Clinical trial NCT06572332: Simulation-informed Modelling and Personalized Evaluation (SIMPLE) in Ageing Populations
Official title: Simulation-informed Modelling and Personalized Evaluation (SIMPLE): A Computational Study of MRI-based Brain Age Matrices
Study type: OBSERVATIONAL
Overall status: ENROLLING_BY_INVITATION
Conditions: Neurodegenerative Diseases
Aging
Brain
Cognitive Dysfunction
Keywords: MRI
Brain age
Deep learning
Healthy longevity
Resilence
Cognitive maintenance
Simulation
Imaging phenotypes
Lead sponsor: Chinese University of Hong Kong
Sponsor class: OTHER
First posted: 2024-08-27
Enrollment: 300
Sex: ALL
Minimum age (years): 50
Maximum age (years): 90
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: yes
Observational model: COHORT
Time perspective: PROSPECTIVE
Sampling method: PROBABILITY_SAMPLE
Study population: Ageing adults and adults with sleep disturbances.

Brief summary: Multimodal magnetic resonance imaging (MRI), detecting brain structural and functional changes, has emerged as a powerful and promising technique to study individual's brain, as T1-weighted scans can detect morphometric features, diffusion tensor imaging (DTI) scans can quantify structural connectivity, and functional MRI can capture the features of functional connectivity. Notably, with the advances in quantitative methods, computational models of brain age and brain-predicted age difference (brain-PAD) detecting the ageing effects on individual's brain features are becoming increasingly popular in clinical studies, which might revolutionize the diagnostic and prognostic phonotypes of age-related brain diseases globally.

Detailed description: The score of brain-PAD has threefold explanations: a. negative score representing decelerated brain ageing (brain age\<chronological age); b. positive score representing accelerated brain ageing (brain age\>chronological age); c. score equal to zero, representing normal brain ageing (brain age=chronological age). The score of brain-PAD indicates the brain ageing pattern with the interaction of lifestyle and cognitive status at individual level. For example, based on structural MRI scans, a younger brain age or a negative score of brain-PAD was found to be associated with better cognition, which indicates the potential utilities of brain age matrices in predicting individual's cognitive maintenance and healthy longevity

Eligibility criteria: Inclusion Criteria:

* Chinese old adults are the ones who are over 60 years of chronological age.
* Sleep disturbance: individual's subjective sleep quality is assessed using the Pittsburgh Sleep Quality Index (PSQI) with a total score \>5.

Exclusion Criteria:

* History of bipolar disorders or psychosis.
* History of major neurological deﬁcits, including stroke, transient ischemic attack or brain tumor.
* Unable to participant magnetic resonance imaging (MRI) scanning.

Primary outcomes:
measure: Estimated brain age
timeFrame: Baseline
measure: Cognitive maintenance
timeFrame: Baseline
measure: Plasma β-amyloid
timeFrame: Baseline
Secondary outcomes:
measure: Brain-predicted age difference (brain-PAD)
timeFrame: Baseline
measure: Complex attention
timeFrame: Baseline
measure: Memory and learning
timeFrame: Baseline
measure: Executive function
timeFrame: Baseline
Other outcomes:
Locations:
city: Hong Kong
country: Hong Kong
facility: Tai Po Hospital
Study officials:
affiliation: Chinese University of Hong Kong
name: Hanna Lu, PhD
role: PRINCIPAL_INVESTIGATOR
References: