Search

Background: Neurodegenerative diseases lead to memory disorders and cognitive impairments with major impacts on day‐to‐day function. Early detection of patients is essential for an efficient care approach, and differential diagnosis is essential for determining prognosis and tailoring management. Most research studies compare patients by pairwise comparison methods, but this does not correspond to daily clinical practice, in which clinicians need to distinguish many different possible types of dementia concomitantly. It has been shown that magnetic resonance imaging (MRI) can mark with good accuracy the different types of dementia, such as: Alzheimer's disease (AD), Frontotemporal dementia (FTD), Parkinson's disease (PD), dementia with Lewy bodies (DLB). Recently, Deep Learning approaches have started being used although differential diagnosis is still almost ignored. The aim of this study was to develop a Convolution Neural Network (CNN) to classify probable AD, FTD, DLB, PD and healthy elderly control (CN) subjects starting from Diffusion Tensor Imaging (DTI). Method: The cohort used in this study came from six different initiatives: ADNI1, NIFD2, NACC3, PDBP4, PPMI5 and Newcastle University6,7,8,9. We analysed a total of 108 CN, 110 AD, 135 FTD, 150 DLB, 132 PD. Demographic and neuropsychological characterization is shown in Table 1. The DTI scans were pre‐processed using the FMRIB software library (FSL) with eddy current correction, skull‐stripping and diffusion tensor calculation. We post‐processed the Fractional Anisotropy (FA) map using 3D CNN. The proposed CNN structure consisted of an image input layer, convolutional filters, several batch normalization with max‐pooling layers and, finally, the classification layer. A data augmentation approach was adopted that ultimately resulted in a dataset of 26'450 brain scans. A hold‐out validation (70% training set 30% test set) was performed. Result: We found excellent performance of the 3D CNN in discriminating the different neurodegenerative diseases. Figure 1 shows the confusion matrix with the following values for the area under the ROC curve in each class: 0.92 for CN, 0.90 for AD, 0.97 for DLB, 0.96 for FTD, 0.99 for PD. Conclusion: These results prove that Deep Learning and the 3D CCN method are suitable for clinical practice and provide additional clues that can help clinicians in diagnosis making. [ABSTRACT FROM AUTHOR]

To test the hypothesis that intrahepatic availability of fatty acid could modify the rate of suppression of endogenous glucose production (EGP), acipimox or placebo was administered before and during a test meal. We used a modified isotopic methodology to measure EGP in 11 healthy subjects, and [sup.1H] magnetic resonance spectroscopic measurement of hepatic triglyceride stores was also undertaken. Acipimox suppressed plasma free fatty acids markedly before the meal (0.05 [+ or -] 0.01 mmol/l at - 10 min, P = 0) and throughout the postprandial period (0.03 [+ or -] 0.01 mmol/l at 150 min). Mean peak plasma glucose was significantly lower after the meal on acipimox days (8.9 [+ or -] 0.4 vs. 10.1 [+ or -] 0.5 mmol/1, P < 0.01), as was mean peak serum insulin (653.1 [+ or -] 99.9 vs. 909 [+ or -] 118 mmol/l, P < 0.01). Fasting EGP was similar (11.15 [+ or -] 0.58 [micro]mol * [kg.sup.-1] * [min.sup.-1] placebo vs. 11.17 [+ or -] 0.89 mg * [kg.sup.-1] * [min.sup.-1] acipimox). The rate of suppression of EGP after the meal was almost identical on the 2 test days (4.36 [+ or -] 1.52 vs. 3.69 [+ or -] 1.21 [micro]mol * [kg.sup.-1] [min.sup.-1] at 40 min). There was a significant negative correlation between the acipimox-induced decrease in peak plasma glucose and liver triglyceride content (r = -0.827, P = 0.002), suggesting that, when levels of liver fat were low, inhibition of lipolysis was able to affect glucose homeostasis. Acute pharmacological sequestration of fatty acids in triglyceride stores improves postprandial glucose homeostasis without effect on the immediate postprandial suppression of EGP. intrahepatic triglyceride; acipimox; [sup.1H] magnetic resonance spectroscopy

