCPT and paper-pencil test batteries had a similar factor structure that included a large "g" component with a high eigenvalue. The correlation for the analogous tests (e.g., Trails A and B, learning memory tests) were significant (p <  0.0001). Further, both the NCPT and established tests significantly (p <  0.01) predicted the University of California San Diego Performance-Based Skills Assessment and Functional Activities Questionnaire, measures of daily functioning.

CONCLUSION

The NCPT, a web-based, self-directed, computerized test, shows high concurrent validity with established tests and hence offers promise for use as a research or clinical tool in MCI. Despite limitations such as a relatively small sample, absence of control group and cross-sectional nature, these findings are consistent with the growing literature on the promise of self-directed, web-based cognitive assessments for MCI.

Diffusion Tensor MRI Structural Connectivity and PET Amyloid Burden in Preclinical Autosomal Dominant Alzheimer Disease: The DIAN Cohort

Background Pathologic evidence of Alzheimer disease (AD) is detectable years before onset of clinical symptoms. Imaging-based identification of structural changes of the brain in people at genetic risk for early-onset AD may provide insights into how genes influence the pathologic cascade that leads to dementia. Purpose To assess structural connectivity differences in cortical networks between cognitively normal autosomal dominant Alzheimer disease (ADAD) mutation carriers versus noncarriers and to determine the cross-sectional relationship of structural connectivity and cortical amyloid burden with estimated years to symptom onset (EYO) of dementia in carriers. Materials and Methods In this exploratory analysis of a prospective trial, all participants enrolled in the Dominantly Inherited Alzheimer Network between January 2009 and July 2014 who had normal cognition at baseline, T1-weighted MRI scans, and diffusion tensor imaging (DTI) were analyzed. Amyloid PET imaging using Pittsburgh compound B was also analyzed for mutation carriers. Areas of the cerebral cortex were parcellated into three cortical networks: the default mode network, frontoparietal control network, and ventral attention network. The structural connectivity of the three networks was calculated from DTI. General linear models were used to examine differences in structural connectivity between mutation carriers and noncarriers and the relationship between structural connectivity, amyloid burden, and EYO in mutation carriers. Correlation network analysis was performed to identify clusters of related clinical and imaging markers. Results There were 30 mutation carriers (mean age ± standard deviation, 34 years ± 10; 17 women) and 38 noncarriers (mean age, 37 years ± 10; 20 women). There was lower structural connectivity in the frontoparietal control network in mutation carriers compared with noncarriers (estimated effect of mutation-positive status, -0.0266; P = .04). Among mutation carriers, there was a correlation between EYO and white matter structural connectivity in the frontoparietal control network (estimated effect of EYO, -0.0015, P = .01). There was no significant relationship between cortical global amyloid burden and EYO among mutation carriers (P > .05). Conclusion White matter structural connectivity was lower in autosomal dominant Alzheimer disease mutation carriers compared with noncarriers and correlated with estimated years to symptom onset. Clinical trial registration no. NCT00869817 © RSNA, 2021 Online supplemental material is available for this article. See also the editorial by McEvoy in this issue.

Cortical thickness predicts remission of depression with antidepressants in patients with late-life depression and cognitive impairment

BACKGROUND

Depression (DEP) and cognitive impairment (CI) share etiological risk factors, anatomical underpinnings, and interact to produce deleterious treatment outcomes. Both DEP and CI exhibit altered patterns of cortical thickness which may impact the course of antidepressant treatment, though inconsistencies in directionality and affected brain regions have been reported. In this study, we examined the relationship between cortical thickness and treatment outcome in older adults with comorbid DEP-CI.

METHODS

55 patients with DEP-CI received baseline MRI scans as part of a larger clinical trial at NYSPI/Columbia University Medical Center and Duke University Medical Center. Mood was assessed using the Hamilton Depression Rating Scale. Patients received open antidepressant treatment for 8 weeks followed by another 8 weeks of the same medication or switch to another antidepressant for a total of 16 weeks. Cortical thickness was extracted using an automated brain segmentation program (FreeSurfer). Vertex-wise analyses evaluated the relationship between cortical thickness and treatment outcome.

RESULTS

Remitters exhibited diffuse clusters of greater cortical thickness and reduced cortical thickness compared to non-remitters. Thicker baseline middle frontal gyrus most consistently predicted greater likelihood and faster rate of remission. White matter hyperintensities and hippocampal volume were not associated with antidepressant treatment outcome.

LIMITATIONS

MRI was conducted at baseline only and sample size was small.

DISCUSSION

Cortical thickness predicts treatment remission and magnitude of early improvement. Results indicate that individuals with DEP-CI exhibit unique patterns of structural abnormalities compared to their depressed peers without CI that have consequences for their recovery with antidepressant treatment.

Magnetic resonance imaging volumetric analysis in patients with Alternating hemiplegia of childhood: A pilot study

Quantitative MRI is increasingly being used as a biomarker in neurological disorders. Cerebellar atrophy occurs in some Alternating Hemiplegia of Childhood (AHC) patients. However, it is not known if cerebellar atrophy can be a potential biomarker in AHC or if quantitative MRI is a reliable method to address this question. Here we determine the reproducibility of an MRI-volumetrics method to investigate brain volumes in AHC and apply it to a population of 14 consecutive AHC patients (ages 4-11 years). We studied method reproducibility in the first 11 patients and then performed correlation of cerebellar volumes, relative to published normal population means, with age in all 14. We used FreeSurfer 6.0.0 to automatically segment MRI images, then performed manual resegmentation correction by two different observers. No significant differences were observed in any of ten brain regions between the two reviewers: p > .591 and interclass Correlation Coefficient (ICC) ≥0.975 in all comparisons. Additionally, there were no significant differences between the means of the two reviewers and the automatic segmentation values: p ≥ .106 and ICC ≥0.994 in all comparisons. We found a negative correlation between cerebellar volume and age (R = -0.631, p = .037), even though only one patient showed any cerebellar atrophy upon formal readings of the MRIs by neuroradiology. Sample size did not allow us to rule out potential confounding variables. Thus, findings from this cross-sectional study should be considered as exploratory. Our study supports the prospective investigation of quantitative MRI-volumetrics of the cerebellum as a potential biomarker in AHC.

