Brain SPET perfusion in early Alzheimer’s disease: where to look?

On the early diagnosis of Alzheimer's Disease from multimodal signals: A survey

INTRODUCTION

The number of Alzheimer's Disease (AD) patients is increasing with increased life expectancy and 115.4 million people are expected to be affected in 2050. Unfortunately, AD is commonly diagnosed too late, when irreversible damages have been caused in the patient.

OBJECTIVE

An automatic, continuous and unobtrusive early AD detection method would be required to improve patients' life quality and avoid big healthcare costs. Thus, the objective of this survey is to review the multimodal signals that could be used in the development of such a system, emphasizing on the accuracy that they have shown up to date for AD detection. Some useful tools and specific issues towards this goal will also have to be reviewed.

METHODS

An extensive literature review was performed following a specific search strategy, inclusion criteria, data extraction and quality assessment in the Inspec, Compendex and PubMed databases.

RESULTS

This work reviews the extensive list of psychological, physiological, behavioural and cognitive measurements that could be used for AD detection. The most promising measurements seem to be magnetic resonance imaging (MRI) for AD vs control (CTL) discrimination with an 98.95% accuracy, while electroencephalogram (EEG) shows the best results for mild cognitive impairment (MCI) vs CTL (97.88%) and MCI vs AD distinction (94.05%). Available physiological and behavioural AD datasets are listed, as well as medical imaging analysis steps and neuroimaging processing toolboxes. Some issues such as "label noise" and multi-site data are discussed.

CONCLUSIONS

The development of an unobtrusive and transparent AD detection system should be based on a multimodal system in order to take full advantage of all kinds of symptoms, detect even the smallest changes and combine them, so as to detect AD as early as possible. Such a multimodal system might probably be based on physiological monitoring of MRI or EEG, as well as behavioural measurements like the ones proposed along the article. The mentioned AD datasets and image processing toolboxes are available for their use towards this goal. Issues like "label noise" and multi-site neuroimaging incompatibilities may also have to be overcome, but methods for this purpose are already available.

Principal component analysis in mild and moderate Alzheimer's disease--a novel approach to clinical diagnosis

Principal component analysis (PCA) provides a method to explore functional brain connectivity. The aim of this study was to identify regional cerebral blood flow (rCBF) distribution differences between Alzheimer's disease (AD) patients and controls (CTR) by means of volume of interest (VOI) analysis and PCA. Thirty-seven CTR, 30 mild AD (mildAD) and 27 moderate AD (modAD) subjects were investigated using single photon emission computed tomography with (99m)Tc-hexamethylpropylene amine oxime. Analysis of covariance (ANCOVA), PCA, and discriminant analysis (DA) were performed on 54 VOIs. VOI analysis identified in both mildAD and modAD subjects a decreased rCBF in six regions. PCA in mildAD subjects identified four principal components (PCs) in which the correlated VOIs showed a decreased level of rCBF, including regions that are typically affected early in the disease. In five PCs, including parietal-temporal-limbic cortex, and hippocampus, a significantly lower rCBF in correlated VOIs was found in modAD subjects. DA significantly discriminated the groups. The percentage of subjects correctly classified was 95, 70, and 81 for CTR, mildAD and modAD groups, respectively. PCA highlighted, in mildAD and modAD, relationships not evident when brain regions are considered as independent of each other, and it was effective in discriminating groups. These findings may allow neurophysiological inferences to be drawn regarding brain functional connectivity in AD that might not be possible with univariate analysis.

Tc-99m HMPAO brain SPECT findings in mild and moderate Alzheimer's disease: Correlation with event related potentials

We investigated whether brain SPECT findings show any differences between patients with mild and moderate Alzheimer's disease (AD) and to compare results with event related potentials (ERPs). Twenty-two patients with mild to moderate AD diagnosed according to NINCDS-ADRDA criteria and 10 age-matched control subjects were included in this prospective study. All subjects underwent ERP recordings and Tc-99m HMPAO brain SPECT study. Cortical perfusion index (CPI) was calculated as the ratio of cortical activity to the cerebellum activity. CPI was found to be statistically lower in bilaterally posterolateral temporal cortex and precuneus in the moderate AD compared to the control group. There was no statistically significant difference between the mild AD and control groups for CPI in any cortical areas. The mean P300 latency was statistically prolonged in the mild and moderate AD compared to the control group. In addition, in moderate AD P300 latency was longer than in mild AD. While the mean P300 amplitude was statistically reduced in moderate AD compared to the control and mild AD, there was no statistically significant difference between the mild AD and control groups. There was a strong negative correlation between P300 latency and CPI in the right and left precuneus in the moderate AD group. The present study suggested that Tc-99m HMPAO SPECT study is the more appropriate technique for patients with moderate AD rather than mild AD. Our results indicated that alterations in ERPs, especially prolongation of P300 latency could be a finding that occurred earlier than the deterioration in cerebral blood flow. We thought that precuneus is closely related to cognitive function and may have an important role in the pathophysiology of AD.

Neuroimaging tools to rate regional atrophy, subcortical cerebrovascular disease, and regional cerebral blood flow and metabolism: consensus paper of the EADC

Neuroimaging is a mainstay in the differential diagnosis of patients with cognitive impairment. The often equivocal clinical pictures, the prognostic uncertainty of the earliest stages of mild cognitive impairment, and the subtle brain changes mean that neuroimaging techniques are of potentially great incremental diagnostic value. A number of methods, ranging from very simple subjective visual ratings to highly sophisticated computerised tools, have been developed, which allow rating of structural and functional brain changes. The choice of the method is not obvious, and current guidelines provide no indications on which tools should be preferred. In this paper, we give indications for tools with demonstrated accuracy for detecting regional atrophy, cerebrovascular disease, and regional brain function, and discuss these according to increasing technological complexity, ranging from those with high feasibility that can be used at the patient's bedside to highly technological ones that require trained personnel and specific hardware and software.