Alzheimer's disease (AD) researchers commonly use MRI as a quantitative measure of disease severity. Historically, hippocampal volume has been favored. Recently, "AD signature" measurements of gray matter (GM) volumes or cortical thicknesses have gained attention. Here, we systematically evaluate multiple thickness- and volume-based candidate-methods side-by-side, built using the popular FreeSurfer, SPM, and ANTs packages, according to the following criteria: (a) ability to separate clinically normal individuals from those with AD; (b) (extent of) correlation with head size, a nuisance covariatel (c) reliability on repeated scans; and (d) correlation with Braak neurofibrillary tangle stage in a group with autopsy. We show that volume- and thickness-based measures generally perform similarly for separating clinically normal from AD populations, and in correlation with Braak neurofibrillary tangle stage at autopsy. Volume-based measures are generally more reliable than thickness measures. As expected, volume measures are highly correlated with head size, while thickness measures are generally not. Because approaches to statistically correcting volumes for head size vary and may be inadequate to deal with this underlying confound, and because our goal is to determine a measure which can be used to examine age and sex effects in a cohort across a large age range, we thus recommend thickness-based measures. Ultimately, based on these criteria and additional practical considerations of run-time and failure rates, we recommend an AD signature measure formed from a composite of thickness measurements in the entorhinal, fusiform, parahippocampal, mid-temporal, inferior-temporal, and angular gyrus ROIs using ANTs with input segmentations from SPM12.

Fluorodeoxyglucose positron emission tomography (FDG-PET) imaging based 3D topographic brain glucose metabolism patterns from normal controls (NC) and individuals with dementia of Alzheimer's type (DAT) are used to train a novel multi-scale ensemble classification model. This ensemble model outputs a FDG-PET DAT score (FPDS) between 0 and 1 denoting the probability of a subject to be clinically diagnosed with DAT based on their metabolism profile. A novel 7 group image stratification scheme is devised that groups images not only based on their associated clinical diagnosis but also on past and future trajectories of the clinical diagnoses, yielding a more continuous representation of the different stages of DAT spectrum that mimics a real-world clinical setting. The potential for using FPDS as a DAT biomarker was validated on a large number of FDG-PET images (N=2984) obtained from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database taken across the proposed stratification, and a good classification AUC (area under the curve) of 0.78 was achieved in distinguishing between images belonging to subjects on a DAT trajectory and those images taken from subjects not progressing to a DAT diagnosis. Further, the FPDS biomarker achieved state-of-the-art performance on the mild cognitive impairment (MCI) to DAT conversion prediction task with an AUC of 0.81, 0.80, 0.77 for the 2, 3, 5 years to conversion windows respectively.

Visually preserved metabolism in posterior cingulate cortex relative to hypometabolism in precuneus and cuneus, the cingulate island sign, is a feature of dementia with Lewy bodies (DLB) on FDG-PET. Lower cingulate island sign ratio (posterior cingulate cortex/cuneus+precuneus; FDG-CISr) values have been associated with a higher Braak neurofibrillary tangle stage in autopsied DLB. Using voxel-wise analysis, we assessed the patterns of regional cortical perfusion and metabolism, and using an atlas-based approach, we measured perfusion cingulate island sign ratio on arterial spin labeling MRI (ASL-CISr), and its associations with FDG-CISr, uptake on tau-PET and clinical severity in DLB. Our study sample (n = 114) included clinically probable DLB patients (n = 19), age-matched patients with probable Alzheimer's disease dementia (AD; n = 19) and matched controls (n = 76) who underwent MRI with 3-dimensional pseudo-continuous arterial spin labeling, 18F-FDG-PET and 18F-AV-1451 tau PET. Patterns of cortical perfusion and metabolism were derived from quantitative maps using Statistical Parametric Mapping. DLB patients showed hypoperfusion on ASL-MRI in precuneus, cuneus and posterior parieto-occipital cortices, compared to controls, and relatively spared posterior cingulate gyrus, similar to pattern of hypometabolism on FDG-PET. DLB patients had higher ASL-CISr and FDG-CISr than AD patients (p <0.001). ASL-CISr correlated with FDG-CISr in DLB patients (r = 0.67; p =0.002). Accuracy of distinguishing DLB from AD patients was 0.80 for ASL-CISr and 0.91 for FDG-CISr. Lower ASL-CISr was moderately associated with a higher composite medial temporal AV-1451 uptake (r = -0.50; p =0.03) in DLB. Lower perfusion in precuneus and cuneus was associated with worse global clinical scores. In summary, the pattern of cortical hypoperfusion on ASL-MRI is similar to hypometabolism on FDG-PET, and respective cingulate island sign ratios correlate with each other in DLB. Non-invasive and radiotracer-free ASL-MRI may be further developed as a tool for the screening and diagnostic evaluation of DLB patients in a variety of clinical settings where FDG-PET is not accessible.

