Quantum-enhanced and AI-powered metabolic MRI Diagnostics (Q-AID)
European Union
Project Duration: 01.04.2025 - 31.03.2029
About the project
Programme
Digital Europe Programme (DIGITAL)
Project coordination
NVISION Imaging Technologies GmbH
Project partners
- Danube Private University
- Fondazione Policlinico Universitario Agostino Gemelli IRCCS
- Fundacio Institut de Bioenginyeria de Catalunya
- Universiteit Antwerpen
- Commissariat à l'énergie atomique et aux énergies alternatives
- Aarhus Universitet
Researchers involved at DPU
- Univ.-Prof. Dr. Ramona Woitek
- Assist.-Prof. Olgica Zaric, PhD
- Ali Haider, PhD
Abstract
Objective: The vision of Q-AID is to facilitate a breakthrough in clinical metabolic imaging by combining quantum-based hyperpolarization (HP) technology for the acquisition of spatially-resolved metabolic data via magnetic resonance imaging (MRI) and bespoke artificial-intelligence (AI) tools to optimally extract information from these data. The Q-AID project thereby enables and demonstrates new broadly applicable capabilities for the diagnosis and response assessment in neurologic diseases and cancer.
Our consortium brings together a pioneering industrial partner with leading academic centres and research hospitals, who propose to
1. Establish the required supply chains and meet the regulatory requirements for the deployment of quantum-based HP technology for preclinical and clinical studies specifically designed for the Q-AID project. This work will offer a robust basis for future deployment of HP technology across the EU.
2. Develop AI models that will provide enhanced capabilities for the analysis and interpretation of HP-MRI data, in particular with regard to spatially locating metabolic information, and segmenting and classifying metabolic profiles determined by HP-MRI. In parallel, we will establish a platform for data sharing across institutions. In the Q-AID preclinical and clinical studies, these tools will be established as broadly applicable elements for future HP-MRI studies.
3. Develop and undertake preclinical HP-MRI studies on models of ovarian and breast cancer as well as of multiple sclerosis (MS) and Alzheimer's disease (AD), with a focus on gaining experience and insight that can be translated to clinical settings in oncology and neurology.
4. Develop and undertake clinical HP-MRI studies in oncology and neurology in cohorts of 20–70 patients each, focusing on early assessment of neoadjuvant treatment response in breast and ovarian cancer, and on improved diagnosis of brain lesions and monitoring of disease-modifying therapy (DMT) response in MS and AD.