TY - JOUR
T1 - Evaluation of novel data-driven metrics of amyloid β deposition for longitudinal PET studies
AU - Bollack, Ariane
AU - Markiewicz, Pawel J.
AU - Wink, Alle Meije
AU - Prosser, Lloyd
AU - Lilja, Johan
AU - Bourgeat, Pierrick
AU - Schott, Jonathan M.
AU - Coath, William
AU - Collij, Lyduine E.
AU - Pemberton, Hugh G.
AU - Farrar, Gill
AU - Barkhof, Frederik
AU - on behalf on the AMYPAD consortium
AU - Cash, David M.
N1 - Funding Information: Insight 46 is funded by Alzheimer's Research UK , the Medical Research Council Dementia Platforms UK , Selfridges Group Foundation , Wolfson Foundation , Wellcome Trust , Brain Research UK , Alzheimer's Association . Avid Radiopharmaceuticals, a wholly owned subsidiary of Eli Lilly, kindly provided the 18 F-florbetapir tracer (Amyvid TM ) free of cost but had no role in the design, conduct, analysis or reporting of Insight 46 study findings. We are grateful to the Insight 46 study team and indebted to the study participants Funding Information: This work is supported by the EPSRC -funded UCL Centre for Doctoral Training in Intelligent, Integrated Imaging in Healthcare ( i4health ) ( EP/S021930/1 ), the Department of Health's NIHR - funded Biomedical Research Centre at University College London, and GE Healthcare. FB is supported by the NIHR biomedical research centre at UCLH. Funding Information: This work is supported by the EPSRC-funded UCL Centre for Doctoral Training in Intelligent, Integrated Imaging in Healthcare (i4health) (EP/S021930/1), the Department of Health's NIHR- funded Biomedical Research Centre at University College London, and GE Healthcare. FB is supported by the NIHR biomedical research centre at UCLH.Insight 46 is funded by Alzheimer's Research UK, the Medical Research Council Dementia Platforms UK, Selfridges Group Foundation, Wolfson Foundation, Wellcome Trust, Brain Research UK, Alzheimer's Association. Avid Radiopharmaceuticals, a wholly owned subsidiary of Eli Lilly, kindly provided the 18F-florbetapir tracer (AmyvidTM) free of cost but had no role in the design, conduct, analysis or reporting of Insight 46 study findings. We are grateful to the Insight 46 study team and indebted to the study participantsThe project leading to this paper has received funding from the Innovative Medicines Initiative 2 Joint Undertaking under grant agreement No 115952. This Joint Undertaking receives the support from the European Union's Horizon 2020 research and innovation programme 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. Funding Information: The project leading to this paper has received funding from the Innovative Medicines Initiative 2 Joint Undertaking under grant agreement No 115952 . This Joint Undertaking receives the support from the European Union's Horizon 2020 research and innovation programme 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. Publisher Copyright: © 2023
PY - 2023/10/15
Y1 - 2023/10/15
N2 - 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.
AB - 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.
KW - Alzheimer's
KW - Amyloid
KW - Longitudinal
KW - Machine learning
KW - PET
KW - Quantification
UR - http://www.scopus.com/inward/record.url?scp=85170410324&partnerID=8YFLogxK
U2 - https://doi.org/10.1016/j.neuroimage.2023.120313
DO - https://doi.org/10.1016/j.neuroimage.2023.120313
M3 - Article
C2 - 37595816
SN - 1053-8119
VL - 280
JO - NeuroImage
JF - NeuroImage
M1 - 120313
ER -