Using Artificial Intelligence to Detect Early Signs of Alzheimer's Disease in People With Memory Concerns
Trial statusNot yet recruiting
Trial phaseNot applicable
Trial typeInterventional
Biological sexAll
Age40+
SponsorIRCCS San Raffaele
About this trial
AHEAD is a prospective, longitudinal, risk-stratified single-arm interventional study enrolling 300 patients with Subjective Cognitive Decline (SCD) at IRCCS San Raffaele Hospital, Milan, Italy.
The study uses artificial intelligence (AI) to integrate multimodal data - including MRI, EEG, Optical Coherence Tomography (OCT), neuropsychological assessments, and plasma biomarkers - to identify individuals with underlying Alzheimer's disease (AD) biology and predict cognitive progression.
Only participants found to be AD plasma biomarker positive (SCD+) undergo longitudinal follow-up at 12 and 24 months. Participants classified as high risk additionally receive a 6-month personalized multidisciplinary intervention combining high-frequency transcranial magnetic stimulation (TMS), digital cognitive training, structured physical exercise, and targeted management of modifiable vascular and behavioral risk factors.
Eligibility criteria
This trial does not accept healthy volunteersQualifiers
Diagnosis of Subjective Cognitive Decline (SCD) according to international diagnostic criteria (Jessen et al., 2014).
Self-experienced persistent decline in cognitive capacity in comparison with a previously normal status and unrelated to an acute event.
Normal age-, gender-, and education-adjusted performance on standardized cognitive tests used to classify mild cognitive impairment (MCI) or prodromal AD.
Age greater than or equal to 40 years.
Disqualifiers
Presence of MCI, prodromal AD, or dementia.
Any major systemic, psychiatric, or neurological disturbance.
Medical conditions or substance abuse that could interfere with cognition.
Pacemaker and/or other implanted neurostimulation devices in the head/neck district.
Trial design
Design model
Single group
Treatments tested in this trial
High-frequency Transcranial Magnetic Stimulation (TMS)
DeviceHigh-frequency repetitive TMS (rTMS) delivered according to an intensive protocol during the first 4 weeks of the intervention period (2-3 sessions per week). Applied to brain regions associated with cognitive function to optimize brain health and reduce risk of cognitive decline. Administered by trained professionals following international safety guidelines (Rossi et al., 2009).
Digital Cognitive Training
BehavioralHome-based cognitive training delivered via digital platform over 5 months: 2 sessions per week of 30 minutes each. Targets perceived cognitive deficits and related domains (memory, executive functions, attention, visuospatial abilities, language) with progressive adaptation to individual performance level. Compliance monitored via dedicated applications and/or activity diaries. Monthly remote meetings with neuropsychologists to monitor progress.
Structured Physical Exercise
BehavioralHome-based structured physical exercise program over 5 months: 2 sessions per week of 30 minutes each. Activities include walking, cycling, and global resistance training. An in-person familiarization session is conducted before program start. Monthly remote meetings with physiotherapists to monitor progress and adapt the program. Compliance remotely monitored via dedicated applications and/or activity diaries.
Management of Modifiable Vascular and Behavioral Risk Factors
Other interventionPersonalized pharmacological and non-pharmacological interventions targeting modifiable vascular and behavioral risk factors including blood pressure, cholesterol, BMI, physical inactivity, dietary habits, sleep quality, and social isolation. Monthly remote follow-up visits over 6 months to monitor treatment adherence and optimize risk factor control.
Treatment groups
300 Participants
are divided into 1 treatment groupGroup A: SCD ParticipantsExperimental treatment 4 interventions
Trial outcomes
Primary outcomes
1
Diagnostic accuracy of AI models in identifying AD biomarker-positive SCD subjects (AUC)
Area under the ROC curve (AUC), sensitivity, and specificity of AI models in discriminating between plasma AD biomarker-positive and biomarker-negative SCD subjects, assessed at study entry.
Time frame
Baseline (study entry)Secondary outcomes
1
Predictive accuracy of AI models for cognitive progression (AUC)
Area under the ROC curve (AUC), sensitivity, and specificity of AI models in discriminating between SCD progressors and non-progressors (conversion to Mild Cognitive Impairment or dementia) over a 24-month follow-up period.
Time frame
Baseline, 12 months (M12), and 24 months (M24)Other outcomes
1
Change in Preclinical Alzheimer Cognitive Composite (PACC) score
Preclinical Alzheimer Cognitive Composite (PACC) score assessed before and after the intervention. Higher scores indicate better cognitive performance. Primary outcome is maintenance of a stable PACC score after the intervention.
Time frame
Before and after the 6-month intervention (Baseline to Month 6 , or Month12 to Month 18 for rSCD cohort)2
Change in self-perceived quality of life (EQ-5D-3L)
Self-perceived quality of life measured by the EQ-5D-3L patient-reported instrument. Higher scores indicate better quality of life.
Time frame
Before and after the 6-month intervention (Baseline to Month 6 , or Month12 to Month 18 for rSCD cohort)3
Change in 6-minute walking test distance
Distance in meters walked in 6 minutes. An increase in distance indicates improved physical performance.
Time frame
Before and after the 6-month intervention (Baseline to Month 6 , or Month12 to Month 18 for rSCD cohort)4
Change in functional upper limb strength
Global upper limb strength changes assessed via standardized functional strength tests before and after the intervention.
Time frame
Before and after the 6-month intervention (Baseline to Month 6 , or Month12 to Month 18 for rSCD cohort)Sponsors and contacts
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Source ClinicalTrials.gov
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