Correlation of OCTA and Volumetric MRI in Mild Cognitive Impairment and Alzheimer's Disease

BACKGROUD AND OBJECTIVE

To evaluate the relationship between retinal microvascular parameters on optical coherence tomography angiography (OCTA) and neurodegenerative changes assessed by measurement of brain volume on volumetric magnetic resonance imaging (MRI) in Alzheimer's disease (AD) and mild cognitive impairment (MCI).

PATIENTS AND METHODS

Sixteen subjects with AD and MCI underwent OCTA imaging (3 mm × 3 mm and 6 mm × 6 mm scans) and volumetric brain MRI imaging with automated volumetric segmentation and quantification. Spearman's correlation (ρ) was performed between forebrain parenchyma, cortical gray matter, inferolateral ventricle (ILV), lateral ventricle (LV), and hippocampus (HP) MRI volumes and vessel density (VD), along with perfusion density (PD) for the 6-mm circle, 6-mm ring, 3-mm circle, and 3-mm ring Early Treatment Diabetic Retinopathy Study regions of the superficial capillary plexus.

RESULTS

Thirty eyes of 16 patients (seven MCI and nine AD) with good-quality OCTA images were analyzed. ILV volume inversely correlated with the VD in the 6-mm circle (ρ = -0 .565, P = .028) and 3-mm ring (ρ = -0.569, P = .027) and PD in the 3-mm ring (ρ = -0.605, P = .0169). Forebrain, cortical gray matter, LV, and HP volumes did not significantly correlate with either VD or PD (P > .05).

CONCLUSIONS

In this pilot investigation, the authors found a significant correlation between reduction in the superficial capillary plexus VD and PD on OCTA and expansion of the ILV in MCI and AD. This relationship between the retinal microvasculature and cerebral volumetric changes deserves further investigation. [Ophthalmic Surg Lasers Imaging Retina. 2019;50:709-718.].

Financial Management Skills in Aging, MCI and Dementia: Cross Sectional Relationship to 18F-Florbetapir PET Cortical β-amyloid Deposition

BACKGROUND

There is a need to more fully characterize financial capacity losses in the preclinical and prodromal stages of Alzheimer's disease (AD) and their pathological substrates.

OBJECTIVES

To test the association between financial skills and cortical β-amyloid deposition in aging and subjects at risk for AD.

DESIGN

Cross-sectional analyses of data from the Alzheimer's Disease Neuroimaging Initiative (ADNI-3) study conducted across 50 plus sites in the US and Canada.

SETTING

Multicenter biomarker study.

PARTICIPANTS

243 subjects (144 cognitively normal, 79 mild cognitive impairment [MCI], 20 mild AD).

MEASUREMENTS

18F-Florbetapir brain PET scans to measure global cortical β-amyloid deposition (SUVr) and the Financial Capacity Instrument Short Form (FCI-SF) to evaluate an individual's financial skills in monetary calculation, financial concepts, checkbook/register usage, and bank statement usage. There are five sub scores and a total score (range of 0-74) with higher scores indicating better financial skill.

RESULTS

FCI-SF total score was significantly worse in MCI [Cohen's d= 0.9 (95%CI: 0.6-1.2)] and AD subjects [Cohen's d=3.1(CI: 2.5-3.7)] compared to normals. Domain scores and completion times also showed significant difference. Across all subjects, higher cortical β-amyloid SUVr was significantly associated with worse FCI-SF total score after co-varying for age, education, and cognitive score [Cohen's f2=0.751(CI: 0.5-1.1)]. In cognitively normal subjects, after covarying for age, gender, and education, higher β -amyloid PET SUVr was associated with longer task completion time [Cohen's f2=0.198(CI: 0.06-0.37)].

CONCLUSION

Using a multicenter study sample, we document that financial capacity is impaired in the prodromal and mild stages of AD and that such impairments are, in part, associated with the extent of cortical β-amyloid deposition. In normal aging, β-amyloid deposition is associated with slowing of financial tasks. These data confirm and extend prior research highlighting the utility of financial capacity assessments in at risk samples.

Clinical and radiological characteristics of early versus late mild cognitive impairment in patients with comorbid depressive disorder

OBJECTIVE

The classification of mild cognitive impairment (MCI) continues to be debated though it has recently been subtyped into late (LMCI) versus early (EMCI) stages. Older adults presenting with both a depressive disorder (DEP) and cognitive impairment (CI) represent a unique, understudied population. Our aim was to examine baseline characteristics of DEP-CI patients in the DOTCODE trial, a randomized controlled trial of open antidepressant treatment for 16 weeks followed by add-on donepezil or placebo for 62 weeks.

METHODS/DESIGN

Key inclusion criteria were diagnosis of major depression or dysthymic disorder with Hamilton Depression Rating Scale (HAM-D) score >14, and cognitive impairment defined by MMSE score ≥21 and impaired performance on the WMS-R Logical Memory II test. Patients were classified as EMCI or LMCI based on the 1.5 SD cutoff on tests of verbal memory, and compared on baseline clinical, neuropsychological, and anatomical characteristics.

RESULTS

Seventy-nine DEP-CI patients were recruited of whom 39 met criteria for EMCI and 40 for LMCI. The mean age was 68.9, and mean HAM-D was 23.0. Late mild cognitive impairment patients had significantly worse ADAS-Cog (P < .001), MMSE (P = .004), Block Design (P = .024), Visual Rep II (P = .006), CFL Animal (P = .006), UPSIT (P = .051), as well as smaller right hippocampal volume (P = .037) compared to EMCI patients. MRI indices of cerebrovascular disease did not differ between EMCI and LMCI patients.

CONCLUSIONS

Cognitive and neuronal loss markers differed between EMCI and LMCI among patients with DEP-CI, with LMCI being more likely to have the clinical and neuronal loss markers known to be associated with Alzheimer's disease.

Donepezil Treatment in Patients With Depression and Cognitive Impairment on Stable Antidepressant Treatment: A Randomized Controlled Trial

OBJECTIVE

Depression and cognitive impairment are often comorbid in older adults, but optimal treatment strategies remain unclear. In a two-site study, the efficacy and safety of add-on donepezil versus placebo were compared in depressed patients with cognitive impairment receiving stable antidepressant treatment.

METHODS

A randomized, double-blind, placebo-controlled trial was conducted in older adults with depression and cognitive impairment (https://clinicaltrials.gov/ct2/show/NCT01658228; NCT01658228). Patients received open-label antidepressant treatment for 16 weeks, initially with citalopram and then with venlafaxine, if needed, followed by random assignment to add-on donepezil 5-10 mg daily or placebo for another 62 weeks. Outcome measures were neuropsychological test performance (Alzheimer's Disease Assessment Scale-Cognitive subscale [ADAS-Cog] and Selective Reminding Test [SRT] total immediate recall) and instrumental activities of daily living (Functional Activities Questionnaire).

