About this trial
Alzheimer's disease causes progressive memory and cognitive decline, driven in part by the buildup of a protein called β-amyloid in the brain. New antibody therapies - lecanemab and donanemab - can remove amyloid and slow down the disease in its early stages. However, it is still unclear how long each patient should continue treatment or when it is safe to stop, because amyloid is cleared at different rates across individuals.
Today, amyloid Positron Emission Tomography (PET) scans are used to measure whether amyloid has been removed from the brain, but these scans are expensive, not always available, and expose patients to radiation. Since repeated PET scans are not ideal, doctors need better ways to monitor treatment progress.
This study will use advanced brain Magnetic Resonance Imaging (MRI) and blood tests to create personalized prediction models. These models will simulate how amyloid spreads or clears in each person's brain and help identify when treatment is still needed. With this approach, monitoring becomes safer, more efficient, and more affordable - helping ensure that each patient receives the right treatment for the right amount of time.
This prospective monocenter study investigates the role of 3Tesla MRI-based predictive modeling in predicting treatment response to anti-amyloid monoclonal antibodies (lecanemab or donanemab administered as clinical practice) in 50 patients with early Alzheimer's disease (AD) at IRCCS Ospedale San Raffaele (Milan, Italy). Advanced MRI techniques, including high- resolution structural imaging for cortical thickness and volumetric atrophy, diffusion imaging for structural connectivity, and resting-state functional MRI for functional network analysis, will be acquired at baseline, 6, 12, and 18 months.
These multimodal MRI measures will be integrated into computational approaches, such as the Aggregation Network Diffusion (AND) model, to simulate individual disease trajectories and predict the probability of achieving negativity at amyloid PET under treatment.
While serial \[¹⁸F\]Flutemetamol PET will be performed as part of standard clinical practice to confirm amyloid removal, the focus of the study is on developing MRI- derived predictive biomarkers. The ultimate goal is to establish robust, non-invasive models capable of guiding individualized treatment monitoring and supporting evidence-based decisions on treatment discontinuation
Overall, the project aims to support more precise care for people with early Alzheimer's disease, while reducing unnecessary procedures and improving quality of life.
Eligibility criteria
This trial does not accept healthy volunteersQualifiers
Participants aged 30-90.
Diagnosis of early symptomatic AD, including MCI or mild dementia [2].
Global Clinical Dementia Rating (CDR) score of 0.5 or 1.0
Confirmed amyloid pathology through CSF or PET imaging. 3. Participant is willing to start Anti-amyloid therapy as part of his/her clinical-practice- therapeutic plan.
Disqualifiers
Significant neurological diseases other than AD that could affect cognition or study participation (e.g., other dementias, serious brain infections, Parkinson's disease, multiple concussions, epilepsy with recurrent seizures).
Homozygous ApoE4 genotype.
Current use of anticoagulant therapy.
Vascular abnormalities: Presence of more than 4 microhemorrhages (defined as ≤10 mm in greatest diameter), a single macrohemorrhage >10 mm, superficial siderosis, evidence of vasogenic edema, multiple lacunar infarcts, or stroke involving a major vascular territory.
Trial design
Single group
Treatments tested in this trial
MRI assessment and blood sample collection
Other interventionParticipants will undergo non-contrast-enhanced 3T MRI, including structural, diffusion, and functional sequences, to assess brain atrophy, connectivity, and other imaging markers relevant to disease progression and treatment response. Peripheral venous blood will be collected at scheduled study visits to measure plasma biomarkers associated with amyloid, tau, and neurodegeneration, providing complementary information on treatment effects through a minimally invasive method. Eventually, multimodal predictive models, using the Aggregation Network Diffusion (AND) model, based on baseline amyloid burden, structural and functional brain connectivity, and clinical, cognitive and plasma biomarkers will be developed to estimate the time to significant amyloid reduction in patients with MCI or mild AD treated with lecanemab or donanemab
Treatment groups
Trial outcomes
Primary outcomes
Predicting time (in months) to amyloid [¹⁸F]Flutemetamol (amyloid) PET negativity on a single scan
Predicting time (in months) to amyloid \[¹⁸F\]Flutemetamol (amyloid) PET negativity, defined as amyloid load \<11 Centiloids on a single scan
Predicting time (in months) to amyloid [¹⁸F]Flutemetamol (amyloid) PET negativity on two consecutive scans
Predicting time (in months) to amyloid \[¹⁸F\]Flutemetamol (amyloid) PET negativity, defined as amyloid load -\<25 Centiloids on two consecutive scans
Secondary outcomes
Change in regional cerebral perfusion expressed in Standardized Uptake Volume Ratio (SUVR)
Change in regional cerebral perfusion expressed in SUVR (as a proxy from early-phase \[¹⁸F\]Flutemetamol - amyloid PET)
Change in global cerebral perfusion expressed in Standardized Uptake Volume Ratio (SUVR)
Change in global cerebral perfusion expressed in SUVR (as a proxy from early-phase \[¹⁸F\]Flutemetamol - amyloid PET)
Longitudinal change in brain volume
Evaluating brain volume changes over time
Longitudinal change in white matter integrity via Neurite Orientation Dispersion and Density Imaging (NODDI)
Evaluating structural white matter integrity over time
Sponsors and contacts
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