Select Atrophied Regions in Alzheimer disease (SARA): An improved volumetric model for identifying Alzheimer disease dementia

Unexpected Low Rate of Amyloid-β Pathology in Multiple Sclerosis Patients

The life expectancy of people with multiple sclerosis (MS) has increased, yet we have noted that development of a typical Alzheimer disease dementia syndrome is uncommon. We hypothesized that Alzheimer disease pathology is uncommon in MS patients. In 100 MS patients, the rate of amyloid-β plasma biomarker positivity was approximately half the rate in 300 non-MS controls matched on age, sex, apolipoprotein E proteotype, and cognitive status. Interestingly, most MS patients who did have amyloid-β pathology had features atypical for MS at diagnosis. These results support that MS is associated with reduced Alzheimer disease risk, and suggest new avenues of research. ANN NEUROL 2024.

From Gut Microbiota to Brain Waves: The Potential of the Microbiome and EEG as Biomarkers for Cognitive Impairment

Alzheimer's disease (AD) is a prevalent neurodegenerative disorder and a leading cause of dementia. Aging is a significant risk factor for AD, emphasizing the importance of early detection since symptoms cannot be reversed once the advanced stage is reached. Currently, there is no established method for early AD diagnosis. However, emerging evidence suggests that the microbiome has an impact on cognitive function. The gut microbiome and the brain communicate bidirectionally through the gut-brain axis, with systemic inflammation identified as a key connection that may contribute to AD. Gut dysbiosis is more prevalent in individuals with AD compared to their cognitively healthy counterparts, leading to increased gut permeability and subsequent systemic inflammation, potentially causing neuroinflammation. Detecting brain activity traditionally involves invasive and expensive methods, but electroencephalography (EEG) poses as a non-invasive alternative. EEG measures brain activity and multiple studies indicate distinct patterns in individuals with AD. Furthermore, EEG patterns in individuals with mild cognitive impairment differ from those in the advanced stage of AD, suggesting its potential as a method for early indication of AD. This review aims to consolidate existing knowledge on the microbiome and EEG as potential biomarkers for early-stage AD, highlighting the current state of research and suggesting avenues for further investigation.

A 3D Sparse Autoencoder for Fully Automated Quality Control of Affine Registrations in Big Data Brain MRI Studies

This paper presents a fully automated pipeline using a sparse convolutional autoencoder for quality control (QC) of affine registrations in large-scale T1-weighted (T1w) and T2-weighted (T2w) magnetic resonance imaging (MRI) studies. Here, a customized 3D convolutional encoder-decoder (autoencoder) framework is proposed and the network is trained in a fully unsupervised manner. For cross-validating the proposed model, we used 1000 correctly aligned MRI images of the human connectome project young adult (HCP-YA) dataset. We proposed that the quality of the registration is proportional to the reconstruction error of the autoencoder. Further, to make this method applicable to unseen datasets, we have proposed dataset-specific optimal threshold calculation (using the reconstruction error) from ROC analysis that requires a subset of the correctly aligned and artificially generated misalignments specific to that dataset. The calculated optimum threshold is used for testing the quality of remaining affine registrations from the corresponding datasets. The proposed framework was tested on four unseen datasets from autism brain imaging data exchange (ABIDE I, 215 subjects), information eXtraction from images (IXI, 577 subjects), Open Access Series of Imaging Studies (OASIS4, 646 subjects), and "Food and Brain" study (77 subjects). The framework has achieved excellent performance for T1w and T2w affine registrations with an accuracy of 100% for HCP-YA. Further, we evaluated the generality of the model on four unseen datasets and obtained accuracies of 81.81% for ABIDE I (only T1w), 93.45% (T1w) and 81.75% (T2w) for OASIS4, and 92.59% for "Food and Brain" study (only T1w) and in the range 88-97% for IXI (for both T1w and T2w and stratified concerning scanner vendor and magnetic field strengths). Moreover, the real failures from "Food and Brain" and OASIS4 datasets were detected with sensitivities of 100% and 80% for T1w and T2w, respectively. In addition, AUCs of > 0.88 in all scenarios were obtained during threshold calculation on the four test sets.