RESULTS

Of 81 patients who signed informed consent, 79 patients completed the baseline evaluation. Open antidepressant treatment was associated with improvement in depression in 63.93% responders by week 16. In the randomized trial, there were no treatment group differences between donepezil and placebo on dementia conversion rates, ADAS-Cog, SRT total immediate recall, or FAQ. Neither baseline cognitive impairment severity nor apolipoprotein E e4 genotype influenced donepezil efficacy. Donepezil was associated with more adverse effects than placebo.

CONCLUSION

The results do not support adjunctive off-label cholinesterase inhibitor treatment in patients with depression and cognitive impairment. The findings highlight the need to prioritize discovery of novel treatments for this highly prevalent population with comorbid illnesses.

Microstructural alterations of cortical and deep gray matter over a season of high school football revealed by diffusion kurtosis imaging

OBJECTIVES

To probe microstructural changes that are associated with subconcussive head impact exposure in deep and cortical gray matter of high school football players over a single season.

METHODS

Players underwent diffusion kurtosis imaging (DKI) and quantitative susceptibility mapping (QSM) scans. Head impact data was recorded. Association between parametric changes and frequency of frontal head impact was assessed.

RESULTS

In deep gray matter, significant decreases in mean kurtosis (MK) and increases in mean diffusivity (MD) over the season were observed in the thalamus and putamen. Correlations between changes in DKI metrics and frequency of frontal impacts were observed in the putamen and caudate. In cortical gray matter, decreases in MK were observed in regions including the pars triangularis and inferior parietal. In addition, increases in MD were observed in the rostral middle frontal cortices. Negative correlations between MK and frequency of frontal impacts were observed in the posterior part of the brain including the pericalcarine, lingual and middle temporal cortices. Magnetic susceptibility values exhibited no significant difference or correlation, suggesting these diffusion changes common within the group may not be associated with iron-related mechanisms.

CONCLUSION

Microstructural alterations over the season and correlations with head impacts were captured by DKI metrics, which suggested that DKI imaging of gray matter may yield valuable biomarkers for evaluating brain injuries associated with subconcussive head impact. Findings of associations between frontal impacts and changes in posterior cortical gray matter also indicated that contrecoup injury rather than coup injury might be the dominant mechanism underlying the observed microstructural alterations.

ADVANCES IN KNOWLEDGE

Significant microstructural changes, as reflected by DKI metrics, in cortical gray matter such as the rostral middle frontal cortices, and in deep gray matter such as the thalamus were observed in high school football players over the course of a single season without clinically diagnosed concussion. QSM showed no evidence of iron-related changes in the observed subconcussive brain injuries. The detected microstructural changes in cortical and deep gray matter correlated with frequency of subconcussive head impacts.

IMPLICATIONS FOR PATIENT CARE

DKI may yield valuable biomarkers for evaluating the severity of brain injuries associated with subconcussive head impacts in contact sport athletes.

Sex Differences in Cognitive Decline in Subjects with High Likelihood of Mild Cognitive Impairment due to Alzheimer's disease

Sex differences in Alzheimer’s disease (AD) biology and progression are not yet fully characterized. The goal of this study is to examine the effect of sex on cognitive progression in subjects with high likelihood of mild cognitive impairment (MCI) due to Alzheimer’s and followed up to 10 years in the Alzheimer’s Disease Neuroimaging Initiative (ADNI). Cerebrospinal fluid total-tau and amyloid-beta (Aβ42) ratio values were used to sub-classify 559 MCI subjects (216 females, 343 males) as having “high” or “low” likelihood for MCI due to Alzheimer’s. Data were analyzed using mixed-effects models incorporating all follow-ups. The worsening from baseline in Alzheimer’s Disease Assessment Scale-Cognitive score (mean, SD) (9 ± 12) in subjects with high likelihood of MCI due to Alzheimer’s was markedly greater than that in subjects with low likelihood (1 ± 6, p < 0.0001). Among MCI due to AD subjects, the mean worsening in cognitive score was significantly greater in females (11.58 ± 14) than in males (6.87 ± 11, p = 0.006). Our findings highlight the need to further investigate these findings in other populations and develop sex specific timelines for Alzheimer’s disease progression.

White Matter Changes Related to Subconcussive Impact Frequency during a Single Season of High School Football

BACKGROUND AND PURPOSE

The effect of exposing the developing brain of a high school football player to subconcussive impacts during a single season is unknown. The purpose of this pilot study was to use diffusion tensor imaging to assess white matter changes during a single high school football season, and to correlate these changes with impacts measured by helmet accelerometer data and neurocognitive test scores collected during the same period.

MATERIALS AND METHODS

Seventeen male athletes (mean age, 16 ± 0.73 years) underwent MR imaging before and after the season. Changes in fractional anisotropy across the white matter skeleton were assessed with Tract-Based Spatial Statistics and ROI analysis.

RESULTS

The mean number of impacts over a 10-g threshold sustained was 414 ± 291. Voxelwise analysis failed to show significant changes in fractional anisotropy across the season or a correlation with impact frequency, after correcting for multiple comparisons. ROI analysis showed significant (P < .05, corrected) decreases in fractional anisotropy in the fornix-stria terminalis and cingulum hippocampus, which were related to impact frequency. The effects were strongest in the fornix-stria terminalis, where decreases in fractional anisotropy correlated with worsening visual memory.

CONCLUSIONS

Our findings suggest that subclinical neurotrauma related to participation in American football may result in white matter injury and that alterations in white matter tracts within the limbic system may be detectable after only 1 season of play at the high school level.

Increasing Rates of Imaging in Failed Back Surgery Syndrome Patients: Implications for Spinal Cord Stimulation

BACKGROUND

Failed back surgery syndrome (FBSS) has a high incidence following spinal surgery, is notoriously refractory to treatment, and results in high health care utilization. Spinal cord stimulation (SCS) is a well-accepted modality for pain relief in this population; however, until recently magnetic resonance imaging (MRI) was prohibited due to risk of heat conduction through the device.

OBJECTIVES

We examined trends in imaging use over the past decade in patients with FBSS to determine its impact on health care utilization and implications for patients receiving SCS.

STUDY DESIGN

Retrospective.

SETTING

Inpatient and outpatient sample.

METHODS

We identified patients from 2000 to 2012 using the Truven MarketScan database. Annual imaging rates (episodes per 1000 patient months) were determined for MRI, computed tomography (CT) scan, x-ray, and ultrasound. A multivariate Poisson regression model was used to determine imaging trends over time, and to compare imaging in SCS and non-SCS populations.

RESULTS

A total of 311,730 patients with FBSS were identified, of which 5.17% underwent SCS implantation (n = 16,118). The median (IQR) age was 58.0 (49.0 - 67.0) years. Significant increases in imaging rate ratios were found in all years for each of the modalities. Increases were seen in the use of CT scans (rate ratio [RR] = 3.03; 95% confidence interval [CI]: 2.79 - 3.29; P < 0.0001), MRI (RR = 1.73; 95% CI: 1.61 - 1.85; P < 0.0001), ultrasound (RR = 2.00; 95% CI: 1.84 - 2.18; P < 0.0001), and x-ray (RR = 1.10; 95% CI: 1.05 - 1.15; P < 0.0001). Despite rates of MRI in SCS patients being half that in the non-SCS group, these patients underwent 19% more imaging procedures overall (P < 0.0001). SCS patients had increased rates of x-ray (RR = 1.27; 95% CI: 1.25 - 1.29), CT scans (RR = 1.32; 95% CI: 1.30 - 1.35), and ultrasound (RR = 1.10; 95% CI: 1.07 - 1.13) (all P < 0.0001).

LIMITATIONS

This study is limited by a lack of clinical and historical variables including the complexity of prior surgeries and pain symptomatology. Miscoding cannot be precluded, as this sample is taken from a large nationwide database.

CONCLUSIONS

We found a significant trend for increased use of advanced imaging modalities between the years 2000 and 2012 in FBSS patients. Those patients treated with SCS were 50% less likely to receive an MRI (as expected, given prior incompatibility of neuromodulation devices), yet 32% and 27% more likely to receive CT and x-ray, respectively. Despite the decrease in the use of MRI in those patients treated with SCS, their overall imaging rate increased by 19% compared to patients without SCS. This underscores the utility of MR-conditional SCS systems. These findings demonstrate that imaging plays a significant role in driving health care expenditures. This is the largest analysis examining the role of imaging in the FBSS population and the impact of SCS procedures. Further studies are needed to assess the impact of MRI-conditional SCS systems on future trends in imaging in FBSS patients receiving neuromodulation therapies. Key words: Failed back surgery syndrome, spinal cord stimulation, imaging, health care utilization, MRI, chronic pain, back pain, neuromodulation.

American Society of Functional Neuroradiology-Recommended fMRI Paradigm Algorithms for Presurgical Language Assessment

INTRODUCTION

Functional MR imaging is increasingly being used for presurgical language assessment in the treatment of patients with brain tumors, epilepsy, vascular malformations, and other conditions. The inherent complexity of fMRI, which includes numerous processing steps and selective analyses, is compounded by institution-unique approaches to patient training, paradigm choice, and an eclectic array of postprocessing options from various vendors. Consequently, institutions perform fMRI in such markedly different manners that data sharing, comparison, and generalization of results are difficult. The American Society of Functional Neuroradiology proposes widespread adoption of common fMRI language paradigms as the first step in countering this lost opportunity to advance our knowledge and improve patient care.

LANGUAGE PARADIGM REVIEW PROCESS

A taskforce of American Society of Functional Neuroradiology members from multiple institutions used a broad literature review, member polls, and expert opinion to converge on 2 sets of standard language paradigms that strike a balance between ease of application and clinical usefulness.

ASFNR RECOMMENDATIONS

The taskforce generated an adult language paradigm algorithm for presurgical language assessment including the following tasks: Sentence Completion, Silent Word Generation, Rhyming, Object Naming, and/or Passive Story Listening. The pediatric algorithm includes the following tasks: Sentence Completion, Rhyming, Antonym Generation, or Passive Story Listening.

DISCUSSION

Convergence of fMRI language paradigms across institutions offers the first step in providing a "Rosetta Stone" that provides a common reference point with which to compare and contrast the usefulness and reliability of fMRI data. From this common language task battery, future refinements and improvements are anticipated, particularly as objective measures of reliability become available. Some commonality of practice is a necessary first step to develop a foundation on which to improve the clinical utility of this field.

Predictive Utility of Marketed Volumetric Software Tools in Subjects at Risk for Alzheimer Disease: Do Regions Outside the Hippocampus Matter?

BACKGROUND AND PURPOSE

Alzheimer disease is a prevalent neurodegenerative disease. Computer assessment of brain atrophy patterns can help predict conversion to Alzheimer disease. Our aim was to assess the prognostic efficacy of individual-versus-combined regional volumetrics in 2 commercially available brain volumetric software packages for predicting conversion of patients with mild cognitive impairment to Alzheimer disease.

MATERIALS AND METHODS

Data were obtained through the Alzheimer's Disease Neuroimaging Initiative. One hundred ninety-two subjects (mean age, 74.8 years; 39% female) diagnosed with mild cognitive impairment at baseline were studied. All had T1-weighted MR imaging sequences at baseline and 3-year clinical follow-up. Analysis was performed with NeuroQuant and Neuroreader. Receiver operating characteristic curves assessing the prognostic efficacy of each software package were generated by using a univariable approach using individual regional brain volumes and 2 multivariable approaches (multiple regression and random forest), combining multiple volumes.

RESULTS

On univariable analysis of 11 NeuroQuant and 11 Neuroreader regional volumes, hippocampal volume had the highest area under the curve for both software packages (0.69, NeuroQuant; 0.68, Neuroreader) and was not significantly different (P > .05) between packages. Multivariable analysis did not increase the area under the curve for either package (0.63, logistic regression; 0.60, random forest NeuroQuant; 0.65, logistic regression; 0.62, random forest Neuroreader).

CONCLUSIONS

Of the multiple regional volume measures available in FDA-cleared brain volumetric software packages, hippocampal volume remains the best single predictor of conversion of mild cognitive impairment to Alzheimer disease at 3-year follow-up. Combining volumetrics did not add additional prognostic efficacy. Therefore, future prognostic studies in mild cognitive impairment, combining such tools with demographic and other biomarker measures, are justified in using hippocampal volume as the only volumetric biomarker.

