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Background: An understudied variant of Alzheimer's disease (AD), the behavioral/dysexecutive variant of AD (bvAD), is associated with progressive personality, behavior, and/or executive dysfunction and frontal atrophy., Objective: This study characterizes the neuropsychological and neuroanatomical features associated with bvAD by comparing it to behavioral variant frontotemporal dementia (bvFTD), amnestic AD (aAD), and subjects with normal cognition., Methods: Subjects included 16 bvAD, 67 bvFTD, 18 aAD patients, and 26 healthy controls. Neuropsychological assessment and MRI data were compared between these groups., Results: Compared to bvFTD, bvAD showed more significant visuospatial impairments (Rey Figure copy and recall), more irritability (Neuropsychological Inventory), and equivalent verbal memory (Philadelphia Verbal Learning Test). Compared to aAD, bvAD indicated more executive dysfunction (F-letter fluency) and better visuospatial performance. Neuroimaging analysis found that bvAD showed cortical thinning relative to bvFTD posteriorly in left temporal-occipital regions; bvFTD had cortical thinning relative to bvAD in left inferior frontal cortex. bvAD had cortical thinning relative to aAD in prefrontal and anterior temporal regions. All patient groups had lower volumes than controls in both anterior and posterior hippocampus. However, bvAD patients had higher average volume than aAD patients in posterior hippocampus and higher volume than bvFTD patients in anterior hippocampus after adjustment for age and intracranial volume., Conclusion: Findings demonstrated that underlying pathology mediates disease presentation in bvAD and bvFTD.

Background: Sensitive measures of cognition are needed in preclinical and prodromal Alzheimer's disease (AD) to track cognitive change and evaluate potential interventions. Neurofibrillary tangle pathology in AD is first observed in Brodmann Area 35 (BA35), the medial portion of the perirhinal cortex. The importance of the perirhinal cortex for semantic memory may explain early impairments of semantics in preclinical AD. Additionally, our research has tied figurative language impairment to neurodegenerative disease., Objective: We aim to identify tasks that are sensitive to cognitive impairment in individuals with mild cognitive impairment (MCI), and that are sensitive to atrophy in BA35., Methods: Individuals with MCI and cognitively normal participants (CN) were tested on productive and receptive experimental measures of semantic memory and experimental tests of figurative language comprehension (including metaphor and verbal analogy). Performance was related to structural imaging and standard neuropsychological assessment., Results: On the experimental tests of semantics and figurative language, people with MCI performed worse than CN participants. The experimental semantic memory tasks are sensitive and specific; performance on the experimental semantic memory tasks related to medial temporal lobe structural integrity, including BA35, while standard neuropsychological assessments of semantic memory did not, demonstrating the sensitivity of these experimental measures. A visuo-spatial analogy task did not differentiate groups, confirming the specificity of semantic and figurative language tasks., Conclusion: These experimental measures appear sensitive to cognitive change and neurodegeneration early in the AD trajectory and may prove useful in tracking cognitive change in clinical trials aimed at early intervention.

Background: Multi-atlas segmentation, a popular technique implemented in the Automated Segmentation of Hippocampal Subfields (ASHS) software, utilizes multiple expert-labelled images ("atlases") to delineate medial temporal lobe substructures. This multi-atlas method is increasingly being employed in early Alzheimer's disease (AD) research, it is therefore becoming important to know how the construction of the atlas set in terms of proportions of controls and patients with mild cognitive impairment (MCI) and/or AD affects segmentation accuracy., Objective: To evaluate whether the proportion of controls in the training sets affects the segmentation accuracy of both controls and patients with MCI and/or early AD at 3T and 7T., Methods: We performed cross-validation experiments varying the proportion of control subjects in the training set, ranging from a patient-only to a control-only set. Segmentation accuracy of the test set was evaluated by the Dice similarity coeffiecient (DSC). A two-stage statistical analysis was applied to determine whether atlas composition is linked to segmentation accuracy in control subjects and patients, for 3T and 7T., Results: The different atlas compositions did not significantly affect segmentation accuracy at 3T and for patients at 7T. For controls at 7T, including more control subjects in the training set significantly improves the segmentation accuracy, but only marginally, with the maximum of 0.0003 DSC improvement per percent increment of control subject in the training set., Conclusion: ASHS is robust in this study, and the results indicate that future studies investigating hippocampal subfields in early AD populations can be flexible in the selection of their atlas compositions.

Neurofibrillary tangle (NFT) pathology is linked to neurodegeneration in the medial temporal lobe (MTL). Using a tailored pipeline, we correlated atrophy rate, as measured from retrospective longitudinal MRI, with NFT burden, measured from 18F-AV-1451 PET, within MTL regions of earliest NFT pathology. In amyloid-β positive but not amyloid-β negative individuals, we found significant correlation between 18F-AV-1451 uptake and atrophy rate that was strongest in the transentorhinal cortex, the first region with NFT pathology. This supports the role of NFTs in driving neurodegeneration and the utility of 18F-AV-1451 PET and structural measurement of transentorhinal cortex in tracking early tau-mediated disease progression.

