Published October 15, 2023 | Version v1
Publication Open

Evaluation of novel data-driven metrics of amyloid β deposition for longitudinal PET studies

  • 1. Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, UCL, London, UK
  • 1. Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, UCL, London, UK
  • 2. Amsterdam UMC, location VUmc, Department of Radiology and Nuclear Medicine, Amsterdam, the Netherlands
  • 3. ementia Research Centre, UCL Queen Square Institute of Neurology, London, UK.
  • 4. Hermes Medical Solutions, Stockholm, Sweden
  • 5. e Australian e-Health Research Centre, CSIRO, Brisbane, Australia
  • 6. Dementia Research Centre, UCL Queen Square Institute of Neurology, London, UK
  • 7. Amsterdam UMC, location VUmc, Department of Radiology and Nuclear Medicine, Amsterdam, the Netherlands; Clinical Memory Research Unit, Department of Clinical Sciences, Lund University, Malmö, Sweden
  • 8. Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, UCL, London, UK; GE HealthCare, Amersham, UK; Queen Square Institute of Neurology, University College London, UK
  • 9. GE HealthCare, Amersham, UK
  • 10. Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, UCL, London, UK; Amsterdam UMC, location VUmc, Department of Radiology and Nuclear Medicine, Amsterdam, the Netherlands; Queen Square Institute of Neurology, University College London, UK
  • 11. Queen Square Institute of Neurology, University College London, UK; UK Dementia Research Institute at University College London, London, UK

Description

Abstract:

Purpose: Positron emission tomography (PET) provides in vivo quantification of amyloid-β (Aβ) pathology. Established methods for assessing Aβ burden can be affected by physiological and technical factors. Novel, data-driven metrics have been developed to account for these sources of variability. We aimed to evaluate the performance of four of these amyloid PET metrics against conventional techniques, using a common set of criteria.

Methods: Three cohorts were used for evaluation: Insight 46 (N=464, [18F]florbetapir), AIBL (N=277, [18F]flutemetamol), and an independent test-retest data (N=10, [18F]flutemetamol). Established metrics of amyloid tracer uptake included the Centiloid (CL) and where dynamic data was available, the non-displaceable binding potential (BPND). The four data-driven metrics computed were the amyloid load (Aβ load), the Aβ-PET pathology accumulation index (Aβ index), the Centiloid derived from non-negative matrix factorisation (CLNMF), and the amyloid pattern similarity score (AMPSS). These metrics were evaluated using reliability and repeatability in test-retest data, associations with BPND and CL, variability of the rate of change and sample size estimates to detect a 25% slowing in Aβ accumulation.

Results: All metrics showed good reliability. Aβ load, Aβ index and CLNMF were strong associated with the BPND. The associations with CL suggest that cross-sectional measures of CLNMF, Aβ index and Aβ load are robust across studies. Sample size estimates for secondary prevention trial scenarios were the lowest for CLNMF and Aβ load compared to the CL.

Conclusion: Among the novel data-driven metrics evaluated, the Aβ load, the Aβ index and the CLNMF can provide comparable performance to more established quantification methods of Aβ PET tracer uptake. The CLNMF and Aβ load could offer a more precise alternative to CL, although further studies in larger cohorts should be conducted.

Notes

This project has received funding from the Innovative Medicines Initiative 2 Joint Undertaking under grant agreement No. 115952. This Joint Undertaking receives support from the European Union's Horizon 2020 research and innovation program and EFPIA. This communication reflects the views of the authors and neither IMI nor the European Union and EFPIA are liable for any use that may be made of the information contained herein 

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Additional details

Funding

European Commission
AMYPAD – Amyloid imaging to Prevent Alzheimer’s Disease – Sofia ref.: 115952 115952

Dates

Available
2023-10-15