A new Centiloid method for 18F-florbetaben and 18F-flutemetamol PET without conversion to PiB

Cho, Soo Hyun; Choe, Yeong Sim; Kim, Hee Jin; Kim, Yeshin; Kim, Si Eun; Kim, Seungjoo; Kim, Jun Pyo; Jung, Young Hee; Kim, Byeong C.; Baker, Suzanne L.; Lockhart, Samuel N.; Na, Duk L.; Park, Seongbeom

doi:10.1007/s00259-019-04596-x

Cited by 28 publications

(36 citation statements)

References 27 publications

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“…The concordance rates of Aβ positivity among 18 F-ligands have not yet been extensively evaluated in direct comparison studies. However, the results of the present study were supported by our previous work showing the spatial distribution of increased FMM uptake was similar to FBB [18]. In addition, FMM and FBB were highly correlated (R 2 = 0.97) and showed similar dynamic ranges (slope = 0.99).…”

Section: Discussionsupporting

confidence: 91%

“…FMM is the 18 F-labelled analogue of 11 C-PiB and shows strong concordance with histopathology for brain brillar Aβ. FMM has been useful for differentiating cognitively normal people and AD patients with high speci city and sensitivity in detection of AD [8].…”

Section: Introductionmentioning

confidence: 58%

“…For direct comparison of the FBB-FMM conversion method, SUVR values of the FBB-FMM cortical target volume of interest (CTX VOI) were directly converted into Centiloid (CL) units using the direct comparison of FBB-FMM CL (dcCL) method based on the CL conversion equation [17,18]:…”

Section: Aβ Pet Positivity Based On Suvr Assessmentmentioning

confidence: 99%

“…The F-labelled ligand is an amyloid PET ligand widely used for diagnosing AD. Among them, 18 Forbetaben (FBB) [5] and 18 F-utemetamol (FMM) [6] are widely used in Europe and Asia. FBB is an 18 F-labelled polyethylene glycol stilbene derivative with high in vitro a nity and speci city for Aβ plaques [7].…”

Section: Introductionmentioning

confidence: 99%

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Concordance in Detecting Amyloid Positivity Between 18F-florbetaben and 18F-flutemetamol Amyloid PET Using Quantitative and Qualitative Assessments

Cho

Choe

Kim

et al. 2020

Preprint

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Background In the present study, the discrepancy in detecting amyloid beta (Aβ) positivity between 18F-florbetaben (FBB) and 18F-flutemetamol (FMM) positron emission tomography (PET) was quantitatively and qualitatively assessed.Methods Paired FBB and FMM PET images were obtained on separate days from 107 participants. Three experts visually quantified the scans as positive or negative for Aβ deposition. Quantitative assessment was performed using global cortical standardized uptake value ratio (SUVR) with the whole cerebellum (WC) as a reference region.Results Inter-rater agreement was excellent for FBB (Fleiss k = 0.86) and FMM (Fleiss k = 0.78). The concordance rates between FBB and FMM were 94.4% (101/107) for visual assessment and 98.1% (105/107) for SUVR cut-off categorisation. Both FBB and FMM showed high agreement rates between visual assessment and SUVR positive or negative categorisation (93.5% in FBB and 91.2% in FMM). When the two ligands were compared based on SUVR cut-off categorisation as standard of truth, although not statistically significant, the false-positive rate (visual assessment-positive, SUVR-negative) was higher in FMM (9.1%) than in FBB (1.8%) (P = 0.13). In those cases, assessing uptakes in the lateral temporal cortex was often more problematic than in other regions in visual analysis, especially near the border with the occipital lobe.Conclusion Our findings suggested that both FBB and FMM had excellent agreement when used to quantitatively and qualitatively evaluate Aβ deposits, thus, combining amyloid PET data associated with the use of different ligands from multi-centers can be useful in future research.