Marked gender differences in progression of mild cognitive impairment over 8 years

Introduction

This study examined whether, among subjects with mild cognitive impairment (MCI), women progressed at faster rates than men.

Methods

We examine longitudinal rates of change from baseline in 398 MCI subjects (141 females and 257 males) in the Alzheimer's Disease Neuroimaging Initiative-1, followed for up to 8 years (mean, 4.1 ± 2.5 years) using mixed-effects models incorporating all follow-ups (mean, 8 ± 4 visits).

Results

Women progressed at faster rates than men on the Alzheimer's disease assessment scale-cognitive subscale (ADAS-Cog; P = .001) and clinical dementia rating-sum of boxes (CDR-SB; P = .003). Quadratic fit for change over time was significant for both ADAS-Cog (P = .001) and CDR-SB (P = .004), and the additional acceleration in women was 100% for ADAS-Cog and 143% for CDR-SB. The variability of change was greater in women. The gender effect was greater in apolipoprotein E (APOE) ε4 carriers.

Discussion

Women with MCI have greater longitudinal rates of cognitive and functional progression than men. Studies to confirm and uncover potential mechanisms appear to be warranted.

Trial Registration

ADNI ClinicalTrials.gov identifier: NCT00106899.

Educational attainment and hippocampal atrophy in the Alzheimer's disease neuroimaging initiative cohort

INTRODUCTION

Subjects with higher cognitive reserve (CR) may be at a lower risk for Alzheimer's disease (AD), but the neural mechanisms underlying this are not known. Hippocampal volume loss is an early event in AD that triggers cognitive decline.

MATERIALS AND METHODS

Regression analyses of the effects of education on MRI-measured baseline HV in 675 subjects (201 normal, 329 with mild cognitive impairment (MCI), and 146 subjects with mild AD), adjusting for age, gender, APOE ɛ4 status and intracranial volume (ICV). Subjects were derived from the Alzheimer's Disease Neuroimaging Initiative (ADNI), a large US national biomarker study.

RESULTS

The association between higher education and larger HV was significant in AD (P=0.014) but not in cognitively normal or MCI subjects. In AD, HV was about 8% larger in a person with 20 years of education relative to someone with 6 years of education. There was also a trend for the interaction between education and APOE ɛ4 to be significant in AD (P=0.056).

CONCLUSION

A potential protective association between higher education and lower hippocampal atrophy in patients with AD appears consistent with prior epidemiologic data linking higher education levels with lower rates of incident dementia. Longitudinal studies are warranted to confirm these findings.

Impact of ¹⁸F-florbetapir PET imaging of β-amyloid neuritic plaque density on clinical decision-making

¹⁸F-florbetapir positron emission tomography (PET) imaging of the brain is now approved by the Food and Drug Administration (FDA) approved for estimation of β -amyloid neuritic plaque density when evaluating patients with cognitive impairment. However, its impact on clinical decision-making is not known. We present 11 cases (age range 67-84) of cognitively impaired subjects in whom clinician surveys were done before and after PET scanning to document the theoretical impact of amyloid imaging on the diagnosis and treatment plan of cognitively impaired subjects. Subjects have been clinically followed for about 5 months after the PET scan. Negative scans occurred in five cases, leading to a change in diagnosis for four patients and a change in treatment plan for two of these cases. Positive scans occurred in six cases, leading to a change in diagnosis for four patients and a change in treatment plan for three of these cases. Following the scan, only one case had indeterminate diagnosis. Our series suggests that both positive and negative florbetapir PET scans may enhance diagnostic certainty and impact clinical decision-making. Controlled longitudinal studies are needed to confirm our data and determine best practices.

The Alzheimer structural connectome: changes in cortical network topology with increased amyloid plaque burden

PURPOSE

To evaluate differences in the structural connectome among patients with normal cognition (NC), mild cognitive impairment (MCI), and Alzheimer disease (AD) and to determine associations between the structural connectome and cortical amyloid deposition.

MATERIALS AND METHODS

Patients enrolled in a multicenter biomarker study (Alzheimer's Disease Neuroimaging Initiative [ADNI] 2) who had both baseline diffusion-tensor (DT) and florbetapir positron emission tomography (PET) data at the time of data analyses in November 2012 were studied. All institutions received institutional review board approval. There were 102 patients in ADNI 2 who met criteria for analysis. Patients' T1-weighted images were automatically parcellated into cortical regions of interest. Standardized uptake value ratio (SUVr) was calculated from florbetapir PET images for composite cortical regions (frontal, cingulate, parietal, and temporal). Structural connectome graphs were created from DT images, and connectome topology was analyzed in each region by using graph theoretical metrics. Analysis of variance of structural connectome metrics and florbetapir SUVr across diagnostic group was performed. Linear mixed-effects models were fit to analyze the effect of florbetapir SUVr on structural connectome metrics.

RESULTS

Diagnostic group (NC, MCI, or AD) was associated with changes in weighted structural connectome metrics, with decreases from the NC group to the MCI group to the AD group shown for (a) strength in the bilateral frontal, right parietal, and bilateral temporal regions (P < .05); (b) weighted local efficiency in the left temporal region (P < .05); and (c) weighted clustering coefficient in the bilateral frontal and left temporal regions (P < .05). Increased cortical florbetapir SUVr was associated with decreases in weighted structural connectome metrics; namely, strength (P = .00001), weighted local efficiency (P = .00001), and weighted clustering coefficient (P = .0006), independent of brain region. For every 0.1-unit increase in florbetapir SUVr, there was a 14% decrease in strength, an 11% decrease in weighted local efficiency, and a 9% decrease in weighted clustering coefficient, regardless of the analyzed cortical region or, in the case of weighted local efficiency and clustering coefficient, diagnostic group.

CONCLUSION

Increased amyloid burden, as measured with florbetapir PET imaging, is related to changes in the topology of the large-scale cortical network architecture of the brain, as measured with graph theoretical metrics of DTI tractography, even in the preclinical stages of AD. Online supplemental material is available for this article.