A Survey of Publicly Available MRI Datasets for Potential Use in Artificial Intelligence Research

Artificial intelligence (AI) has the potential to bring transformative improvements to the field of radiology; yet, there are barriers to widespread clinical adoption. One of the most important barriers has been access to large, well-annotated, widely representative medical image datasets, which can be used to accurately train AI programs. Creating such datasets requires time and expertise and runs into constraints around data security and interoperability, patient privacy, and appropriate data use. Recognizing these challenges, several institutions have started curating and providing publicly available, high-quality datasets that can be accessed by researchers to advance AI models. The purpose of this work was to review the publicly available MRI datasets that can be used for AI research in radiology. Despite being an emerging field, a simple internet search for open MRI datasets presents an overwhelming number of results. Therefore, we decided to create a survey of the major publicly accessible MRI datasets in different subfields of radiology (brain, body, and musculoskeletal), and list the most important features of value to the AI researcher. To complete this review, we searched for publicly available MRI datasets and assessed them based on several parameters (number of subjects, demographics, area of interest, technical features, and annotations). We reviewed 110 datasets across sub-fields with 1,686,245 subjects in 12 different areas of interest ranging from spine to cardiac. This review is meant to serve as a reference for researchers to help spur advancements in the field of AI for radiology. LEVEL OF EVIDENCE: Level 4 TECHNICAL EFFICACY: Stage 6.

Machine Learning-Derived MRI-Based Neurodegeneration Biomarker for Alzheimer's Disease: A Multi-Database Validation Study

BACKGROUND

Pilot study showed that Alzheimer's disease resemblance atrophy index (AD-RAI), a machine learning-derived MRI-based neurodegeneration biomarker of AD, achieved excellent diagnostic performance in diagnosing AD with moderate to severe dementia.

OBJECTIVE

The primary objective was to validate and compare the performance of AD-RAI with conventional volumetric hippocampal measures in diagnosing AD with mild dementia. The secondary objectives were 1) to investigate the association between imaging biomarkers with age and gender among cognitively unimpaired (CU) participants; 2) to analyze whether the performance of differentiating AD with mild dementia from CU will improve after adjustment for age/gender.

METHODS

AD with mild dementia (n = 218) and CU (n = 1,060) participants from 4 databases were included. We investigated the area under curve (AUC), sensitivity, specificity, and balanced accuracy of AD-RAI, hippocampal volume (HV), and hippocampal fraction (HF) in differentiating between AD and CU participants. Among amyloid-negative CU participants, we further analyzed correlation between the biomarkers with age/gender. We also investigated whether adjustment for age/gender will affect performance.

RESULTS

The AUC of AD-RAI (0.93) was significantly higher than that of HV (0.89) and HF (0.89). Subgroup analysis among A + AD and A- CU showed that AUC of AD-RAI (0.97) was also higher than HV (0.94) and HF (0.93). Diagnostic performance of AD-RAI and HF was not affected by age/gender while that of HV improved after age adjustment.

CONCLUSIONS

AD-RAI achieves excellent clinical validity and outperforms conventional volumetric hippocampal measures in aiding the diagnosis of AD mild dementia without the need for age adjustment.

Improving Structural MRI Preprocessing with Hybrid Transformer GANs

Magnetic resonance imaging (MRI) is a technique that is widely used in practice to evaluate any pathologies in the human body. One of the areas of interest is the human brain. Naturally, MR images are low-resolution and contain noise due to signal interference, the patient's body's radio-frequency emissions and smaller Tesla coil counts in the machinery. There is a need to solve this problem, as MR tomographs that have the capability of capturing high-resolution images are extremely expensive and the length of the procedure to capture such images increases by the order of magnitude. Vision transformers have lately shown state-of-the-art results in super-resolution tasks; therefore, we decided to evaluate whether we can employ them for structural MRI super-resolution tasks. A literature review showed that similar methods do not focus on perceptual image quality because upscaled images are often blurry and are subjectively of poor quality. Knowing this, we propose a methodology called HR-MRI-GAN, which is a hybrid transformer generative adversarial network capable of increasing resolution and removing noise from 2D T1w MRI slice images. Experiments show that our method quantitatively outperforms other SOTA methods in terms of perceptual image quality and is capable of subjectively generalizing to unseen data. During the experiments, we additionally identified that the visual saliency-induced index metric is not applicable to MRI perceptual quality assessment and that general-purpose denoising networks are effective when removing noise from MR images.

