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Background and Purpose: In vivo detection of β-amyloid (Aβ) plaques in Alzheimer's disease (AD) is now possible with 11 C-PiB positron emission tomography (PET). Conventionally, a cortical:cerebellar PiB uptake ratio threshold of 1.4-1.5 has been used to categorize at-risk subjects as "amyloid-positive" and "amyloid-negative." It has been suggested that this threshold is too conservative and may miss early amyloid pathology. We investigated the relationship between conventional and lower baseline 11 C-PiB PET thresholds for raised amyloid load and the subsequent clinical and radiological progression of mild cognitive impairment (MCI) cases longitudinally., Methods: We serially determined the cortical amyloid load with 11 C-PiB PET of 44 MCI subjects over 2 years and compared findings with those for 12 healthy controls (HC) and 5 AD cases., Results: Twenty-four subjects were classified as normal at baseline with mean cortical PiB standard uptake value ratios (SUVR) between 1.2 and 1.5. Their cognitive status remained stable over time. Three of these cases increased their amyloid load above a threshold of 1.5 over 2 years. Twenty-seven "raised amyloid" MCI cases with baseline cortical SUVRs above 1.5, showed deteriorating cognition. Note that 50% of these cases converted clinically to AD during the follow-up period., Conclusion: Use of a PiB SUVR threshold of >1.5 for raised amyloid missed 14.3% of MCI cases who likely had Thal stage 1 or 2 pathology and showed a progressive amyloid increase over 2 years. Lowering the threshold for abnormality to 1.3 abolished all false negatives but resulted in 75% of HCs being falsely diagnosed as raised amyloid subjects., (© 2019 by the American Society of Neuroimaging.)

White matter tract integrity (WMTI) can characterize brain microstructure in areas with highly aligned fiber bundles. Several WMTI biomarkers have now been validated against microscopy and provided promising results in studies of brain development and aging, as well as in a number of brain disorders. Currently, WMTI is mostly used in dedicated animal studies and clinical studies of slowly progressing diseases, and has not yet emerged as a routine clinical tool. To this end, a less data intensive experimental method would be beneficial by enabling high resolution validation studies, and ease clinical applications by speeding up data acquisition compared with typical diffusion kurtosis imaging (DKI) protocols utilized as part of WMTI imaging. Here, we evaluate WMTI based on recently introduced axially symmetric DKI, which has lower data demand than conventional DKI. We compare WMTI parameters derived from conventional DKI with those calculated analytically from axially symmetric DKI. We employ numerical simulations, as well as data from fixed rat spinal cord (one sample) and in vivo human (three subjects) and rat brain (four animals). Our analysis shows that analytical WMTI based on axially symmetric DKI with sparse data sets (19 images) produces WMTI metrics that correlate strongly with estimates based on traditional DKI data sets (60 images or more). We demonstrate the preclinical potential of the proposed WMTI technique in in vivo rat brain (300 μm isotropic resolution with whole brain coverage in a 1 h acquisition). WMTI parameter estimates are subject to a duality leading to two solution branches dependent on a sign choice, which is currently debated. Results from both of these branches are presented and discussed throughout our analysis. The proposed fast WMTI approach may be useful for preclinical research and e.g. clinical evaluation of patients with traumatic white matter injuries or symptoms of neurovascular or neuroinflammatory disorders., (Copyright © 2017 John Wiley & Sons, Ltd.)

Finding very early biomarkers of Alzheimer's Disease (AD) to aid in individual prognosis is of major interest to accelerate the development of new therapies. Among the potential biomarkers, neurodegeneration measurements from MRI are considered as good candidates but have so far not been effective at the early stages of the pathology. Our objective is to investigate the efficiency of a new MR-based hippocampal grading score to detect incident dementia in cognitively intact patients. This new score is based on a pattern recognition strategy, providing a grading measure that reflects the similarity of the anatomical patterns of the subject under study with dataset composed of healthy subjects and patients with AD. Hippocampal grading was evaluated on subjects from the Three-City cohort, with a followup period of 12 years. Experiments demonstrate that hippocampal grading yields prediction accuracy up to 72.5% (P < 0.0001) 7 years before conversion to AD, better than both hippocampal volume (58.1%, P = 0.04) and MMSE score (56.9%, P = 0.08). The area under the ROC curve (AUC) supports the efficiency of imaging biomarkers with a gain of 8.4 percentage points for hippocampal grade (73.0%) over hippocampal volume (64.6%). Adaptation of the proposed framework to clinical score estimation is also presented. Compared with previous studies investigating new biomarkers for AD prediction over much shorter periods, the very long followup of the Three-City cohort demonstrates the important clinical potential of the proposed imaging biomarker. The high accuracy obtained with this new imaging biomarker paves the way for computer-based prognostic aides to help the clinician identify cognitively intact subjects that are at high risk to develop AD., (© 2015 Wiley Periodicals, Inc.)