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Ribaldi F, Mendes AJ, Galazzo IB, Natale V, Mathoux G, Pievani M, Lovblad KO, Scheffler M, Frisoni GB, Garibotto V, Pizzini FB. Agreement between early-phase amyloid-PET and pulsed arterial spin labeling in a memory clinic cohort. J Mol Med (Berl) 2025:10.1007/s00109-025-02545-w. [PMID: 40392338 DOI: 10.1007/s00109-025-02545-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2023] [Revised: 04/04/2025] [Accepted: 04/07/2025] [Indexed: 05/22/2025]
Abstract
Relative cerebral blood flow (rCBF), assessed using pulsed arterial spin labeling (pASL) MRI, and the standardized uptake value ratio (SUVr) in early-phase amyloid-PET (ePET) are used as proxies for brain perfusion. These methods have the potential to streamline clinical workflows and reduce the burden on patients by eliminating the need for additional procedures. While both techniques have shown good agreement with the gold standard for glucose metabolism assessment, F-fluorodeoxyglucose-PET, a direct comparison between them has yet to be fully clarified. This retrospective study aimed to compare perfusion-like data from pASL (rCBF) and ePET (SUVr) in a memory clinic cohort. We included 46 subjects (69 ± 8 years; 37 women) from the Geneva Memory Center (cognitively impaired-CI n = 29; cognitively unimpaired-CU n = 17), with available pASL and ePET. We evaluated the association between rCBF and SUVr values across 18 cortical and subcortical regions using linear regression and the within-subject coefficient of variation (wsCV). Regional differences between CU and CI groups were assessed using linear regression model corrected for age. We observed significant association between rCBF and SUVr in precuneus (β = 0.69, wsCV = 16.9), angular gyrus (β = 0.64, wsCV = 19.4), and hippocampus (β = 0.23, wsCV = 16.1). Additionally, significant differences in rCBF between CU and CI were also observed in the posterior cingulate, precuneus, calcarine, hippocampus, and composite (p < 0.05), while SUVr showed significant differences only in the hippocampus. Our findings indicate weak to moderate local correlations between the two techniques. However, both exhibited differing regional perfusion levels in CU and CI groups, with rCBF showing more regional differences between cognitive stages in comparison with SUVr. KEY MESSAGES: rCBF is assessed through pASL MRI and SUVr through ePET, both serving as proxies of brain perfusion. Weak to moderate associations between rCBF and SUVr were found in a number of brain regions. rCBF and SUVr differences between cognitive stages were observed mostly in cortical and subcortical regions respectively. Both techniques were able to identify AD perfusion-like differences expected in cognitively impaired vs unimpaired.
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Affiliation(s)
- F Ribaldi
- Geneva Memory Center, Department of Rehabilitation and Geriatrics, Geneva University Hospitals, Geneva, Switzerland.
- Laboratory of Neuroimaging of Aging (LANVIE), University of Geneva, Geneva, Switzerland.
| | - A J Mendes
- Geneva Memory Center, Department of Rehabilitation and Geriatrics, Geneva University Hospitals, Geneva, Switzerland
- Laboratory of Neuroimaging of Aging (LANVIE), University of Geneva, Geneva, Switzerland
| | - I Boscolo Galazzo
- Department of Engineering for Innovation Medicine, University of Verona, Verona, Italy
| | - V Natale
- Department of Diagnostic and Public Health, Rivoli Hospital, Rivoli (TO), Italy
| | - G Mathoux
- Division of Nuclear Medicine and Molecular Imaging, Diagnostic Department, Geneva University Hospitals, Geneva, Switzerland
| | - M Pievani
- Laboratory Alzheimer's Neuroimaging & Epidemiology, IRCCS Istituto Centro San Giovanni Di Dio Fatebenefratelli, Brescia, Italy
| | - K O Lovblad
- Neurodiagnostic and Neurointerventional Division, Diagnostic Department, Geneva University Hospitals, Geneva, Switzerland
| | - M Scheffler
- Division of Radiology, Geneva University Hospitals, Geneva, Switzerland
| | - G B Frisoni
- Geneva Memory Center, Department of Rehabilitation and Geriatrics, Geneva University Hospitals, Geneva, Switzerland
- Laboratory of Neuroimaging of Aging (LANVIE), University of Geneva, Geneva, Switzerland
| | - V Garibotto
- Division of Nuclear Medicine and Molecular Imaging, Diagnostic Department, Geneva University Hospitals, Geneva, Switzerland
- Laboratory of Neuroimaging and Innovative Molecular Tracers (NIMTlab), Neurocenter and Faculty of Medicine, Geneva University, University of Geneva, Geneva, Switzerland
- CIBM Center for Biomedical Imaging, Geneva, Switzerland
| | - F B Pizzini
- Radiology and Department of Engineering forInnovation Medicine, Verona University, Verona, Italy
