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Background: The retina has received increasing intention as possible non‐invasive diagnostic biomarker for (preclinical) Alzheimer's disease (AD). Several studies suggest changes in retinal layer thickness or vasculature in patients with AD. Here, we aim to discriminate (preclinical) Alzheimer's disease from controls using three retinal imaging modalities in a multimodal prediction model. Method: We used images of 103 controls, 26 clinical AD cases, and 13 preclinical AD cases. Control subjects were cognitively healthy with a negative amyloid‐PET. Preclinical AD participants were defined as cognitively healthy subjects with a positive amyloid‐PET. The 26 clinical AD participants were recruited from the Amsterdam Dementia Cohort and fulfilled the NIA‐AA criteria with evidence of amyloid pathology based on amyloid‐PET or cerebrospinal fluid. Participants underwent three imaging modalities (Optical Coherence Tomography, Optical Coherence Tomography Angiography, fundus photography) and ophthalmological examinations to exclude ophthalmological comorbidities that could influence retinal parameters. First, we performed a multivariable logistic regression analyses per imaging modality, adjusted for age and sex, using all parameters provided by each device. Second, we created an explorative multimodal prediction model including the best performing variable per imaging modality, using the following parameters: retinal nerve fiber layer inner ring, macular vessel density outer ring and the central retinal vein equivalent (CRVE). We used Receiver Operating Characteristic (ROC) curves to test the overall predictive accuracy. Result: The final explorative multimodal prediction model showed an acceptable predictive accuracy in discriminating AD from controls with an area under the receiving operating characteristic curve (AUC) of 0.987, and less so in the discrimination between preclinical AD and controls with an AUC of 0.775. However, with differences in the way the coefficients of identical parameters contributed to make the differentiation between AD and controls and preclinical AD and controls. Conclusion: Despite of a relatively small sample size, our multimodal retinal imaging prediction model seems promising in discriminating between AD versus controls, and preclinical AD versus controls. We found that two parameters, the macular vessel density outer ring and CRVE behaved differently in AD cases compared to preclinical AD cases. More prospective studies with larger sample sizes are needed to confirm these findings. [ABSTRACT FROM AUTHOR]

Grey matter (GM) atrophy is a prominent aspect of multiple sclerosis pathology and an important outcome in studies. GM atrophy measurement requires accurate GM segmentation. Several methods are used in vivo for measuring GM volumes in MS, but assessing their validity in vivo remains challenging. In this postmortem study, we evaluated the correlation between postmortem MRI cortical volume or thickness and the cortical thickness measured on histological sections. Sixteen MS brains were scanned in situ using 3DT1-weighted MRI and these images were used to measure regional cortical volume using FSL-SIENAX, FreeSurfer, and SPM, and regional cortical thickness using FreeSurfer. Subsequently, cortical thickness was measured histologically in 5 systematically sampled cortical areas. Linear regression analyses were used to evaluate the relation between MRI regional cortical volume or thickness and histological cortical thickness to determine which postprocessing technique was most valid. After correction for multiple comparisons, we observed a significant correlation with the histological cortical thickness for FSL-SIENAX cortical volume with manual editing (std. β = 0.345, adjusted R2 = 0.105, P = 0.005), and FreeSurfer cortical volume with manual editing (std. β = 0.379, adjusted R2 = 0.129, P = 0.003). In addition, there was a significant correlation between FreeSurfer cortical thickness with manual editing and histological cortical thickness (std. β = 0.381, adjusted R2 = 0.130, P = 0.003). The results support the use of FSL-SIENAX and FreeSurfer in cases of severe MS pathology. Interestingly none of the methods were significant in automated mode, which supports the use of manual editing to improve the automated segmentation. Hum Brain Mapp 37:2223-2233, 2016. © 2016 Wiley Periodicals, Inc. [ABSTRACT FROM AUTHOR]

Abstract: Objective: To investigate the effect of a medical food on cognitive function in people with mild Alzheimer''s disease (AD). Methods: A total of 225 drug-naïve AD patients participated in this randomized, double-blind controlled trial. Patients were randomized to active product, Souvenaid, or a control drink, taken once-daily for 12 weeks. Primary outcome measures were the delayed verbal recall task of the Wechsler Memory Scale–revised, and the 13-item modified Alzheimer''s Disease Assessment Scale–cognitive subscale at week 12. Results: At 12 weeks, significant improvement in the delayed verbal recall task was noted in the active group compared with control (P = .021). Modified Alzheimer''s Disease Assessment Scale–cognitive subscale and other outcome scores (e.g., Clinician Interview Based Impression of Change plus Caregiver Input, 12-item Neuropsychiatric Inventory, Alzheimer''s disease Co-operative Study–Activities of Daily Living, Quality of Life in Alzheimer''s Disease) were unchanged. The control group neither deteriorated nor improved. Compliance was excellent (95%) and the product was well tolerated. Conclusions: Supplementation with a medical food including phosphatide precursors and cofactors for 12 weeks improved memory (delayed verbal recall) in mild AD patients. This proof-of-concept study justifies further clinical trials. [Copyright &y& Elsevier]