Funded by the European Union (PREDICTFTD, 101156175). Views and opinions expressed are, however, those of the author(s) only and do not necessarily reflect those of the European Union or the Health and Digital Executive Agency. Neither the European Union nor the granting authority can be held responsible for them.
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About
PREDICTFTD will be the first to use the predictive value of multimodal clinical, imaging, and fluid biomarker data to train an AI-algorithm as a diagnostic tool for quick and early clinical FTD diagnosis.
Objectives
To collect cohort data and samples for biomarker validation and AI model development.
To validate candidate fluid biomarkers in genetically defined FTD cases.
To develop, train and validate AI learning algorithms and FTDetect tool for biomarker prediction and clinical diagnosis in genetically confirmed FTD cases.
To validate selected fluid biomarkers and AI prediction algorithms for FTD and FTLD subtype diagnosis of sporadic FTD and presymptomatic detection of disease onset in at-risk mutation carriers.
To develop economic evaluation models to assess the incremental net benefit of biomarker-led and FTD diagnosis.
Regulatory roadmap, dissemination, exploitation, and recommendations for future FTD diagnosis.
Why PREDICTFTD?
Debilitating effect
on patients and their caregivers
Frontotemporal dementia (FTD) has a debilitating effect on patients and their caregivers and leads to substantial economic costs.
15-30% of patients have familial FTD caused by known pathogenetic mutations.
For the other 70-85% of patients, termed sporadic FTD, diagnosis is slow (~3.6 years) with frequent misdiagnosis due to clinical, genetic and molecular heterogeneity.
We implement a novel robust two-stage strategy for biomarker and AI algorithm validation, where phase I validates biomarkers and algorithms on a cohort of genetic and autopsied cases and phase II assesses biomarker value for diagnosis of sporadic FTD and at-risk pre-symptomatic mutation carriers.
We are the first to use multimodal clinical and liquid biomarker data to train an AI-algorithm as a diagnostic tool for quick and early clinical FTD diagnosis.
We combine 11 geographically diverse cohorts of sporadic and familial FTD with retrospective and prospective longitudinal liquid biopsy samples and extensive clinical and behavioural data.
We implement a novel robust two-stage strategy for biomarker and AI algorithm validation, where phase I validates biomarkers and algorithms on a cohort of genetic and autopsied cases and phase II assesses biomarker value for diagnosis of sporadic FTD and at-risk pre-symptomatic mutation carriers.
We combine 11 geographically diverse cohorts of sporadic and familial FTD with retrospective and prospective longitudinal liquid biopsy samples and extensive clinical and behavioural data.
We are the first to use multimodal clinical and liquid biomarker data to train an AI-algorithm as a diagnostic tool for quick and early clinical FTD diagnosis.
diagnosis and management.
enhance the landscape of FTD
PREDICTFTD seeks to significantly
Impact
By developing and validating novel fluid biomarkers and pioneering AI-assisted diagnostic tools, this initiative aims to achieve a paradigm shift in early detection and accurate classification of FTD and its subtypes, such as FTLD-Tau and FTLDTDP.
Utilizing an extensive network of 11 European dementia and FTD cohorts, PREDICTFTD endeavours to refine these biomarkers in a diverse range of clinical scenarios, including sporadic cases confirmed by autopsy, presymptomatic mutation carriers, and genetically defined cases.
The primary goal is to reliably differentiate FTD from other NDDs, discern FTD subtypes, and anticipate disease onset in individuals at heightened risk, even before the emergence of clinical symptoms.
PREDICTFTD seeks to significantly
Impact
enhance the landscape of FTD
diagnosis and management.
By developing and validating novel fluid biomarkers and pioneering AI-assisted diagnostic tools, this initiative aims to achieve a paradigm shift in early detection and accurate classification of FTD and its subtypes, such as FTLD-Tau and FTLDTDP.
Utilizing an extensive network of 11 European dementia and FTD cohorts, PREDICTFTD endeavours to refine these biomarkers in a diverse range of clinical scenarios, including sporadic cases confirmed by autopsy, presymptomatic mutation carriers, and genetically defined cases.
The primary goal is to reliably differentiate FTD from other NDDs, discern FTD subtypes, and anticipate disease onset in individuals at heightened risk, even before the emergence of clinical symptoms.
Impact
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First to use multimodal clinical, imaging, and fluid biomarkers to train AI for fast, early FTD diagnosis.
-
First reliable biomarkers for early detection of sporadic FTD and its subtypes.
-
Biomarkers to detect FTD onset in at-risk mutation carriers before symptoms.
-
-
AI tools will redefine diagnostics by combining multi-parametric data to boost prediction.
-
Validated biomarker set to distinguish FTD from NDDs and non-NDDs.
-
Diagnostic tool will deepen understanding of neurodegenerative diseases.
-
-
Diagnosing FTD three years earlier could save €75,000 per patient.
-
Earlier diagnosis improves quality of life through timely, tailored treatments.
-
Supports WHO goals by reducing early mortality and improving mental health.
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Raises FTD awareness, hope, and societal mental well-being.
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-
With 12,000 new cases yearly, income loss savings could reach €900M/year.
-
Early, accurate diagnosis cuts costs by avoiding misdiagnosis and ineffective treatments.
-
Better use of healthcare resources and team coordination. Enables spin-offs and value-based care models across the EU.
-
-
First to use multimodal clinical, imaging, and fluid biomarkers to train AI for fast, early FTD diagnosis.
-
First reliable biomarkers for early detection of sporadic FTD and its subtypes.
-
Biomarkers to detect FTD onset in at-risk mutation carriers before symptoms.
-
-
AI tools will redefine diagnostics by combining multi-parametric data to boost prediction.
-
Validated biomarker set to distinguish FTD from NDDs and non-NDDs.
-
Diagnostic tool will deepen understanding of neurodegenerative diseases.
-
-
Diagnosing FTD three years earlier could save €75,000 per patient.
-
Earlier diagnosis improves quality of life through timely, tailored treatments.
-
Supports WHO goals by reducing early mortality and improving mental health.
-
Raises FTD awareness, hope, and societal mental well-being.
-
-
With 12,000 new cases yearly, income loss savings could reach €900M/year.
-
Early, accurate diagnosis cuts costs by avoiding misdiagnosis and ineffective treatments.
-
Better use of healthcare resources and team coordination. Enables spin-offs and value-based care models across the EU.
-
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