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Journal Article Meta-Analysis Comment Ppublish 7 citations

PubMed: 42441390 DOI: 10.1001/jama.2026.13116

Amyloid PET Quantitation and Centiloid Thresholds in the Diagnosis of Alzheimer Disease: An Individual Participant Data Meta-Analysis.

JAMA 336(13):1135-1148

Authors: Ganna Blazhenets, David N Soleimani-Meigooni, Konstantinos Chiotis, Isabel E Allen, Gil D Rabinovici, Renaud La Joie, Liana G Apostolova, Breton M Asken, Alexandre Bejanin, Tammie L S Benzinger, Tobey J Betthauser, Marina Bluma, Stephanie Bombois, Pierrick Bourgeat, Vincent Bouteloup, Meredith N Braskie, Matthias Brendel, Adam M Brickman, Natalie Bryant, Santiago Bullich, Maria C Carrillo, Kaitlin Casaletto, David M Cash, Chiung-Chih Chang, Hsin-I Chang, Yishu Chao, Genevieve Chêne, Gaël Chételat, William Coath, Lyduine E Collij, Lise Colmant, Maria M Corrada, Suzanne Craft, Bradford C Dickerson, Bruno Dubois, Carole Dufouil, Alfonso Fajardo, Gill Farrar, Juan Fortea, Lars Frings, Giovanni B Frisoni, Raquel C Gardner, Valentina Garibotto, Johannes S Gnörich, Brian A Gordon, Yuna Gu, Yihui Guan, Tengfei Guo, Bernard J Hanseeuw, Oskar Hansson … and 70 other authors

Affiliations

  • Edward and Pearl Fein Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco.
  • Molecular Biophysics and Integrated Bioimaging, Lawrence Berkeley National Laboratory, Berkeley, California.
  • Center for Alzheimer Research, Division of Clinical Geriatrics, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden.
  • Department of Radiology and Biomedical Imaging, University of California, San Francisco.
  • Indiana University School of Medicine, Indianapolis.
  • Department of Clinical and Health Psychology, 1Florida Alzheimer's Disease Research Center, University of Florida, Gainesville.
  • Sant Pau Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Institut d'Investigació Biomèdica Sant Pau (IIB SANT PAU), Facultad de Medicina - Universitat Autònoma de Barcelona, Barcelona, Spain.
  • Center of Biomedical Investigation Network for Neurodegenerative Diseases, Madrid, Spain.
  • Department of Radiology, Washington University in St Louis, St Louis, Missouri.
  • Wisconsin Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison.
  • Department of Medicine, University of Wisconsin, Madison.
  • Institute of Memory and Alzheimer's Disease, Department of Neurology, Pitié-Salpêtrière Hospital, AP-HP, Paris, France.
  • Australian eHealth Research Centre, CSIRO, Brisbane, Australia.
  • Université de Bordeaux, Bordeaux, France.
  • Pôle de Santé Publique Centre Hospitalier Universitaire de Bordeaux, Inserm, UMR 1219, Inserm, CIC 1401-EC, Bordeaux, France.
  • Mark and Mary Stevens Neuroimaging and Informatics Institute, University of Southern California, Los Angeles.
  • Department of Nuclear Medicine, University Hospital of Munich, Munich, Germany.
  • Munich Cluster for Systems Neurology, Munich, Germany.
  • German Center for Neurodegenerative Diseases, Munich, Germany.
  • Department of Neurology, College of Physicians and Surgeons, Columbia University, New York, New York.
  • University of California, Irvine.
  • Life Molecular Imaging GmbH, Berlin, Germany.
  • Medical and Scientific Relations, Alzheimer's Association, Chicago, Illinois.
  • Dementia Research Centre, UCL Queen Square Institute of Neurology, London, United Kingdom.
  • Department of Neurology, Cognition and Aging Center, Kaohsiung Chang Gung Memorial Hospital, Chang Gung University College of Medicine, Kaohsiung, Taiwan.
  • Department of Medicine, National Sun Yat-Sen University, Taiwan.
  • Department of Neuroscience, University of California, Berkeley.
  • Normandie Universitć, UNICAEN, INSERM, UA20, Neuropresage, Caen, France.
  • Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Faculty of Medicine, Lund University, Lund, Sweden.
  • Department of Radiology and Nuclear Medicine, Amsterdam UMC, location VUmc, Amsterdam, the Netherlands.
  • Amsterdam Neuroscience, Brain Imaging, Amsterdam, the Netherlands.
  • Department of Neurology Cliniques Universitaires Saint-Luc, Brussel, Belgium.
  • Wake Forest University School of Medicine, Winston-Salem, North Carolina.
  • Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston.
  • Department of Psychiatry, McGill University, Montreal, Quebec, Canada.
  • GE HealthCare Life Sciences, Amersham, United Kingdom.
  • Barcelona Down Medical Center, Fundació Catalana de Síndrome de Down, Barcelona, Spain.
  • Medical Center-University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany.
  • Laboratory of Neuroimaging of Aging, University of Geneva, Geneva, Switzerland.
  • Geneva Memory Centre, Department of Rehabilitation and Geriatrics, Geneva University Hospitals, Geneva, Switzerland.
  • Joseph Sagol Neuroscience Center, Sheba Medical Center, Ramat Gan, Israel.
  • Laboratory of Neuroimaging and Innovative Molecular Tracers, Geneva University Neurocentre and Faculty of Medicine, University of Geneva, Geneva, Switzerland.
  • Division of Nuclear Medicine and Molecular Imaging, Geneva University Hospitals, Geneva, Switzerland.
  • Centre for Biomedical Imaging, University of Geneva, Geneva, Switzerland.
  • Samsung Medical Center, Seoul, Republic of Korea.
  • Department of Health Sciences and Technology, SAIHST, Sungkyunkwan University, Seoul, South Korea.
  • Department of Nuclear Medicine & PET Center, Huashan Hospital, Fudan University, Shanghai, China.
  • Institute of Neurological and Psychiatric Disorders, Shenzhen Bay Laboratory, Shenzhen, China.