The objective of our study was to evaluate whether cognitively normal (CN) elderly participants showing elevated cortical beta-amyloid (Aβ) deposition have a consistent neuroanatomical signature of brain atrophy that may characterize preclinical Alzheimer's disease (AD). 115 CN participants who were Aβ-positive (CN +) by amyloid PET imaging; 115 CN participants who were Aβ-negative (CN -); and 88 Aβ-positive mild cognitive impairment or AD participants (MCI/AD +) were identified. Cortical thickness (FreeSurfer) and gray matter volume (SPM5) were measured for 28 regions-of-interest (ROIs) across the brain and compared across groups. ROIs that best discriminated CN - from CN + differed for FreeSurfer cortical thickness and SPM5 gray matter volume. Group-wise discrimination was poor with a high degree of uncertainty in terms of the rank ordering of ROIs. In contrast, both techniques showed strong and consistent findings comparing MCI/AD + to both CN - and CN + groups, with entorhinal cortex, middle and inferior temporal lobe, inferior parietal lobe, and hippocampus providing the best discrimination for both techniques. Concordance across techniques was higher for the CN - and CN + versus MCI/AD + comparisons, compared to the CN - versus CN + comparison. The weak and inconsistent nature of the findings across technique in this study cast doubt on the existence of a reliable neuroanatomical signature of preclinical AD in elderly PiB-positive CN participants.

The aims of this study were: to examine regional rates of change in tau-PET uptake and grey matter volume in atypical Alzheimer's disease (AD); to investigate the role of age in such changes; to describe multimodal regional relationships between tau accumulation and atrophy. Thirty atypical AD patients underwent baseline and one-year follow-up MRI, [18F]AV-1451 PET and PiB PET. Region- and voxel-level rates of tau accumulation and grey matter atrophy relative to cognitively unimpaired individuals, and the influence of age on such rates, were assessed. Univariate and multivariate analyses were performed between baseline measurements and rates of change, between baseline tau and atrophy, and between the two rates of change. Regional patterns of change in tau and volume differed, with highest rates of tau accumulation in frontal lobe and highest rates of atrophy in temporoparietal regions. Age had a negative effect on disease progression, predominantly on tau, with younger patients having a more rapid accumulation. Baseline tau uptake and regions of tau accumulation were disconnected, with high baseline tau uptake across the cortex correlated with high rates of tau accumulation in frontal and sensorimotor regions. In contrast, baseline volume and atrophy were locally related in the occipitoparietal regions. Higher tau uptake at baseline was locally related to higher rates of atrophy in frontal and occipital lobes. Tau accumulation rates positively correlated with rates of atrophy. In summary, our study showed that tau accumulation and atrophy presented different regional patterns in atypical AD, with tau spreading into the frontal lobes while atrophy remains in temporoparietal and occipital cortex, suggesting a temporal disconnect between protein deposition and neurodegeneration.

Transactive response DNA-binding protein of ∼43 kDa (TDP-43), a primary pathologic substrate in tau-negative frontotemporal lobar degeneration (FTLD), is also often found in the brains of elderly individuals without FTLD and is a key player in the process of neurodegeneration in brains with and without FTLD. It is unknown how rates and trajectories of TDP-43-associated brain atrophy compare between these two groups. Additionally, non-FTLD TDP-43 inclusions are not homogeneous and can be divided into two morphologic types: type-α and neurofibrillary tangle-associated type-β. Therefore, we explored whether neurodegeneration also varies due to the morphologic type. In this longitudinal retrospective study of 293 patients with 843 MRI scans spanning over ∼10 years, we used a Bayesian hierarchical linear model to quantify similarities and differences between the non-FTLD TDP-43 (type-α/type-β) and FTLD-TDP (n = 68) in both regional volume at various timepoints before death and annualized rate of atrophy. Since Alzheimer's disease (AD) is a frequent co-pathology in non-FTLD TDP-43, we further divided types α/β based on presence/absence of intermediate-high likelihood AD: AD-TDP type-β (n = 90), AD-TDP type-α (n = 104), and Pure-TDP (n = 31, all type-α). FTLD-TDP was associated with faster atrophy rates in the inferior temporal lobe and temporal pole compared to all non-FTLD TDP-43 groups. The atrophy rate in the frontal lobe was modulated by age with younger FTLD-TDP having the fastest rates. Older FTLD-TDP showed a limbic predominant pattern of neurodegeneration. AD-TDP type-α showed faster rates of hippocampal atrophy and smaller volumes of amygdala, temporal pole, and inferior temporal lobe compared to AD-TDP type-β. Pure-TDP was associated with slowest rates and less atrophy in all brain regions. The results suggest that there are differences and similarities in longitudinal brain volume loss between FTLD-TDP and non-FTLD TDP-43. Within FTLD-TDP age plays a role in which brain regions are the most affected. Additionally, brain atrophy regional rates also vary by non-FTLD TDP-43 type.

