Harmonisation
Practical standards for patient preparation, acquisition, reconstruction, processing and quantitative analysis can support reliable specialist interpretation across different hospitals and PET systems.
Research & collaboration
Advancing the role of brain FDG-PET in neurodegenerative disease
BrainDx is interested in research and collaboration that improves the use of molecular brain imaging in neurodegenerative disease.
From diagnosis to research
Identifying the right patients at the right stage
Brain FDG-PET can contribute to identifying and phenotyping patients at an earlier stage of neurodegenerative disease, including when structural imaging may still show limited or non-specific abnormalities.
Earlier patient phenotyping can support the development and validation of biomarkers, improve the characterisation of research cohorts, and contribute to the discovery and development of disease-specific treatments.
Clinical presentation→FDG-PET→Earlier patient phenotyping→Biomarker development · research cohorts · disease-specific treatment development
Improving access to FDG-PET expertise
Expertise should not depend on where a scan is performed
BrainDx is interested in models that allow specialist expertise to be shared between institutions while maintaining high standards of image acquisition, processing and interpretation.
Shared expertise
Reliable exchange and central assessment of imaging, development of specialist reporting expertise and organisational models through which hospitals can access that expertise.
Quantitative & AI support
Research into quantitative and AI-supported analysis where it can support expert interpretation, consistency and workflow—supporting, not replacing, specialist assessment.
A growing biomarker ecosystem
FDG-PET alongside emerging diagnostic tools
Molecular imaging is increasingly complemented by disease-specific PET and fluid biomarkers. Research can explore how FDG-PET, amyloid and tau PET, plasma or CSF biomarkers, genetic risk and future biomarkers provide complementary information and can be combined in efficient diagnostic pathways.