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Section: Discussionsupporting

confidence: 91%

Section: Introductionmentioning

confidence: 58%

Section: Aβ Pet Positivity Based On Suvr Assessmentmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Concordance in Detecting Amyloid Positivity Between 18F-florbetaben and 18F-flutemetamol Amyloid PET Using Quantitative and Qualitative Assessments

Cho

Choe

Kim

et al. 2020

Preprint

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“…In this study, we investigated which reference regions are most appropriate to calculate CL unit when using the FBB and FMM ligands. We used head-to-head comparisons of Aβ PET with the FBB and FMM ligands using a direct comparison of the FBB-FMM CL (dcCL) method 11 with four reference regions: CG, WC, WC + B, and pons, which have been frequently used in previous studies. We hypothesized that we would find differences in the appropriateness of the different reference regions between FBB and FMM in terms of the largest effect size between the AD and YC groups and the smallest variability within the YC group.…”

mentioning

confidence: 99%

Appropriate reference region selection of 18F-florbetaben and 18F-flutemetamol beta-amyloid PET expressed in Centiloid

Cho

Choe

Park

et al. 2020

Sci Rep

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The Centiloid (CL) is a method for standardizing amyloid beta (Aβ) quantification through different ligands and methods. To find the most appropriate reference region to reduce the variance in the Aβ CL unit between 18F-florbetaben (FBB) and 18F-flutemetamol (FMM), we conducted head-to-head comparisons from 56 participants using the direct comparison of FBB-FMM CL (dcCL) method with four reference regions: cerebellar gray (CG), whole cerebellum (WC), WC with brainstem (WC + B), and pons. The FBB and FMM dcCL units were highly correlated in four reference regions: WC (R2 = 0.97), WC + B (R2 = 0.98), CG (R2 = 0.92), and pons (R2 = 0.98). WC showed the largest effect size in both FBB and FMM. Comparison of the variance of the dcCL values within the young control group showed that with FBB, WC + B had the smallest variance and with FMM, the WC had the smallest variance. Additionally, WC + B showed the smallest absolute difference between FBB and FMM, followed by the WC, pons, and CG. We found that it would be reasonable to use the WC or WC + B as the reference region when converting FBB and FMM SUVRs into dcCL, which can increase the accuracy of standardizing FBB and FMM PET results.

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Longitudinal amyloid and tau PET imaging in Alzheimer's disease: A systematic review of methodologies and factors affecting quantification

Bollack

Pemberton

Collij

et al. 2023

Alzheimer's & Dementia

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Deposition of amyloid and tau pathology can be quantified in vivo using positron emission tomography (PET). Accurate longitudinal measurements of accumulation from these images are critical for characterizing the start and spread of the disease. However, these measurements are challenging; precision and accuracy can be affected substantially by various sources of errors and variability. This review, supported by a systematic search of the literature, summarizes the current design and methodologies of longitudinal PET studies. Intrinsic, biological causes of variability of the Alzheimer's disease (AD) protein load over time are then detailed. Technical factors contributing to longitudinal PET measurement uncertainty are highlighted, followed by suggestions for mitigating these factors, including possible techniques that leverage shared information between serial scans. Controlling for intrinsic variability and reducing measurement uncertainty in longitudinal PET pipelines will provide more accurate and precise markers of disease evolution, improve clinical trial design, and aid therapy response monitoring.

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A new Centiloid method for 18F-florbetaben and 18F-flutemetamol PET without conversion to PiB

Cited by 28 publications

References 27 publications

Concordance in Detecting Amyloid Positivity Between 18F-florbetaben and 18F-flutemetamol Amyloid PET Using Quantitative and Qualitative Assessments

Concordance in Detecting Amyloid Positivity Between 18F-florbetaben and 18F-flutemetamol Amyloid PET Using Quantitative and Qualitative Assessments

Appropriate reference region selection of 18F-florbetaben and 18F-flutemetamol beta-amyloid PET expressed in Centiloid

Longitudinal amyloid and tau PET imaging in Alzheimer's disease: A systematic review of methodologies and factors affecting quantification

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