Optimization of the k2′ Parameter Estimation for the Pharmacokinetic Modeling of Dynamic PIB PET Scans Using SRTM2

Peretti, Débora E; Reesink, Fransje E.; Doorduin, Janine; Jong, Bauke M. de; Deyn, Peter Paul De; Dierckx, Rudi; Boellaard, Ronald; García, David Vállez

doi:10.3389/fphy.2019.00212

Cited by 8 publications

(9 citation statements)

References 39 publications

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“…Both systems were from the same vendor and generation; the acquisition and reconstruction protocols were harmonized, and the systems were (cross-)calibrated. No significant differences between the images provided by these two different scanners were found, as shown also in a previously published study using the same dataset [ 29 ]. Scans were performed under standard resting conditions with eyes closed.…”

Section: Methodssupporting

confidence: 83%

Amyloid burden quantification depends on PET and MR image processing methodology

et al. 2021

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Quantification of amyloid load with positron emission tomography can be useful to assess Alzheimer’s Disease in-vivo. However, quantification can be affected by the image processing methodology applied. This study’s goal was to address how amyloid quantification is influenced by different semi-automatic image processing pipelines. Images were analysed in their Native Space and Standard Space; non-rigid spatial transformation methods based on maximum a posteriori approaches and tissue probability maps (TPM) for regularisation were explored. Furthermore, grey matter tissue segmentations were defined before and after spatial normalisation, and also using a population-based template. Five quantification metrics were analysed: two intensity-based, two volumetric-based, and one multi-parametric feature. Intensity-related metrics were not substantially affected by spatial normalisation and did not significantly depend on the grey matter segmentation method, with an impact similar to that expected from test-retest studies (≤10%). Yet, volumetric and multi-parametric features were sensitive to the image processing methodology, with an overall variability up to 45%. Therefore, the analysis should be carried out in Native Space avoiding non-rigid spatial transformations. For analyses in Standard Space, spatial normalisation regularised by TPM is preferred. Volumetric-based measurements should be done in Native Space, while intensity-based metrics are more robust against differences in image processing pipelines.

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Section: Methodssupporting

confidence: 83%

Amyloid burden quantification depends on PET and MR image processing methodology

et al. 2021

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“…The grey matter of the cerebellum VOI was used as the reference region due to the absence of specific binding of the radiotracer in this tissue ( Joachim et al, 1989 , Klunk et al, 2004 , Price et al, 2005 , Yamaguchi et al, 1989 ). This frequently used model is based on a two-step approach: firstly an estimation of R 1 , BP ND , and k 2 ′ is done using the simplified reference tissue model (SRTM) ( Lammertsma and Hume, 1996 ); secondly, the k 2 ′ parameter is fixed as the median value of all voxels that presented a BP ND estimation of 0.5 or above ( Peretti et al, 2019a ); and then, the model is fitted again using the results from the first run as input, generating the final R 1 and BP ND parametric maps.…”

Section: Methodsmentioning

confidence: 99%

“…This can be done in vivo , for example, by the use of 11 C-labelled Pittsburgh Compound B (PIB) PET scans. The quantification of these Aβ deposits can be obtained by means of pharmacokinetic modelling of the tracer using the simplified reference tissue model 2 (SRTM2) ( Peretti et al, 2019a , Yaqub et al, 2008 ), which provides a measure of Aβ load through binding potential ( BP ND ), as well as information on regional cerebral blood flow (rCBF) through the relative tracer flow parameter ( R 1 ) ( Chen et al, 2015 , Meyer et al, 2011 , Peretti et al, 2019c , Peretti et al, 2019b ). Previous studies have shown that rCBF is closely related to glucose metabolism measured with [ 18 F]-2-fluoro-2-deoxy- d -glucose (FDG) PET ( Jueptner and Weiller, 1995 ), another PET radiotracer used routinely for the classification of AD patients and, therefore, has been suggested as an alternative to performing two scans ( Meyer et al, 2011 , Peretti et al, 2019c , Peretti et al, 2019b ).…”

Section: Introductionmentioning

confidence: 99%

Feasibility of pharmacokinetic parametric PET images in scaled subprofile modelling using principal component analysis