Neuroimaging and the search for a cure for Alzheimer disease

As radiologists, our role in the workup of the dementia patient has long been limited by the sensitivity of our imaging tools and lack of effective treatment options. Over the past 30 years, we have made tremendous strides in understanding the genetic, molecular, and cellular basis of Alzheimer disease (AD). We now know that the pathologic features of AD are present 1 to 2 decades prior to development of symptoms, though currently approved symptomatic therapies are administered much later in the disease course. The search for true disease-modifying therapy continues and many clinical trials are underway. Current outcome measures, based on cognitive tests, are relatively insensitive to pathologic disease progression, requiring long, expensive trials with large numbers of participants. Biomarkers, including neuroimaging, have great potential to increase the power of trials by matching imaging methodology with therapeutic mechanism. One of the most important advances over the past decade has been the development of in vivo imaging probes targeted to amyloid beta protein, and one agent is already available for clinical use. Additional advances include automated volumetric imaging methods to quantitate cerebral volume loss. Use of such techniques in small, early phase trials are expected to significantly increase the number and quality of candidate drugs for testing in larger trials. In addition to a critical role in trials, structural, molecular, and functional imaging techniques can give us a window on the etiology of AD and other neurodegenerative diseases. This combination of developments has potential to bring diagnostic radiology to the forefront in AD research, therapeutic trials, and patient care.

Mapping the effect of the apolipoprotein E genotype on 4-year atrophy rates in an Alzheimer disease-related brain network

PURPOSE

To determine the effect of the apolipoprotein E (APOE) genotype on atrophy rates of specific brain gray matter regions hypothesized to be key components of cognitive networks disrupted in Alzheimer disease.

MATERIALS AND METHODS

The Alzheimer's Disease Neuroimaging Initiative (ADNI) was approved by the institutional review boards of all participating sites. All subjects and their legal representatives gave written informed consent prior to data collection. The authors analyzed data from 237 subjects (mean age, 79.9 years; 40% female) with mild cognitive impairment (MCI) in the ADNI database and assessed the effect of the APOE ε4 and ε2 alleles on regional brain atrophy rates over a 12-48-month period. Brain regions were selected a priori: 15 experimental and five control regions were included. Regional atrophy rates were derived by using a fully automated algorithm applied to T1-weighted magnetic resonance (MR) imaging data. Analysis consisted of mixed-effects linear regression with repeated measures; results were adjusted for multiple testing with Bonferroni correction.

RESULTS

Thirteen of 15 experimental regions showed a significant effect of ε4 for higher atrophy rates (P < .001 for all). Cohen d values ranged from 0.26 to 0.42, with the largest effects seen in the amygdalae and hippocampi. The transverse temporal cortex showed a trend (P = .02, but did not survive Bonferroni correction) for a protective effect (Cohen d value = 0.15) of ε2. No control region showed an APOE effect.

CONCLUSION

The APOE ε4 allele is associated with accelerated rates of atrophy in 13 distinct brain regions in limbic and neocortical areas. This suggests the possibility of a genotype-specific network of related brain regions that undergo faster atrophy in MCI and potentially contribute to cognitive decline. Online supplemental material is available for this article.

Donepezil treatment of older adults with cognitive impairment and depression (DOTCODE study): clinical rationale and design

Treatment strategies for patients with depression and cognitive impairment (DEP-CI), who are at high risk to develop a clinical diagnosis of dementia, are not established. This issue is addressed in the donepezil treatment of cognitive impairment and depression (DOTCODE) pilot clinical trial. The DOTCODE study is the first long-term treatment trial that assesses differences in conversion to dementia and cognitive change in DEP-CI patients using a study design of open antidepressant medication plus add-on randomized, double-blind, placebo-controlled treatment with the acetylcholinesterase inhibitor donepezil. In Phase 1, DEP-CI patients receive optimized antidepressant treatment for 16 weeks. In Phase 2, antidepressant treatment is continued with the addition of randomized, double-blind treatment with donepezil or placebo. The total study duration for each patient is 78 weeks (18 months). Eighty DEP-CI outpatients (age 55 to 95 years) are recruited: 40 at New York State Psychiatric Institute/Columbia University and 40 at Duke University Medical Center. The primary outcome is conversion to a clinical diagnosis of dementia. The secondary outcomes are cognitive change scores in Selective Reminding Test (SRT) total recall and the modified Alzheimer's Disease Assessment Scale (ADAS-cog). Other key assessments include the 24-item Hamilton Depression Rating Scale and antidepressant response; Clinical Global Impression (CGI) for depression, cognition, and global status; neuropsychological test battery for diagnosis; informant report of functional abilities (Pfeffer FAQ); and Treatment Emergent Symptom Scale (TESS) for somatic side effects. Apolipoprotein E ε4 status, odor identification deficits, and MRI entorhinal/hippocampal cortex atrophy at baseline are evaluated as neurobiological moderators of donepezil treatment effects.

Complex biomarker discovery in neuroimaging data: Finding a needle in a haystack

Neuropsychiatric disorders such as schizophrenia, bipolar disorder and Alzheimer's disease are major public health problems. However, despite decades of research, we currently have no validated prognostic or diagnostic tests that can be applied at an individual patient level. Many neuropsychiatric diseases are due to a combination of alterations that occur in a human brain rather than the result of localized lesions. While there is hope that newer imaging technologies such as functional and anatomic connectivity MRI or molecular imaging may offer breakthroughs, the single biomarkers that are discovered using these datasets are limited by their inability to capture the heterogeneity and complexity of most multifactorial brain disorders. Recently, complex biomarkers have been explored to address this limitation using neuroimaging data. In this manuscript we consider the nature of complex biomarkers being investigated in the recent literature and present techniques to find such biomarkers that have been developed in related areas of data mining, statistics, machine learning and bioinformatics.

Mapping the effects of ApoE4, age and cognitive status on 18F-florbetapir PET measured regional cortical patterns of beta-amyloid density and growth

BACKGROUND

Although it is well known that many clinical and genetic factors have been associated with beta-amyloid deposition, few studies have examined the interactions of such factors across different stages of Alzheimer's pathogenesis.

METHODS

We used 18F-florbetapir F18 PET imaging to quantify neuritic beta-amyloid plaque density across four cortical regions in 602 elderly (55-94 years) subjects from the national ADNI biomarker study. The group comprised of 194 normal elderly, 212 early mild cognitive impairment [EMCI], 132 late mild cognitive impairment [LMCI], and 64 mild Alzheimer's (AD).