Apraxia of speech is a motor speech disorder thought to result from impaired planning or programming of articulatory movements. It can be the initial or only manifestation of a degenerative disease, termed primary progressive apraxia of speech (PPAOS). The aim of this study was to use task-free functional magnetic resonance imaging (fMRI) to assess large-scale brain network pathophysiology in PPAOS. Twenty-two PPAOS participants were identified from a prospective cohort of degenerative speech and language disorders patients. All participants had a comprehensive, standardized evaluation including an evaluation by a speech-language pathologist, examination by a behavioral neurologist and a multimodal imaging protocol which included a task-free fMRI sequence. PPAOS participants were age and sex matched to amyloid-negative, cognitively normal participants with a 1:2 ratio. We chose a set of hypothesis driven, predefined intrinsic connectivity networks (ICNs) from a large, out of sample independent component analysis and then used them to initialize a spatiotemporal dual regression to estimate participant level connectivity within these ICNs. Specifically, we evaluated connectivity within the speech and language, face and hand sensorimotor, left working memory, salience, superior parietal, supramarginal, insular and deep gray ICNs in a multivariate manner. The spatial maps for each ICN were then compared between PPAOS and control participants. We used clinical measures of apraxia of speech severity to assess for clinical-connectivity correlations for regions found to differ between PPAOS and control participants. Compared to controls, PPAOS participants had reduced connectivity of the right supplementary motor area and left posterior temporal gyrus to the rest of the speech and language ICN. The connectivity of the right supplementary motor area correlated negatively with an articulatory error score. PPAOS participants also had reduced connectivity of the left supplementary motor area to the face sensorimotor ICN, between the left lateral prefrontal cortex and the salience ICN and between the left temporal-occipital junction and the left working memory ICN. The latter connectivity correlated with the apraxia of speech severity rating scale, although the finding did not survive correction for multiple comparisons. Increased connectivity was noted in PPAOS participants between the dorsal posterior cingulate and the left working memory ICN. Our results support the importance of the supplementary motor area in the pathophysiology of PPAOS, which appears to be disconnected from speech and language regions. Supplementary motor area connectivity may serve as a biomarker of degenerative apraxia of speech severity.

Idiopathic normal pressure hydrocephalus (iNPH) is an important and treatable cause of neurologic impairment. Diagnosis is complicated due to symptoms overlapping with other age related disorders. The pathophysiology underlying iNPH is not well understood. We explored FDG-PET abnormalities in iNPH patients in order to determine if FDG-PET may serve as a biomarker to differentiate iNPH from common neurodegenerative disorders.

Quantitative susceptibility mapping (QSM) can detect iron distribution in the brain by estimating local tissue magnetic susceptibility properties at every voxel. Iron deposition patterns are well studied in typical Alzheimer's disease (tAD), but little is known about these patterns in atypical clinical presentations of AD such as logopenic progressive aphasia (LPA) and posterior cortical atrophy (PCA). Seventeen PCA patients and eight LPA patients were recruited by the Neurodegenerative Research Group at Mayo Clinic, Rochester, MN, and underwent MRI that included a five-echo gradient echo sequence for calculation of QSM. Mean QSM signal was extracted from gray and white matter for regions-of-interest across the brain using the Mayo Clinic Adult Lifespan Template. Bayesian hierarchical models were fit per-region and per-hemisphere to compare PCA, LPA, 63 healthy controls, and 20 tAD patients. Strong evidence (posterior probability > 0.99) was observed for greater susceptibility in the middle occipital gyrus and amygdala in both LPA and PCA, and in the right inferior parietal, inferior temporal, and angular gyri in PCA and the caudate and substantia nigra in LPA compared to controls. Moderate evidence for greater susceptibility (posterior probability > 0.90) was also observed in the inferior occipital gyrus, precuneus, putamen and entorhinal cortex in both LPA and PCA, along with superior frontal gyrus in PCA and inferior temporal gyri, insula and basal ganglia in LPA, when compared to controls. Between phenotypic comparisons, LPA had greater susceptibility in the caudate, hippocampus, and posterior cingulate compared to PCA, while PCA showed greater susceptibility in the right superior frontal and middle temporal gyri compared to LPA. Both LPA and PCA showed moderate and strong evidence for greater susceptibility than tAD, particularly in medial and lateral parietal regions, while tAD showed greater susceptibility in the hippocampus and basal ganglia. This study proposes the possibility of unique iron profiles existing between LPA and PCA within cortical and subcortical structures. These changes match well with the disease-related changes of the clinical phenotypes, suggesting that QSM could be an informative candidate marker to study iron deposition in these patients.

