![]() Reflecting this and the call for the biological evidence for AD diagnosis, several AD specific biomarkers have been identified, including multivariate patterns of structural brain atrophy measured by magnetic resonance imaging (MRI) ( Moradi et al., 2015, Bron et al., 2015, Salvatore et al., 2015, Coupé et al., 2015, Eskildsen et al., 2013, Wee et al., 2013). The disease processes leading to AD are known to start while individuals are still cognitively normal and may precede clinical symptoms by years or decades ( Jack et al., 2010, Adaszewski et al., 2013). Recently revised diagnostic criteria and recommendations emphasize the importance of early diagnosis of AD ( Dubois et al., 2010, McKhann et al., 2011, American Psychiatric Association, 2013). (2010) indicated of the importance of RAVLT in a clinical setting for discriminating normally aging subjects from mild cognitive impairment (MCI) and AD subjects. (2003) suggested inclusion of the RAVLT to the cognitive test battery used in evaluation and early detection of AD. Rey's auditory verbal learning test (RAVLT) is a well-known measure of episodic memory, and in previous studies it has had a significant role in early diagnosis of AD ( Estévez-González et al., 2003) as well as it has been demonstrated to be useful in differentiating AD from psychiatric disorders ( Ricci et al., 2012, Schoenberg et al., 2006, Tierney et al., 1996). This is evident in recent diagnostic recommendations, which highlight the significance of standardized neuropsychological testing as well as the supportive role of biological evidence for AD pathology ( Dubois et al., 2010, Jack et al., 2011, American Psychiatric Association, 2013). The progressive episodic memory impairment characteristic to AD is best measured by neuropsychological testing. ![]() ![]() Further, the conversion of MCI subjects to AD in 3-years could be predicted based on either observed or estimated RAVLT scores with an accuracy comparable to MRI-based biomarkers.Īlzheimer's disease (AD) is a progressive neurodegenerative disorder characterized by memory deficit, which is followed by problems in other cognitive domains that cause a severe decline in the usual level of functioning. The top predictors were medial temporal lobe structures and amygdala for the estimation of RAVLT Immediate and angular gyrus, hippocampus and amygdala for the estimation of RAVLT Percent Forgetting. In addition, the selected machine learning method provided more accurate estimates of RAVLT scores than the relevance vector regression used earlier for the estimation of RAVLT based on MRI data. The proposed approach provided highly significant cross-validated correlation between the estimated and observed RAVLT Immediate (R = 0.50) and RAVLT Percent Forgetting (R = 0.43) in a dataset consisting of 806 AD, mild cognitive impairment (MCI) or healthy subjects. For this, we built a predictive model to estimate RAVLT scores from gray matter density via elastic net penalized linear regression model. The aim was to comprehensively study to what extent the RAVLT scores are predictable based on structural magnetic resonance imaging (MRI) data using machine learning approaches as well as to find the most important brain regions for the estimation of RAVLT scores. ![]() We investigated the association between RAVLT scores (RAVLT Immediate and RAVLT Percent Forgetting) and the structural brain atrophy caused by AD. Several studies have shown that an impairment in RAVLT scores reflect well the underlying pathology caused by Alzheimer's disease (AD), thus making RAVLT an effective early marker to detect AD in persons with memory complaints. Rey's Auditory Verbal Learning Test (RAVLT) is a powerful neuropsychological tool for testing episodic memory, which is widely used for the cognitive assessment in dementia and pre-dementia conditions. ![]()
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