Positron emission tomography and magnetic resonance imaging methods and datasets within the Dominantly Inherited Alzheimer Network (DIAN)

The Dominantly Inherited Alzheimer Network (DIAN) is an international collaboration studying autosomal dominant Alzheimer disease (ADAD). ADAD arises from mutations occurring in three genes. Offspring from ADAD families have a 50% chance of inheriting their familial mutation, so non-carrier siblings can be recruited for comparisons in case-control studies. The age of onset in ADAD is highly predictable within families, allowing researchers to estimate an individual's point in the disease trajectory. These characteristics allow candidate AD biomarker measurements to be reliably mapped during the preclinical phase. Although ADAD represents a small proportion of AD cases, understanding neuroimaging-based changes that occur during the preclinical period may provide insight into early disease stages of 'sporadic' AD also. Additionally, this study provides rich data for research in healthy aging through inclusion of the non-carrier controls. Here we introduce the neuroimaging dataset collected and describe how this resource can be used by a range of researchers.

Cortical atrophy and leukoaraiosis, imaging markers of cerebrovascular small vessel disease, are associated with driving behavior changes among cognitively normal older adults

BACKGROUND

Cerebral small vessel disease (CSVD) as measured by cortical atrophy and white matter hyperintensities [leukoaraiosis], captured via magnetic resonance imaging (MRI) are increasing in prevalence due to the growth of the aging population and an increase in cardiovascular risk factors in the population. CSVD impacts cognitive function and mobility, but it is unclear if it affects complex, functional activities like driving.

METHODS

In a cohort of 163 cognitively normal, community-dwelling older adults (age ≥ 65), we compared naturalistic driving behavior with mild/moderate leukoaraiosis, cortical atrophy, or their combined rating in a clinical composite termed, aging-related changes to those without any, over a two-and-a-half-year period.

RESULTS

Older drivers with mild or moderate cortical atrophy and aging-related changes (composite) experienced a greater decrease in the number of monthly trips which was due to a decrease in the number of trips made within a one-to-five-mile diameter from their residence. Older drivers with CSVD experience a larger reduction in daily driving behaviors than drivers without CSVD, which may serve as an early neurobehavioral marker for functional decline.

CONCLUSIONS

As CSVD markers, leukoaraiosis and cortical atrophy are standard MRI metrics that are widely available and can be used for screening individuals at higher risk for driving safety risk and decline in community mobility.

Validity Assessment of an Automated Brain Morphometry Tool for Patients with De Novo Memory Symptoms

BACKGROUND AND PURPOSE

Automated volumetric analysis of structural MR imaging allows quantitative assessment of brain atrophy in neurodegenerative disorders. We compared the brain segmentation performance of the AI-Rad Companion brain MR imaging software against an in-house FreeSurfer 7.1.1/Individual Longitudinal Participant pipeline.

MATERIALS AND METHODS

T1-weighted images of 45 participants with de novo memory symptoms were selected from the OASIS-4 database and analyzed through the AI-Rad Companion brain MR imaging tool and the FreeSurfer 7.1.1/Individual Longitudinal Participant pipeline. Correlation, agreement, and consistency between the 2 tools were compared among the absolute, normalized, and standardized volumes. Final reports generated by each tool were used to compare the rates of detection of abnormality and the compatibility of radiologic impressions made using each tool, compared with the clinical diagnoses.

