Validation of amyloid PET positivity thresholds in centiloids : a multisite PET study approach
BACKGROUND: Inconsistent positivity thresholds, image analysis pipelines, and quantitative outcomes are key challenges of multisite studies using more than one β-amyloid (Aβ) radiotracer in positron emission tomography (PET). Variability related to these factors contributes to disagreement and lack of replicability in research and clinical trials. To address these problems and promote Aβ PET harmonization, we used [18F]florbetaben (FBB) and [18F]florbetapir (FBP) data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) to derive (1) standardized Centiloid (CL) transformations and (2) internally consistent positivity thresholds based on separate young control samples.
METHODS: We analyzed Aβ PET data using a native-space, automated image processing pipeline that is used for PET quantification in many large, multisite AD studies and trials and made available to the research community. With this pipeline, we derived SUVR-to-CL transformations using the Global Alzheimer's Association Interactive Network data; we used reference regions for cross-sectional (whole cerebellum) and longitudinal (subcortical white matter, brain stem, whole cerebellum) analyses. Finally, we developed a FBB positivity threshold using an independent young control sample (N=62) with methods parallel to our existing FBP positivity threshold and validated the FBB threshold using a data-driven approach in ADNI participants (N=295).
RESULTS: The FBB threshold based on the young sample (1.08; 18 CL) was consistent with that of the data-driven approach (1.10; 21 CL), and the existing FBP threshold converted to CL with the derived transformation (1.11; 20 CL). The following equations can be used to convert whole cerebellum- (cross-sectional) and composite- (longitudinal) normalized FBB and FBP data quantified with the native-space pipeline to CL units: [18F]FBB: CLwhole cerebellum = 157.15 × SUVRFBB - 151.87; threshold=1.08, 18 CL [18F]FBP: CLwhole cerebellum = 188.22 × SUVRFBP - 189.16; threshold=1.11, 20 CL [18F]FBB: CLcomposite = 244.20 × SUVRFBB - 170.80 [18F]FBP: CLcomposite = 300.66 × SUVRFBP - 208.84 CONCLUSIONS: FBB and FBP positivity thresholds derived from independent young control samples and quantified using an automated, native-space approach result in similar CL values. These findings are applicable to thousands of available and anticipated outcomes analyzed using this pipeline and shared with the scientific community. This work demonstrates the feasibility of harmonized PET acquisition and analysis in multisite PET studies and internal consistency of positivity thresholds in standardized units.
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2021 |
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| Erschienen: |
2021 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:13 |
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| Enthalten in: |
Alzheimer's research & therapy - 13(2021), 1 vom: 10. Mai, Seite 99 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Royse, Sarah K [VerfasserIn] |
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| Links: |
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| Anmerkungen: |
Date Completed 24.06.2021 Date Revised 24.06.2021 published: Electronic Citation Status MEDLINE |
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| doi: |
10.1186/s13195-021-00836-1 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| PPN (Katalog-ID): |
NLM325235767 |
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| 245 | 1 | 0 | |a Validation of amyloid PET positivity thresholds in centiloids |b a multisite PET study approach |
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| 500 | |a Date Completed 24.06.2021 | ||
| 500 | |a Date Revised 24.06.2021 | ||
| 500 | |a published: Electronic | ||
| 500 | |a Citation Status MEDLINE | ||
| 520 | |a BACKGROUND: Inconsistent positivity thresholds, image analysis pipelines, and quantitative outcomes are key challenges of multisite studies using more than one β-amyloid (Aβ) radiotracer in positron emission tomography (PET). Variability related to these factors contributes to disagreement and lack of replicability in research and clinical trials. To address these problems and promote Aβ PET harmonization, we used [18F]florbetaben (FBB) and [18F]florbetapir (FBP) data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) to derive (1) standardized Centiloid (CL) transformations and (2) internally consistent positivity thresholds based on separate young control samples | ||
| 520 | |a METHODS: We analyzed Aβ PET data using a native-space, automated image processing pipeline that is used for PET quantification in many large, multisite AD studies and trials and made available to the research community. With this pipeline, we derived SUVR-to-CL transformations using the Global Alzheimer's Association Interactive Network data; we used reference regions for cross-sectional (whole cerebellum) and longitudinal (subcortical white matter, brain stem, whole cerebellum) analyses. Finally, we developed a FBB positivity threshold using an independent young control sample (N=62) with methods parallel to our existing FBP positivity threshold and validated the FBB threshold using a data-driven approach in ADNI participants (N=295) | ||
| 520 | |a RESULTS: The FBB threshold based on the young sample (1.08; 18 CL) was consistent with that of the data-driven approach (1.10; 21 CL), and the existing FBP threshold converted to CL with the derived transformation (1.11; 20 CL). The following equations can be used to convert whole cerebellum- (cross-sectional) and composite- (longitudinal) normalized FBB and FBP data quantified with the native-space pipeline to CL units: [18F]FBB: CLwhole cerebellum = 157.15 × SUVRFBB - 151.87; threshold=1.08, 18 CL [18F]FBP: CLwhole cerebellum = 188.22 × SUVRFBP - 189.16; threshold=1.11, 20 CL [18F]FBB: CLcomposite = 244.20 × SUVRFBB - 170.80 [18F]FBP: CLcomposite = 300.66 × SUVRFBP - 208.84 CONCLUSIONS: FBB and FBP positivity thresholds derived from independent young control samples and quantified using an automated, native-space approach result in similar CL values. These findings are applicable to thousands of available and anticipated outcomes analyzed using this pipeline and shared with the scientific community. This work demonstrates the feasibility of harmonized PET acquisition and analysis in multisite PET studies and internal consistency of positivity thresholds in standardized units | ||
| 650 | 4 | |a Journal Article | |
| 650 | 4 | |a Research Support, N.I.H., Extramural | |
| 650 | 4 | |a Alzheimer’s disease | |
| 650 | 4 | |a Amyloid imaging | |
| 650 | 4 | |a Beta-amyloid | |
| 650 | 4 | |a Centiloid | |
| 650 | 4 | |a Florbetaben | |
| 650 | 4 | |a Florbetapir | |
| 650 | 4 | |a Standardization | |
| 650 | 7 | |a Amyloid beta-Peptides |2 NLM | |
| 650 | 7 | |a Amyloidogenic Proteins |2 NLM | |
| 650 | 7 | |a Aniline Compounds |2 NLM | |
| 700 | 1 | |a Minhas, Davneet S |e verfasserin |4 aut | |
| 700 | 1 | |a Lopresti, Brian J |e verfasserin |4 aut | |
| 700 | 1 | |a Murphy, Alice |e verfasserin |4 aut | |
| 700 | 1 | |a Ward, Tyler |e verfasserin |4 aut | |
| 700 | 1 | |a Koeppe, Robert A |e verfasserin |4 aut | |
| 700 | 1 | |a Bullich, Santiago |e verfasserin |4 aut | |
| 700 | 1 | |a DeSanti, Susan |e verfasserin |4 aut | |
| 700 | 1 | |a Jagust, William J |e verfasserin |4 aut | |
| 700 | 1 | |a Landau, Susan M |e verfasserin |4 aut | |
| 700 | 0 | |a Alzheimer’s Disease Neuroimaging Initiative |e verfasserin |4 aut | |
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| 773 | 1 | 8 | |g volume:13 |g year:2021 |g number:1 |g day:10 |g month:05 |g pages:99 |
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