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Ottoy J, Ozzoude M, Zukotynski K, Kang MS, Adamo S, Scott C, Ramirez J, Swardfager W, Lam B, Bhan A, Mojiri P, Kiss A, Strother S, Bocti C, Borrie M, Chertkow H, Frayne R, Hsiung R, Laforce RJ, Noseworthy MD, Prato FS, Sahlas DJ, Smith EE, Kuo PH, Chad JA, Pasternak O, Sossi V, Thiel A, Soucy JP, Tardif JC, Black SE, Goubran M. Amyloid-PET of the white matter: Relationship to free water, fiber integrity, and cognition in patients with dementia and small vessel disease. J Cereb Blood Flow Metab 2023; 43:921-936. [PMID: 36695071 DOI: 10.1177/0271678x231152001] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/26/2023]
Abstract
White matter (WM) injury is frequently observed along with dementia. Positron emission tomography with amyloid-ligands (Aβ-PET) recently gained interest for detecting WM injury. Yet, little is understood about the origin of the altered Aβ-PET signal in WM regions. Here, we investigated the relative contributions of diffusion MRI-based microstructural alterations, including free water and tissue-specific properties, to Aβ-PET in WM and to cognition. We included a unique cohort of 115 participants covering the spectrum of low-to-severe white matter hyperintensity (WMH) burden and cognitively normal to dementia. We applied a bi-tensor diffusion-MRI model that differentiates between (i) the extracellular WM compartment (represented via free water), and (ii) the fiber-specific compartment (via free water-adjusted fractional anisotropy [FA]). We observed that, in regions of WMH, a decrease in Aβ-PET related most closely to higher free water and higher WMH volume. In contrast, in normal-appearing WM, an increase in Aβ-PET related more closely to higher cortical Aβ (together with lower free water-adjusted FA). In relation to cognitive impairment, we observed a closer relationship with higher free water than with either free water-adjusted FA or WM PET. Our findings support free water and Aβ-PET as markers of WM abnormalities in patients with mixed dementia, and contribute to a better understanding of processes giving rise to the WM PET signal.
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Affiliation(s)
- Julie Ottoy
- LC Campbell Cognitive Neurology Unit, Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada
| | - Miracle Ozzoude
- LC Campbell Cognitive Neurology Unit, Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada
| | - Katherine Zukotynski
- LC Campbell Cognitive Neurology Unit, Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada.,Departments of Medicine and Radiology, McMaster University, Hamilton, ON, Canada.,Department of Medical Imaging, Schulich School of Medicine & Dentistry, Western University, London, ON, Canada.,Department of Radiology, University of British Columbia, Vancouver, BC, Canada
| | - Min Su Kang
- LC Campbell Cognitive Neurology Unit, Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada.,Montreal Neurological Institute, McGill University, Montreal, QC, Canada
| | - Sabrina Adamo
- LC Campbell Cognitive Neurology Unit, Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada
| | - Christopher Scott
- LC Campbell Cognitive Neurology Unit, Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada
| | - Joel Ramirez
- LC Campbell Cognitive Neurology Unit, Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada
| | - Walter Swardfager
- Department of Pharmacology & Toxicology, University of Toronto, Toronto, ON, Canada
| | - Benjamin Lam
- Department of Medicine (Division of Neurology), Dr. Sandra Black Centre for Brain Resilience and Recovery, Hurvitz Brain Sciences Research Program, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON, Canada
| | - Aparna Bhan
- LC Campbell Cognitive Neurology Unit, Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada
| | - Parisa Mojiri
- LC Campbell Cognitive Neurology Unit, Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada
| | - Alex Kiss
- Department of Research Design and Biostatistics, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada
| | - Stephen Strother
- Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada.,The Rotman Research Institute Baycrest, University of Toronto, Toronto, ON, Canada
| | - Christian Bocti
- Service de Neurologie, Département de Medicine, Université de Sherbrooke, Sherbrooke, QC, Canada
| | - Michael Borrie
- Lawson Health Research Institute, Western University, London, ON, Canada
| | - Howard Chertkow
- Jewish General Hospital and Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada
| | - Richard Frayne
- Departments of Radiology and Clinical Neuroscience, Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada
| | - Robin Hsiung
- Physics and Astronomy Department and DM Center for Brain Health, University of British Columbia, Vancouver, BC, Canada
| | - Robert Jr Laforce
- Clinique Interdisciplinaire de Mémoire, Département des Sciences Neurologiques, Université Laval, Québec, QC, Canada
| | - Michael D Noseworthy
- Departments of Medicine and Radiology, McMaster University, Hamilton, ON, Canada.,Department of Electrical and Computer Engineering, McMaster University, Hamilton, ON, Canada
| | - Frank S Prato
- Lawson Health Research Institute, Western University, London, ON, Canada
| | | | - Eric E Smith
- Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada
| | - Phillip H Kuo
- Department of Medical Imaging, Medicine, and Biomedical Engineering, University of Arizona, Tucson, AZ, USA
| | - Jordan A Chad
- Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada.,The Rotman Research Institute Baycrest, University of Toronto, Toronto, ON, Canada
| | - Ofer Pasternak
- Departments of Psychiatry and Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, USA
| | - Vesna Sossi
- Physics and Astronomy Department and DM Center for Brain Health, University of British Columbia, Vancouver, BC, Canada
| | - Alexander Thiel
- Jewish General Hospital and Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada
| | - Jean-Paul Soucy
- Montreal Neurological Institute, McGill University, Montreal, QC, Canada
| | | | - Sandra E Black
- LC Campbell Cognitive Neurology Unit, Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada.,Department of Medicine (Division of Neurology), Dr. Sandra Black Centre for Brain Resilience and Recovery, Hurvitz Brain Sciences Research Program, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON, Canada
| | - Maged Goubran
- LC Campbell Cognitive Neurology Unit, Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada.,Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada.,Physical Sciences Platform, Sunnybrook Research Institute, Sunnybrook Health Sciences Centre, Toronto, ON, Canada
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Nai YH, Shidahara M, Seki C, Watabe H. Biomathematical screening of amyloid radiotracers with clinical usefulness index. ALZHEIMERS & DEMENTIA-TRANSLATIONAL RESEARCH & CLINICAL INTERVENTIONS 2017; 3:542-552. [PMID: 29124113 PMCID: PMC5671631 DOI: 10.1016/j.trci.2017.08.006] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
Introduction To facilitate radiotracers' development, a screening methodology using a biomathematical model and clinical usefulness index (CUI) was proposed to evaluate radiotracers' diagnostic capabilities. Methods A total of 31 amyloid positron emission tomography radiotracers were evaluated. A previously developed biomathematical model was used to simulate 1000 standardized uptake value ratios with population and noise simulations, which were used to determine the integrated receiver operating characteristics curve (Az), effect size (Es), and standardized uptake value ratio (Sr) of conditions-pairs of healthy control–mild cognitive impaired and mild cognitive impaired–Alzheimer's disease. CUI was obtained from the product of averaged Az(Az¯), Es(Es¯), and Sr(Sr¯). Results The relationships of Az¯, Es¯, and Sr¯ with CUI were different, suggesting that they assessed different radiotracer properties. The combination of Az, Es, and Sr complemented each other and resulted in CUI of 0.10 to 5.72, with clinically applied amyloid positron emission tomography radiotracers having CUI greater than 3.0. Discussion The CUI rankings of clinically applied radiotracers were close to their reported clinical results, attesting to the applicability of the screening methodology. Clinical usefulness index was proposed to evaluate radiotracers' diagnostic power. CUI rankings of amyloid radiotracers were close to their clinical results. CUI allows for simultaneous and objective comparison of candidate radiotracers.
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Affiliation(s)
- Ying-Hwey Nai
- Division of Radiation Informatics for Medical Imaging, Graduate School of Biomedical Engineering, Tohoku University, Sendai, Japan.,Division of Radiation Protection and Safety Control, Cyclotron and Radioisotope Center, Tohoku University, Sendai, Japan
| | - Miho Shidahara
- Department of Medical Physics, Graduate School of Medicine, Tohoku University, Sendai, Japan
| | - Chie Seki
- Department of Functional Brain Imaging Research, National Institute of Radiological Sciences, National Institutes for Quantum and Radiological Science and Technology, Chiba, Japan
| | - Hiroshi Watabe
- Division of Radiation Informatics for Medical Imaging, Graduate School of Biomedical Engineering, Tohoku University, Sendai, Japan.,Division of Radiation Protection and Safety Control, Cyclotron and Radioisotope Center, Tohoku University, Sendai, Japan
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