RESULTS

We observed strong correlation, moderate consistency, and poor agreement between absolute volumes of the main cortical lobes and subcortical structures measured by the AI-Rad Companion brain MR imaging tool compared with FreeSurfer. The strength of the correlations increased after normalizing the measurements to the total intracranial volume. Standardized measurements differed significantly between the 2 tools, likely owing to differences in the normative data sets used to calibrate each tool. When considering the FreeSurfer 7.1.1/Individual Longitudinal Participant pipeline as a reference standard, the AI-Rad Companion brain MR imaging tool had a specificity of 90.6%-100% and a sensitivity of 64.3%-100% in detecting volumetric abnormalities. There was no difference between the rate of compatibility of radiologic and clinical impressions when using the 2 tools.

CONCLUSIONS

The AI-Rad Companion brain MR imaging tool reliably detects atrophy in cortical and subcortical regions implicated in the differential diagnosis of dementia.

Twelve Weeks of Intermittent Caloric Restriction Diet Mitigates Neuroinflammation in Midlife Individuals with Multiple Sclerosis: A Pilot Study with Implications for Prevention of Alzheimer's Disease

BACKGROUND

Multiple sclerosis (MS) is a prototype neuroinflammatory disorder with increasingly recognized role for neurodegeneration. Most first-line treatments cannot prevent the progression of neurodegeneration and the resultant disability. Interventions can improve symptoms of MS and might provide insights into the underlying pathology.

OBJECTIVE

To investigate the effect of intermittent caloric restriction on neuroimaging markers of MS.

METHODS

We randomized ten participants with relapsing remitting MS to either a 12-week intermittent calorie restriction (iCR) diet (n = 5) or control (n = 5). Cortical thickness and volumes were measured through FreeSurfer, cortical perfusion was measured by arterial spin labeling and neuroinflammation through diffusion basis spectrum imaging.

RESULTS

After 12 weeks of iCR, brain volume increased in the left superior and inferior parietal gyri (p: 0.050 and 0.049, respectively) and the banks of the superior temporal sulcus (p: 0.01). Similarly in the iCR group, cortical thickness improved in the bilateral medial orbitofrontal gyri (p: 0.04 and 0.05 in right and left, respectively), the left superior temporal gyrus (p: 0.03), and the frontal pole (p: 0.008) among others. Cerebral perfusion decreased in the bilateral fusiform gyri (p: 0.047 and 0.02 in right and left, respectively) and increased in the bilateral deep anterior white matter (p: 0.03 and 0.013 in right and left, respectively). Neuroinflammation, demonstrated through hindered and restricted water fractions (HF and RF), decreased in the left optic tract (HF p: 0.02), and the right extreme capsule (RF p: 0.007 and HF p: 0.003).

CONCLUSION

These pilot data suggest therapeutic effects of iCR in improving cortical volume and thickness and mitigating neuroinflammation in midlife adults with MS.

Molecular mechanisms in Alzheimer's disease and related potential treatments such as structural target convergence of antibodies and simple organic molecules

The amyloid cascade is the most frequently accepted hypothesis of Alzheimer's Disease (AD). According to this hypothesis, the formation of plaques precedes the appearance of fibrillary tangles. Therapeutic agents able to inhibit the formation of plaques are therefore considered as potential disease-modifying treatments (DMT) that could prevent or limit the progression of AD. Plaques are deposits formed by aggregates of amyloid-β (Aβ)-peptides. These peptides are metabolites of amyloid precursor protein (APP) first mediated by two enzymes: β-secretase 1 (BACE1) and γ-secretase. Molecular identification of these two enzymes has stimulated the development of their inhibitors. The clinical testing of these two classes of molecules has not been successful to date. The oligomerization of Aβ-peptides into plaques is now targeted by immunological approaches such as antibodies and vaccines. Structural consideration of the Aβ-peptide sequence led to the launch of the antibody Aducanumab. Several other antibodies are in late clinical phases. Progress in the understanding of the effects of N-truncated Aβ-peptides such as pE3-42, formed by the action of recently well characterized enzymes (aminopeptidase A, dipeptidylpeptidase-4 and glutaminyl cyclase) suggests that oligomerization can be limited either by enzyme inhibitors or antibody approaches. This strategy associating two structurally interconnected mechanisms is focused in this review.

