Abstract
Background: Recently, efforts have been made to combine complementary perspectives in the assessment of Alzheimer type dementia. Of particular interest is the definition of the fingerprints of an early stage of the disease known as Mild Cognitive Impairment or prodromal Alzheimer's Disease. Machine learning approaches have been shown to be extremely suitable for the implementation of such a combination.
Methods: In the present pilot study we combined the machine learning approach with structural magnetic resonance imaging and cognitive test assessments to classify a small cohort of 11 healthy participants and 11 patients experiencing Mild Cognitive Impairment. Cognitive assessment included a battery of standardised tests and a battery of experimental visuospatial memory tests. Correct classification was achieved in 100% of the participants, suggesting that the combination of neuroimaging with more complex cognitive tests is suitable for early detection of Alzheimer Disease.
Results: In particular, the results highlighted the importance of the experimental visuospatial memory test battery in the efficiency of classification, suggesting that the high-level brain computational framework underpinning the participant's performance in these ecological tests may represent a “natural filter” in the exploration of cognitive patterns of information able to identify early signs of the disease.
Keywords: Visuospatial memory, spatial abilities, support vector machine, magnetic resonance imaging, mild cognitive impairment, classification.
Current Alzheimer Research
Title:Combining Structural Magnetic Resonance Imaging and Visuospatial Tests to Classify Mild Cognitive Impairment
Volume: 15 Issue: 3
Author(s): Fabrizio Fasano*, Micaela Mitolo, Simona Gardini, Annalena Venneri, Paolo Caffarra and Francesca Pazzaglia
Affiliation:
- Neuroscience Department, Parma University, Parma,Italy
Keywords: Visuospatial memory, spatial abilities, support vector machine, magnetic resonance imaging, mild cognitive impairment, classification.
Abstract: Background: Recently, efforts have been made to combine complementary perspectives in the assessment of Alzheimer type dementia. Of particular interest is the definition of the fingerprints of an early stage of the disease known as Mild Cognitive Impairment or prodromal Alzheimer's Disease. Machine learning approaches have been shown to be extremely suitable for the implementation of such a combination.
Methods: In the present pilot study we combined the machine learning approach with structural magnetic resonance imaging and cognitive test assessments to classify a small cohort of 11 healthy participants and 11 patients experiencing Mild Cognitive Impairment. Cognitive assessment included a battery of standardised tests and a battery of experimental visuospatial memory tests. Correct classification was achieved in 100% of the participants, suggesting that the combination of neuroimaging with more complex cognitive tests is suitable for early detection of Alzheimer Disease.
Results: In particular, the results highlighted the importance of the experimental visuospatial memory test battery in the efficiency of classification, suggesting that the high-level brain computational framework underpinning the participant's performance in these ecological tests may represent a “natural filter” in the exploration of cognitive patterns of information able to identify early signs of the disease.
Export Options
About this article
Cite this article as:
Fasano Fabrizio *, Mitolo Micaela , Gardini Simona , Venneri Annalena , Caffarra Paolo and Pazzaglia Francesca, Combining Structural Magnetic Resonance Imaging and Visuospatial Tests to Classify Mild Cognitive Impairment, Current Alzheimer Research 2018; 15 (3) . https://dx.doi.org/10.2174/1567205014666171030112339
DOI https://dx.doi.org/10.2174/1567205014666171030112339 |
Print ISSN 1567-2050 |
Publisher Name Bentham Science Publisher |
Online ISSN 1875-5828 |
Call for Papers in Thematic Issues
New Advances in the Prevention, Diagnosis, Treatment, and Rehabilitation of Alzheimer's Disease
Aims and Scope: Introduction: Alzheimer's disease (AD) poses a significant global health challenge, with an increasing prevalence that demands concerted efforts to advance our understanding and strategies for prevention, diagnosis, treatment, and rehabilitation. This thematic issue aims to bring together cutting-edge research and innovative approaches from multidisciplinary perspectives to address ...read more
Current updates on the Role of Neuroinflammation in Neurodegenerative Disorders
Neuroinflammation is an invariable hallmark of chronic and acute neurodegenerative disorders and has long been considered a potential drug target for Alzheimer?s disease (AD) and dementia. Significant evidence of inflammatory processes as a feature of AD is provided by the presence of inflammatory markers in plasma, CSF and postmortem brain ...read more
Deep Learning for Advancing Alzheimer's Disease Research
Alzheimer's disease (AD) poses a significant global health challenge, with an increasing number of individuals affected yearly. Deep learning, a subfield of artificial intelligence, has shown immense potential in various domains, including healthcare. This thematic issue of Current Alzheimer Research explores the application of deep learning techniques in advancing our ...read more
Diagnostic and therapeutic biomarkers of dementia
Dementia affects 18 million people worldwide. Dementia is a syndrome of symptoms caused by brain disease, usually chronic or progressive, clinically characterized by multiple impairments of higher cortical functions such as memory, thinking, orientation, and learning. In addition, in the course of dementia, cognitive deficits are observed, which often hinder ...read more
- Author Guidelines
- Graphical Abstracts
- Fabricating and Stating False Information
- Research Misconduct
- Post Publication Discussions and Corrections
- Publishing Ethics and Rectitude
- Increase Visibility of Your Article
- Archiving Policies
- Peer Review Workflow
- Order Your Article Before Print
- Promote Your Article
- Manuscript Transfer Facility
- Editorial Policies
- Allegations from Whistleblowers
- Announcements
Related Articles
-
Pharmacological Treatment of Hypertension in Pregnancy
Current Pharmaceutical Design Deciphering the Role of Nanoparticle-based Treatment for Parkinson’s Disease
Current Drug Metabolism Gels and Jellies as a Dosage Form for Dysphagia Patients: A Review
Current Drug Therapy Upregulated Long Non-coding RNA ALMS1-IT1 Promotes Neuroinflammation by Activating NF-κB Signaling in Ischemic Cerebral Injury
Current Pharmaceutical Design Harmaline and its Derivatives Against the Infectious Multi-Drug Resistant Escherichia coli
Medicinal Chemistry Editorial [Hot Topic: Drug Targets in Alzheimers Disease (Executive Editors: G. Munch and G. Stuchbury)]
Current Pharmaceutical Design The Cell Cycle Molecules Behind Neurodegeneration in Alzheimers Disease: Perspectives for Drug Development
Current Medicinal Chemistry Relationship Between the Chemokine Receptor CCR5 and Microglia in Neurological Disorders: Consequences of Targeting CCR5 on Neuroinflammation, Neuronal Death and Regeneration in a Model of Epilepsy
CNS & Neurological Disorders - Drug Targets Effects of 8-Residue Beta Sheet Breaker Peptides on Aged Aβ40 – Induced Memory Impairment and Aβ40 Expression in Rat Brain and Serum Following Intraamygdaloid Injection
Current Alzheimer Research Aging Affects Nicotinic Acetylcholine Receptors in Brain
Central Nervous System Agents in Medicinal Chemistry DNA and RNA Code-reading Molecules as Potential Gene Silencers in Neurobiology- What are They and what are They Good for?
Current Medicinal Chemistry - Central Nervous System Agents Novel Drug Targets for the Treatment of Cardiac Diseases
Current Pharmacogenomics and Personalized Medicine High Throughput Binding Analysis Determines the Binding Specificity of ASF/SF2 on Alternatively Spliced Human Pre-mRNAs
Combinatorial Chemistry & High Throughput Screening Multi-Target-Directed Ligands and other Therapeutic Strategies in the Search of a Real Solution for Alzheimer’s Disease
Current Neuropharmacology Defining Dystonic Tremor
Current Neuropharmacology Intranasal Insulin Prevents Anesthesia-induced Cognitive Impairments in Aged Mice
Current Alzheimer Research High Serum Alkaline Phosphatase Levels in Relation to Multi-Cerebral Microbleeds in Acute Ischemic Stroke Patients with Atrial Fibrillation and/or Rheumatic Heart Disease
Current Neurovascular Research The Economic Costs for the Control of Cardiovascular Risk: An Overview
Current Pharmaceutical Design Dampening the Progression of Dementia
Current Neurovascular Research Association of SORL1 Alleles with Late-Onset Alzheimer's Disease. Findings from the GIGAS_LOAD Study and Mega-Analysis
Current Alzheimer Research