FINDINGS

In a model incorporating multiple predictive factors, the effect of apolipoprotein E ε4 and diagnosis was significant on all four cortical regions. The highest signals were seen in cingulate followed by frontal and parietal with lowest signals in temporal lobe (p<0.0001). The effect of apolipoprotein E ε4 (Cohen's D 0.96) on beta-amyloid plaque density was approximately twice as large as the effect of a diagnosis of AD (Cohen's D 0.51) and thrice as large as the effect of a diagnosis of LMCI (Cohen's D 0.34) (p<0.0001). Surprisingly, ApoE ε4+ normal controls had greater mean plaque density across all cortical regions than ε4- EMCI and ε4- LMCI (p<0.0001, p=0.0009) and showed higher, though non-significant, mean value than ε4- AD patients (p<0.27). ApoE ε4+ EMCI and LMCI subjects had significantly greater mean plaque density across all cortical regions than ε4- AD patients (p<0.027, p<0.0001).

INTERPRETATION

Neuritic amyloid plaque load across progressive clinical stages of AD varies strongly by ApoE4 genotype. These findings support the need for better pathology-based and supported diagnosis in routine practice. Our data also provides additional evidence for a temporal offset between amyloid deposition and clinically relevant symptoms.

Prevalence of Alzheimer's pathologic endophenotypes in asymptomatic and mildly impaired first-degree relatives

Objective

A positive family history (FH) is a risk factor for late-onset Alzheimer’s disease (AD). Our aim was to examine the effects of FH on pathological and neuronal loss biomarkers across the cognitive spectrum.

Design

Cross-sectional analyses of data from a national biomarker study.

Setting

The Alzheimer’s Disease Neuroimaging Initiative national study.

Patients

257 subjects (ages 55–89), divided into cognitively normal (CN), mild cognitive impairment (MCI), and AD groups, with CSF and FH data.

Outcome Measures

Cerebrospinal fluid (CSF) Aβ42, tau, and tau/Aβ42 ratio, MRI-measured hippocampal volumes.

Statistics

Univariate and multivariate analyses.

Results

In MCI, CSF Aβ42 was lower (p = .005), t-tau was higher (p = 0.02) and t-tau/Aβ42 ratio was higher (p = 0.002) in FH+ than FH− subjects. A significant residual effect of FH on pathologic markers in MCI remained after adjusting for ApoE4 (p<0.05). Among CN, 47% of FH+ exhibited “pathologic signature of AD” (CSF t-tau/Aβ42 ratio >0.39) versus 21% of FH− controls (p = 0.03). The FH effect was not significant in AD subjects. Hippocampal and intracranial volumes did not differ between FH+ and FH− subjects in any group.

Conclusions

A positive family history of late-onset AD is associated with a higher prevalence of an abnormal cerebral beta-amyloid and tau protein phenotype in MCI. The unexplained genetic heritability in family history is about the half the size of the ApoE4 effect. Longitudinal studies are warranted to more definitively examine this issue.

Dissecting the gene dose-effects of the APOE ε4 and ε2 alleles on hippocampal volumes in aging and Alzheimer's disease

OBJECTIVE

To investigate whether there is a specific dose-dependent effect of the Apolipoprotein E (APOE) ε4 and ε2 alleles on hippocampal volume, across the cognitive spectrum, from normal aging to Alzheimer's Disease (AD).

MATERIALS AND METHODS

We analyzed MR and genetic data on 662 patients from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database-198 cognitively normal controls (CN), 321 mild-cognitive impairment (MCI) subjects, and 143 AD subjects-looking for dose-dependent effects of the ε4 and ε2 alleles on hippocampal volumes. Volumes were measured using a fully-automated algorithm applied to high resolution T1-weighted MR images. Statistical analysis consisted of a multivariate regression with repeated-measures model.

RESULTS

There was a dose-dependent effect of the ε4 allele on hippocampal volume in AD (p = 0.04) and MCI (p = 0.02)-in both cases, each allele accounted for loss of >150 mm(3) (approximately 4%) of hippocampal volume below the mean volume for AD and MCI subjects with no such alleles (Cohen's d = -0.16 and -0.19 for AD and MCI, respectively). There was also a dose-dependent, main effect of the ε2 allele (p<0.0001), suggestive of a moderate protective effect on hippocampal volume-an approximately 20% per allele volume increase as compared to CN with no ε2 alleles (Cohen's d = 0.23).

CONCLUSION

Though no effect of ε4 was seen in CN subjects, our findings confirm and extend prior data on the opposing effects of the APOE ε4 and ε2 alleles on hippocampal morphology across the spectrum of cognitive aging.

Predicting cognitive decline in subjects at risk for Alzheimer disease by using combined cerebrospinal fluid, MR imaging, and PET biomarkers

PURPOSE

To assess the extent to which multiple Alzheimer disease (AD) biomarkers improve the ability to predict future decline in subjects with mild cognitive impairment (MCI) compared with predictions based on clinical parameters alone.

MATERIALS AND METHODS

All protocols were approved by the institutional review board at each site, and written informed consent was obtained from all subjects. The study was HIPAA compliant. Alzheimer's Disease Neuroimaging Initiative (ADNI) baseline magnetic resonance (MR) imaging and fluorine 18 fluorodeoxyglucose (FDG) positron emission tomography (PET) studies for 97 subjects with MCI were used. MR imaging-derived gray matter probability maps and FDG PET images were analyzed by using independent component analysis, an unbiased data-driven method to extract independent sources of information from whole-brain data. The loading parameters for all MR imaging and FDG components, along with cerebrospinal fluid (CSF) proteins, were entered into logistic regression models (dependent variable: conversion to AD within 4 years). Eight models were considered, including all combinations of MR imaging, PET, and CSF markers with the covariates (age, education, apolipoprotein E genotype, Alzheimer's Disease Assessment Scale-Cognitive subscale score).

RESULTS

Combining MR imaging, FDG PET, and CSF data with routine clinical tests significantly increased the accuracy of predicting conversion to AD compared with clinical testing alone. The misclassification rate decreased from 41.3% to 28.4% (P < .00001). FDG PET contributed more information to routine tests (P < .00001) than CSF (P = .32) or MR imaging (P = .08).

CONCLUSION

Imaging and CSF biomarkers can improve prediction of conversion from MCI to AD compared with baseline clinical testing. FDG PET appears to add the greatest prognostic information.

Investigation of long-term reproducibility of intrinsic connectivity network mapping: a resting-state fMRI study

BACKGROUND AND PURPOSE

Connectivity mapping based on resting-state fMRI is rapidly developing, and this methodology has great potential for clinical applications. However, before resting-state fMRI can be applied for diagnosis, prognosis, and monitoring treatment for an individual patient with neurologic or psychiatric diseases, it is essential to assess its long-term reproducibility and between-subject variations among healthy individuals. The purpose of the study was to quantify the long-term test-retest reproducibility of ICN measures derived from resting-state fMRI and to assess the between-subject variation of ICN measures across the whole brain.