The Value of Neuroimaging in Dementia Diagnosis

PURPOSE OF REVIEW

This article discusses neuroimaging in dementia diagnosis, with a focus on new applications of MRI and positron emission tomography (PET).

RECENT FINDINGS

Although the historical use of MRI in dementia diagnosis has been supportive to exclude structural etiologies, recent innovations allow for quantification of atrophy patterns that improve sensitivity for supporting the diagnosis of dementia causes. Neuronuclear approaches allow for localization of specific amyloid and tau neuropathology on PET and are available for clinical use, in addition to dopamine transporter scans in dementia with Lewy bodies and metabolic studies with fludeoxyglucose PET (FDG-PET).

SUMMARY

Using computerized software programs for MRI analysis and cross-sectional and longitudinal evaluations of hippocampal, ventricular, and lobar volumes improves sensitivity in support of the diagnosis of Alzheimer disease and frontotemporal dementia. MRI protocol requirements for such quantification are three-dimensional T1-weighted volumetric imaging protocols, which may need to be specifically requested. Fluid-attenuated inversion recovery (FLAIR) and 3.0T susceptibility-weighted imaging (SWI) sequences are useful for the detection of white matter hyperintensities as well as microhemorrhages in vascular dementia and cerebral amyloid angiopathy. PET studies for amyloid and/or tau pathology can add additional specificity to the diagnosis but currently remain largely inaccessible outside of research settings because of prohibitive cost constraints in most of the world. Dopamine transporter PET scans can help identify Lewy body dementia and are thus of potential clinical value.

Fluid Biomarkers in Dementia Diagnosis

PURPOSE OF REVIEW

This article discusses how fluid biomarkers can augment the routine dementia evaluation and improve diagnostic accuracy. The tests that are currently available and the indications for their use are described. Further, tests that are under development and likely to be used in the future are identified.

RECENT FINDINGS

Technical improvements in assay sensitivity and precision have led to the rapid development of blood-based biomarkers for Alzheimer disease (AD) over the past several years. Studies have found that the ratio of amyloid-β (Aβ) peptides (Aβ42/Aβ40) and concentrations of phosphorylated tau isoforms in plasma can identify individuals with AD brain pathology. Blood-based tests may enable much broader use of AD biomarkers in the evaluation of patients with cognitive impairment.

SUMMARY

Even after a detailed history, examination, routine laboratory testing, and brain imaging, the cause of dementia sometimes remains unclear. CSF and blood-based biomarkers can evaluate for a range of neurologic disorders that are associated with dementia, including AD. Integrating data from fluid biomarker tests and the routine dementia evaluation may improve the accuracy of dementia diagnosis.

Baseline Microglial Activation Correlates With Brain Amyloidosis and Longitudinal Cognitive Decline in Alzheimer Disease

BACKGROUND AND OBJECTIVES

This study aims to quantify microglial activation in individuals with Alzheimer disease (AD) using the 18-kDa translocator protein (TSPO) PET imaging in the hippocampus and precuneus, the 2 AD-vulnerable regions, and to evaluate the association of baseline neuroinflammation with amyloidosis, tau, and longitudinal cognitive decline.

METHODS

Twenty-four participants from the Knight Alzheimer Disease Research Center (Knight ADRC) were enrolled and classified into stable cognitively normal, progressor, and symptomatic AD groups based on clinical dementia rating (CDR) at 2 or more clinical assessments. The baseline TSPO radiotracer [11C]PK11195 was used to image microglial activation. Baseline CSF concentrations of Aβ42, Aβ42/Aβ40 ratio, tau phosphorylated at position 181 (p-tau181), and total tau (t-tau) were measured. Clinical and cognitive decline were examined with longitudinal CDR and cognitive composite scores (Global and Knight ADRC-Preclinical Alzheimer Cognitive Composite [Knight ADRC-PACC] Score).