Objectives: Impaired olfaction may be a biomarker for early Lewy body disease, but its value in mild cognitive impairment with Lewy bodies (MCI-LB) is unknown. We compared olfaction in MCI-LB with MCI due to Alzheimer's disease (MCI-AD) and healthy older adults. We hypothesized that olfactory function would be worse in probable MCI-LB than in both MCI-AD and healthy comparison subjects (HC). Design: Cross-sectional study assessing olfaction using Sniffin' Sticks 16 (SS-16) in MCI-LB, MCI-AD, and HC with longitudinal follow-up. Differences were adjusted for age, and receiver operating characteristic (ROC) curves were used for discriminating MCI-LB from MCI-AD and HC. Setting: Participants were recruited from Memory Services in the North East of England. Participants: Thirty-eight probable MCI-LB, 33 MCI-AD, 19 possible MCI-LB, and 32HC. Measurements: Olfaction was assessed using SS-16 and a questionnaire. Results: Participants with probable MCI-LB had worse olfaction than both MCI-AD (age-adjusted mean difference (B) = 2.05, 95% CI: 0.62–3.49, p = 0.005) and HC (B = 3.96, 95% CI: 2.51–5.40, p < 0.001). The previously identified cutoff score for the SS-16 of ≤ 10 had 84% sensitivity for probable MCI-LB (95% CI: 69–94%), but 30% specificity versus MCI-AD. ROC analysis found a lower cutoff of ≤ 7 was better (63% sensitivity for MCI-LB, with 73% specificity vs MCI-AD and 97% vs HC). Asking about olfactory impairments was not useful in identifying them. Conclusions: MCI-LB had worse olfaction than MCI-AD and normal aging. A lower cutoff score of ≤ 7 is required when using SS-16 in such patients. Olfactory testing may have value in identifying early LB disease in memory services. [ABSTRACT FROM AUTHOR]

Patients who have dementia with Lewy bodies and Alzheimer's disease show early degeneration of the cholinergic nucleus basalis of Meynert. However, how white matter projections between the nucleus basalis of Meynert and the cortex are altered in neurodegenerative disease is unknown. Tractography of white matter pathways originating from the nucleus basalis of Meynert was performed using diffusion-weighted imaging in 46 patients with Alzheimer's disease dementia, 48 with dementia with Lewy bodies, 35 with mild cognitive impairment with Alzheimer's disease, 38 with mild cognitive impairment with Lewy bodies and 71 control participants. Mean diffusivity of the resulting pathways was compared between groups and related to cognition, attention, functional EEG changes and dementia conversion in the mild cognitive impairment groups. We successfully tracked a medial and a lateral pathway from the nucleus basalis of Meynert. Mean diffusivity of the lateral pathway was higher in both dementia and mild cognitive impairment groups than controls (all P < 0.03). In the patient groups, increased mean diffusivity of this pathway was related to more impaired global cognition (β = -0.22, P = 0.06) and worse performance on an attention task (β = 0.30, P = 0.03). In patients with mild cognitive impairment, loss of integrity of both nucleus basalis of Meynert pathways was associated with increased risk of dementia progression [hazard ratio (95% confidence interval), medial pathway: 2.51 (1.24-5.09); lateral pathway: 2.54 (1.24-5.19)]. Nucleus basalis of Meynert volume was reduced in all clinical groups compared to controls (all P < 0.001), but contributed less strongly to cognitive impairment and was not associated with attention or dementia conversion. EEG slowing in the patient groups as assessed by a decrease in dominant frequency was associated with smaller nucleus basalis of Meynert volumes (β = 0.22, P = 0.02) and increased mean diffusivity of the lateral pathway (β = -0.47, P = 0.003). We show that degeneration of the cholinergic nucleus basalis of Meynert in Alzheimer's disease and dementia with Lewy bodies is accompanied by an early reduction in integrity of white matter projections that originate from this structure. This is more strongly associated with cognition and attention than the volume of the nucleus basalis of Meynert itself and might be an early indicator of increased risk of dementia conversion in people with mild cognitive impairment. [ABSTRACT FROM AUTHOR]

Background: Recently published diagnostic criteria for mild cognitive impairment with Lewy bodies (MCI-LB) include five neuropsychiatric supportive features (non-visual hallucinations, systematised delusions, apathy, anxiety and depression). We have previously demonstrated that the presence of two or more of these symptoms differentiates MCI-LB from MCI due to Alzheimer's disease (MCI-AD) with a likelihood ratio >4. The aim of this study was to replicate the findings in an independent cohort. Methods: Participants ⩾60 years old with MCI were recruited. Each participant had a detailed clinical, cognitive and imaging assessment including FP-CIT SPECT and cardiac MIBG. The presence of neuropsychiatric supportive symptoms was determined using the Neuropsychiatric Inventory (NPI). Participants were classified as MCI-AD, possible MCI-LB and probable MCI-LB based on current diagnostic criteria. Participants with possible MCI-LB were excluded from further analysis. Results: Probable MCI-LB (n = 28) had higher NPI total and distress scores than MCI-AD (n = 30). In total, 59% of MCI-LB had two or more neuropsychiatric supportive symptoms compared with 9% of MCI-AD (likelihood ratio 6.5, p < 0.001). MCI-LB participants also had a significantly greater delayed recall and a lower Trails A:Trails B ratio than MCI-AD. Conclusions: MCI-LB is associated with significantly greater neuropsychiatric symptoms than MCI-AD. The presence of two or more neuropsychiatric supportive symptoms as defined by MCI-LB diagnostic criteria is highly specific and moderately sensitive for a diagnosis of MCI-LB. The cognitive profile of MCI-LB differs from MCI-AD, with greater executive and lesser memory impairment, but these differences are not sufficient to differentiate MCI-LB from MCI-AD. [ABSTRACT FROM AUTHOR]