En Attendant Centiloid
Victor L. Villemagne *
Department of Nuclear Medicine and Centre for PET, Austin Health, Melbourne, Australia and The Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Melbourne, Australia and Department of Medicine, Austin Health, The University of Melbourne, Melbourne, Australia
Vincent Doré
Commonwealth Scientific Industrial Research Organization Preventative Health Flagship, CCI, Brisbane, Australia
Paul Yates
Department of Nuclear Medicine and Centre for PET, Austin Health, Melbourne, Australia
Belinda Brown
Centre of Excellence for Alzheimer’s Disease Research and Care, School of Medical Sciences, Edith Cowan University, Perth, Australia
Rachel Mulligan
Department of Nuclear Medicine and Centre for PET, Austin Health, Melbourne, Australia
Pierrick Bourgeat
Commonwealth Scientific Industrial Research Organization Preventative Health Flagship, CCI, Brisbane, Australia
Robyn Veljanoski
Department of Nuclear Medicine and Centre for PET, Austin Health, Melbourne, Australia
Stephanie R. Rainey-Smith
Centre of Excellence for Alzheimer’s Disease Research and Care, School of Medical Sciences, Edith Cowan University, Perth, Australia and Sir James McCusker Alzheimer’s Disease Research Unit (Hollywood Private Hospital), Perth, Australia
Kevin Ong
Department of Nuclear Medicine and Centre for PET, Austin Health, Melbourne, Australia
Alan Rembach
The Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Melbourne, Australia
Robert Williams
Department of Nuclear Medicine and Centre for PET, Austin Health, Melbourne, Australia
Samantha C. Burnham
Commonwealth Scientific Industrial Research Organization Preventative Health Flagship, Melbourne, Australia
Simon M. Laws
Centre of Excellence for Alzheimer’s Disease Research and Care, School of Medical Sciences, Edith Cowan University, Perth, Australia and Sir James McCusker Alzheimer’s Disease Research Unit (Hollywood Private Hospital), Perth, Australia
Olivier Salvado
Commonwealth Scientific Industrial Research Organization Preventative Health Flagship, CCI, Brisbane, Australia
Kevin Taddei
Commonwealth Scientific Industrial Research Organization Preventative Health Flagship, CCI, Brisbane, Australia
S. Lance Macaulay
Commonwealth Scientific Industrial Research Organization Preventative Health Flagship, Melbourne, Australia
Ralph N. Martins
Centre of Excellence for Alzheimer’s Disease Research and Care, School of Medical Sciences, Edith Cowan University, Perth, Australia andSir James McCusker Alzheimer’s Disease Research Unit (Hollywood Private Hospital), Perth, Australia and School of Psychiatry and Clinical Neurosciences, University of Western Australia, Perth, Australia
David Ames
National Ageing Research Institute, Melbourne, Australia and University of Melbourne Academic Unit for Psychiatry of Old Age, St George's Hospital, Melbourne, Australia
Colin L. Masters
The Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Melbourne, Australia
Christopher C. Rowe
Department of Nuclear Medicine and Centre for PET, Austin Health, Melbourne, Australia
*Author to whom correspondence should be addressed.
Abstract
Aims: Test the robustness of a linear regression transformation of semiquantitative values from different Aβ tracers into a single continuous scale.
Study Design: Retrospective analysis.
Place and Duration of Study: PET imaging data acquired in Melbourne and Perth, Australia, between August 2006 and May 2014.
Methodology: Aβ imaging in 633 participants was performed with four different radiotracers: flutemetamol (n=267), florbetapir (n=195), florbetaben (n=126) and NAV4694 (n=45). SUVR were generated with the methods recommended for each tracer, and classified as high (Aβ+) or low (Aβ-) based on their respective thresholds. Linear regression transformation based on reported head-to-head comparisons of each tracer with PiB was applied to each tracer result. Each tracer native classification was compared with the classification derived from the transformed data into PiB-like SUVR units (or BeCKeT: Before the Centiloid Kernel Transformation) using 1.50 as a cut-off.
Results: Misclassification after transformation to PiB-like SUVR compared to native classification was extremely low with only 3/267 (1.1%) of flutemetamol, 1/195 (0.5%) of florbetapir, 1/45 (2.2%) of NAV4694, and 1/126 (0.8%) of florbetaben cases assigned into the wrong category. When misclassification occurred (<1% of all cases) it was restricted to an extremely narrow margin (±0.02 BeCKeT) around the 1.50 BeCKeT threshold. Conclusion: While a definitive transformation into centesimal units is being established, application of linear regression transformations provide an interim, albeit robust, way of converting results from different Aβ imaging tracers into more familiar PiB-like SUVR units.
Keywords: Alzheimer’s disease, the Australian imaging biomarkers and lifestyle study of ageing, Aβ imaging, dementia, centiloid