Among nondemented elderly patients, memory loss alone rarely progresses to dementia in the subsequent 2 years. However, the risk of dementia is significantly increased among patients with clear cognitive impairments beyond memory loss. Further study is needed to determine whether patients with impairments limited to memory loss have a distinctive clinical course or pathophysiology.

In vivo imaging of brain β-amyloid, a hallmark of Alzheimer disease, may assist in the clinical assessment of suspected Alzheimer disease. OBJECTIVE To determine the sensitivity and specificity of positron emission tomography imaging with flutemetamol injection labeled with radioactive fluorine 18 to detect β-amyloid in the brain using neuropathologically determined neuritic plaque levels as the standard of truth. DESIGN, SETTING, AND PARTICIPANTS Open-label multicenter imaging study that took place at dementia clinics, memory centers, and hospice centers in the United States and England from June 22, 2010, to November 23, 2011. Participants included terminally ill patients who were 55 years or older with a life expectancy of less than 1 year. INTERVENTIONS Flutemetamol injection labeled with radioactive fluorine 18 (Vizamyl; GE Healthcare) administration followed by positron emission tomography imaging and subsequent brain donation. MAIN OUTCOMES AND MEASURES Sensitivity and specificity of flutemetamol injection labeled with radioactive fluorine 18 positron emission tomography imaging for brain β-amyloid. Images were reviewed without and with computed tomography scans and classified as positive or negative for β-amyloid by 5 readers who were blind to patient information. In patients who died, neuropathologically determined neuritic plaque levels were used to confirm scan interpretations and determine sensitivity and specificity. RESULTS Of 176 patients with evaluable images, 68 patients (38%) died during the study, were autopsied, and had neuritic plaque levels determined; 25 brains (37%) were β-amyloid negative; and 43 brains (63%) were β-amyloid positive. Imaging was performed a mean of 3.5 months (range, 0 to 13 months) before death. Sensitivity without computed tomography was 81% to 93% (median, 88%). Median specificity was 88%, with 4 of 5 of the readers having specificity greater than 80%. When scans were interpreted with computed tomography images, sensitivity and specificity improved for most readers but the differences were not significant. The area under the receiver operating curve was 0.90. There were no clinically meaningful findings in safety parameters. CONCLUSIONS AND RELEVANCE This study showed that flutemetamol injection labeled with radioactive fluorine 18 was safe and had high sensitivity and specificity in an end-of-life population. In vivo detection of brain β-amyloid plaque density may increase diagnostic accuracy in cognitively impaired patients.

Background Certain patterns can induce perceptual illusions/distortions and visual discomfort in most people, headaches in patients with migraine, and seizures in patients with photosensitive epilepsy. Visual stimuli are common triggers for migraine attacks, possibly because of a hyperexcitability of the visual cortex shown in patients with migraine. Precision ophthalmic tints (POTs) are claimed to reduce perceptual distortions and visual discomfort and to prevent migraine headaches in some patients. We report an fMRI visual cortical activation study designed to investigate neurological mechanisms for the beneficial effects of POTs in migraine. Methods Eleven migraineurs and 11 age- and sex-matched non-headache controls participated in the study using non-stressful and stressful striped patterns viewed through gray, POT, and control coloured lenses. Results For all lenses, controls and migraineurs did not differ in their response to the non-stressful patterns. When the migraineurs wore gray lenses or control coloured lenses, the stressful pattern resulted in activation that was greater than in the controls. There was also an absence of the characteristic low-pass spatial frequency (SF) tuning in extrastriate visual areas. When POTs were worn, however, both cortical activation and SF tuning were normalized. Both when observing the stressful pattern and under more typical viewing conditions, the POTs reduced visual discomfort more than either of the other two lenses. Conclusion The normalization of cortical activation and SF tuning in the migraineurs by POTs suggests a neurological basis for the therapeutic effect of these lenses in reducing visual cortical hyperactivation in migraine.

This study examined whether distinct neuropsychological profiles could be delineated in a sample with Mild Cognitive Impairment (MCI) and whether white matter lesion (WML) burden contributed to MCI group differences. A heterogeneous, clinical sample of 70 older adults diagnosed with MCI was assessed using cognitive scores, and WML was quantified using a semiautomated, volumetric approach on T 2 -weighted fluid-attenuated inversion recovery (FLAIR) images. Using cluster and discriminant analyses, three distinct groups (Memory/Language, Executive/Processing Speed, and Pure Memory) were empirically derived based on cognitive scores. Results also showed a dose dependent relationship of WML burden to MCI subgroup, with the Executive/Processing Speed subgroup demonstrating significantly higher levels of WML pathology when compared to the other subgroups. In addition, there was a dissociation of lesion type by the two most impaired subgroups (Memory/Language and Executive/Processing Speed) such that the Memory/Language subgroup showed higher periventricular lesion (PVL) and lower deep white matter lesion (DWML) volumes, whereas the Executive/Processing Speed demonstrated higher DWML and lower PVL volumes. Results demonstrate that distinct MCI subgroups can be empirically derived and reliably differentiated from a heterogeneous MCI sample, and that these profiles differ according to WML burden. Overall, findings suggest different underlying pathologies within MCI and contribute to our understanding of MCI subtypes.

BackgroundIndividuals with mild cognitive impairment (MCI) have a substantially increased risk of developing dementia due to Alzheimer's disease (AD). In this study, we developed a multivariate prognostic model for predicting MCI-to-dementia progression at the individual patient level.MethodsUsing baseline data from 259 MCI patients and a probabilistic, kernel-based pattern classification approach, we trained a classifier to distinguish between patients who progressed to AD-type dementia (n = 139) and those who did not (n = 120) during a three-year follow-up period. More than 750 variables across four data sources were considered as potential predictors of progression. These data sources included risk factors, cognitive and functional assessments, structural magnetic resonance imaging (MRI) data, and plasma proteomic data. Predictive utility was assessed using a rigorous cross-validation framework.ResultsCognitive and functional markers were most predictive of progression, while plasma proteomic markers had limited predictive utility. The best performing model incorporated a combination of cognitive/functional markers and morphometric MRI measures and predicted progression with 80% accuracy (83% sensitivity, 76% specificity, AUC = 0.87). Predictors of progression included scores on the Alzheimer's Disease Assessment Scale, Rey Auditory Verbal Learning Test, and Functional Activities Questionnaire, as well as volume/cortical thickness of three brain regions (left hippocampus, middle temporal gyrus, and inferior parietal cortex). Calibration analysis revealed that the model is capable of generating probabilistic predictions that reliably reflect the actual risk of progression. Finally, we found that the predictive accuracy of the model varied with patient demographic, genetic, and clinical characteristics and could be further improved by taking into account the confidence of the predictions.ConclusionsWe developed an accurate prognostic model for predicting MCI-to-dementia progression over a three-year period. The model utilizes widely available, cost-effective, non-invasive markers and can be used to improve patient selection in clinical trials and identify high-risk MCI patients for early treatment.