Identifying Imaging Biomarkers Predictive of Disability Progression in Alzheimer's Disease: Pilot Study
Overview
- Phase
- Not Applicable
- Intervention
- Not specified
- Conditions
- Alzheimer Disease
- Sponsor
- Poitiers University Hospital
- Enrollment
- 80
- Locations
- 1
- Primary Endpoint
- To identify Magnetic Resonance Imaging biomarkers concentration (mmol/l) at baseline that are predictive of disability progression in individuals with Mild Alzheimer's disease as assessed by the Clinical Dementia Rating (CDR) scale
- Status
- Recruiting
- Last Updated
- last year
Overview
Brief Summary
The pathophysiology of AD is complex. In addition to amyloid plaques and neurofibrillary degeneration, there is a metabolic alteration of the energy pathways, oxidative phosphorylation and glycolysis, which are involved in brain function. Several authors have shown a series of early metabolic dysregulations via an increase in phosphorylation at the origin of neuronal death.
Ultra-high field imaging (7T MRI) may allow, with its better spatial resolution and advanced imaging techniques, to shed light on the mechanisms of progression of Alzheimer's disease. A Magnetic Resonance Spectroscopy (MRS) examination can be coupled to brain MRI without additional risk for the patient. Multinuclear 1H-31P metabolic imaging is a promising tool that can provide information on the metabolic evolutionary profile of AD. Thus, we propose a longitudinal study in patients with early-stage AD on 7T MRI-MRS.
Investigators
Eligibility Criteria
Inclusion Criteria
- •French-speaking patients aged 60 to 90 years,
- •Patient in the context of Alzheimer's disease \* for which imaging after MRI is prescribed as part of the usual diagnostic process,
- •\*Alzheimer's disease is diagnosed by the doctor of the memory consultation and is defined by :Evidence of a storage disorder in verbal episodic memory at LR/RI defined by a sum of LR \< 17/48 and sum of RT \< 40/48 +/- Impairment of executive functions possible (BREF, TMT grefex, verbal fluencies) +/- Impairment of instrumental functions possible (Grémots noun naming, Rey's figure, Mahieux's Battery).
- •MMSE score ≥18,
- •Written informed consent after the patient has been informed,
- •Progressive decline for at least 6 months.
Exclusion Criteria
- •-Partially or completely illiterate patient unable to read and write,
- •Patient with an absolute contraindication to 7T MRI
- •Severe psychiatric pathology not balanced,
- •Non-degenerative neurological disease (stroke, multiple sclerosis ...),
- •Patient with tumor or inflammatory pathology, or vascular leukopathy visualized in MRI (Fazekas score \> 3)
Outcomes
Primary Outcomes
To identify Magnetic Resonance Imaging biomarkers concentration (mmol/l) at baseline that are predictive of disability progression in individuals with Mild Alzheimer's disease as assessed by the Clinical Dementia Rating (CDR) scale
Time Frame: Baseline
CDR scale : No dementia (CDR = 0), Uncertain disorders (CDR = 0.5), Mild disorders (CDR = 1), Moderate disorders (CDR = 2), Severe disorders (CDR = 3).
Secondary Outcomes
- Correlation between Imaging biomarkers concentration (mmol/l) and Urinary metabolic parameters (mmol/l) at baseline, Month 6 (M6) and Month 12 (M12).(up of 12 months)
- Correlation between Imaging biomarkers concentration (mmol/l) and plasma metabolic parameters concentration (mmol/l) at baseline, Month 6 (M6) and Month 12 (M12).(up of 12 months)
- Correlation between Imaging biomarkers concentration (mmol/l) and Enzymatic and protein parameters concentration (mmol/l) at baseline, Month 6 (M6) and Month 12 (M12).(up of 12 months)
- Develop realistic mathematical models that integrate multiple parameters from all generated data to predict the progression of Alzheimer's disease, as evaluated using the Clinical Dementia Rating (CDR)(up of 12 months)
- Build an Artificial Intelligence (AI) algorithm to predict disability progression in individuals with Mild Alzheimer's disease, as assessed by the Clinical Dementia Rating scale(up of 12 months)