Construction of Diagnosis System for Early AD Based on Multi-Modality MRI Technology

One purpose of this study is to construct the diagnosis system for early Alzheimer's disease(AD), which is also called amnestic mild cognitive impairment (aMCI), and then further construct the predictable classifier from aMCI to AD based on Multi-Modality MRI characteristics of aMCI patients.

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Key information

Conditions

Mild Cognitive Impairment Alzheimer Disease Alzheimer's Disease Brain Diseases Central Nervous System Diseases Cognition Disorders Cognitive Dysfunction Dementia Mental Disorders Nervous System Diseases Neurocognitive Disorders Neurodegenerative Diseases Tauopathies

Sex eligibility

All sexes

Study type

Observational

Primary location

Department of Neurolgy,Xuanwu Hospital of Capital Medical University

Beijing, Beijing Municipality, 100053, China

About this study

The cognition of aMCI is between normal aging and dementia, which is thought the transitional stage of dementia. Patients with aMCI have heavy risk to convert to AD, so in this study, the investigators focus on the construction of the diagnosis system for early AD based on multi-modality MRI characteristics of aMCI patients. Every patient underwent β-Amyloid PET, fluorodeoxyglucose-PET(FDG-PET), structural MRI, diffusion tensor imaging and functional MRI. Then investigators further study the patients who convert to AD and explore their MRI and metabolism characteristics on baseline, in order to construct the predictable classifier from aMCI to AD. The investigators want to achieve the early diagnosis of AD and help clinicians interfere with the progress of this disease.

Who can participate

Healthy volunteers accepted: Yes

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

Memory loss complaint and confirmed by an informant
Cognitive impairment in single or multiple domains, adjusted for age and education
Normal or near-normal performance on general cognitive function and no or minimum impairment of daily life activities
A Clinical Dementia Rating (CDR) score is 0.5 and consistent with the boundary of neuropsychological scale
Failure to meet the criteria for dementia
Must be able to accept examination of MRI, sight and hearing allow to complete test
Right handedness

Exclusion criteria

Other diseases that cause cognitive impairment, such as thyroid disease, stroke and so on
People who have severe visual and hearing impairment

Treatment and study plan

Primary outcomes

number of participants correctly classified by the support vector machine (SVM) classifier for the aMCI diagnosis

Time frame: 3 years

two-hundred aMCI subjects and 100 normal controls recruited will undergo structure,resting-state functional magnetic resonance imaging and diffusion tensor imaging. An SVM classifier for diagnosis will be trained based on these neuroimaging data.Then leave-one-out cross validation will be used to estimate the performance of the classifier including accuracy，sensitivity，specificity.The classification accuracy will be measured by the proportion of observations that are correctly classified into the aMCI or control groups.The sensitivity is defined as TP/(TP+FN), and specificity is defined as TN/(TN+FP). The TP (true positive) is the number of aMCI images correctly classified,whereas the TN (true negative) is the number of control images correctly classified. The FP (false positive) is the number of control images classified as the aMCI, whereas the FN (false negative) is the number of aMCI images classified as controls.
number of participants correctly predicted by the SVM classifier for predicting conversion from aMCI to AD

Time frame: 3 years

During 2-year follow-up, the group of aMCI will be divided into progressive aMCI (aMCIp) and stable aMCI（aMCIs）.According to the baseline neuroimaging data, an SVM classifier for predicting conversion from aMCI to AD will be trained. Then leave-one-out cross validation will be used to validate the performance of the classifier including accuracy，sensitivity，specificity.The classification accuracy will be measured by the proportion of aMCI that are correctly classified into the aMCIp or aMCIs groups.The sensitivity is defined as TP/(TP+FN), and specificity is defined as TN/(TN+FP). The TP (true positive) is the number of aMCIp images correctly classified,whereas the TN (true negative) is the number of aMCIs correctly classified. The FP (false positive) is the number of aMCIs classified as aMCIp, whereas the FN (false negative) is the number of aMCIp classified as aMCIs.

Secondary outcomes

regional cerebral metabolism (CMgl) measured by FDG-PET

Time frame: 3 years

different glucose consumption rate in some regions between aMCI and normal controls, and also between aMCIp and aMCIs
changed regional cerebral blood flow measured by FDG-PET

Time frame: 3 years

Sponsors and collaborators

Lead sponsor

XuanwuH 2

Other

Registry information

Important dates

Study start: 2013
Primary completion: 2015
Study completion: 2016
First posted: Feb 3, 2015
Registry last updated: Aug 23, 2016

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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