Elsevier

NeuroImage

Volume 183, December 2018, Pages 387-393
NeuroImage

Implementing the centiloid transformation for 11C-PiB and β-amyloid 18F-PET tracers using CapAIBL

https://doi.org/10.1016/j.neuroimage.2018.08.044Get rights and content

Highlights

  • PET-only quantification method CapAIBL is calibrated to the centiloid scale.

  • Reliable quantification can be obtained using CapAIBL with 11C-PiB and 18F tracers.

  • Scanner specific differences might require an extra linear adjustment.

Abstract

The centiloid scale was recently proposed to provide a standard framework for the quantification of β-amyloid PET images, so that amyloid burden can be expressed on a standard scale. While the framework prescribes SPM8 as the standard analysis method for PET quantification, non-standard methods can be calibrated to produce centiloid values. We have previously developed a PET-only quantification: CapAIBL. In this study, we show how CapAIBL can be calibrated to the centiloid scale.

Methods

Calibration images for 11C-PiB, 18F-NAV4694, 18F-Florbetaben, 18F-Flutemetamol and 18F- Florbetapir were analysed using the standard method and CapAIBL. Using these images, both methods were calibrated to the centiloid scale. Centiloid values computed using CapAIBL were compared to those computed using standard method. For each tracer, a separate validation was performed using an independent dataset from the AIBL study.

Results

Using the calibration images, there was a very strong agreement, and very little bias between the centiloid values computed using CapAIBL and those computed using the standard method with R2 > 0.97 across all tracers. Using images from AIBL, the agreement was also high with R2 > 0.96 across all tracers. In this dataset, there was a small underestimation of the centiloid values computed using CapAIBL of less than 0.8% in PiB, and a small over-estimation of 1.3% in Florbetapir, and 0.8% in Flutemetamol. There was a larger overestimation of 8% in NAV images, and 14% underestimation in Florbetaben images. However, some of these differences could be explained by the use of different scanners between the calibration scans and the ones used in AIBL.

Conclusion

The PET-only quantification method, CapAIBL, can produce reliable centiloid values. The bias observed in the AIBL dataset for 18F-NAV4694 and 18F-Florbetaben may indicate that using different scanners or reconstruction methods might require scanner-specific adjustments.

Introduction

β-amyloid (Aβ) imaging using PET has become the de facto standard to identify one of the neuropathological signs of Alzheimer's disease (AD) in vivo. There is however great variability in the way Aβ burden is quantified from PET images, with each research centre developing their own pipeline to analyse the images, and using their own volume of interest (VOI) to compute the mean uptake in the neocortical and reference regions. This leads to great variability in the resulting numbers (Rowe and Villemagne, 2011), and makes comparison across sites or studies difficult (Carrillo et al., 2013). This also means that pooling data across studies requires all images to be reanalysed to minimise bias. The variability is also exacerbated by the use of different tracers, each having different pharmacokinetics, binding potentials, recommended acquisition protocol and reference region (Clark et al., 2012; Rowe et al., 2007, 2008; Thurfjell et al., 2013). There are currently 5 different tracers that are commonly used in research studies, namely 11C-PiB (PiB), 18F- NAV4694 (NAV), 18F-Florbetaben (FBB), 18F-Flutemetamol (FLUTE) and 18F-Florbetapir (FBP), with each tracer having their own recommended acquisition protocol, reference region and cut-off value for Aβ positivity. However, due to the variability from the quantification method, these cut-off values often need to be adjusted at each site so that they match visual reading.

The centiloid (CL) scale was developed by an international working group to alleviate some of these issues and provide a framework to standardise measures of Aβ burden from PET images (Klunk et al., 2015). The framework allows any tracer or quantification method to be linearly mapped to the same scale: the centiloid scale. In this scale, 0 represents the typical Aβ burden in young controls, and 100 the typical Aβ burden in mild AD patients. A standard quantification pipeline based on SPM8 is prescribed to perform the initial anchoring of the centiloid scale, and calibration of new tracers or methods. To promote wide adoption of the centiloid scale, the VOI masks required for the quantification and the images needed for the calibration are all made freely available on the GAAIN website. As part of this effort, the calibration images and associated equations have already been released for 11C-PiB (Klunk et al., 2015), 18F- NAV4694 (Rowe et al., 2016), 18F-Florbetaben (Rowe et al., 2017), 18F-Flutemetamol (Battle et al., 2016) and 18F- Florbetapir (Navitsk et al., 2016).

One of the limitation of the standard SPM8 pipeline is that each PET image requires a corresponding MR image to provide anatomical constrain during the spatial normalisation to the common template. This can be an issue when MR imaging is impossible (claustrophobia, metal implants, non-compliant subject …), as this would prevent the automatic quantification of the accompanying PET image. For this reason, we have developed a PET-only approach (Computational Analysis of PET from AIBL or CapAIBL for short) that provide SUVR quantification of Aβ PET images without the need of a corresponding MR image (Bourgeat et al., 2015a, 2015b). In this study, we apply the centiloid framework to the calibration of CapAIBL, and compare centiloid value derived from all 5 tracers to those computed using the standard method.

Section snippets

Standard SPM pipeline

Each subject's MRI was spatially normalised to the MNI-152 template using the SPM8 unified segmentation method. Each subject's PET was then co-registered to their corresponding MRI, and spatially normalised to the template using the deformation parameters calculated from the MRI. For each subject, the mean retention within the standard VOIs from the GAAIN website, namely global cortical target (CTX) VOI and whole cerebellum (WC) VOI, was computed. The CTX/WC ratio was used to define the

Level-2 calibration of CapAIBL using PiB

There was little bias between the PiB SUVR computed using CapAIBL and those computed using SPM, with the slope PiBmCapAIBL = 0.991 and intercept PiBbCapAIBL = 0.030. The R2 was 0.993, indicating good agreement between both methods. The combined equation that converts PiBSUVRCapAIBL into CL was defined as:CPiBLCapAIBL=100×SPiBUVRCapAIBL1.0341.063

The mean centiloid for the YC using CapAIBL was −0.04, and 100.3 for the AD subjects. The standard deviation in the YC was 4.40, compared to 4.34 when

Discussion

This study showed that the PET-only quantification method, CapAIBL, can be used to perform centiloid quantification using the most commonly used Aβ PET tracers. CapAIBL generated SUVR values that were in very good agreement with those generated using the standard pipeline for all tracers on the calibration data. We have also illustrated how a new method can be calibrated to generate centiloid values.

On an independent dataset from the AIBL study, the centiloid values computed for PiB, FLUTE and

Conclusions

This is the first study showing the calibration of SUVR values produced using a non-standard PET quantification method to the centiloid scale. Using CapAIBL, we showed that reliable centiloid estimates could be obtained using a PET-only quantification method, which could facilitate its adoption in the clinic, as the centiloid values could be produced directly on the PET scanner. The bias observed in NAV and Florbetaben images from the AIBL study indicates that a scanner specific linear

Disclosures

Vincent Doré, Olivier Salvado, Jurgen Fripp, Chris Rowe, Victor Villemagne are inventors on patent US9361686B2 that describes some aspects of the software CapAIBL. Chris Rowe has received research grants from Piramal Imaging, GE Healthcare, Cerveau, Astra Zeneca, Biogen. Victor Villemagne is and has been a consultant or paid speaker at sponsored conference sessions for Eli Lilly, Piramal Imaging, GE Healthcare, Abbvie, Lundbeck, Shanghai Green Valley Pharmaceutical Co Ltd, and Hoffmann La Roche.

References (16)

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