Frontotemporal dementia (FTD) is a neurodegenerative disease with a strong genetic basis. Understanding the structural brain changes during pre-symptomatic stages may allow for earlier diagnosis of patients suffering from FTD; therefore, we investigated asymptomatic members of FTD families with mutations in C9orf72 and granulin (GRN) genes. Clinically asymptomatic subjects from families with C9orf72 mutation (15 mutation carriers, C9orf72+; and 23 non-carriers, C9orf72-) and GRN mutations (9 mutation carriers, GRN+; and 15 non-carriers, GRN-) underwent structural neuroimaging (MRI). Cortical thickness and subcortical gray matter volumes were calculated using FreeSurfer. Group differences were evaluated, correcting for age, sex and years to mean age of disease onset within the subject's family. Mean age of C9orf72+ and C9orf72- were 42.6 ± 11.3 and 49.7 ± 15.5 years, respectively; while GRN+ and GRN- groups were 50.1 ± 8.7 and 53.2 ± 11.2 years respectively. The C9orf72+ group exhibited cortical thinning in the temporal, parietal and frontal regions, as well as reduced volumes of bilateral thalamus and left caudate compared to the entire group of mutation non-carriers (NC: C9orf72- and GRN- combined). In contrast, the GRN+ group did not show any significant differences compared to NC. C9orf72 mutation carriers demonstrate a pattern of reduced gray matter on MRI prior to symptom onset compared to GRN mutation carriers. These findings suggest that the preclinical course of FTD differs depending on the genetic basis and that the choice of neuroimaging biomarkers for FTD may need to take into account the specific genes involved in causing the disease.

Understanding the variation in uptake between different amyloid PET tracers is important to appropriately interpret data using different amyloid tracers. Therefore, we compared the uptake differences in [18F]Flutemetamol (FMT) and [11C]PiB (PiB) PET in the same people.

Brain imaging research studies increasingly use "de-facing" software to remove or replace facial imagery before public data sharing. Several works have studied the effects of de-facing software on brain imaging biomarkers by directly comparing automated measurements from unmodified vs de-faced images, but most research brain images are used in analyses of correlations with cognitive measurements or clinical statuses, and the effects of de-facing on these types of imaging-to-cognition correlations has not been measured. In this work, we focused on brain imaging measures of amyloid (A), tau (T), neurodegeneration (N), and vascular (V) measures used in Alzheimer's Disease (AD) research. We created a retrospective sample of participants from three age- and sex-matched clinical groups (cognitively unimpaired, mild cognitive impairment, and AD dementia, and we performed region- and voxel-wise analyses of: hippocampal volume (N), white matter hyperintensity volume (V), amyloid PET (A), and tau PET (T) measures, each from multiple software pipelines, on their ability to separate cognitively defined groups and their degrees of correlation with age and Clinical Dementia Rating (CDR)-Sum of Boxes (CDR-SB). We performed each of these analyses twice: once with unmodified images and once with images de-faced with leading de-facing software mri_reface, and we directly compared the findings and their statistical strengths between the original vs. the de-faced images. Analyses with original and with de-faced images had very high agreement. There were no significant differences between any voxel-wise comparisons. Among region-wise comparisons, only three out of 55 correlations were significantly different between original and de-faced images, and these were not significant after correction for multiple comparisons. Overall, the statistical power of the imaging data for AD biomarkers was almost identical between unmodified and de-faced images, and their analyses results were extremely consistent.

Patients with dementia with Lewy bodies (DLB) are characterized by hypometabolism in the parieto-occipital cortex and the cingulate island sign (CIS) on 18F-fluorodeoxyglucose (FDG) PET. Whether this pattern of hypometabolism is present as early as the prodromal stage of DLB is unknown. We investigated the pattern of hypometabolism in patients with mild cognitive impairment (MCI) who progressed to probable DLB compared to MCI patients who progressed to Alzheimer's disease (AD) dementia and clinically unimpaired (CU) controls.

Aging and dementia involve the disruption of brain molecular pathways leading to the alterations in tissue composition and gross morphology of the brain. Phenotypic and biomarker overlap between various etiologies of dementia supports a need for new modes of information to more accurately distinguish these disorders. Brain mechanical properties, which can be measured noninvasively by MR elastography, represent one understudied feature that are sensitive to neurodegenerative processes. In this study, we used two stiffness estimation schemes to test the hypothesis that different etiologies of dementia are associated with unique patterns of mechanical alterations across the cerebral cortex.