RESULTS

Participants in the progressor and symptomatic AD groups had significantly elevated [11C]PK11195 standard uptake value ratios (SUVRs) in the hippocampus but not in the precuneus region. In the subcohort with CSF biomarkers (16 of the 24), significant negative correlations between CSF Aβ42 or Aβ42/Aβ40 and [11C]PK11195 SUVR were observed in the hippocampus and precuneus. No correlations were observed between [11C]PK11195 SUVR and CSF p-tau181 or t-tau at baseline in those regions. Higher baseline [11C]PK11195 SUVR averaged in the whole cortical regions predicted longitudinal decline on cognitive tests.

DISCUSSION

Microglial activation is increased in individuals with brain amyloidosis and predicts worsening cognition in AD.

CLASSIFICATION OF EVIDENCE

This study provides Class II evidence that in patients with AD, higher baseline [11C]PK11195 SUVR averaged in the whole cortical regions was associated with longitudinal decline on cognitive tests.

Neurodegeneration and Astrogliosis in the Human CA1 Hippocampal Subfield Are Related to hsp90ab1 and bag3 in Alzheimer's Disease

Alzheimer's disease (AD), the most prevalent neurodegenerative disorder, is characterized by executive dysfunction and memory impairment mediated by the accumulation of extracellular amyloid-β peptide (Aβ) and intracellular hyperphosphorylated tau protein. The hippocampus (HIPP) is essential for memory formation and is involved in early stages of disease. In fact, hippocampal atrophy is used as an early biomarker of neuronal injury and to evaluate disease progression. It is not yet well-understood whether changes in hippocampal volume are due to neuronal or glial loss. The aim of the study was to assess hippocampal atrophy and/or gliosis using unbiased stereological quantification and to obtain hippocampal proteomic profiles related to neurodegeneration and gliosis. Hippocampal volume measurement, stereological quantification of NeuN-, Iba-1- and GFAP-positive cells, and sequential window acquisition of all theoretical mass spectrometry (SWATH-MS) analysis were performed in AD and non-AD cases. Reduced hippocampal volume was identified using the Cavalieri probe, particularly in the CA1 region, where it correlated with neuronal loss and astrogliosis. A total of 102 downregulated and 47 upregulated proteins were identified in the SWATH-MS analysis after restrictive filtering based on an FC > 1.5 and p value < 0.01. The Hsp90 family of chaperones, particularly BAG3 and HSP90AB1, are closely related to astrocytes, indicating a possible role in degrading Aβ and tau through chaperone-mediated autophagy.

Communicating 5-Year Risk of Alzheimer's Disease Dementia: Development and Evaluation of Materials that Incorporate Multiple Genetic and Biomarker Research Results

BACKGROUND

Cognitively normal (CN) older adults participating in Alzheimer's disease (AD) research increasingly ask for their research results-including genetic and neuroimaging findings-to understand their risk of developing AD dementia. AD research results are typically not returned for multiple reasons, including possible psychosocial harms of knowing one is at risk of a highly feared and untreatable disease.

OBJECTIVE

We developed materials that convey information about 5-year absolute risk of developing AD dementia based on research results.

METHODS

20 CN older adults who received a research brain MRI result were interviewed regarding their wishes for research results to inform material development (Pilot 1). Following material development, 17 CN older adults evaluated the materials for clarity and acceptability (Pilot 2). All participants were community-dwelling older adults participating in longitudinal studies of aging at a single site.

RESULTS

Participants want information on their risk of developing AD dementia to better understand their own health, satisfy curiosity, inform family, and future planning. Some articulated concerns, but the majority wanted to know their risk despite the limitations of information. Participants found the educational materials and results report clear and acceptable, and the majority would want to know their research results after reviewing them.

CONCLUSION

These materials will be used in a clinical study examining the psychosocial and cognitive effects of offering research results to a cohort of CN older adults. Future AD research may incorporate the return of complex risk information to CN older adults, and materials are needed to communicate this information.