Abstract

IMPORTANCE

Amyloid positron emission tomography (PET) is increasingly used in research and clinical settings to determine the etiology of cognitive decline and eligibility for amyloid-targeting therapies. To assist with amyloid PET evaluation and to guide clinical decision-making, images can be quantified in a standardized unit called Centiloid, the interpretation of which can vary according to the method and threshold used.

OBJECTIVE

To collect Centiloid values from available studies and determine robust positivity cutoffs using data-driven methods and correspondence with visual reads.

DATA SOURCES

PubMed search (October 2024) identified studies with Centiloid values. Corresponding authors were invited to share individual participant data. Additional data were obtained through access-controlled repositories and conference outreach (July 2024-July 2025).

STUDY SELECTION

Studies were included if they provided Centiloids, radiotracer, age, and sex.

DATA EXTRACTION AND SYNTHESIS

Each study was analyzed using a unified statistical pipeline; study estimates were pooled using random-effects meta-analysis.

MAIN OUTCOMES AND MEASURES

Gaussian mixture models (GMMs) were fitted to Centiloid values for each study. In studies with a bimodal distribution (per integrated completed likelihood), single cutoffs for positivity were set as mean plus 2 SDs of the lower gaussian component. Using GMMs, a double-cutoff approach defined a lower certainty range using a 90% posterior probability cutoff for assignment to the low (amyloid-negative) vs high (amyloid-positive) component. An alternative Centiloid cutoff was derived from maximizing the correspondence (Cohen κ) with the binary visual reads when available.

RESULTS

This meta-analysis included cross-sectional amyloid PET scans acquired with 5 radiotracers from 49 227 participants across 53 studies from 15 countries (mean age, 71 years; 54% female, 62% cognitively impaired). The data-driven GMM approach identified a bimodal distribution in 51 studies (n = 48 786), resulting in a single cutoff for positivity of 18 Centiloids (95% CI,16-19; I2 = 97%). The double-cutoff approach revealed high confidence for interpreting scans as negative when Centiloid values were lower than 11 (95% CI, 9-13; I2 = 95%) and interpreting scans as positive if Centiloid values were higher than 26 (95% CI, 24-28; I2 = 95%). In analyses of correspondence with binary (positive or negative) visual reads of amyloid PET scans (n = 35 045; 36 studies), Centiloids were highly predictive of visual positivity (Cohen κ, 0.86; 95% CI, 0.83-0.89; I2 = 96%) with a cutoff of 27 Centiloids (95% CI, 24-30; I2 = 80%).

CONCLUSIONS AND RELEVANCE

In this individual participant data meta-analysis, positivity cutoffs converged around 18 Centiloids (data-driven) and 27 Centiloids (visual reads). Findings from a double-cutoff analysis suggest that scans in the 11 to 26 Centiloid range should be interpreted with caution depending on the context of use.

MeSH

Alzheimer Disease, Positron-Emission Tomography, Diagnosis, Amyloid