MATERIALS AND METHODS

Longitudinal resting-state fMRI data of 6 healthy volunteers were acquired from 9 scan sessions during >1 year. The within-subject reproducibility and between-subject variation of ICN measures, across the whole brain and major nodes of the DMN, were quantified with the ICC and COV.

RESULTS

Our data show that the long-term test-retest reproducibility of ICN measures is outstanding, with >70% of the connectivity networks showing an ICC > 0.60. The COV across 6 healthy volunteers in this sample was >0.2, suggesting significant between-subject variation.

CONCLUSIONS

Our data indicate that resting-state ICN measures (eg, the correlation coefficients between fMRI signal-intensity profiles from 2 different brain regions) are potentially suitable as biomarkers for monitoring disease progression and treatment effects in clinical trials and individual patients. Because between-subject variation is significant, it may be difficult to use quantitative ICN measures in their current state as a diagnostic tool.

Default mode network connectivity in stable vs progressive mild cognitive impairment

OBJECTIVE

Dysfunction of the default mode network (DMN) has been identified in prior cross-sectional fMRI studies of Alzheimer disease (AD) and mild cognitive impairment (MCI); however, no studies have examined its utility in predicting future cognitive decline.

METHODS

fMRI scans during a face-name memory task were acquired from a cohort of 68 subjects (25 normal control, 31 MCI, and 12 AD). Subjects with MCI were followed for 2.4 years (±0.8) to determine progression to AD. Maps of DMN connectivity were compared with a template DMN map constructed from elderly normal controls to obtain goodness-of-fit (GOF) indices of DMN expression. Indices were compared between groups and correlated with cognitive decline.

RESULTS

GOF indices were highest in normal controls, intermediate in MCI, and lowest in AD (p < 0.0001). In a predictive model (that included baseline GOF indices, age, education, Mini-Mental State Examination score, and an index of DMN gray matter volume), the effect of GOF index on progression from MCI to dementia was significant. In MCI, baseline GOF indices were correlated with change from baseline in functional status (Clinical Dementia Rating-sum of boxes) (r = -0.40, p < 0.04). However, there was no additional predictive value for DMN connectivity when baseline delayed recall was included in the models.

CONCLUSIONS

fMRI connectivity indices distinguish patients with MCI who undergo cognitive decline and conversion to AD from those who remain stable over a 2- to 3-year follow-up period. Our data support the notion of different functional brain connectivity endophenotypes for "early" vs "late" MCI, which are associated with different baseline memory scores and different rates of progression and conversion.

fMRI activation mapping as a percentage of local excitation: consistent presurgical motor maps without threshold adjustment

PURPOSE

To evaluate the performance of a relative activation amplitude algorithm, versus standard t-value thresholding, for reliably establishing the location, amplitude, and spatial extent of functional magnetic resonance imaging (fMRI) brain activation for presurgical planning.

MATERIALS AND METHODS

Diagnostic fMRI maps from 42 neurosurgical patients performing a simple hand movement task were analyzed. Relative activation maps were made by normalizing statistical t-value maps to the local peak activation amplitude within each functional brain region. The spatial distribution of activation was quantified and compared across mapping algorithms, subjects, and scan duration.

RESULTS

Whereas the spatial distribution of blood oxygenation level-dependent (BOLD) t-value statistical activation maps was highly variable across subjects and scan duration, the spatial distribution of relative activation maps was highly reproducible both within individual subjects and across different subjects. In every case the 40% most active voxels in the cortical hand region were consistently localized to the pre- and postcentral gyri of the sensorimotor cortex.

CONCLUSION

The reproducibility and anatomical specificity of the spatiotemporal pattern of BOLD activation makes relative amplitude fMRI mapping a useful tool for clinical imaging, where accuracy, reproducibility, and quality control are critical concerns.

Effects of donepezil on cortical activation in mild cognitive impairment: a pilot double-blind placebo-controlled trial using functional MR imaging

BACKGROUND AND PURPOSE

Cholinesterase-inhibitor therapy is approved for treatment of Alzheimer disease; however, application in patients with mild cognitive impairment (MCI) is still under active investigation. The purpose of this study was to determine the effect of such therapy on the neural substrates underlying memory processing in subjects with MCI by using functional MR imaging (fMRI).

MATERIALS AND METHODS

Thirteen subjects with MCI (mean age, 68 +/- 6.9 years) enrolled in a multicenter double-blind placebo-controlled trial testing the clinical efficacy of the cholinesterase-inhibitor, donepezil, were studied with fMRI at baseline and following 12 or 24 weeks of therapy (single-site pilot study). The cognitive paradigm was delayed-response visual memory for novel faces. Within-group 1-sample t tests were performed on the donepezil and placebo groups at baseline and at follow-up. A repeated-measures analysis of variance design was used to look for a Treatment Group x Time interaction showing a significant donepezil- but not placebo-related change in blood oxygen level-dependent response during the course of the study.

RESULTS

At baseline, both groups showed multiple areas of activation, including the bilateral dorsolateral prefrontal cortex, fusiform gyrus, and anterior cingulate cortex. On follow-up, the placebo group demonstrated a decreased extent of dorsolateral prefrontal activation, whereas the donepezil group demonstrated an increased extent of activation in the ventrolateral prefrontal cortex. Interaction demonstrated significant donepezil- but not placebo-related change in the left inferior frontal gyrus.

CONCLUSIONS

Despite the limitations inherent to a pilot study of a small sample, our results point to specific cortical substrates underlying the actions of donepezil, which can be tested in future studies.

Imaging genetics of brain longevity and mental wellness: the next frontier?

The advent of new "omics" technologies (genomics, proteomics, and metabolomics) has ushered in a new era of biomedical discovery that is already affecting every field of medicine. With the rapid growth of the older population worldwide, there is great interest in applying these technologies not only to diagnose and prevent disease, but also to enhance brain longevity and mental wellness. Nearly two-thirds of the approximately 30,000 genes in the human genome are related to brain function, and up to half of the variance in age-related changes in cognition, brain volume, and neuronal function appears to be genetically determined. Selected examples will be used to illustrate how neuroimaging is being employed to study the effects of genes and how neurogenetics may affect future radiology research and practice.