Peretti

Renken

Reesink

et al. 2021

NeuroImage: Clinical

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Scaled subprofile model using principal component analysis (SSM/PCA) is a multivariate analysis technique used, mainly in [ 18 F]-2-fluoro-2-deoxy- d -glucose (FDG) PET studies, for the generation of disease-specific metabolic patterns (DP) that may aid with the classification of subjects with neurological disorders, like Alzheimer’s disease (AD). The aim of this study was to explore the feasibility of using quantitative parametric images for this type of analysis, with dynamic [ 11 C]-labelled Pittsburgh Compound B (PIB) PET data as an example. Therefore, 15 AD patients and 15 healthy control subjects were included in an SSM/PCA analysis to generate four AD-DPs using relative cerebral blood flow ( R 1 ), binding potential ( BP ND ) and SUVR images derived from dynamic PIB and static FDG-PET studies. Furthermore, 49 new subjects with a variety of neurodegenerative cognitive disorders were tested against these DPs. The AD-DP was characterized by a reduction in the frontal, parietal, and temporal lobes voxel values for R 1 and SUVR-FDG DPs; and by a general increase of values in cortical areas for BP ND and SUVR-PIB DPs. In conclusion, the results suggest that the combination of parametric images derived from a single dynamic scan might be a good alternative for subject classification instead of using 2 independent PET studies.

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“…[ 11 C]PIB is a well-characterized radioligand for amyloid-β plaques (Price et al, 2005; Peretti et al, 2019), routinely used to quantify amyloid-β plaques and for differential diagnosis and staging in neurodegenerative diseases. Although [ 11 C]PIB has the highest affinity to amyloid plaques, it also displays affinity towards other β-sheet structures like tau and α-synuclein.…”

Section: Discussionmentioning

confidence: 99%

Anin vivopig model for testing novel PET radioligands targeting cerebral protein aggregates

Raval

Nasser

Madsen

et al. 2022

Preprint

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Positron emission tomography (PET) has become an essential clinical tool for diagnosing neurodegenerative diseases with abnormal accumulation of proteins like amyloid-β or tau. Despite many attempts, it has not been possible to develop an appropriate radioligand for imaging aggregated α-synuclein, which is seen in, e.g., Parkinson's Disease. Access to a large animal model with α-synuclein pathology would critically enable a more translationally appropriate evaluation of novel radioligands. We here established a pig model with cerebral injections of α-synuclein preformed fibrils or brain homogenate from postmortem human brain tissue from individuals with Alzheimer's disease (AD) or dementia with Lewy body (DLB) into the pig's brain using minimally invasive surgery and validated against saline injections. In the absence of a suitable α-synuclein radioligand, we validated the model with an unselective amyloid-β tracer [11C]PIB, which has a high affinity for β-sheet structures in aggregates. Gadolinium-enhanced MRI confirmed that the blood-brain barrier function was intact. A few hours post-injection, pigs were PET scanned with [11C]PIB. Quantification was done with Logan invasive graphical analysis and simplified reference tissue model 2 using the occipital cortex as a reference region. After the scan, we retrieved the brains to confirm successful injection using autoradiography and immunohistochemistry. We found four times higher [11C]PIB uptake in AD-homogenate-injected regions and two times higher uptake in α-synuclein-preformed-fibrils-injected regions compared to the saline-injected regions. The [11C]PIB uptake was the same in the occipital cortex, cerebellum, DLB-homogenate, and saline-injected regions. With its large brains and ability to undergo repeated PET scans as well as neurosurgical procedures, the pig provides a robust, cost-effective, and good translational model for assessment of novel radioligands including, but not limited to, proteinopathies.

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Optimization of the k2′ Parameter Estimation for the Pharmacokinetic Modeling of Dynamic PIB PET Scans Using SRTM2

Cited by 8 publications

References 39 publications

Amyloid burden quantification depends on PET and MR image processing methodology

Amyloid burden quantification depends on PET and MR image processing methodology

Feasibility of pharmacokinetic parametric PET images in scaled subprofile modelling using principal component analysis

Anin vivopig model for testing novel PET radioligands targeting cerebral protein aggregates

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