Background: Volumetry of medial temporal lobe (MTL) structures to diagnose Alzheimer's disease (AD) in its earliest symptomatic stage could be of great importance for interventions or disease modifying pharmacotherapy., Objective: This study aimed to demonstrate the first application of an automatic segmentation method of MTL subregions in a clinical population. Automatic segmentation of magnetic resonance images (MRIs) in a research population has previously been shown to detect evidence of neurodegeneration in MTL subregions and to help discriminate AD and mild cognitive impairment (MCI) from a healthy comparison group., Methods: Clinical patients were selected and T2-weighted MRI scan quality was checked. An automatic segmentation method of hippocampal subfields (ASHS) was applied to scans of 67 AD patients, 38 amnestic MCI patients, and 57 healthy controls. Hippocampal subfields, entorhinal cortex (ERC), and perirhinal cortex were automatically labeled and subregion volumes were compared between groups., Results: One fourth of all scans were excluded due to bad scan quality. There were significant volume reductions in all subregions, except BA36, in aMCIs (p < 0.001), most prominently in Cornu Ammonis 1 (CA1) and ERC, and in all subregions in AD. However, sensitivity of CA1 and ERC hardly differed from sensitivity of WH in aMCI and AD., Conclusion: Applying automatic segmentation of MTL subregions in a clinical setting as a potential biomarker for prodromal AD is feasible, but issues of image quality due to motion remain to be addressed. CA1 and ERC provided strongest group discrimination in differentiating aMCIs from controls, but discriminatory power of different subfields was low overall.

Background: Psychometric tests predict conversion of mild cognitive impairment (MCI) to probable Alzheimer's disease (AD). Because the definition of clinical AD relies on those same psychometric tests, the ability of these tests to identify underlying AD pathology remains unclear., Objective: To determine the degree to which psychometric testing predicts molecular evidence of AD amyloid pathology, as indicated by cerebrospinal fluid (CSF) amyloid-β (Aβ)1 - 42, in patients with MCI, as compared to neuroimaging biomarkers., Methods: We identified 408 MCI subjects with CSF Aβ levels, psychometric test data, FDG-PET scans, and acceptable volumetric MR scans from the Alzheimer's Disease Neuroimaging Initiative (ADNI). We used psychometric tests and imaging biomarkers in univariate and multivariate models to predict Aβ status., Results: The 30-min delayed recall score of the Rey Auditory Verbal Learning Test was the best predictor of Aβ status among the psychometric tests, achieving an AUC of 0.67 ± 0.02 and odds ratio of 2.5 ± 0.4. FDG-PET was the best imaging-based biomarker (AUC 0.67 ± 0.03, OR 3.2 ± 1.2), followed by hippocampal volume (AUC 0.64 ± 0.02, OR 2.4 ± 0.3). A multivariate analysis based on the psychometric tests improved on the univariate predictors, achieving an AUC of 0.68 ± 0.03 (OR 3.38 ± 1.2). Adding imaging biomarkers to the multivariate analysis did not improve the AUC., Conclusion: Psychometric tests perform as well as imaging biomarkers to predict presence of molecular markers of AD pathology in MCI patients and should be considered in the determination of the likelihood that MCI is due to AD.

The measurement of hippocampal volumes using MRI is a useful in-vivo biomarker for detection and monitoring of early Alzheimer's disease (AD), including during the amnestic mild cognitive impairment (a-MCI) stage. The pathology underlying AD has regionally selective effects within the hippocampus. As such, we predict that hippocampal subfields are more sensitive in discriminating prodromal AD (i.e., a-MCI) from cognitively normal controls than whole hippocampal volumes, and attempt to demonstrate this using a semi-automatic method that can accurately segment hippocampal subfields. High-resolution coronal-oblique T2-weighted images of the hippocampal formation were acquired in 45 subjects (28 controls and 17 a-MCI (mean age: 69.5 ± 9.2; 70.2 ± 7.6)). CA1, CA2, CA3, and CA4/DG subfields, along with head and tail regions, were segmented using an automatic algorithm. CA1 and CA4/DG segmentations were manually edited. Whole hippocampal volumes were obtained from the subjects' T1-weighted anatomical images. Automatic segmentation produced significant group differences in the following subfields: CA1 (left: p = 0.001, right: p = 0.038), CA4/DG (left: p = 0.002, right: p = 0.043), head (left: p = 0.018, right: p = 0.002), and tail (left: p = 0.019). After manual correction, differences were increased in CA1 (left: p < 0.001, right: p = 0.002), and reduced in CA4/DG (left: p = 0.029, right: p = 0.221). Whole hippocampal volumes significantly differed bilaterally (left: p = 0.028, right: p = 0.009). This pattern of atrophy in a-MCI is consistent with the topography of AD pathology observed in postmortem studies, and corrected left CA1 provided stronger discrimination than whole hippocampal volume (p = 0.03). These results suggest that semi-automatic segmentation of hippocampal subfields is efficient and may provide additional sensitivity beyond whole hippocampal volumes.